Some data
I spent a bit of time on Statistikbanken, a site run by Statistics Denmark which gives you access to a lot of neat Danish data. Below a table I made from (SKI5), one of the databases; click to view full size:
The variable to the left is a marriage duration indicator at the time of measurement – note that the years at the top (1980, 1990,…) are not the years where the marriages were formed, but rather the years of measurement – and they’re looking back in time and implicitly include marriages which were dissolved decades ago. So if you take the year 1980 for example, back then 21 % of marriages which had been going on (/…would have been going on…) for 10 years had been dissolved through divorce, whereas 36 % of marriages which had been going on for 30 years had ended in divorce. When I last looked at this stuff, I didn’t include these particular numbers and I got curious (plus I was bored).
Here’s what happens if you zoom in on the first 10 years of marriage:
The bolded ones are the cohorts with the highest divorce rate for that specific marriage duration. Interestingly, although the 2012 numbers are generally a bit smaller than the rest the 1990 numbers are in most cases marginally higher than the 1980 numbers; some constant, ‘rule-based’ (monotonous?) development in divorce risk over time is hard to identify when you demand it be consistent with the information provided in the two tables above. That said, the numbers are actually in my opinion very similar all things considered – I’d assume that if you could compare these cohorts with earlier cohorts, you’d see more dramatic differences.
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Okay, what about cars, busses and so on? How many of those are there in Denmark? This is the kind of question children ask, but when you become an adult most people stop asking these questions. I (childishly..) had a look, here are the numbers for the entire country (Statistikbanken, BIL707):
Despite population growth there’s been a decrease in the number of Danish busses, vans, and lorries during the last six years – the number of lorries has dropped 15%, and the number of vans dropped by roughly 10 %.
Here are the numbers for Region Hovedstaden, the area around Copenhagen. With 1.7 million people, this area makes up almost a third of the Danish population:
Whereas the population share of the region is around ~30%, the 2013 share of car-owners is ~27% – quite close to the national average. This really surprised me; I’d have assumed the number of car-owners was smaller than this, and that people relied more on public transportation; but the proportion of all Danish busses committed to this region is actually around ~30% (28,7), close to the population share of the region. I’d have expected the numbers to look different; that a biggish proportion of all Danish busses were committed to this region and that the number of car-owners was lower.
Incidentally there’s roughly one bus per 400 people in Denmark.
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How many people are actually caught violating the national gun laws (‘weapons laws’ – the laws also regulate the use of other weapons such as knives and explosives; e.g. in Denmark it’s illegal to carry a knife with a blade longer than 7 centimeters on you, and until last year a violation of that law would lead to a mandatory one week prison sentence in the absence of exceptional extenuating circumstances)? I didn’t know and so I got curious. I looked at the data included in STRAF11, and it turns out that there were 6808 violations of the weapons law in Denmark in 2007 (before the knife law mentioned above was introduced in 2008), and 6517 in 2012. This is close to 18 people per day over the course of the year.
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Computer and internet? How many families own a computer and/or have internet access at home? Unfortunately there are some missing data problems here, but here’s what they got (VARFORBR):
As you’d expect internet lags computers a bit but there seems to have been convergence over time, and by now only a small minority do not have a computer at home. The above data is not, however, all the stuff they have when it comes to internet usage. I looked around and I found the DIS129 dataset, which deals with active internet subscriptions in Denmark. A funny thing is that if you compare the numbers you get from the two datasets, the numbers don’t really add up; internet penetrance is significantly lower if you base your conclusions on the register data from DIS129 than if you use VARFORBR, which is survey based (actually it’s clear from the description that the DIS129 dataset is also partly survey based, but it’s also made clear that the specific data I use here (there’s a lot of data in that dataset) are from the register-based part of the dataset).
I combined the DIS129 data – limiting myself to private (non-corporate) subscriptions and corporate internet subscriptions used by private individuals as well (i.e. ‘purely corporate’ internet subscriptions were excluded from the sample) – with the household data from FAM55N (we don’t care about internet subscriptions as such, we care about penetrance/adoption rates) to construct a variable indicating the proportion of households with active internet subscriptions. The DIS129 data has a data point for each six months; I decided I didn’t like that very much and so I averaged the data out in order to report only one data-point for each year – results are given below, first the ‘raw’ (averaged) subscription numbers, then the household data, and lastly the proportion of households with active internet subscriptions:
Maybe I should have included the word ‘estimated’ in front of ‘proportion’ in the title above, but all we have are estimates anyway, so… Do note that the x-axes are not identical for the figures based on the VARFORBR and the DIS129 data – unsurprisingly the growth rate was much higher in the 90es than it has been later on; what you want to compare is the last graph above and the part of the VARFORBR graph for which the two x-axes match each other. It’s obvious that the VARFORBR numbers are significantly higher than the DIS129 numbers. In case you were wondering why I don’t compare similar time periods; I figured the development in the 90es was interesting (most adoption took place in the 90es), however the register data didn’t go back further than 2003. If it had I’d have included the data, but I didn’t think it made a lot of sense to exclude the data from the 90es from the VARFORBR data set just because corresponding figures didn’t exist in the DIS129 data set.
Purely corporate subscriptions make up roughly 10 percent of the market share, so not excluding those when calculating adoption rates may lead to a significant overestimate of household internet use. I believe I’ve seen higher adoption rates than the ones derived from the DIS129 data set reported in the media before, but I also believe these estimates have all been based on surveys by Statistics Denmark – so presumably they’re derived from the VARFORBR data set or the source material of this data set. Note that if you’re basing your estimate on the DIS129 sample then you could probably argue that the numbers provided are overestimates of the actual penetrance rates; some households may have more than one active internet subscription, and this arrangement is presumably more common than is the one where different households share the same internet connection. On the other hand they note in the documentation that the registers, despite being very comprehensive, may not be complete and that some relevant data here may be missing from the registers.
Basing our analysis on the register data provided, in the second half of 2011 there were 1.94 million active internet subscriptions used by private individuals, and there were 2,58 million households. I think that I consider the data from DIS129 to be more reliable than the data from VARFORBR; register data is usually better than survey data, although measurement error is always a potential problem. I also think an overestimate of the adoption rate resulting from the use of survey data, which is likely here given the discrepancy, is more plausible from a theoretical point of view than would be an underestimate; people participating in surveys are more likely to say that they have an internet connection even though they don’t than they are to say that they don’t have an internet connection even though they do. I also believe that this bias is likely to increase in people’s estimates of the ‘true’ penetrance rate; when you think everybody else have internet access you become less likely to admit that you don’t if you don’t. But there are multiple ways to explain the gap – for now perhaps the important point is that there is a gap, and that this should be kept in mind the next time the media talks about the results of the latest survey they’ve conducted (people rarely talk about the results of the latest register update…).
Stuff
I have a paper deadline approaching, so I’ll be unlikely to blog much more this week. Below some links and stuff of interest:
“we surveyed the faculty and trainees at MD Anderson Cancer Center using an anonymous computerized questionnaire; we sought to ascertain the frequency and potential causes of non-reproducible data. We found that ~50% of respondents had experienced at least one episode of the inability to reproduce published data; many who pursued this issue with the original authors were never able to identify the reason for the lack of reproducibility; some were even met with a less than “collegial” interaction. [...] These results suggest that the problem of data reproducibility is real. Biomedical science needs to establish processes to decrease the problem and adjudicate discrepancies in findings when they are discovered.”
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ii. The development in the number of people killed in traffic accidents in Denmark over the last decade (link):
For people who don’t understand Danish: The x-axis displays the years, the y-axis displays deaths – I dislike it when people manipulate the y-axis (…it should start at 0, not 200…), but this decline is real; the number of Danes killed in traffic accidents has more than halved over the last decade (463 deaths in 2002; 220 deaths in 2011). The number of people sustaining traffic-related injuries dropped from 9254 in 2002 to 4259 in 2011. There’s a direct link to the data set at the link provided above if you want to know more.
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iii. Gender identity and relative income within households, by Bertrand, Kamenica & Pan.
“We examine causes and consequences of relative income within households. We establish that gender identity – in particular, an aversion to the wife earning more than the husband – impacts marriage formation, the wife’s labor force participation, the wife’s income conditional on working, marriage satisfaction, likelihood of divorce, and the division of home production. The distribution of the share of household income earned by the wife exhibits a sharp cli ff at 0.5, which suggests that a couple is less willing to match if her income exceeds his. Within marriage markets, when a randomly chosen woman becomes more likely to earn more than a randomly chosen man, marriage rates decline. Within couples, if the wife’s potential income (based on her demographics) is likely to exceed the husband’s, the wife is less likely to be in the labor force and earns less than her potential if she does work. Couples where the wife earns more than the husband are less satisfi ed with their marriage and are more likely to divorce. Finally, based on time use surveys, the gender gap in non-market work is larger if the wife earns more than the husband.” [...]
“In our preferred speci fication [...] we fi nd that if the wife earns more than the husband, spouses are 7 percentage points (15%) less likely to report that their marriage is very happy, 8 percentage points (32%) more likely to report marital troubles in the past year, and 6 percentage points (46%) more likely to have discussed separating in the past year.”
These are not trivial effects…
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iv. Some Khan Academy videos of interest:
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v. The Age Distribution of Missing Women in India.
“Relative to developed countries, there are far fewer women than men in India. Estimates suggest that among the stock of women who could potentially be alive today, over 25 million are “missing”. Sex selection at birth and the mistreatment of young girls are widely regarded as key explanations. We provide a decomposition of missing women by age across the states. While we do not dispute the existence of severe gender bias at young ages, our computations yield some striking findings. First, the vast majority of missing women in India are of adult age. Second, there is significant variation in the distribution of missing women by age across different states. Missing girls at birth are most pervasive in some north-western states, but excess female mortality at older ages is relatively low. In contrast, some north-eastern states have the highest excess female mortality in adulthood but the lowest number of missing women at birth. The state-wise variation in the distribution of missing women across the age groups makes it very difficult to draw simple conclusions to explain the missing women phenomenon in India.”
A table from the paper:
“We estimate that a total of more than two million women in India are missing in a given year. Our age decomposition of this total yields some striking findings. First, the majority of missing women, in India die in adulthood. Our estimates demonstrate that roughly 12% of missing women are found at birth, 25% die in childhood, 18% at the reproductive ages, and 45% die at older ages. [...] There are just two states in which the majority of missing women are either never born or die in childhood (i e, [sic] before age 15), and these are Haryana and Rajasthan. Moreover, the missing women in these three states add up to well under 15% of the total missing women in India.
For all other states, the majority of missing women die in adulthood. [...]
Because there is so much state-wise variation in the distribution of missing women across the age groups, it is difficult to provide a clear explanation for missing women in India. The traditional explanation for missing women, a strong preference for the birth of a son, is most likely driving a significant proportion of missing women in the two states of Punjab and Haryana where the biased sex ratios at birth are undeniable. However, the explanation for excess female deaths after birth is far from clear.”
The World’s Muslims: Religion, Politics and Society (Pew)
Here’s the link. I won’t comment on this stuff (much), but here’s some data – click to view figures/tables full size:
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Some people might say there’s a problem here. To take an example in order to illustrate that problem, take a closer look at the preferences of the South Asian (Afghanistan, Pakistan, Bangladesh) muslims. Among South Asian muslims the median % of muslims who back the idea of sharia as the official law of the land is 84 % (p.16). 76 % of the sharia supporters in that region favour executing those who leave islam (see above). Multiply the two and you get that ~64% of South Asian muslims – a clear majority – are in favour of killing apostates. Yet 97 % of them say religious freedom is a good thing. You do the math.
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Patient Compliance – Sweetening the pill
“Compliance is the degree to which a patient is compliant with the instructions that are given by a healthcare professional and written on the medication label (for example, prescribed dose and time schedule).” (p.8 – I didn’t know that definition before reading the book so it made sense to me to start out with this quote, to make sure people are aware of what this book is about.)
It’s an interesting book with a lot of stuff I didn’t know and/or at the very least hadn’t thought about. A couple of the chapters were quite weak and I basically skipped most of chapter 6, which was written by a pharmaceutical marketing consultant who wrote about branding stuff which I couldn’t care less about – but most of the book was quite good. One of the chapters (chapter 8) very surprisingly included undocumented claims which were to some extent proven wrong in a previous chapter (chapter 3) – it seemed as if the authors of that chapter had not read the previous chapter in question. Here’s what they wrote at the very beginning of their chapter (chapter 8):
“Compliance is important. Better adherence to treatment regimes leads to less healthcare resource utilization overall, as fewer illness recurrence or medication errors leading to side-effects take place.” (p.109)
And here’s what Dr. Dyffrig Hughes told us in chapter 3:
From the studies evaluated, the direction and magnitude of the change in costs and consequences resulting from applying sensitivity analysis to the compliance rate was measured and taken as an indicator of the impact of non-compliance. There was consistency among studies, in that as compliance decreased (whatever the measure), the [health] benefits also decreased [...] There is no consistency, however, in the direction of change in costs resulting from changes in compliance [my bold, US] [...] Whilst some studies show that costs increase as compliance decreases, others showed the opposite trend. This difference did not appear to be related to the nature of the disease, the measure of non-compliance or the assumptions relating to the health benefits experienced by non-compliers.
And here’s even a figure illustrating this point:
A little more from chapter 3 on the same subject: “The economic evaluations described demonstrate that medical expenditures do not always increase because of poor compliance. However, the limitations in the methodology adopted in many of the studies would suggest that the reported changes in healthcare expenditure may not necessarily be observed in practice. It is difficult, therefore, to predict the true economic impact of non-compliance with drug therapy, particularly as evidence relating to discontinuers is often not reported. It is the case, however, that decisions on optimal treatments, based on economic criteria, are influenced by non-compliance [...] Health economic evaluations often fail to include non-compliance with medications. As a significant proportion of evaluations are based on efficacy trials, attention should be given to how their findings might be generalized. In particular, as poor compliance is one of the most important elements responsible for the differences that may exist between the effectiveness and efficacy of an intervention, greater consideration should be given to compliance when generalizing from the results of a controlled clinical trial. An optimal cost-effective treatment strategy chosen on the basis of efficacy data may not be so attractive once real-world compliance figures are taken into account.”
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I don’t consider this to be an unforgiveable error in a book like this with a lot of authors writing about different aspects of the problem, but it doesn’t help that the authors of chapter 8 repeat the claim that improved compliance will have cost-saving effects in their conclusion of the chapter as well, and at the very least it doesn’t make them look good to me (a more cautious and tentative approach in the introduction and the conclusion of the chapter would have suited me better). A good editor sh(/w)ould probably have caught something like this.
The efficacy/effectiveness difference he talks about relates to the fact that the results of randomized controlled trials (RCTs) could/should be considered estimates of the health effects related to something close to the ideal treatment scenario, whereas real world implementation (effectiveness) of the treatment in question will often provide patients a sometimes significantly lower health benefit in terms of average treatment effect (or similar metrics), because of differences in the composition of the two groups and the settings of the treatment protocols applied, among other things. RCTs often deliberately try to maximize compliance e.g. by excluding patients who are likely to be non-compliers, and that of course will lead to biased estimates if you apply such estimates to the total patient population. There are many variables affecting how big the potential difference between efficacy and effectiveness may be for a particular drug and they cover that stuff, as well as a lot of other stuff, in the book. Non-compliance rates are much bigger than I’d imagined, but there are a lot of reasons for this that I hadn’t considered. The fact that non-compliance is widespread can be inferred even from the definitions applied in clinical trials:
“ultimately it is the outcome that is important. This might not always require that all doses of a drug are taken. Indeed, in short-term efficacy clinical trials patients who take 80 per cent or more of their medication, based upon pill counts, are usually considered ‘compliant’.” (p.14)
You can fail to take one-fifth of the medicine and still be considered compliant. Indeed as Parkinson, Wei and McDonald put it in their chapter:
“As the reader of this chapter it might be informative to reflect on your own behaviour: can you honestly say that you have always complied fully with every tablet of every prescription and have always finished the course? A very few readers will say yes, with honesty. The reality is that nearly everyone is non-compliant; the variable is the degree of non-compliance.”
A few numbers from the book illustrating the extent of the problem:
“reports (for example, Sung et al., 1998) have suggested that only 37 percent of participants take greater than 90 per cent of all doses of statins over a two-year period. [...]
[Astma:] When patients were aware of being monitored a majority (60 per cent) were fully compliant, but when unaware the majority had a compliance rate between 30 and 51 per cent (Yeung et al., 1994). [...]
Significant levels of non-redemption [of prescriptions], as seen in this study, have subsequently been confirmed within the large UK general practice databases such as GPRD where there is only about 90 per cent concordance between the prescriptions issued by the GP and those recorded as being redeemed at a pharmacy by the UK Prescription Pricing Authority (Rodriguez et al., 2000). [...]
Chapman et al. (2005) recently examined compliance with concomitant antihypertensive and lipid-lowering drug therapy in 8406 enrollees in a US-managed care plan [...] Less than half of patients (44.7 per cent) were adherent with both therapies three months after medication initiation, a figure that decreased to 35.8 per cent at 12 months. [...]
Despite international clinical guidelines recommending lipid-lowering treatment in patients with clinically evident atherosclerotic vascular disease, study after study has documented low treatment rates in this high-risk patient population, thereby creating a clinical practice and public health dilemma (Fonarow and Watson, 2003).
Only about 30 per cent of patients with established CVD and raised serum lipids, and fewer than 10 per cent of individuals eligible for primary prevention, receive lipidlowering therapy. Target total cholesterol concentrations are then achieved in fewer than 50 per cent of patients who do receive such treatment (Primatesta and Poulter, 2000).
Poor patient compliance to medication regimen is a major factor in the lack of success in treating hyperlipidaemia (Schedlbauer et al., 2004). All of the lipid-lowering drugs must be continued indefinitely; when they are stopped, plasma cholesterol concentrations generally return to pretreatment levels (Anon, 1998). [...]
Up to half of the patients treated for hypertension drop out of care entirely within a year of diagnosis (ibid. [WHO, 2003b], Flack et al., 1996). [...]
Non-compliance comes in many forms: depending on the disease area, as many as one in five patients fail to take the first step of collecting a prescription from the pharmacy. Many patients on short-term medications depart from recommended doses within a day or two of starting treatment. And many of those on longer-term medication may take a break from their medication or vary their dose depending on how they feel. A review of the evidence (Horne and Weinman, 1999) concluded that compliance overall is approximately 50 per cent but varies across different medication regimens, different illnesses and different treatment settings.”
A little more stuff from the book:
“Compliance depends on many factors, including the study population (better in educated compared to disadvantaged patients) type of intervention, duration of treatment, complexity of treatment, real or perceived side-effects and life circumstances (see Table 8.1). The reasons are often patient-specific, multifaceted and can change over time. Demographically, the very young, the very old, teenagers and those taking very complex treatment regimes are the least likely to comply. [...]
asymptomatic and chronic diseases needing long-term treatment [...] result in poorer compliance; and [...] the longer the remission in chronic diseases, the lower the compliance (Blackwell, 1976). [...] patient-controlled non-compliance was lower in treatment for diseases in which the relationship between non-compliance and recurrence is very clear, such as diabetes, compared to treatment for diseases in which this relationship is less clear [...] Of course, cognitive deficit, helplessness, poor motivation and withdrawal all lead to forgetfulness and passive or structural noncompliance (Gitlin et al., 1989; Shaw, 1986). [...] most non-compliance is intentional and results from conscious choices. [...]
As a rule, patients cannot be simply classified as compliers or non-compliers. Rather, the level of compliance ranges from patients who take every prescribed dose precisely as directed to those who never do with the typical patient lying between these two extremes. The degree to which patients intend to comply with a regimen can be subdivided into patient-controlled and structural. Patient-controlled factors can be subdivided further into rational behaviour (as seen in patients with Parkinson’s disease who regulate their own dosing) and irrational behaviours (such as self-induced seizures). Structural factors are those beyond the patient’s control, such as impaired memory or difficulty accessing medication (Leppik, 1990). [...]
Compliance and adherence to therapy are complex issues with no obvious ‘one size fits all’ solution available. It appears that actively involving patients in treatment decisions, empowering patients with access to medical information and providing ongoing monitoring all contribute to improved compliance and adherence rates. The challenge for health services, however, is to provide these enhanced levels of support cost-effectively.”
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The book is a few years old and sometimes you can tell. I was curious along the way about how much things have changed in the meantime. I’m guessing less than would have been optimal.
I should point out lastly that I have made a goodreads profile. I haven’t added a lot of books to my profile yet, but I may decide to use that site actively in the future. At goodreads I gave the book 3 stars, corresponding to an ‘I liked it’ evalution.
Stuff
i. I had a doctor’s appointment today and got the results of my bloodwork back. My Hba1c was 48, or 6.5%. This is the lowest it’s been for as long as I can remember. I have had some trouble with hypoglycemic episodes now and then, but not significantly more than usual and I’ve had no major episodes. I believe the lowered Hba1c is probably mostly a result of lowered nocturnal blood glucose values. These have however at some points been uncomfortably low, so I’m not sure 6,5 is a realistic long-term goal and because of those uncomfortably low values I have made adjustments along the way which probably means that the Hba1c may be a bit higher next time if other things stay pretty much the same (which I know they won’t; for instance I’m planning on significantly increasing my running over the next four months). But even so I was very happy about this result, as I choose to believe that it means I’ll actually be able to obtain <7.0% results in the future without major adverse events if I’m careful and vigilant.
This recent post goes into more detail about the hypoglycemia risk and what it’s about. This Danish post has some data on the distribution of Hba1c results among Danish diabetics – the relevant figure is this one (with 6.5%, I’m in the 10% fractile).
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ii. I’m now ‘officially’ a researcher. I have just become a member of Statistics Denmark’s research programme (-forskerordning), which means that I’ve obtained access to a specific data set which I’ll do work on during the next year. Danish registers contain a lot of good information compared to the registers of most other countries, so I may actually be able to look at stuff that a lot of researchers elsewhere are simply not able to analyze due to data issues – which is exciting. Unfortunately I’ll not be comfortable blogging anything about this stuff, as there are a huge number of restrictions on data access/sharing etc. – but I believe it’ll be interesting to work with this stuff and I’m looking forward to it.
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iii. A couple of Khan Academy videos:
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Abstract: “We analyzed one decade of data collected by the Programme for International Student Assessment (PISA), including the mathematics and reading performance of nearly 1.5 million 15 year olds in 75 countries. Across nations, boys scored higher than girls in mathematics, but lower than girls in reading. The sex difference in reading was three times as large as in mathematics. There was considerable variation in the extent of the sex differences between nations. There are countries without a sex difference in mathematics performance, and in some countries girls scored higher than boys. Boys scored lower in reading in all nations in all four PISA assessments (2000, 2003, 2006, 2009). Contrary to several previous studies, we found no evidence that the sex differences were related to nations’ gender equality indicators. Further, paradoxically, sex differences in mathematics were consistently and strongly inversely correlated with sex differences in reading: Countries with a smaller sex difference in mathematics had a larger sex difference in reading and vice versa. We demonstrate that this was not merely a between-nation, but also a within-nation effect. This effect is related to relative changes in these sex differences across the performance continuum: We did not find a sex difference in mathematics among the lowest performing students, but this is where the sex difference in reading was largest. In contrast, the sex difference in mathematics was largest among the higher performing students, and this is where the sex difference in reading was smallest. The implication is that if policy makers decide that changes in these sex differences are desired, different approaches will be needed to achieve this for reading and mathematics. Interventions that focus on high-achieving girls in mathematics and on low achieving boys in reading are likely to yield the strongest educational benefits.”
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v. Genomic responses in mouse models poorly mimic human inflammatory diseases.
Abstract: “A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are non-existent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g.,R^2 between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases.”
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vi. Married men at the age of 40 can expect to live on average 7.1 years longer than unmarried men at the age of 40, and 6.6 years longer than divorced men at the age of 40. For women the life expectancy difference between the married and unmarried group is 4.8 years, and the difference between married women and divorced women is 4.3 years. The excess mortality for unmarried men in their forties (compared with married males) is around 250%, and for men in their fifties it’s still above 200%.
The data reported above is from a new publication by Statistics Denmark which you can read here. Here’s a related publication. Here is a recent publication on the education levels of Danish emigrants. All three publications are unfortunately in Danish.
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vii. Nasa – The Tyranny of the Rocket Equation. This part was surprising to me, because I’d never really thought about this:
“If the radius of our planet were larger, there could be a point at which an Earth escaping rocket could not be built. Let us assume that building a rocket at 96% propellant (4% rocket), currently the limit for just the Shuttle External Tank, is the practical limit for launch vehicle engineering. Let us also choose hydrogen-oxygen, the most energetic chemical propellant known and currently capable of use in a human rated rocket engine. By plugging these numbers into the rocket equation, we can transform the calculated escape velocity into its equivalent planetary radius. That radius would be about 9680 kilometers (Earth is 6670 km). If our planet was 50% larger in diameter, we would not be able to venture into space, at least using rockets for transport.”
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Stuff
i. Remember ‘the good old days’ of film-making? Here’s a reminder: The Hays Code.
“1. No picture shall be produced that will lower the moral standards of those who see it. Hence the sympathy of the audience should never be thrown to the side of crime, wrongdoing, evil or sin.
2. Correct standards of life, subject only to the requirements of drama and entertainment, shall be presented.
3. Law, natural or human, shall not be ridiculed, nor shall sympathy be created for its violation. [...]
The sanctity of the institution of marriage and the home shall be upheld. Pictures shall not infer that low forms of sex relationship are the accepted or common thing.
1. Adultery, sometimes necessary plot material, must not be explicitly treated, or justified, or presented attractively.
2. Scenes of Passion
a. They should not be introduced when not essential to the plot.
b. Excessive and lustful kissing, lustful embraces, suggestive postures and gestures, are not to be shown.
c. In general passion should so be treated that these scenes do not stimulate the lower and baser element. [...]
1. No film or episode may throw ridicule on any religious faith.
2. Ministers of religion in their character as ministers of religion should not be used as comic characters or as villains. [...]
The reason why ministers of religion may not be comic characters or villains is simply because the attitude taken toward them may easily become the attitude taken toward religion in general. Religion is lowered in the minds of the audience because of the lowering of the audience’s respect for a minister.”
Background etc. here and here.
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ii. I’d love to see some corresponding Danish numbers:
“Italians born in 1970, who are about 43 now, will pay 50% more in taxes as a percentage of their lifetime income than those born in 1952, according to research from the Bank of Italy and the University of Verona. The research also found they will receive half the pension benefits that Italy’s 60-somethings are getting or are poised to get.” (link, via MR)
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iii. Longevity AmongHunter-Gatherers: A Cross-Cultural Examination. Some main findings and conclusions from the paper:
“Post-reproductive longevity is a robust feature of hunter-gatherers and of the life cycle of Homo sapiens. Survivorship to grandparental age is achieved by over two-thirds of people who reach sexual maturity and can last an average of 20 years.
Adult mortality appears to be characterized by two stages. Mortality rates remain stable and fairly low at around 1 percent per year from the age of maturity until around age 40. After age 40, the rate of mortality increase is exponential (Gompertz) with a mortality rate doubling time of about 6–9 years. The two decades without detectable senescence in early and mid-adulthood appear to be an important component of human life span extension.
The average modal age of adult death for hunter-gatherers is 72 with a range of 68–78 years. This range appears to be the closest functional equivalent of an “adaptive” human life span.
Departures from this general pattern in published estimates of life expectancy in past populations (e.g., low child and high adult mortality) are most likely due to a combination of high levels of contact-related infectiousdisease, excessive violence or homicide, and methodological problems that lead to poor age estimates of older individuals and inappropriate use of model life tables for deriving demographic estimates.
Illnesses account for 70 percent, violence and accidents for 20 percent, and degenerative diseases for 9 percent of all deaths in our sample. Illnesses largely include infectious and gastrointestinal disease, although less than half of all deaths in our sample are from contact-related disease.
Comparisons among hunter-gatherers, acculturated hunter-gatherers, wild chimpanzees, and captive chimpanzees illustrate the interaction of improved conditions and species differences. Within species, improved conditions tend to decrease mortality rates at all ages, with a diminishing effect at older ages. Human and chimpanzee mortality diverge dramatically at older ages, revealing selection for a longer adult period in humans. [...]
Our results contradict Vallois’s (1961: 222) claim that among early humans, “few individuals passed forty years, and it is only quite exceptionally that any passed fifty,” and the more traditional Hobbesian view of a nasty, brutish, and short human life (see also King and Jukes 1969; Weiss 1981). The data show that modal adult lifespan is 68–78 years, and that it was not uncommon for individuals to reach these ages”
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iv. What is it like when one of your parents gets Alzheimer’s? It’s not fun.
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In people with impaired glucose tolerance interventions are clinically and cost effective
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Screening for type 2 diabetes to allow early detection might be cost effective in certain groups
What this study adds
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Modelling the whole screening and intervention pathway from screening to death shows that screening for type 2 diabetes and impaired glucose tolerance, followed by interventions, seems to be cost effective compared with no screening
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Uncertainty still exists concerning the cost effectiveness of screening for type 2 diabetes alone
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Screening populations with a higher prevalence of glucose intolerance might result in better clinical outcomes, although cost effectiveness seems unaffected”
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N is small but even so this is an interesting finding.
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vii. “Commercial fishing operations in the past 40 years have precipitated a dramatic change in ocean fish stocks, with tuna and other big predators declining and small fish like anchovies and sardines surging. That’s the conclusion of the most ambitious study ever completed of fish populations in the Earth’s oceans, conducted by Villy Christensen of the University of British Columbia’s Fisheries Centre.In the past 100 years, 80% of the biomass of fish in the world’s oceans has been lost, Christensen says in a AAAS video that coincided with a symposium at the Annual Meeting. “Just in the last 40 years, we have lost 60% of the biomass,” he explained. “So we’ve seen some very serious declines, and there’s no doubt about what the cause is: We’re talking about overfishing—overfishing at the global scale.” [...] Christensen’s team of scientists based their conclusions on more than 200 marine ecosystem models and more than 68,000 estimates of fish biomass from 1880 to 2007, the Vancouver Sun reported, citing a University of British Columbia news release.”
A few crime data
“Key Figures – Denmark: Among 35 year old men in 2004: 28% convicted at least once (non-trafic), 14% convicted at least twice (non-trafic), 12% prison sentence (suspended or not).”
From a course lecture note. I’ve written about the crime rates of immigrants in Denmark before (Danish link). The number you need to know from that article is this one: In 2007, 27,2% of (n=1449) male descendants of non-Western immigrants at the age of 20-29 years old got a conviction. I will emphasize that this is in that year alone; this is not an estimate of how many of the 30 year-olds got convicted while they were at the age of 20-29 – this is a snapshot, and during one year more than a fourth of these people got convicted of a crime.
You’d be tempted to say that the fraction of non-Western descendants in Denmark that commit crime while at the age of 20-29 corresponds to the fraction of Danes at the age of 35 who’ve ever been convicted. It’s not quite that bad, because the descendant numbers include traffic violations which are excluded in the other measure and traffic crimes make up a large chunk of the total – 58% of convictions of all descendants (Statistics Denmark doesn’t make it easy to separate non-Westerners from the rest) were traffic-related in 2011 (STRAFNA1). It’s noteworthy that the proportion of all crimes which are traffic-related when using this data at least seems to be significantly higher for ethnic Danes than it is for descendants; for persons of Danish ethnic origin 67% of all convictions were traffic-related (STRAFNA1). If we trust the 58% estimate above, roughly 16% of non-Westerners got a non-traffic conviction in 2008. Note that numbers vary across sources; this measure gives 117.517 traffic law convictions out of 200.091 total convictions, which corresponds to ~59% – I don’t have a good explanation for why the sources differ here. Using the numbers from StrafNA1 only gives you 102.265 traffic law convictions in total, 14575 (7%) of which were committed by immigrants or descendants (who make up 10,1% of the population).
Of course one might argue that the ‘key figures’ above include descendants and immigrants at the age of 35 as well – but I don’t think using it as an ‘ethnic Danes’ ballpark estimate is too problematic, it’s the best I’ve got anyway. So while the fraction of non-Western descendants in Denmark at the age of 20-29 who get convicted of a crime during any given year doesn’t exactly correspond to the fraction of Danes at the age of 35 who’ve ever been convicted, it probably does correspond to more than half (~57% – ~16/28).
The ‘key figures’ for 35 year olds also included a recidivism measure; half of those convicted during their first 35 years of life got at least one more conviction. Note that if you want the hypothetical proportion of repeat offenders in the descendants group at the age of 35 to be similar to the Danish total, the number of repeat offenders in the 27,2%/~16% (year by year) group would have to be very low and the number of total convicts would have to be very high. According to this article (Danish), ‘for ordinary criminals the recidivism rate is 30 % within 2 years of release’ (“For almindelige kriminelle er tilbagefaldsprocenten på 30 procent inden for to år efter løsladelsen.”). My brief look at Statistikbanken didn’t give me any numbers on recidivism rates (the menu here is blank), and I’m not sure it’s a good idea to use this estimate in calculations here because the use of the word ‘release’ likely means that the people included in this measure served time – and most convictions do not lead to jail time (..and the recidivism rate for a previous jail convict is likely different from the recidivism rate of a person who has not served jail-time). I’m lazy and it’s probably not a good estimate to use so I won’t model or do a lot of number crunching on this stuff. However it’s safe to say from the data that either a huge number of non-Western descendants will end up having been convicted of a crime, or a quite big number of them commit a huge amount of crime each. Unless you assume a high recidivism rate it’s also safe to say that the proportion of criminals grows pretty damn fast with crime rates like that (even though the growth rate falls ‘over time’). There certainly isn’t far from 16% to 28% when you add a significant amount to the first number each period and you have a lot of periods in which to add more stuff.
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Update: The numbers in this recent (Danish) publication on recidivism rates seem relevant. It confirms my suspicion that the group of people who’ve been released from jail after having served their time have quite high recidivism rates (60%) compared to other groups. On average offenders with only ‘grundskole’ (1st-9th grade), the educational grouping with the by far highest average recidivism rate, had a recidivism rate of 44%. Via that link I also came across this publication from Statistics Denmark which may be of interest – there’s a lot of data here. They haven’t written the stuff in English, but they have added English translations of key concepts at the end of the publication so that it should theoretically be possible to read the tables if you’re patient.
As to the original remark that: ‘There certainly isn’t far from 16% to 28% when you add a significant amount to the first number each period and you have a lot of periods in which to add more stuff,’ note that if we assume that the two-year descendant recidivism rate is 50% and that the traffic crime proportion estimate is correct so that ~16% of the male descendants at the age of 20-29 got a non-traffic conviction during 2008, then the proportion of descendants with a conviction after two years is 0.16 +(1-0,5)*0.16 = 24%. A 50% recidivism rate is higher than the average recidivism rate of the lowest educated group in the publication linked to above. As I said, there isn’t far from 16% to 28%.
More preliminary data on the blood glucose/mental performance ‘study’
Previous posts here and here. I haven’t been very good at gathering data and during the exam period I basically stopped, but I do have 105 observations at this point.
The R-squared and the estimated effect size in a simple linear model both look almost identical at this point in time as they did 55 observations ago – I’ve posted both the old scatterplot (first) and an updated version (second) below – click to view the full size versions:
I have however been a little suspicious about a few data-points which were collected around the time of the London Chess Classics tournament last year – I spent a significant amount of time on chess during that week and my playing strength when playing blitz games went up a lot those days too (I gained ~150 elo points over 4-5 days, which is a lot – I’ve lost that rating again at this point). Here’s what the image looks like without those observations:
I am not convinced that ‘blood glucose has no effect on tactics trainer performance’ is the conclusion to draw from this data-set, so I’m still collecting data at this point. The true data generating process of course includes many variables not included above – you may want to reread the first article if you want to know more about the ‘true’ DTG.
I wrote in my first post that: “I know myself well enough to know that I don’t want to bother with non-linear models when I look at this stuff later; it’s a poor and underspecified model to begin with.” If I actually have to work with methods which prove useful when analysing this type of dataset during my statistics course this semester (do remember that I have not included all the data I’ve gathered in the above plots), I may change my mind about how much work I’ll do on this dataset. Maybe I’ll be reminded of useful ways to handle stuff like this during the course; stuff that I’ve forgotten about at this point. We’ll see how it goes.
If anyone else would like to have a look at the data, just leave a comment below – I’d be happy to send you a copy of the data.
Stuff
i. PLOS ONE: Till Death (Or an Intruder) Do Us Part: Intrasexual-Competition in a Monogamous Primate.
“Polygynous animals are often highly dimorphic, and show large sex-differences in the degree of intra-sexual competition and aggression, which is associated with biased operational sex ratios (OSR). For socially monogamous, sexually monomorphic species, this relationship is less clear. Among mammals, pair-living has sometimes been assumed to imply equal OSR and low frequency, low intensity intra-sexual competition; even when high rates of intra-sexual competition and selection, in both sexes, have been theoretically predicted and described for various taxa. Owl monkeys are one of a few socially monogamous primates. Using long-term demographic and morphological data from 18 groups, we show that male and female owl monkeys experience intense intra-sexual competition and aggression from solitary floaters. Pair-mates are regularly replaced by intruding floaters (27 female and 23 male replacements in 149 group-years), with negative effects on the reproductive success of both partners. Individuals with only one partner during their life produced 25% more offspring per decade of tenure than those with two or more partners. The termination of the pair-bond is initiated by the floater, and sometimes has fatal consequences for the expelled adult. The existence of floaters and the sporadic, but intense aggression between them and residents suggest that it can be misleading to assume an equal OSR in socially monogamous species based solely on group composition. Instead, we suggest that sexual selection models must assume not equal, but flexible, context-specific, OSR in monogamous species.”
You sort of want to extrapolate out of sample (/…out of species?) here, but be careful:
“Our findings differ from those reported for some monogamous birds, where remaining life-time reproductive success (i.e., the expected future gains) of the individual that initiates or tolerates a ‘divorce’ was higher than if it remained with its initial partner. For example, in kittiwakes (Rissa tridactyla) and many other pair-living birds, but also in some human societies, it is sometimes advantageous to ‘divorce’, if partners prove incompatible [25], [27], [35]. In contrast, our data strongly indicate that break-ups were associated with factors extrinsic to the pair, and that partners did not voluntarily leave or “divorce” as it has been reported for birds, gibbons, and (in at least one case) brown titi monkeys (Callicebus brunneus) [25]–[27], [36], [37]. On the other hand, in some species (oystercatchers, Haematopus ostralegus), the reproductive success of stable pairs is not only higher, but there are also accrued benefits with increased duration of the pair-bond, independent of effects of age or experience [38]. This was not the case for owl monkeys, since the number of offspring produced did not change with increased duration of the pair-bond (Fig. 2).”
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ii. Smbc (click to watch in a higher resolution):
Just to remind you that SMBC is still awesome. Here are a couple of related comics from the site.
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“The ability to control fire was a crucial turning point in human evolution, but the question when hominins first developed this ability still remains. Here we show that micromorphological and Fourier transform infrared microspectroscopy (mFTIR) analyses of intact sediments at the site of Wonderwerk Cave, Northern Cape province, South Africa, provide unambiguous evidence—in the form of burned bone and ashed plant remains—that burning took place in the cave during the early Acheulean occupation, approximately 1.0 Ma. To the best of our knowledge, this is the earliest secure evidence for burning in an archaeological context.”
[Another reminder that SMBC is awesome: Here's a recent comic which is very handy here - it explains what a Fourier transform is, in case you don't know... (If you actually want to know there's always wikipedia...)]
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iv. I never covered this here and though some of you may already have read it I thought I might as well link to Ed Yong’s write-up on replication studies in Nature published last year. A few quotes from the article:
“Positive results in psychology can behave like rumours: easy to release but hard to dispel. They dominate most journals, which strive to present new, exciting research. Meanwhile, attempts to replicate those studies, especially when the findings are negative, go unpublished, languishing in personal file drawers or circulating in conversations around the water cooler. “There are some experiments that everyone knows don’t replicate, but this knowledge doesn’t get into the literature,” says Wagenmakers. The publication barrier can be chilling, he adds. “I’ve seen students spending their entire PhD period trying to replicate a phenomenon, failing, and quitting academia because they had nothing to show for their time.
These problems occur throughout the sciences, but psychology has a number of deeply entrenched cultural norms that exacerbate them. It has become common practice, for example, to tweak experimental designs in ways that practically guarantee positive results. And once positive results are published, few researchers replicate the experiment exactly, instead carrying out ‘conceptual replications’ that test similar hypotheses using different methods. This practice, say critics, builds a house of cards on potentially shaky foundations.
These problems have been brought into sharp focus by some high-profile fraud cases, which many believe were able to flourish undetected because of the challenges of replication. Now psychologists are trying to fix their field.”
Good luck with that. I don’t see a fix happening anytime soon. A few numbers:
“In a survey of 4,600 studies from across the sciences, Daniele Fanelli, a social scientist at the University of Edinburgh, UK, found that the proportion of positive results rose by more than 22% between 1990 and 2007 (ref. 3). Psychology and psychiatry, according to other work by Fanelli4, are the worst offenders: they are five times more likely to report a positive result than are the space sciences, which are at the other end of the spectrum [...]. The situation is not improving. In 1959, statistician Theodore Sterling found that 97% of the studies in four major psychology journals had reported statistically significant positive results5. When he repeated the analysis in 1995, nothing had changed6.”
But maybe other fields are just as bad? Well, as already mentioned the space sciences do better – and that goes for other fields too (though I’d say there seems to be major problems in many areas besides psychology and psychiatry):
A major problem here is that unless you’re actually a researcher in the field or know whom to ask, the file drawer effect can be completely invisible to you.
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v. Globalization of Diabetes – The role of diet, lifestyle, and genes. A new publication in Diabetes Care. As usual when they say ‘diabetes’ they mean ‘type 2 diabetes’. Some numbers from the article:
“According to the International Diabetes Federation (1), diabetes affects at least 285 million people worldwide, and that number is expected to reach 438 million by the year 2030, with two-thirds of all diabetes cases occurring in low- to middle-income countries. The number of adults with impaired glucose tolerance will rise from 344 million in 2010 to an estimated 472 million by 2030.
Globally, it was estimated that diabetes accounted for 12% of health expenditures in 2010, or at least $376 billion—a figure expected to hit $490 billion in 2030 (2). [...] Asia accounts for 60% of the world’s diabetic population. [Do note that this does not mean that Asian countries are on average overrepresented in the diabetes statistics. Asia also has roughly 60% of the World's population. - US] [...] In 1980, less than 1% of Chinese adults had the disease. By 2008, the prevalence had reached nearly 10% [...] in urban areas of south India, the prevalence of diabetes has reached nearly 20% [...] Compared with Western populations, Asians develop diabetes at younger ages, at lower degrees of obesity, and at much higher rates given the same amount of weight gain [...]
If current worldwide trends continue, the number of overweight people (BMI >25 kg/m^2) is projected to increase from 1.3 billion in 2005 to nearly 2.0 billion by 2030 (6). [...] the prevalence of overweight and obesity in Chinese adults increased from 20% in 1992 to 29.9% in 2002 (8) [...]
In the NHS (26), each 2-h/day increment of time spent watching television (TV) was associated with a 14% increase in diabetes risk. [...] Each 1-h/day increment of brisk walking was associated with a 34% reduction in risk [...] Cigarette smoking is an independent risk factor for type 2 diabetes. A meta-analysis found that current smokers had a 45% increased risk of developing diabetes compared with nonsmokers (29). Moreover, there was a dose-response relationship between the number of cigarettes smoked and diabetes risk. [That one I did not know about!] [...] Light-to-moderate alcohol consumption is associated with reduced risk of diabetes. A meta-analysis of 370,000 individuals with 12 years of follow-up showed a U-shaped relationship, with a 30–40% reduced risk of the disease among those consuming 1–2 drinks/day compared with heavy drinkers or abstainers (37). [...]
common variants of the TCF7L2 gene that are significantly associated with diabetes risk are present in 20–30% of Caucasian populations but only 3–5% of Asians [...] Conversely, a variant in the KCNQ1 gene associated with a 20–30% increased risk of diabetes in several Asian populations (43,44) is common in East Asians, but rare in Caucasians [...]
Several randomized clinical trials have demonstrated that diabetes is preventable. One of the first diabetes prevention trials was conducted in Daqing, China (58). After 6 years of active intervention, risk was reduced by 31, 46, and 42% in the diet-only, exercise-only, and diet-plus-exercise groups, respectively, compared with the control group. In a subsequent 14-year follow-up study, the intervention groups were combined and compared with control subjects to assess how long the benefits of lifestyle change can extend beyond the period of active intervention (59). Compared with control subjects, individuals in the combined lifestyle intervention group had a 51% lower risk of diabetes during the active intervention period, and a 43% lower risk over a 20-year follow-up.”
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vi. Why chess sucks.
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Close Relationships (II)
I’m now more than half-way through and I’m no longer in doubt this book is great, so I should make that clear right away.
There’s a lot of stuff about variables of interests and qualitative results, but not much stuff on, say, effect sizes, statistical power, or similar stuff. A lot of the studies covering these things involve WEIRD people. But it’s interesting stuff anyway, and the book is great at handling the conceptual stuff and telling you what people in the field find and how they arrive at the findings they do. I may post one more post about it, but I probably won’t; there’s just way too much good stuff to cover it all here and I don’t want to struggle with the question of what to include and what not to include. You should just read the damn book.
Below some stuff from the book that I put into this post before I realized that I really shouldn’t blog this in that much detail:
“many individuals assume that they have adequately conveyed their attraction to a partner when in fact they have not. The signal amplification bias occurs when people believe that their overtures communicate more romantic interest to potential partners than is actually the case; consequently, they fail to realize that the partner may not be aware of their attraction (Vorauer, Cameron, Holmes, & Pearce, 2003). [...]
Most relationship scholars now agree that relationships develop gradually over time rather than by passing through a series of discrete stages. Process models suggest that relationship development is fueled by sometimes imperceptible changes in intimacy, self-disclosure, exchange of benefits and costs, and other interpersonal processes that occur between partners. [...]
it is not only the depth and the breadth of self-disclosure that propel a relationship along its developmental path but also how responsive each partner is to the other’s disclosures. Intimacy Theory, developed by psychologist Harry Reis and his colleagues (Reis, Clark, & Holmes, 2004; Reis & Patrick, 1996; Reis & Shaver, 1988), posits that attentive, supportive responses that leave the partner feeling validated, understood, cared for, and accepted promote the growth of intimacy and the subsequent development of the relationship. These responses may be of a verbal or a nonverbal nature. In their review of the literature, Karen Prager and Linda Roberts (2004; also see Prager, 2000) observed that an individual who is engaged in an intimate interaction displays a host of behavioral cues that signal attentiveness and responsiveness to the partner as well as positive involvement in the interaction. These include increased eye contact, more forward lean and direct body orientation, more frequent head nods, increased physical proximity, greater facial expressiveness, longer speech duration, more frequent or more intense interruptions, and more intense paralinguistic cues (e.g., speaking rate, tone of voice, pauses, silences, laughter). Recent research reveals that people do, in fact, interpret these behavioral cues as communicating validation, understanding, and caring—in short, responsiveness (see Maisel, Gable, & Strachman, 2008). [...] it is not simply the act of disclosing information or making personal revelations that contributes to relationship development. Rather, reciprocal and responsive disclosures that contribute to feelings of intimacy — in other words, verbal and nonverbal behaviors that reflect mutual perceptions of understanding, caring, and validation — are what encourage and sustain the growth of relationships. [...]
self-disclosure and intimacy appear to be integrally connected with both relationship satisfaction and stability. Research conducted with romantic partners and with friends generally reveals that people who self-disclose, who perceive their partners as self-disclosing, and who believe that their disclosures and confidences are understood by their partners experience greater satisfaction, closeness, commitment, need fulfillment, and love than people whose relationships contain lower levels of intimacy and disclosure (e.g., Laurenceau, Barrett, & Rovine, 2005; Meeks, Hendrick, & Hendrick, 1998; Morry, 2005; Prager & Buhrmester, 1998; Rosenfeld & Bowen, 1991; Sprecher & Hendrick, 2004). [...]
U.S. census data indicate that between the years 1935 and 1939, approximately 66% of men and 83% of women were married by the age of 25. Twenty years later, between 1955 and 1959, 51% of men and 65% of women were married by the time they reached 25 years of age. And two decades after this, between 1975 and 1979, only 37% of 25-year-old men and 50% of 25-year-old women were married (U.S. Census Bureau, 2007a). Currently, approximately one third of the adult U.S. population consists of single men and women who have never married; an additional 10% of adults are divorced and single (U.S. Census Bureau, 2007b, 2007c). [...]
recent surveys conducted in Turkey, Jordan, Yemen, Afghanistan, and Pakistan revealed that approximately 20% to 50% of all marriages were between first cousins (e.g., Gunaid, Hummad, & Tamim, 2004; Kir, Gulec, Bakir, Hosgonul, & Tumerdem, 2005; Sueyoshi & Ohtsuka, 2003; Wahab & Ahmad, 2005; Wahab, Ahmad, & Shah, 2006). [...]
More than 40 years ago, social scientist William Kephart (1967) asked a sample of young men and women whether they would marry someone with whom they were not in love if that person possessed all of the other qualities they desired in a spouse. More than one third (35%) of the men and three fourths (76%) of the women responded affirmatively—they were willing to marry without love. However, by the mid-1980s there was evidence of a dramatic shift in attitude. When psychologists Jeffrey Simpson, Bruce Campbell, and Ellen Berscheid (1986) asked a group of young adults the very same question, only 14% of the men and 20% of the women indicated that they would marry someone they did not love [...] A similar attitude shift is occurring around the world. In the mid-1990s another group of researchers (Levine, Sato, Hashimoto, & Verma, 1995) asked a large sample of adults from 11 countries to answer the question first posed by Kephart [...] the percentage of participants who said “no” in response to the question was as follows: United States (86%), England (84%), Mexico (81%), Australia (80%), Philippines (64%), Japan (62%), Pakistan (39%), Thailand (34%), and India (24%). [...] sociologist Fumie Kumagai (1995) reported that the ratio of arranged (miai ) to love-based (renai) marriages in Japan shifted dramatically over the last half of the twentieth century. Specifically, during the time of World War II, approximately 70% of new marriages were arranged by parents whereas 30% were love-based or personal choice matches. By 1988, however, only 23% of new marriages were arranged; the rest either were completely love-based (75%) or refl ected a combination of parental arrangement and personal choice (2%). Data collected more recently reveal an even greater decline in the proportion of arranged marriages: among Japanese couples marrying in 2005, only 6.4% reported an arranged marriage (National Institute of Population and Social Security Research, 2005, as cited in Farrer, Tsuchiya, & Bagrowicz, 2008). Similar changes have been documented in other countries (e.g., China, Nepal; Ghimire et al., 2006; Xu & Whyte, 1990). [...]
longitudinal research consistently reveals that most newlywed couples (whether in their first or subsequent marriage) begin their married lives with a “honeymoon” period characterized by high amounts of satisfaction and well-being which then progressively decline during the next several years, stabilize for a period of time (often between the fourth and sixth years of marriage), and then continue to decline, assuming the couple stays together. In general, husbands and wives show the same changes in marital happiness. [...] A large literature about the impact of parenthood on marital quality exists, with the majority of studies finding that the transition to parenthood is marked by a reduction in marital satisfaction (e.g., Perren et al., 2005; for reviews, see Belsky, 1990, 2009; Sanders, Nicholson, & Floyd, 1997; Twenge, Campbell, & Foster, 2003). [...] there is some evidence that spouses’ marital satisfaction levels may increase once their children reach adulthood and leave home (see Gorchoff, John, & Helson, 2008). [...]
A vast body of social psychological research reveals that, as people go about their daily lives, they tend to interpret the situations they encounter and the events they experience in a decidedly selfcentered, self-aggrandizing, and self-justifying way (Greenwald, 1980). For example, the majority of men and women possess unrealistically positive self-views—they judge positive traits as overwhelmingly more characteristic of themselves than negative traits; dismiss any unfavorable attributes they may have as inconsequential while at the same time emphasizing the uniqueness and importance of their favorable attributes; recall personal successes more readily than failures; take credit for positive outcomes while steadfastly denying responsibility for negative ones; and generally view themselves as “better” than the average person (and as better than they actually are viewed by others; for reviews, see Mezulis, Abramson, Hyde, & Hankin, 2004; Taylor & Brown, 1988). In addition, people often fall prey to an illusion of control consisting of exaggerated perceptions of their own ability to master and control events and situations that are solely or primarily determined by chance (e.g., Langer, 1975; for reviews, see Taylor & Brown, 1988; Thompson, 1999). Moreover, most individuals are unrealistically optimistic about the future, firmly believing that positive life events are more likely (and negative events are less likely) to happen to them than to others (Weinstein, 1980, 1984). [...] These cognitive processes, collectively known as self-serving biases or self-enhancement biases, not only function to protect and enhance people’s self-esteem (see Taylor & Brown, 1988, 1994) but also color perceptions of the events that occur in their closest and most intimate relationships. For example, two early investigations (Ross & Sicoly, 1979; Thompson & Kelley, 1981) demonstrated that married individuals routinely overestimate the extent of their own contributions, relative to their spouses, to a variety of joint marital activities (e.g., planning mutual leisure activities, carrying the conversation, resolving conflict, providing emotional support, initiating discussions about the relationship). Moreover, they more readily call to mind instances of the specific ways in which they (as opposed to their partners) contribute to each activity.
Research also demonstrates that people tend to adopt a self-serving orientation when interpreting and responding to negative relationship events. [...] Although self-serving biases may benefit the individual partners by protecting their self-esteem, such cognitions may have additional, less-than-beneficial consequences for their relationship. [...]
People not only perceive their own attributes, behaviors, and future outcomes in an overly positive manner, but they also tend to idealize the characteristics of their intimate partners and relationships. Several relationship-enhancement biases have been identified. For example, research reveals a pervasive memory bias for relationship events, such that partners recall more positive experiences, fewer negative experiences, and greater improvement over time in relationship well-being than actually occurred (e.g., Halford, Keefer, & Osgarby, 2002; Karney & Coombs, 2000). [...]
Not only do people rewrite the history of their relationships, but they also tend to view those relationships (and their partners) in an overly positive manner (e.g., Barelds & Dijkstra, 2009; Buunk, 2001; Buunk & van der Eijnden, 1997; Murray & Holmes, 1999; Murray, Holmes, & Griffin, 1996a; Neff & Karney, 2002; Van Lange & Rusbult, 1995). A large body of research reveals that most of us:
● perceive our own relationships as superior to the relationships of other people;
● view our current partners more favorably than we view other possible partners;
● view our partners more positively than our partners view themselves;
● minimize any seeming faults that our partners possess by miscasting them as virtues (“Sure, she can seem kind of rude, but that’s because she’s so honest”) or downplaying their significance (“He’s not very communicative, but it’s no big deal. He shows his love for me in many other ways”);
● accentuate our partners’ virtues by emphasizing their overall impact on the relationship (“Because she is so honest, I know I can trust her completely—she will never give me any reason to doubt her love”). [...]
Together, these findings suggest that most people “see their partners through the filters provided by their ideals, essentially seeing them . . . as they wish to see them” (Murray et al., 1996a, p. 86).
The idealization effect is not limited to perceptions of romantic partners. Research indicates that parents view their children as possessing more positive qualities than the average child (Cohen & Fowers, 2004; Wenger & Fowers, 2008). Similarly, adults rate their friends more favorably than those friends rate themselves (Toyama, 2002). [...] In sum, people appear to see their partners as their partners see themselves—only better. [...]
Current evidence suggests that [...] Partners are happiest and most satisfied when they are realistically idealistic—that is, when they possess an accurate understanding of each other’s most self-relevant attributes but maintain an exaggeratedly positive view of each other’s overall character and their relationship.”
Adult development and aging: Biopsychosocial Perspectives, 4th edition (IV)
I’ve now finished the book. I must say that I’m a bit disappointed but thinking about it this is likely mostly due to the huge variation in the quality of the material here; some of it is really great (I’ve tried to cover that stuff here), some of it is downright awful. If you’re interested in this kind of stuff, you may also like this previous post of mine (I liked that book better).
Below I’ve tried to pick out the good stuff from chapters 10-14 (there’s quite a bit of not-very-good-stuff as well). As always, you can click on the figures/tables to see them in a higher resolution:
“Looking at the intrinsic–extrinsic dimension of vocational satisfaction, researchers have found that people with high neuroticism scores are less likely to feel that their jobs are intrinsically rewarding. Perhaps for this reason, neuroticism is negatively related to job satisfaction; by contrast, people high in the traits of conscientiousness and extraversion are more satisfied in their jobs (Furnham, Eracleous, & Chamorro-Premuzic, 2009; Judge, Heller, & Mount, 2002; Seibert & Kraimer, 2001).
The relationship between personality and job satisfaction works both ways. In one longitudinal study of adults in Australia, although personality changes predicted changes in work satisfaction, changes in personality were also found to result from higher job satisfaction. Over time, workers who were more satisfied with their jobs became more extraverted (Scollon & Diener, 2006).
People’s affect can also have an impact on the extent to which they perceive that there is a good fit between their work-related needs and the characteristics of the job. People who tend to have a positive approach to life in general will approach their work in a more positive manner, which in turn will lead to a better person–environment fit (Yu, 2009). [...]
The Whitehall II Study, a longitudinal investigation of health in more than 10,300 civil employees in Great Britain, provides compelling data to show the links between workrelated stress and the risk of metabolic syndrome (Chandola, Brunner, & Marmot, 2006). Carried out over five phases from 1985 to 1997, the study included measurements of stress, social class, intake of fruits and vegetables, alcohol consumption, smoking, exercise, and obesity status at the start of the study. Holding all other factors constant and excluding participants who were initially obese, men under high levels of work stress over the course of the study had twice the risk of subsequently developing metabolic syndrome. Women with high levels of stress had over five times the risk of developing this condition.
More recent research suggests that Whitehall II men who reported higher justice at work (such as perceived job fairness) had a far lower risk of metabolic syndrome compared with men who experienced lower work justice (Gimeno et al., 2010). For women, stress encountered at work independently predicted Type 2 diabetes, even after controlling for socioeconomic position and stressors unrelated to work (Heraclides, Chandola, Witte, & Brunner, 2009). [...]
When work–family conflict does occur, it takes its toll on the individual’s physical and mental health, causing emotional strain, fatigue, perception of overload, and stress (van Hooff et al., 2005). There are variations in the extent and impact of work–family conflict, however, and not all workers feel the same degree of conflict. Conflict is most likely to occur among mothers of young children, dual-career couples, and those who are highly involved with their jobs.Workers who devote a great deal of time to their jobs at the expense of their families ultimately pay the price in terms of experiencing a lower overall quality of life (Greenhaus, Collins, & Shaw, 2003). There are higher levels of work-family conflict among those employed in the private sector than those employed in the public sector (Dolcos & Daley, 2009).
Age also plays into the work–family conflict equation. Younger workers (under age 45) typically experience more conflict than older workers (46 and older); though when older workers experience conflict the effects seem to be stronger (Matthews, Bulger, & Barnes-Farrell, 2010). [...]
Overall, workers over the age of 55 are nearly half as likely to suffer a nonfatal injury as those who are 35 years and younger, and about half as likely to suffer death due to a work-related injury. However, when older workers (55–64) must miss work due to injury or illness, they spend twice as many days away from work (12) per year than do younger workers (25–34) (Bureau of Labor Statistics, 2010c). [...]
Few retirees show a ‘‘crisp’’ pattern of leaving the workplace in a single, unreversed, clear-cut exit. Most experience a ‘‘blurred’’ exit in which they exit and reenter the workplace several times. They may have retired from a long-term job to accept bridge employment, such as an insurance agent who retires from the insurance business but works as a crossing guard or server at a fast-food restaurant. Other workers may retire from one job in a company and accept another job performing another role in the same company.
Workers who have a long, continuous history of employment in private sector jobs tend not to seek bridge employment because they typically have sufficient financial resources (Davis, 2003). In general, involvement in bridge employment is strongly related to financial need. [...]
about 17% of the 65 and older population are still considered to be in the labor force, meaning that they are either working or actively seeking employment. Virtually all of those 75 years and older (93%) have ended their full-time participation in the nation’s workforce (Bureau of Labor Statistics, 2010b). However, many remain employed on a part-time basis; nearly half of all men and 61% of all women 70 years and older engage in some paid work (He et al., 2005). [...]
Retirement is in many ways a 20th-century phenomenon (Sterns & Gray, 1999). Throughout the 1700s andmid-1800s very few people retired, a trend that continued into the 1900s; in 1900 about 70% of all men over 65 years were still in the labor force. [...] Attitudes toward retirement were largely negative in the United States until the mid-1960s because lack of employment was associated with poverty. People did not want to retire because their financial security would be placed at risk. However, with increases in earnings and Social Security benefits, retirement began to gain more acceptance. [...]
The transition itself from work to retirement seems to take its toll on marital satisfaction when partners have high levels of conflict. The greatest conflict is observed when one partner is working while the other has retired. Eventually, however, these problems seem to subside, and after about 2 years of retirement for both partners, levels of marital satisfaction once again rise (Moen, Kim, & Hofmeister, 2001). [So large spousal age differences would seem to predict higher levels of conflict, US...] [...]
[...]
Approximately 90% of adults who complete suicide have a diagnosable psychiatric disorder. The most frequent diagnoses of suicidal individuals are major depressive disorder, alcohol abuse or dependence, and schizophrenia. Among suicidal adults of all ages, the rates of psychiatric disorders are very high, ranging from 71% to over 90%.
Each year, approximately 33,000 people in the U.S. population as a whole die of suicide. The majority are ages 25 to 54 (Xu et al., 2010). The age-adjusted suicide rate in the United States of all age, race, and sex groups is highest for all demographic categories among White males aged 85 and older at about 48 suicide deaths per 100,000 in the population (Centers for Disease Control and Prevention, 2010f). [...]
Typically, nursing homes are thought of as permanent residences for the older adults who enter them, but about 30% of residents are discharged and able to move back into the community after being treated for the condition that required their admission. About one quarter of people admitted to nursing homes die there, and another 36% move to another facility (Sahyoun, Pratt, Lentzner, Dey, & Robinson, 2001). [I found this to be very surprising and would love to see some Danish numbers..., US] [...] As of 2008, there were approximately 15,700 nursing homes in the Unites States with a total of over 1.7million beds, 83% of which were occupied (National Center for Health Statistics, 2009). [...]
In 2008 [Medicaid] provided health care assistance amounting to $344.3 billion. Nursing homes received $56.3 billion from Medicaid in 2008. Together Medicare and Medicaid (federal and state) financed $813.5 billion in health care services in 2008, which was 34% of the nation’s total health care bill of $2.3 trillion (private and public funding combined) and 82% of all federal spending on health (Center for Medicare and Medicaid Services, 2010b). [...]
deficiencies in nursing homes remain a significant problem, limiting severely the quality of care that many residents receive. Continued reporting of these deficiencies, monitoring by government agencies, and involvement of family members advocating for residents are important safeguards. If you have a relative in a nursing home, it is important for you to be aware of these problems and vigilant for ways to prevent them from affecting your relatives. [...] Although there is a relatively small percentage overall of people 65 and older living in nursing homes, the percentage of older adults who are institutionalized increases dramatically with age. As of 2004 (the most recent date available), the percentages rise from 0.9% for persons 65 to 74 years to 3.6% for persons 75 to 84 years and 13.9% for persons 85+ (Federal Interagency Forum on Age-Related Statistics, 2009). [...]
Alzheimer’s disease is found in nearly half of all nursing home residents (45% in 2008) [...] 56.8% of nursing home residents are chairbound, meaning that they are restricted to a wheelchair. Despite the large number of residents with Alzheimer’s disease, only 5% of nursing homes have special care units devoted specifically to their care (Harrington, Carrillo, & Blank, 2009). [...] Nearly two thirds (65.2%) of residents receive psychotropic medications, including antidepressants, antianxiety drugs, sedatives and hypnotics, and antipsychotics (Harrington et al., 2009). [...] A study of the daily life of residents conducted in 2002 revealed that, as was the case in the 1960s, residents spend almost two thirds of the time in their room, doing nothing at all (Ice, 2002). Thus, for many residents, there are simply not enough activities in the average nursing home (Martin et al., 2002). [...]
In a dying person, the symptoms that death is imminent include being asleep most of the time, being disoriented, breathing irregularly, having visual and auditory hallucinations, being less able to see, producing less urine, and having mottled skin, cool hands and feet, an overly warm trunk, and excessive secretions of bodily fluids (Gavrin & Chapman, 1995). An older adult who is close to death is likely to be unable to walk or eat, recognize family members, in constant pain, and finds breathing to be difficult. A common syndrome observed at the end of life is the anorexia-cachexia syndrome, in which the individual loses appetite (anorexia) and muscle mass (cachexia). The majority of cancer patients experience cachexia, a condition also found commonly in patients who have AIDS and dementia. In addition to the symptoms already mentioned, patients who are dying are likely to experience nausea, difficulty swallowing, bowel problems, dry mouth, and edema, or the accumulation of liquid in the abdomen and extremities that leads to bloating. [...]
Marital status and education are two significant predictors of mortality. The age-adjusted death rate for those who never married is substantially higher than for those who were ever married, even taking into account the higher mortality of those who are widowed and divorced. The advantage holds for both men and women across all age groups of adults ages 15 and older (Xu et al., 2010). Educational status is also related to mortality rate. In all age groups, those with a college education or better have lower mortality rates. [...] Not only the level of occupation, but also the pattern of jobs people hold throughout adulthood, are related to mortality rates. The risk of mortality is lower in men who move up from manual to professional or managerial-level occupations (House, Kessler, Herzog, & Mero, 1990; Moore & Hayward, 1990). Men who hold a string of unrelated jobs have higher rates of early mortality than those with stable career progressions (Pavalko, Elder, & Clipp, 1993). [...]
Across all countries studied by the World Health Organization, the poor are over four times as likely to die between the ages of 15 and 59 as are the nonpoor (World Health Organization, 2009). [...]
The majority of patients in SUPPORT ['Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments' - US] stated that they preferred to die at home; nonetheless, most of the deaths occurred in the hospital (Pritchard et al., 1998). Furthermore, the percentage of SUPPORT patients who died in the hospital varied by more than double across the five hospitals in the study (from 29 to 66%). The primary factor accounting for the probability of a patient dying in the hospital rather than at home was the availability of hospital beds. Later studies in countries such as Great Britain, Belgium, and the Netherlands have confirmed that place of death varies according to availability of hospital beds rather than any specific characteristics of patients or wishes of their families (Houttekier et al., 2010). [...]
[...]
Identity processes may provide a means of maintaining high levels of well-being in the face of less than satisfactory circumstances. Through identity assimilation, people may place a positive interpretation on what might otherwise cause them to feel that they are not accomplishing their desired objectives. The process of the life story, through which people develop a narrative view of the past that emphasizes the positive, is an example of identity assimilation as it alters the way that people interpret events that might otherwise detract from self-esteem (Whitbourne et al., 2002). For instance, older psychiatric patients minimized and in some cases denied the potentially distressing experience of having spent a significant part of their lives within a state mental hospital. Therefore, they were not distressed in thinking back on their lives and past experiences (Whitbourne & Sherry, 1991). People can maintain their sense of subjective well-being and can portray their identity in a positive light, even when their actual experiences would support less favorable interpretations.”
Adult development and aging: Biopsychosocial Perspectives, 4th edition (III)
I’ve read chapters 7-9 today so far. Some stuff from those chapters:
“In using written language, older adults may experience deficits in retrieval that can lead to spelling errors for words they once knew (Burke, 1997). [...] slower cognitive processes may also have an effect on the complexity of grammatical structures that older adults use. As you form sentences, you must keep one clause in mind while you compose the next one, a process that places demands on your working memory. As we saw in Chapter 6, working memory undergoes significant changes with age. Consequently, compared with young adults, older adults speak in simpler sentences (Kemper, Marquis, & Thompson, 2001). Their writing also becomes simpler, in both the expression of ideas and the use of grammatical complexity (Kemper, Greiner, Marquis, Prenovost, & Mitzner, 2001). Thus, although older adults retain their knowledge of grammatical rules (a form of semantic memory), declines in working memory can cause older adults to lose track of what they mean to say while they are saying it.
On the positive side, their greater experience with language gives older adults the potential to compensate for other cognitive changes that affect their ability to produce and understand speech. Most older adults retain the ability to understand individual words (James & MacKay, 2007). [...]
Longitudinal estimates of changes in the PMA [primary mental abilities] scale, shown in Figure 7.6, reveal that there is an overall picture of relatively stability until the 50s or 60s, followed by decline through the oldest age tested. However, caution is required in making conclusions from these findings (Schaie, 1996). For example, although some individuals may show declines in intelligence by the mid-50s, there are not significant losses until the decade of the 70s. [...]
[...]
Specific theories about aging and personality based on the cognitive perspective place importance on the ways that people interpret their experiences and understand themselves over time. An important principle of the cognitive perspective is the idea that people do not always view themselves realistically. In part, this is because people strive to maintain a sense of themselves as consistent (Baumeister, 1996; 1997). In other words, most people prefer to see themselves as stable and predictable (even if they are not). Another basic tendency is for people to view their abilities and personal qualities in a positive light (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001). [...]
Apart from the original investigation by Levinson and colleagues, little empirical support has been presented for the existence of the midlife crisis as a universal phenomenon (Lachman, 2004). Even before the data were available, however, psychologists in the adult development field expressed considerable skepticism about the concept of the midlife crisis based on what at the time appeared to be extrapolation far beyond the available evidence (Brim, 1976; Whitbourne, 1986). [...] As a scientific concept, the midlife crisis simply fails to withstand multiple tests. By now you must surely be wondering why a concept so thoroughly debunked by the data continues to remain alive. Some argue that the idea of a midlife crisis makes a ‘‘good story’’ (Rosenberg, Rosenberg, & Farrell, 1999). [...] Similarly, the idea that personality is subject to major upheavals in the middle years may lead to the persistence of this phenomenon in the public mind far longer than warranted by the data. [...]
Among all adults 18 and older, over half of Whites (56%) are married. [...] Among people 65 and older in the United States, there is a higher percentage of men (72%) than women (42%) married and living with a spouse [...] Consequently, women over the age of 65 are about twice as likely (39%) as men (19%) to be living alone (Administration on Aging, 2009). Therefore, older women are at greater risk for some of the disadvantages that come with single status, including fewer financial resources, less access to care, and lower social support. [...]
Living in a stable relationship prior to or instead of marrying is referred to as cohabitation. Since the 1960s, there has been a steady increase in the number of couples who choose this lifestyle. In 1960 an estimated 439,000 individuals in the United States reported that they were cohabitating with a person of the opposite sex. By 2009 this number was estimated at about 6.7 million (U.S. Bureau of the Census, 2010f). From 50 to 60% of all marriages are now preceded by cohabitation (Stanley, Amato, Johnson, & Markman, 2006); looking at the data on couples who cohabitate, approximately 28% of women 44 and under who cohabitate eventually marry their partner (National Center for Health Statistics, 2010). [...] Along with a rise in the overall number of couples who cohabitate is a parallel increase in the number of cohabitating adults with children under the age of 15. In 1960 this number amounted to 197,000, but by 2009 it was estimated to have increased greatly to the present estimated level of 2.6 million (U.S. Bureau of the Census, 2010d).
Approximately 10% of the adult population in the United States is divorced (U.S. Bureau of the Census, 2010d). Taking into account all marriages that end in divorce, the average length of first marriage prior to divorce is about 8 years (Kreider, 2005). [...] Studies on divorced (compared with married) individuals show that they have lower levels of psychological well-being, poorer health, higher mortality rates, more problems with substance abuse and depression, less satisfying sex lives, and more negative life events (Amato, 2000). The negative consequences of divorce are more severe for individuals who have young children, especially women (Williams & Dunne-Bryant, 2006). These effects may persist for many years, particularly for individuals who remain psychologically attached to their ex-partner, experience conflict in coparenting, or who have unusual difficulty in living on their own (Sweeper & Halford, 2006). Divorced or widowed adults who do not remarry are in poorer health (including chronic conditions and depressive symptoms) than those who remarry (Hughes & Waite, 2009). Divorce in older adults has negative effects on health in that newly divorced older adults experience more physical limitations in their daily lives (Bennett, 2006). [...]
In the United States, approximately 18% of all marriages are second marriages, and 4% are third marriages. The average duration of a second marriage that ends in divorce is slightly longer than that of a first marriage—8 years for men and 9 years for women (Kreider, 2005). The probability of a second marriage ending in divorce after 10 years is .39, slightly higher than that of the ending of a first marriage, which is .33 (Bramlett & Mosher, 2002). [...]
In the United States, currently there are approximately 14.3 million widowed adults ages 18 and older; 77% of these are 65 and older. The majority (81%) of the over-65 widowed adults are women. By the age of 85 and older, the majority of women are widows (76%), about double the rate for men (38%) (U.S. Bureau of the Census, 2010d). The highest rate of widowhood is among Black women 85 and older, among whom the large majority (87.5%) have lost their spouses (He, Sangupta, Velkoff, & DeBarros, 2005). [...]
In what is called the widowhood effect, there is a greater probability of death in those who have become widowed compared to those who are married (Manzoli et al., 2007), an effect that is stronger for men (Lee, DeMaris, Bavin, & Sullivan, 2001)
[...]
Despite population trends toward more single-parent and cohabitating families, the large majority of households in the United States (77%) consist of people living together as a family. In the United States, the average household size is 2.57 people. Households with married couples constitute 53.6% of all households (U.S. Bureau of the Census, 2010d). [...] Approximately 4.3 million women in the United States give birth each year. In the United States in 2006, 75% of all children were born to mothers between the ages of 20 and 34 years old (National Vital Statistics System, 2010). [...]
Fatherhood is increasingly being studied as an aspect of identity in adulthood reflecting, in part, the increasing role of fathers in the raising of their children (Marsiglio, Amato, Day, & Lamb, 2002). Becoming a first-time father can significantly influence a man’s patterns of interaction outside the home. A 7-year longitudinal study of nearly 3,100 fathers of children under the age of 18 described the ‘‘transformative’’ process that occurs as new fathers become more involved with their own parents, grandparents, and other relatives. Fathers also become more involved with service-oriented groups and church. These effects occur along with the birth of each child, but are particularly pronounced at the time of the
first child’s birth (Knoester & Eggebeen, 2006).” [...]
Stuff you may not want to know:
[...]
“Children do undergo developmental changes that alter their relationships with parents, a concept referred to as filial maturity (Blenkner, 1963). During early adulthood, but particularly in the 30s, children begin to relate to their parents in a different way than they did when they were younger. By taking on the responsibilities and status of an adult (employment, parenthood, involvement in the community), the adult child begins to identify with the parent. Over time, the relationship may change as a consequence of this process, and parents and children relate to each other more like equals (Fingerman, 1996). [...]
A model incorporating the various dimensions present in the adult child–parent relations is the intergenerational solidarity model (Bengtson & Schrader, 1982; Silverstein & Bengtson, 1997). According to this model (see Figure 9.6), six dimensions characterize the cohesiveness of family relationships: distance apart, frequency of interaction, feelings of emotional closeness, agreement in areas such as values and lifestyles, exchanges of help, and feelings of obligation. [...]
Estimates are that there are approximately 56 million grandparents in the United States (Fields, O’Connell, &Downs, 2006); about 11% (6.2 million) live with their under-18-year-old grandchildren. Of grandparents living with grandchildren, 2.5 million are responsible entirely for their basic needs (U.S. Bureau of the Census, 2009b). This situation, referred to as a skip generation family, may occur for a variety of reasons, including substance abuse by parents, child abuse or neglect by parents, teenage pregnancy or failure of parents to handle children, and parental unemployment, divorce, AIDS, or incarceration.
Although only a small percentage (14%) of grandparents in skip generation households are over the age of 60 years, substantial percentages live in poverty (Economist, 2007). Many have a disability. [...]
From a life course perspective, the major dimension that underlies close friendships is reciprocity, or a sense of mutuality (Hartup & Stevens, 1997). The fundamental characteristic of reciprocity is that there is give and take within the relationship at a deep, emotional level involving intimacy, support, sharing, and companionship. At the behavioral level, reciprocity is expressed in such actions as exchanging favors, gifts, and advice.
Close friends in adulthood confide in each other, help each other in times of trouble, and attempt to enhance each other’s sense of well-being. Although there may be developmental differences across the life span in the expression of reciprocity, the essence of all friendships remains this sense of deep mutuality. Another important function of friendships is socializing, or helping each other through life transitions in other spheres, such as changes in health, marital relationships, residence, and work.”
Adult development and aging: Biopsychosocial Perspectives, 4th edition (II)
The first post about the book is here. Below some stuff from chapters 4 and 5, which I liked a lot better than the first ones because they had a lot more data:
“The overall pattern of body weight in adulthood shows an upside-down U-shaped trend reflecting the fact that most people increase in their weight from the 20s until the mid-50s, after which their weight decreases. Most of the weight gain that occurs through the years of middle adulthood is due to an increase in BMI (Ding, Cicuttini, Blizzard, Scott, & Jones, 2007), which is manifested mainly as the accumulation of body fat around the waist and hips (commonly referred to as the ‘‘middle-aged spread’’). The loss of body weight in the later years of adulthood is not, however, due to a loss of this accumulated fat and so does not mean that older adults necessarily become healthier or more fit. Instead, older adults lose pounds because they suffer a reduction of FFM [fat-free mass] due to loss of muscle mass, even if they maintain high levels of activity (Manini et al., 2009).
At the other end of the spectrum, some older adults continue to gain weight to the point of developing a BMI that places them in the overweight or obese categories. Between the mid-1990s and mid-2000s, the percent of older adults classified as overweight increased from 60 to 69% and as obese from 22 to 31% (Houston, Nicklas, & Zizza, 2009). [...]
You are able to move around in your environment due to the actions of the structures that support this movement, including the bones, joints, tendons, and ligaments that connect the muscles to the bones, and the muscles that control flexion and extension. In the average person, all these structures undergo age-related changes that compromise their ability to function effectively. Beginning in the 40s (or earlier in the case of injury), each component of mobility undergoes significant age-related losses. Consequently, a gradual reduction of walking speed occurs (Shumway-Cook et al., 2007). [...] The adult years are characterized by a progressive age-related loss of muscle tissue, a process known as sarcopenia. There is a reduction in the number and size of muscle fibers, especially the fast-twitch fibers involved in speed and strength. As indicated by research from cross-sectional studies, muscle strength (as measured by maximum force) reaches a peak in the 20s and 30s, remains at a plateau until the 40s to 50s, and then declines at a faster rate of 12 to 15% per decade (Kostka, 2005), with more pronounced decreases, at least cross-sectionally, for men. Muscular endurance (as measured by isometric strength) is, however, generally maintained throughout adulthood (Lavender & Nosaka, 2007). [...] The loss of muscle mass brings with it a set of negative consequences including increased risk of falling, limitations in mobility, and reduced quality of everyday life. Unfortunately, sarcopenia can become part of a vicious cycle because the greater the loss of muscle mass, the greater the difficulty in undertaking exercise, causing an exacerbation of muscle loss and further weakening (Lang et al., 2009). [...]
Bone is living tissue that constantly reconstructs itself through a process of bone remodeling in which old cells are destroyed and replaced by new cells. The general pattern of bone development in adulthood involves an increase in the rate of bone destruction compared to renewal and greater porosity of the calcium matrix, leading to loss of bone mineral content. [...] Estimates of the decrease in bone mineral content over adulthood are about .5% per year for men and 1% per year for women (Emaus, Berntsen, Joakimsen, & Fonnebo, 2006). Further weakening occurs due to microcracks that develop in response to stress placed on the bones (Diab, Condon, Burr, & Vashishth, 2006). Part of the older bone’s increased susceptibility to fracture can be accounted for by a loss of collagen, which reduces the bone’s flexibility when pressure is put upon it (Saito & Marumo, 2009). [...]
Cardiovascular efficiency is indexed by aerobic capacity, the maximum amount of oxygen that can be delivered through the blood, and cardiac output, the amount of blood that the heart pumps perminute. Both indices decline consistently at a rate of about 10% per decade from age 25 and up so that the average 65-year-old has 40% lower cardiovascular efficiency than the young adult (Betik & Hepple, 2008). The decline is more pronounced in males than females (Goldspink et al., 2009). Maximum heart rate, the heart rate achieved at the point of maximum oxygen consumption, also shows a linear decrease across the years of adulthood. Declines in aerobic capacity occur even in highly trained athletes, but those who continue to exercise at a high level of intensitymaintain their aerobic capacity longer than non-athletes (Tanaka&Seals, 2003). [...] With regard to aerobic functioning, exercise is one of the best ways you can slow down the rate of your body’s aging process. [...]
Approximately 30% of all adults 65 and older suffer from urge incontinence, a form of urinary incontinence in which the individual experiences a sudden need to urinate, and often results in urine leakage. Stress incontinence involves loss of urine experienced during exertion. The prevalence of daily incontinence ranges from 12% in women 60 to 64 years old to 21% in women 85 years old or older [...] A variety of treatments are available to counteract incontinence, but because people often mistakenly assume that bladder dysfunction is a normal part of aging, they are less likely to seek active treatment. In one study of more than 7.2 million patients diagnosed with overactive bladder, 76% went untreated (Helfand, Evans,&McVary, 2009). Medications such as tolderodine (Detrol LA) are becoming increasingly available to help control bladder problems. [...]
Although men do not experience a loss of sexual function comparable to the menopause (despite what you might hear about the ‘‘male menopause’’), men undergo andropause, which refers to age-related declines in the male sex hormone testosterone. The decline in testosterone is equal to 1% per year after the age of 40, a decrease observed in longitudinal as well as cross-sectional studies (Feldman et al., 2002). The term ‘‘late-onset hypogonadism’’ or ‘‘age-associated hypogonadism’’ has begun to replace the term andropause, although all three terms are currently in use. [...] Erectile dysfunction (ED), a condition in which a man is unable to achieve an erection sustainable for intercourse, is estimated to increase with age in adulthood, from a rate of 31% among men 57–65 to 44% of those 65 and older. ED is related to health problems in older men, including metabolic syndrome (Borges et al., 2009). [...]
Normal aging seems to have major effects on the prefrontal cortex, the area of the brain most involved in planning and the encoding of information into long-term memory, as well as in the temporal cortex, involved in auditory processing (Fjell et al., 2009). The hippocampus, the structure in the brain responsible for consolidating memories, becomes smaller with increasing age, although this decline is more pronounced in abnormal aging such as in Alzheimer’s disease (Zhang et al., 2010). [...]
Most people require some form of corrective lenses by the time they reach their 50s or 60s. Presbyopia, or loss of the ability to focus vision on near objects, is the primary culprit for the need for reading glasses, and is the visual change that most affects people in midlife and beyond.
Presbyopia is caused by a thickening and hardening of the lens, the focusing mechanism of the eye (Sharma & Santhoshkumar, 2009). As a result, the lens cannot adapt its shape when needed to see objects up close to the face. By the age of 50, presbyopia affects the entire population. Treatment for the cause of presbyopia does not exist, and although bifocals were the only correction since the time of Benjamin Franklin (who invented them) newer multifocal contact lenses are increasingly becoming available on the market (Woods, Woods, & Fonn, 2009). Though you cannot cure presbyopia, you may be able to alter its onset because lifestyle habits seem to affect the rate at which the presbyopic aging process occurs. For example, smoking accelerates the aging of the lens (Kessel, Jorgensen, Glumer, & Larsen, 2006).
Older adults are also likely to experience the loss of visual acuity, or the ability to see details at a distance. The level of acuity in an 85-yearold individual is approximately 80% less than that of a person in their 40s. [...]
Loss of balance is one of the main factors responsible for falls in older adults (Dickin, Brown, & Doan, 2006). In 2007 alone, more than 15,800 people 65 and older were known to have died directly from injuries related to falls (Kung, Hoyert, Xu, & Murphy, 2008); 1.8 million were treated in emergency departments for fall-related nonfatal injuries, and about 460,000 of these people were hospitalized (Stevens, Ryan, & Kresnow, 2006). [...]
Smell and taste belong to the chemical sensing system referred to as chemosensation. The sensory receptors in these systems are triggered when molecules released by certain substances stimulate special cells in the nose, mouth, or throat. Despite the fact that the olfactory receptors constantly replace themselves, the area of the olfactory epithelium shrinks with age, and ultimately the total number of receptors becomes reduced throughout the adult years. At birth, the olfactory epithelium covers a wide area of the upper nasal cavities, but by the 20s and 30s, its area has started to shrink noticeably.
Approximately one third of all older adults suffer some form of olfactory impairment (Shu et al., 2009) with almost half of those 80 years and older having virtually no ability to smell at all (Lafreniere & Mann, 2009). The loss of olfactory receptors reflects intrinsic changes associated with the aging process, as well as damage caused by disease, injury, and exposure to toxins. Research suggests that these environmental toxins may play a larger role in olfactory impairment than changes due to the aging process. [...]
A sedentary lifestyle is the first major risk factor for heart disease. The relationship between leisure activity and heart disease is well established (Yung et al., 2009), with estimates ranging from a 24% reduction in the risk of myocardial infarction among non-strenuous exercisers to a 47% reduced risk among individuals engaging in a regular pattern of strenuous exercise (Lovasi et al., 2007). As it happens, the majority of adults at highest risk for heart disease (i.e., those 75 and older) are the least likely to exercise. Only about 36% of people 65 to 74 and 16% of those 75 and older engage in vigorous leisure activity (National Health Interview Survey, 2009). [...] Approximately one fifth of all adults in the United States are current smokers. The rates of current smokers decrease across age groups of adults to 10% of those 65 and older (National Health Interview Survey, 2009). [...]
In 2009, it was estimated that nearly 1.5 million Americans received a diagnosis of cancer (not including skin cancer or noninvasive cancers) and that about 10.5 million are living with the disease. The lifetime risk of developing cancer is about 1 in 2 for men and 1 in 3 for women (American Cancer Society, 2009). [...] All cancer is genetically caused in the sense that it reflects damage to the genes that control cell replication. [...this is actually, I think, a very good way to put it.] [...]
A nationwide study of over 900,000 adults in the United States who were studied prospectively (before they had cancer) from 1982 to 1998 played an important role in identifying the role of diet. During this period of time, there were more than 57,000 deaths within the sample from cancer. The people with the highest BMIs had death rates from cancer that were 52% higher for men and 62% higher for women compared with men and women of normal BMI. The types of cancer associated with higher BMIs included cancer of the esophagus, colon and rectum, liver, gallbladder, pancreas, and kidney. Significant trends of increasing risk with higher BMIs were observed for death from cancers of the stomach and prostate in men and for death from cancers of the breast, uterus, cervix, and ovary in women (Calle, Rodriguez, Walker-Thurmond, & Thun, 2003). We can conclude from this research that maintaining a low BMI is a critical preventive step in lowering your risk of cancer.
In addition to BMI, eating specific foods seems to play a role in cancer prevention. Stomach cancer is more common in parts of the world—such as Japan, Korea, parts of Eastern Europe, and Latin America—in which people eat foods that are preserved by drying, smoking, salting, or pickling. By contrast, fresh foods, especially fresh fruits and vegetables, may help protect against stomach cancer. Similarly, the risk of developing colon cancer is thought to be higher in people whose diet is high in fat, low in fruits and vegetables, and low in highfiber foods such as whole-grain breads and cereals. [...]
It is estimated that 8 million women and 2 million men in the United States suffer from osteoporosis (Sweet, Sweet, Jeremiah, & Galazka, 2009). Women are at higher risk than men because they have lower bone mass in general but nevertheless, osteoporosis is a significant health problem in men. Rates of osteoporosis-related bone fracture are equivalent to the rates of myocardial infarction (Binkley, 2009). Women vary by race and ethnicity in their risk of developing osteoporosis; White and Asian women have the highest risk, whereas Blacks and Hispanics the lowest. In addition, women who have small bone structures and are underweight have a higher risk for osteoporosis than heavier women. [...]
According to the World Health Organization, the number of people suffering from diabetes worldwide is approximately 171 million in 2010, a number that will double by 2030. [...]
Approximately 20% of cases of dementia are due to cerebrovascular disease (Knopman, 2007). [...] In vascular dementia, progressive loss of cognitive functioning occurs as the result of damage to the arteries supplying the brain. Dementia can follow a stroke, in which case it is called acute onset vascular dementia, but the most common form of vascular dementia is multi-infarct dementia or MID, caused by transient ischemic attacks. In this case, a number of minor strokes (‘‘infarcts’’) occur in which blood flow to the brain is interrupted by a clogged or burst artery. Each infarct is too small to be noticed, but over time, the progressive damage caused by the infarcts leads the individual to lose cognitive abilities. There are important differences between MID and Alzheimer’s disease. The development of MID tends to be more rapid than Alzheimer’s disease, and personality changes are less pronounced. The higher the number of infarcts, the greater the decline in cognitive functioning (Saczynski et al., 2009). [...]
People who develop Parkinson’s disease show a variety of motor disturbances, including tremors (shaking at rest), speech impediments, slowing of movement, muscular rigidity, shuffling gait, and postural instability or the inability to maintain balance. Dementia can develop during the later stages of the disease, and some people with Alzheimer’s disease develop symptoms of Parkinson’s disease. Patients typically survive 10 to 15 years after symptoms appear.”
Adult development and aging: Biopsychosocial Perspectives, 4th edition
“Everyone ages. This very fact should be enough to draw you into the subject matter of this course, whether you are the student or the instructor. Yet, for many people, it is difficult to imagine the future in 50, 40, or even 10 years from now. The goal of our book is to help you imagine your future and the future of your family, your friends, and your society. We have brought together the latest scientific findings about aging with a more personal approach to encourage you to take this imaginative journey into your future. [...]
Our goal is to engage you by presenting you with information that is of both personal and professional interest. We will explore the variety of ways individuals can affect their own aging process, such as through incorporating behaviors and activities designed to maintain high levels of functioning well into the later decades of life.”
From the introduction and first part of chapter 1. You can find the book here. I thought the subject would be interesting to read about, and apparently this is the kind of stuff that’s available. I’m not super impressed at this point as there’s a lot of ‘talk’ included in the first chapters of the book – they tend to use many words to say very little. And quite a bit of the talk stuff is just unscientific theorizing without data. But there’s some interesting stuff here as well. Below some stuff from the first 3 chapters (click to view figures in a higher resolution):
“In 1900, the number of Americans over the age of 65 years made up about 4% of the population [...] People 65 and older now represent 12.3% of the total U.S. population [...] In 1990, an estimated 37,306 people over the age of 100 lived in the United States. By 2004 this number increased 73% to 64,658, and by 2050 there will be over 1.1 million of these exceptionally aged individuals.”
“Women over the age of 65 currently outnumber men, amounting to approximately 58% of the total over-65 population [in the US]. [...] In 2010, there were 531 million people worldwide over the age of 65. Predictions suggest that this number will triple to 1.53 billion by the year 2050 (U.S. Bureau of the Census, 2010c). China currently has the largest number of older adults (106 million), but Japan has the highest percentage of people 65 and older (20%) (Kinsella & He, 2009). [...]
[...]
“The most compelling attempts to explain aging through genetics are based on the principle of replicative senescence, or the loss of the ability of cells to reproduce. Scientists have long known that there are a finite number of times (about 50) that normal human cells can proliferate in culture before they become terminally incapable of further division (Hayflick, 1994).
Until relatively recently, scientists did not know why cells had a limited number of divisions. It was only when the technology needed to look closely at the chromosome developed that researchers uncovered some of the mystery behind this process.
As we saw in Figure 2.6, the chromosome is made up largely of DNA. However, at either end of the chromosomes are telomeres, repeating sequences of proteins that contain no genetic information (see Figure 2.8). The primary function of the telomere is to protect the chromosome from damage. With each cell division, the telomeres become shorter, ultimately altering patterns of gene expression affecting the functioning of the cell and the organ system in which it operates. Once telomeres shorten to the point of no longer being able to protect the chromosome, adjacent chromosomes fuse, the cell cycle is halted, and ultimately the cell dies (Shin, Hong, Solomon, & Lee, 2006). Evidence linking telomere length to mortality in humans suggests that the telomeres may ultimately hold the key to understanding the aging process (Cluett & Melzer, 2009).
However, biology does not completely explain the loss of telomeres over the course of life. Supporting the idea of biopsychosocial interactions in development, researchers have linked telomere length to social factors. Analyzing blood samples from more than 1,500 female twins, researchers in the United Kingdom determined that telomere length was shorter in women from lower socioeconomic classes (Cherkas et al., 2006). There was a difference of seven ‘‘biological years’’ (measured in terms of telomeres) between twins with manual jobs and their co-twins in higher-ranking occupations. The researchers attributed this difference to the stress of being in a lower-level occupation in which people have less control over their day-to-day activities. Body mass index, smoking, and lack of exercise were additional factors influencing telomere length. A subsequent study on this sample provided further research of the important role of lifestyle factors. Even after the researchers adjusted for such factors as age, socioeconomic status, smoking, and body mass index, people who engaged in higher levels of physical activity had longer telomeres than those who did not (Cherkas et al., 2008). [...]
Random error theories are based on the assumption that aging reflects unplanned changes in an organism over time. The wear and tear theory of aging is one that many people implicitly refer to when they say they feel that they are ‘‘falling apart’’ as they get older. According to this view, the body, like a car, acquires more and more damage as it is exposed to daily wear and tear from weather, use, accidents, and mechanical insults. Programmed aging theories, in contrast, would suggest that the car was not ‘‘built to last,’’ but rather was meant to deteriorate over time in a systematic fashion. [...]
The free radical theory, or oxidative stress theory (Sohal, 2002), focuses on a set of unstable compounds known as free radicals, produced when certain molecules in cells react with oxygen. The primary goal of a free radical is to seek out and bind to other molecules. When this occurs, the molecule attacked by the free radical loses functioning. Although oxidation caused by free radicals is a process associated with increasing age, researchers have questioned the utility of this approach as a general theory of aging (Perez et al., 2009).”
Chapter 3 has some stuff on problems with making causal claims in this area of research and some stuff on longitudinal studies and cross-sectional studies in this area, including pros and cons of the two types of studies. After that they note that:
“considerable progress in some areas of research has been made through the application of sequential designs. These designs consist of different combinations of the variables age, cohort, and time of measurement. Simply put, a sequential design involves a ‘‘sequence’’ of studies, such as a cross-sectional study carried out twice (two sequences) over a span of 10 years. The sequential nature of these designs is what makes them superior to the truly descriptive designs conducted on one sample, followed over time (longitudinal design) or on different-aged samples, tested on one occasion (cross-sectional design). Not only do sequential studies automatically provide an element of replication, but when they are carried out as intended, statistical analyses can permit remarkably strong inferences to be drawn about the effect of age as distinct from cohort or time of measurement.”
Much of the stuff covered in chapter 3 on research methods should be known stuff to people reading a blog like this, because aging research isn’t that different from other types of research. I skimmed over some of this stuff because much of it is (a wordier and less formalized way to deal with) known stuff from introductionary statistics classes in my past.
Sexually Transmitted Diseases (4th edition) (II)
My initial plan was to read the book from cover to cover. Today I realized that the book has more than 2000 pages, and so I probably will not read all of it.
Anyway, some stuff from part 2 (chapters 6-9) of the book, on Social and Psychological Dimensions of Sexuality, which I read today:
i. 
(click to view full size. In Denmark 50% of the females have had their sexual debut at age 16 (Danish link). The Norwegian number is similar (link).)
ii. “Network epidemiology offers a comprehensive way of thinking about individual sexual behavior and its consequences for STI. Unlike other health-related behaviors (e.g., smoking and seat belts), behaviors that transmit STI directly involve at least two people, and the links either of these persons might have to others. Understanding this process requires moving beyond the standard, individual-centered research paradigm. This has important implications for the analytic framework, data collection, and intervention planning. [...] the network perspective changes the way we think about targeting concepts such as “risk groups” and “risk behaviors.” The inadequacy of these concepts became clear as HIV prevalence rose among groups that do not engage in individually risky behavior, for example, monogamous married women.2, 3, 4, 5 By the same token, a group of persons with extremely “risky” individual behavior may have little actual risk of STI exposure if their partners are uninfected, and not linked to the rest of the partnership network. It is not only individuals’ behaviors that define their risk, it is their partners’ behavior and (ultimately) their positions in a network.
The network perspective also changes the way we think about population-level risk factors: the key issue is not simply the mean number of partners but the connectivity of the network, and connectivity can be established even in low density networks. One of the primary ways in which this happens is through concurrent partnerships. Serial monogamy in sexual partnerships creates a highly segmented network with no links between each pair of persons at any moment in time. Relax this constraint, allowing people to have more than one partner concurrently, and the network can become much more connected. The result is a large increase in the potential spread of STI, even at low levels of partnership formation.
Finally, the network perspective changes the way we think about behavior change. Because the relevant behavior occurs in the context of a partnership, individual knowledge, attitudes, and beliefs do not affect behavior directly. Instead, the impact of these individual-level variables is mediated by the relationship between the partners. A young woman who knows that condoms help prevent the sexual spread of HIV may be unable to convince her male partner to use one. It is not her knowledge that is deficient, but her control over joint behavior.
Networks thus determine the level of individual exposure, the population dynamics of spread, and the interactional context that constrains behavioral change. Taking this seriously represents a paradigm shift in the study of STI.”
iii. “Using network analysis, researchers have identified two basic behavioral patterns that have a large impact on the STI transmission network: selective mixing and partnership timing. Selective mixing is about how we choose partners: the population comprises several subgroups and the question is how many partnerships form within and between groups. Partnership timing is about the dynamics of relationships: monogamy requires partnerships to be strictly sequential, concurrency allows a new partnership to begin while an existing partnership is still active. Both are guided by norms that influence individual behavior, which in turn create partnership network structures that leave distinctive signatures on transmission dynamics and prevalence.
Partnership networks also have other structural features that can be important for STI spread. One example is closed cycles, e.g., the triangles and odd-numbered cycles that can emerge in same sex networks, and larger even-numbered cycles for heterosexual networks. Closed cycles have the effect of sequestering an infection and preventing further spread outside the cycle.”
iv. “Age mixing is generally assortative, but shows an asymmetry among heterosexual couples, with males typically older than their female partners. Age is also an attribute that changes over time. The net impact on transmission dynamics depends on whether the STI is curable or incurable. For curable STIs, prevalence will typically peak among youth, since rates of partner change are high in this group and partners are typically of similar ages, so the STI circulates rapidly within group. In the United States, for example, about 70% of all chlamydia cases and 60% of all gonorrhea cases are found among persons 15-24 years of age.48 Age matching will lead to higher prevalence among youth in this case, as it intensifies the spread within this group. Incurable STI, by contrast, will accumulate with years of exposure, so higher prevalence should be found among older groups for these STIs. For example, in the United States, only 11% of persons living with HIV are in the 15-24-year-old age group.55 In this case, assortative age mixing will (all else equal) protect youth by lowering their exposure to higher prevalence older partners.56“
(click to view full size)
v. “In the earliest studies of partnership sequencing effects, researchers focused on monogamy and the duration of monogamous partnerships. Long-term monogamous pair formation slows down the rate of disease transmission, as concordant pairs provide no opportunity for spread, and discordant pairs remain together after transmission has occurred. Analytic findings support this intuition: increasing partnership duration raises the number of contacts needed to reach the reproductive threshold, lowers the peak number infected, and increases the time to peak infection.89, 90, 91, 92
Attention then turned to the impact of concurrency, to understand the impact of relaxing the rule of monogamy.93, 94, 95 Concurrency has several consequences that lead to amplified transmission. First, as the earlier research showed, concurrency reduces the time between transmissions: the pathogen is not trapped in a partnership since there is another partner available for immediate subsequent transmission. Second, concurrency removes the protective effect of sequence. Under serial monogamy, earlier partners in the sequence are not exposed to infections that the index case acquires from later partners. Under concurrency, earlier partners lose this protection. In Fig. 7-2, partner 1 is indirectly exposed to partner 2, and partner 3 is exposed to partner 4. Not only does this expose two additional persons, it creates two new potential chains of infection from these persons to others.96 Third, concurrent partnerships link individuals together to create large connected “components” in a network—if you have more than one partner, then your partner may have more than one partner, and so on. Such connected components function like a well-designed road network—they allow a pathogen to travel rapidly and efficiently to many destinations.
Concurrency increases the speed of STI transmission through a population. [...] a substantial number of studies have examined concurrency, and in general the findings have confirmed its importance for STI transmission.”
vi. “Given the high prevalence of HIV among MSM [men who have sex with men, US] in many large cities, averaging about 25% in the United States but ranging by city from 18 to 40%,66 HIV infection per se has become a very salient issue for MSM partnerships. The likelihood of being in a partnership, albeit of short or long duration, with someone having HIV infection is much more likely for MSM than it is for heterosexuals. This makes discussion of HIV status a particularly important dynamic for MSM within their partnerships. Disclosure of HIV status remains a challenge for HIV-positive MSM; among those reporting unprotected sex, almost half67,68 reported not disclosing their HIV status to prospective sex partners prior to having unprotected sex, and even fewer report disclosing within their casual partnerships.69 Within more intimate partnerships there is a tension between facing fear of rejection from a partner and wanting to share the information with that partner, often resulting in a delay of the discussion. 70“
vii. “Hart23 has argued not only that there is increasing recognition of venereal disease as a behavioral disease, but that psychological variables implicated in venereal disease may be primarily related to the personality of the individual. He reported for his heterosexual sample that an increase in extroversion, and to a lesser extent neuroticism as measured by the Eysenck Personality Inventory,24 were associated with increased STI. Similar findings are reported by other researchers: Eysenck found that extroverts will have intercourse earlier, more frequently, with more different partners and in more different positions than introverts: they will also engage in more varied sexual behavior outside intercourse and engage in longer foreplay.25 [...]
Eysenck25 found that high psychoticism scorers (those who tend to be isolated, affectless, and aggressive) were also more sexually curious, more accepting of premarital sex, more promiscuous, and more hostile. Extroverts scored as more promiscuous and less sexually nervous, while high scorers on the neuroticism scale had significantly lower scores on sexual satisfaction and significantly higher scores on excitement, nervousness, sexual hostility, sexual guilt, and sexual inhibition.
The association between romantic love, conceptualized as a possibly biologically programmed urge to fall in love, that intellectually blinds the individual, and STD acquisition, is reviewed by Goldmeier and Richardson.35 They see romantic love as akin to an obsessional condition in which euphoric mental states override the rational aspects of a decision to have sex or safer sex. Goldmeier and Richardson note research36 shows that people “in love” differed from controls in having reduced serotonin transporter sites (measured in platelets, and perhaps reflecting a putative “altered serotonergic tone,”) and that being “in love” is associated with raised cortisol levels until the initial throes of love dissipate in 12-24 months. They argue that these data support the contention that romantic love produces a “deterministic and nonlogical response to have sex and thus acquire an STI” and that biological states produced by being “in love” may drive some STI-related risk behaviors.”
viii. “There is a large literature on the response to genital herpes infection, reviewed by Longo and Koehn.69 [...] For people who have had genital herpes for less than a year, negative life events, depression, anxiety, anger, and social alienation predict herpes simplex virus (HSV) recurrences; after a year, high levels of depression and low self-esteem are consistently associated with more frequent HSV recurrences. It is important to note that responses to infection may lead to these states, thus setting up a cycle of response and recurrence. [...] Carney et al.,71 in a longitudinal study, found that the first episode of genital herpes had a substantially negative psychological impact, with over 60% meeting screening criteria for being a psychiatric case as measured by the General Health Questionnaire. However, two-thirds of these became noncases if there were no recurrences of disease: if there were recurrences, the level of psychiatric case classification stayed high. A clinical study72 found that the majority of people with genital HSV report that infection made them less capable of physical warmth and intimacy, enjoy sex less, and feel less sexually desirable. This extended outside sexual contacts: all reported that work performance was also hampered. A majority reported disturbance of affect, feeling that genital HSV is incompatible with happiness, and feeling pessimistic about the future course of the illness. Depression was also reported by 84%. Sexual dysfunctions including reduced interest, reduced ability to achieve orgasm, avoidance of intimacy, and reduced enjoyment of sex, as well as feeling repugnant to others [...]
Psychological complications of HIV infection may be exogenous or endogenous. Exogenous complications arise from the psychosocial stresses resulting from negative societal and interpersonal reactions to AIDS. Faulstich87 notes that the “worried well” (whether infected or not) may exhibit generalized anxiety and panic attacks, along with excessive somatic preoccupation and fear of the disease. On diagnosis of HIV infection or AIDS, individuals may exhibit disbelief and denial, followed by depressive and anxiety symptoms. Emotional distress may commonly lead to adjustment disorders with depressed mood or major depression. Recurrent psychological themes include uncertainty about disease progression, social isolation (imposed or adopted), dealing with terminal illness, and guilt or blame over lifestyle. Suicidal ideation may be present. The advent of HAART may have lowered the intensity of the psychological impact of HIV infection in places where HAART is accessible, as can medical feedback about success or failure of treatment regimens.88
Endogenous complications result from the neuropsychiatric sequelae of HIV infection, either from the direct effect of HIV infection, on the central nervous system (CNS), opportunistic CNS infections, or CNS neoplasia. Up to half of patients with AIDS in the absence of HAART may present signs and symptoms of CNS infection, including subacute encephalitis characterized by malaise, social withdrawal, lethargy, and reduced sexual drive (these may also be signs and symptoms of depressed mood, or of systemic disease).
Subsequently, signs of progressive dementia may appear. Neuropsychiatric deficits resulting from HIV may typically involve impaired language, memory and integrative abilities, and occasionally depressed mood, and their insidious onset makes it important to maintain a high index of suspicion that psychological symptoms may indicate onset of CNS involvement. Although rarer, tertiary syphilis may also involve the CNS and include psychological symptoms. [...]
Nilsson Schönnesson and Ross90 found that psychological adaptation occurs but as the disease enters each new phase (asymptomatic, mild symptomatic, severe, and terminal), psychologic symptoms reoccur. Mood states in the asymptomatic and mild symptomatic phase typically included anger, whereas disappointment, sense of violation, and feelings of aloneness characterized the terminal phase, with powerlessness and helplessness being expressed in all phases.”
Sexually Transmitted Diseases (4th edition)
…by King Holmes, P. Sparling, Walter Stamm, Peter Piot, Judith Wasserheit, Lawrence Corey, Myron Cohen (…and many others: “This edition welcomes new editors Myron Cohen, Larry Corey, and Heather Watts, and 119 new authors”).
I thought that since I brought up my recent doctor’s appointment (not STD-related in any way…) in my last post, I should update you on that stuff here before getting to the book blogging. It was good news all around: There was nothing unusual about the EKG, I do not have microalbuminuria and my Hba-1c was 0.070 (/53) [relevant link to Danish readers]. HDL cholesterol was higher- and LDL and total cholesterol levels, as well as triglycerides, were much lower than required, and the BP was 123/82. I’m always a little concerned about the BP values because they’re sort of the ‘weakest link’ when it comes to my regular test results, but it’s nowhere near high enough to justify any kind of pharmacological intervention at this point.
Back to the book: I’ve read roughly the first 100 pages (Introduction and Overview as well as Part 1 – i.e. the first 5 chapters), and I like it so far. Some good stuff from the first part of the book:
1. “The prevalence, of persistent vaginal and cervical infections are remarkably high in young women; and the incidence, and prevalence, of the chronic STIs are exceptionally high in adults, with seroprevalence increasing steadily with advancing age for infections caused by HIV, syphilis, hepatitis B, and especially, HSV-2 and the genital types of HPV. It is therefore, undoubtedly true that a very large proportion of patients seen by clinicians of all disciplines—perhaps the majority of all adults in the world—have one or more STIs.”
2. “Cohort studies demonstrate condom effectiveness against STI acquisition, not only vs. HIV, but also vs. HSV, gonorrhea, and chlamydial and vaginal infections, and specifically against HPV infection—refuting earlier concerns that condoms did not prevent HPV acquisition.” (that condoms do seem to offer protection against HPV was news to me. Later on in the book the protection offered is made more explicit: “Even for human papilloma virus, which can be transmitted without exposure of mucosal surfaces, condoms have been found to reduce the risk of acquisition by 70%.28“)
3. One major effect of the introduction of penicillin [...] was loss of public health interest in STD control. Public spending on STD control declined throughout the world, and these diseases became a low priority.24 For example, India developed the capacity to manufacture its own penicillin in 1954, after which the state governments of India turned their attention to other health problems.40
One significant exception to this trend was China. Partly because the Chinese had blamed STDs on foreign occupation of China and foreign cultural decadence, the Communist government adopted STD control as one of its major policy initiatives immediately after its 1949 political victory. In a campaign that included widespread public relations efforts through plays, radio programs, and small discussion groups, the government undertook a massive screening and treatment program including vocational rehabilitation for former female sex workers. By 1964, the government claimed to have eliminated STDs, a statement that is impossible to verify but widely accepted as a general indication of a very low Chinese prevalence rate. The long-term effects of the campaign are, however, less clear. Because STDs were represented as a social evil and sign of decadence, Chinese patients tried to avoid public hospitals, which charged STD patients to punish them for their having acquired these diseases. Social stigma became a major problem. Furthermore, the medical specialty of venereology was no longer practiced and taught after 1960s. With the liberalization of employment policies in 1989 and the subsequent development of an enormous migrant labor population (between 50 and 120 million people), rates of STDs began to increase, with insufficient medical resources and ability to respond.41“
4.”Historically, prevention is the neglected aspect of STD control programs. Moral reformers have often asserted their control over prevention efforts by defining STD prevention as a problem of morality. Whether led by church groups themselves or by charitable organizations, these efforts focused on fear-based messages about the consequences of immorality (death, disfigurement, infertility, shame) along with representations of happy family life with abundant, healthy offspring as a consequence of correct moral choices..24
This approach seldom focused on the structural factors which influence sexual behavior, such as long-term labor migration which keeps spouses separated, population displacement, and lack of economic opportunities for young females. [...] Not until the threat of HIV/AIDS emerged during the 1980s, when a fatal STD with no cure threatened the lives of millions, did governments begin to invest substantial resources into systematically studying behavioral science approaches to changing behavior.”
5. “STI/HIV are not spread randomly. Unprotected sex with an infected partner is by far the most important risk factor for STI/HIV infection.1,9 This in turn is influenced by prevalence and distribution of infection in a population, as well as the behavior of an individual and his/her partners.
Economic deprivation, low education, economic inequality, and economically driven migration and mobility have all been found to be associated with the risk of STI/HIV infection.10, 11, 12 [...] processes associated with development such as increases in disposable income and increases in mobility among certain groups and not others are associated with increased risk.10,18 Professions involving high mobility and extended periods away from families, such as migrant labor, serving in the military, driving trucks, or working as sailors are also associated with augmented risk.”
6. “The primary mechanism through which STI contribute to mortality is through mortality associated with HIV. And with an estimated median survival time, a little above 9 years from HIV infection to death in developing countries in the absence of antiretroviral therapy, HIV has had a dramatic impact on adult mortality.25,37 [I've written about these numbers before here on the blog, but the 9 year time frame was news to me. Note that it's age-dependant: "most infected [at birth or as a result of breast-feeding] children, in absence of antiretroviral therapy, will develop AIDS and die before their fifth birthday”. There’s a lot more in the book about this stuff if you’re interested.] [...]
7. “Data on cost-effectiveness [of interventions] are extremely limited and a function of the scarcity of both effectiveness and cost data. The best available data are for health facility-based interventions such as syndromic STI management, screening of blood for transfusion, and prevention of MTCT. The data on cost-effectiveness of behavioral, community, and structural interventions are far weaker. [...] the position taken in the current chapter is that estimates of the cost-effectiveness of STI interventions are highly variable, reflecting both the great heterogeneity in environments as well as the great heterogeneity in the efficiency of service delivery:
The health benefit in terms of numbers of disability-adjusted, discounted, healthy life years saved by curing or preventing a case of syphilis varies from 3 years in a person who has ceased all sexual activity to as many as 161 years in a sex worker with two partners a day. The cost of treating that prostitute for syphilis varies from US$ 5 to US$ 100. Thus the cost per disability adjusted life year (DALY) of syphilis treatment can range from 100/3 or US$ 33 per DALY to 5/161 or less than a US$ 0.05 per DALY. As we learn more about the complexities of delivering STI treatment services and take into account the diversity of risk behavior, the ease with which STI interventions can be ascribed a simple cost-effectiveness ratio has declined. [...]
Almost by definition, there is more to be gained by changing the behavior of people with high levels of risk behavior than by changing that of an equivalent number of people with lower levels of risk behavior. However, the difference in the effectiveness between the two falls as epidemics become more generalized, such that in heavily affected countries prevention interventions are likely to become extremely cost-effective even when targeted to individuals with relatively low levels of risk behavior. Consequently, countries with low-level and concentrated epidemics should emphasize interventions that are targeted to individuals at especially high risk of becoming infected or transmitting the virus, whereas countries with generalized epidemics should also invest heavily in interventions that target entire populations or population subgroups. Thus, any determination of the likely effectiveness and cost-effectiveness of specific interventions in particular circumstances requires an accurate understanding of the stage and nature of the national epidemic.”
8. “The natural history of an infection is the relationship between that infection and disease and associated patterns of infectiousness. In understanding this natural history, individuals can be divided between mutually exclusive categories and the flows between them illustrated schematically in flow diagrams. Figure 3-1 shows the assumptions frequently made about a range of the key STIs in such flow diagrams.”
(click to view full size)
9. “Those with many sexual partners can drive the incidence of an STI in the population and have been described as a “core group”.48 Axiomatically, for a sexually transmitted disease (STD) to exist there must be individuals with sufficient sexual partners to transmit infection to more than one other person.49 If interventions could reliably prevent infection in these individuals, the STI could be eliminated. Studies of risk behaviors and the distribution of STIs have attempted to identify the characteristics of those within the core group as a target for interventions. [...]
The lower the incidence of an STI in a population, the more it will be concentrated in those with higher risk behaviors. If the behaviors placing individuals at risk are similar then those most at risk of one STI would be the same as those most at risk of another infection. We would expect infections with a higher combined transmission probability and duration to not only be more widespread, but to also be found in those with STIs with a lower combined reproductive potential.52 If this is not the case as has been suggested in some observations,53 potential explanations include the acquisition of immunity against one infection, different likelihoods of receiving treatment, and different risk behaviors placing individuals at risk. [...]
The choice of sexual partners of an individual will have a large influence on whether or not they are exposed to someone infected. The choice of sexual partners will depend upon the contexts in which potential couples meet, for instance, schools, church groups, beer halls, and family gatherings and how they relate. Studies show that individuals tend to choose sexual partners, particularly spouses, who are similar with respect to social and demographic variables such as age, education and income.47,49 Such a choice will lead to assortative (like-with-like) sexual mixing within the population with respect to the specific variables. [...] Assortative mixing restricts the spread of STIs but helps maintain chains of infection within high-risk groups. Thus if mixing were assortative, an STI would be more likely to invade rapidly and persist within a population but would also be less likely to spread widely. In contrast, random mixing would spread infection from high- to low-risk individuals who are dead ends for the infection.”
10. “The basic reproductive number (R0) is a measure of the potential for the spread of an infection and can be defined for STIs as the average number of infections caused by one infectious individual entering an entirely susceptible population.69 The key components determining the value of the basic reproductive number are those discussed above: the transmission likelihood (β), the contact rate (c ) and the duration of infectiousness (D), with, in a simple, illustrative model, the product of these three being the basic reproductive number: R0 = βcD.69 The value of R0 determines: the chances of an epidemic when an infection enters a population; the rate of spread of the epidemic; the endemic level of infection, and the effort required to bring the infection under control. An important distinction has to be drawn between the basic reproductive number, R0, which measures the potential for spread in a naive population, and the effective reproductive number, Rt, which changes depending on the experience of infection in the population.70 This effective reproductive number is the number of new infections caused by an average infection at a given time, t, which at time zero equals the basic reproductive number. Once some contacts are already infected or immune, the effective reproductive number is reduced and is the product of the basic reproductive number and the fraction of contacts remaining susceptible. When an infection successfully invades a population its prevalence will initially grow exponentially, until it saturates and the effective reproductive number falls. [...] the greater the value of R0, the higher predicted prevalence of infection and immunity. In the case of STIs, where there is heterogeneity of risk, contacts are concentrated in a small fraction of the population and infection saturates long before it would in a homogenous population. [...]
The pattern of spread of the epidemic and its subsequent progress to an endemic level depends upon the duration of infection and the role of acquired immunity [...] For a short-lived infection with no acquired immunity, such as gonorrhea, we can expect a steady state to be reached quickly. If death or acquired immunity reduces the susceptible pool, the prevalence of infection can fall until the resupply of susceptibles through newly susceptible individuals entering the population either balances the losses or builds up over time to cause new epidemics. The associated declines in prevalence could be confused for the impact of interventions but are the natural course of the epidemic. In the case of syphilis, acquired or concomitant immunity can explain the long-term cycles in incidence observed in US case reports.10 In the case of HIV, declines in prevalence can reflect earlier declines in incidence caused by saturation.73″
11. “To reduce the incidence of STI infection interventions must alter the reproductive potential of the infection. Shortening the infectious period, reducing the contact rate, or reducing the transmission probability, all reduce the basic reproductive number of infection, while introducing artificial immunity through vaccination would reduce the proportion of the population susceptible and thereby reduce the effective reproductive number. Reducing the basic reproductive number has a nonlinear impact on the endemic prevalence of infection [...] heterogeneity in risk plays a key role in the epidemiology of STIs. In populations with a distribution of risk, small reductions in risk can have a large impact in a lower risk group while having little impact in higher risk groups.75 Thus, initially interventions can have a large impact, but as their intensity is increased it generates diminishing returns, as infection is removed from low-risk sections of the population and becomes more concentrated. [...]
The relative success of different STIs is likely to have changed in response to treatment, with chancroid, syphilis, and gonorrhea becoming relatively less common if their symptoms are more likely to receive attention. Similarly within microbial populations, treatment is likely to provide a selective advantage to organisms that generate negligible symptoms, more so than organisms that have partial drug resistance. Over time, we might expect the pathogenicity of curable STIs to decline unless there is a correlation between symptoms and transmissibility, which is hypothetically likely if disease is associated with larger bacterial colonies and transmission depends upon the infectious dose of bacteria. However, if interventions through screening target both asymptomatic and symptomatic infections, then selection is likely to favor organisms that transmit more readily, with a concomitant shorter duration of infection in the absence of treatment.77 Similarly, drug resistance becomes a better adaptive strategy if both symptomatic and asymptomatic infections are rapidly treated through active screening.”
12. “An estimated 1.9 million people (1.3-2.6 million) are living with HIV in North America and in Western and Central Europe.
In high-income countries, where the great majority of people who need antiretroviral treatment do have access to it, people living with HIV are staying healthy and surviving longer than infected people elsewhere. Widespread access to life-extending antiretroviral treatment kept the number of AIDS deaths at between 19,000 and 42,000 in 2005. However, prevention efforts are not keeping pace with the changing epidemics in several countries. Sex between men is the most common route of infection in Australia, Canada, Denmark, Germany, Greece, and the United States. Patterns of HIV transmission are changing with an increasing proportion of people becoming infected through unprotected heterosexual intercourse. In Belgium, Norway, and the UK, the increase in heterosexually transmitted infections is dominated by people from countries with generalized epidemics, predominantly sub-Saharan Africa. In the United States, about half of newly reported infections are among African Americans who represent 12% of the population. [...] Drug injecting accounted for more than 10% of all reported HIV infections in Western Europe in 2002 (in Portugal it was responsible for over 50% of cases). In Canada and the United States, about 25% of HIV infections are attributed to drug injecting.”
13. “The incidence, prevalence, and population distribution of sexually transmitted infections (STIs) are largely determined by the complex interplay of dynamically changing demographic, economic, social, and behavioral forces and the response of the health system to emergent STI morbidity patterns. Over the past 3 decades, overall incidence and prevalence of bacterial STI, in particular gonorrhea, syphilis, chancroid, and chlamydial infections have declined in the United States, Western Europe, and many developing countries, to their lowest levels since World War II. Declines in bacterial STI in developing countries are attributed to the widespread implementation of syndromic management and to a large-scale shift to safer sexual behaviors in response to the HIV epidemic. Despite such remarkable declines, rates of some bacterial STI are still high and/or increasing in some subpopulations [...] During the past decade prevalences of viral STI, particularly genital herpes infections (HSV), appear to have increased in many countries [...] Diagnosis, management, and control of viral STIs have changed drastically over the past decade. The introduction of new diagnostic technologies has increased recognition of viral STI, improved sensitivity in identification of bacterial STI, and expanded the repertoire of usable specimens. The use of urine and vaginal swabs has greatly expanded coverage of screening services and has led to the availability of true population-based estimates of the prevalences of STIs.1 [...] In all societies, for many reasons discussed in this chapter, STIs tend to concentrate in certain populations including urban, poor, and minority populations, with highest rates among sexually active adolescent females followed by adolescent and young adult men. This pattern is particularly pronounced in western industrialized countries where effective prevention and control efforts result in concentrated STI morbidity. During the past decade commercial sex has become an increasingly important factor in STI transmission6,7 in many areas of the world including the United States and Western Europe.”
14. “Trajectories whereby STI epidemics evolve differ for different types of population-pathogen interactions.30, 31, 32 Whereas highly infectious, short duration bacterial STIs—for instance, gonorrhea—depend on the presence of core groups marked by multiple sex partnerships (often of short duration) for their spread, less infectious, long duration viral STIs—for example, herpes simplex virus (HSV) or human papillomavirus (HPV) infections—are less dependent on multiple partnerships of short duration or on short gaps between partnerships. Thus, the pattern of spatial and population distribution of various STIs differs markedly. Syphilis and gonorrhea tend to be concentrated in individuals with multiple partnerships and in populations with highly connected sexual networks; whereas genital chlamydial infections, genital herpes, and genital HPV infections are much more ecumenically, widely distributed across the entire population.33
15. “The most recent updated estimates for prevalence and incidence of STIs globally are provided by the WHO.47 These estimates suggest that of 340 million new cases of gonorrhea, syphilis, chlamydial infection, chancroid, and trichomoniasis STIs in 1999 under 10% occurred in North America and Western Europe; over 90% of new infections were in developing countries (Table 5-1). In 1999, the overall estimated number of new cases of chlamydia, gonorrhea, and syphilis infections among 15-49-year-old men and women totaled over 166 million with close to 92 million cases of chlamydial infection, 62.35 million cases of gonorrhea, and 11.76 million cases of syphilis (Table 5-2). In addition, there were an estimated 173.46 million cases of trichomoniasis.
In developing countries, passive surveillance of STI morbidity is particularly inadequate. However, in recent years the epidemiology of STIs in sub-Saharan Africa is better defined based on large population-based prevalence surveys. The results of these surveys have confirmed the high prevalences of STIs even in rural populations, for example, syphilis (5-10% of adults infected), vaginal trichomoniasis (20-30% of women), and bacterial vaginosis (up to 50% of women). Syphilis has been estimated to cause 490,000 stillbirths and neonatal deaths per year in Africa—a figure similar to the number of children dying of HIV/AIDS worldwide.48
16. “Data on gonococcal antimicrobial resistance across the EU are not comprehensive. Plasmid-mediated resistance to penicillin and tetracycline had increased in Europe during the early 1990s. Sporadic resistance to fluoroquinolones was also documented in the early 1990s, mainly imported from South East Asia.52 [...] Recently, increases in fluoroquinolone resistance have been reported in many countries in Europe. In Denmark, the laboratory-confirmed percentage of gonococci with fluoroquinolone resistance increased from 0% to 27% in 1999, 17% of the strains were resistant to both penicillin and fluoroquinolones.52 [...] By early 2004, fluoroquinolones were no longer recommended in the United States as first-line treatment for MSM, and by early 2007, were no longer recommended as first-line treatment of gonorrhea in any group.86
17. “Chlamydia trachomatis is still the most prevalent sexually transmitted bacterial infection in North America and Europe.52,54 It is difficult to describe temporal trends in the incidence of chlamydial infection because of the large proportion of asymptomatic infections; the increasing use of increasingly sensitive diagnostic tests, with expansion of chlamydia screening activities in Europe and the United States; the increased emphasis on case reporting by providers; and the improvements in the information systems for reporting. In many European countries, case reporting of genital chlamydial infections is not mandatory; consequently, relatively little information is available from national surveillance sources. [...]
In a recent study,122 U.S. women aged 14-49 participating in the National Health and Examination Survey (NHANES) cycles 2001-2004 provided self-collected vaginal swabs; vaginal fluids extracted from the swabs were evaluated for Trichomonas vaginalis using polymerase chain reaction (PCR). The overall prevalence of T. vaginalis was 3.1%; it was highest among non-Hispanic blacks (13.3%) and lower among Mexican Americans (1.8%) and non-Hispanic whites (1.3%). [...]
Viral STIs are not notifiable in most European countries and relatively limited temporal trend data have been published.52 Genital HSV infection is the most common ulcerative STI in the UK and the United States. However, many patients with genital herpes do not perceive or recognize symptoms of the infection, and clinical case-reports grossly underrepresent the true incidence of genital herpes as reflected by serologic testing for antibody to HSV-2. [...] HSV-2 prevalence appears to be higher in Northern Europe and in North America than in Western and Southern Europe. The highest prevalence of HSV-2 infection was found among women in Greenland, reaching 57% among 20-26-year olds and 74% in 25-39-year olds. In Scandinavia, HSV-2 prevalence was relatively higher than in other areas of Europe—15-35% among women between 25 and 35 years of age.124 [...] The most recent data on HSV-2 seroprevalence in the United States were collected in a stratified random sample of the United States population through the NHANES during 1988 through 1994 and 1999 through 2004.126 Persons between ages 14 and 49 were included in the analyses. The overall age-adjusted HSV-2 seroprevalence was to 21.0% in the period 1988-1994, decreasing to 17.0% in 1999-2004, representing a relative decline of 19% between the two surveys. [...] The seroprevalence of HSV-1 also decreased from 62% to 57.7% between the two surveys—a relative decrease of 6.9%. [...]
Genital HPV infections are the most prevalent STIs in the United States and in the world. HPV infections other than those causing genital warts (usually types 6 and 11) are nearly always subclinical, not recognized by the infected individual. By screening for HPV DNA every 3 months, using PCR amplification tests, the cumulative incidence of genital HPV infections in one study was 43% over a 3-year period in one study of sexually active female University students127 and 32% over a 2-year period in another.128 [...] A recent pooled analysis showed the age standardized prevalence of all types of HPV infection to vary 20-fold among different regions of the world.130 The prevalence of high risk types of the virus was 18% in sub-Saharan Africa, 5% in Asia, 10% in South America, and 4% in Europe. The prevalence of HPV infection is highest among young women and appears to drop-off with increasing age.131 [...] Risk factors for HPV infection include increased number of sex partners, increased number of male partners’ lifetime partners, a short-time interval between meeting a partner and engaging in sexual intercourse, increased age difference between partners, and current smoking.128 [...] Based on these preliminary findings from cohort studies, and together with data from national surveys of sexual behavior [...] it is not unlikely that the majority of adults in the United States, perhaps three-quarters, have been infected with one or more types of genital HPV.”
18. “Worldwide, more men than women report multiple partnerships except in some industrialized countries, where the proportions of men and women who report multiple partnerships are similar.10 The mean age difference between married men and women is lower in industrialized countries (1.9 in Australia and 2.2 in United States) than in developing countries; data are not available on age differences between sex partners. According to a recent review153 of estimates of lifetime, prevalence of men having had sexual intercourse with other men is lower in industrialized countries (6% in the UK and 5% in France) than in most other regions of the world. Rates of condom use are generally higher in industrialized countries than in developing countries, especially in women.10 The increase in condom use in recent years has also often been more substantial in industrialized countries; the only exception to this pattern is France where women have reported declining condom use in more recent years.”
19. “Historically, the predominant focus of STI epidemiology has been on the attributes and behaviors of individuals, and on the risk of acquiring, rather than of transmitting infection. This approach is consistent with the approaches of clinical medicine, chronic disease epidemiology, and psychology. However, when considered as the “sole” or “main” focus, it appears to be inconsistent with STI transmission dynamics190 and it has been increasingly challenged in recent years. The new paradigm includes at least three principles: that one person’s health outcome is highly dependent on other person’s health outcomes;191,192 that transmission of infection and its prevention is at least as important and perhaps more important than acquisition of infection and its prevention—thus focusing attention on infected individuals and the role they play in the spread of infection; that characteristics of sex partners and partner selection processes are an important component of risk determination—thereby focusing on behaviors of sex partners as well.186
20. “The inadequacy of the STD health service infrastructure and the resulting preventable increment in duration of infectiousness is a major reason why the United States has the highest rates of STIs among developed countries.”
21. “In the light of all these considerations, it is obvious that in evaluating behavioral interventions to prevent STIs, and HIV, data from randomized controlled trials are particularly important, the choice of outcome measure is critical, and the outcome measure of choice is the appropriate biomedical measure of the STI or STIs of interest.264,270
Most evaluations of behavioral interventions to date have employed less rigorous study designs and behavioral outcome measures. A systematic review of computerized abstracts from International AIDS conferences between 1989 and 1992 showed that only 10 of 15,946 abstracts reported on randomized controlled trials of behavioral interventions.264 Two subsequent critical reviews of behavioral interventions in general and behavioral interventions for young people reported similar findings.271,272 These reviews also indicated that many behavioral intervention studies focused only on determinants of behavior such as knowledge, beliefs, and attitudes as outcome measures. [...] In the past 2 decades a number of behavioral intervention trials have been conducted including those mentioned above. Many of these studies showed efficacy in reducing risky behaviors, and a smaller number showed efficacy in reducing incidence of bacterial STI in study subjects. Interestingly, to date, no cluster randomized trial of behavioral interventions (where at least one arm of the study represented a behavioral intervention) has showed significant impact at the population level.”
Stuff
I don’t like when the blog isn’t updated for several days, so here are some links to stuff I’ve encountered on the internet in the recent past:
i. Diabetic Autonomic Neuropathy. An overview article which covers a lot of ground; it has approximately 1000 citations and I believe it’s one of the most read articles published in Diabetes Care, a journal you incidentally should know about if you’re diabetic or are interested in diabetes.
ii. Also diabetes-related and closely related to the above paper: The EKG in Diabetes Mellitus. This article is particularly relevant to me because I had an EKG last week and will be told the results of it tomorrow where I have a doctor’s appointment – reading stuff like this first makes it easier to ask the right questions. I jokingly explained to a friend yesterday that if the results of that test come out a specific way, it will be much easier for me to make pension plans (meaning I’d most likely be dead long before the official retirement age – naturally I do not hope for that outcome to happen). I’ll also learn the results of the standard Hba-1c blood test – which is measured 3-4 times a year – as well as the annual urin-sample analysis to check for microalbuminuria (kidney damage). Also, cholesterol levels and triglycerides. So I’ll learn more from this check-up than I usually do. I hope everything is fine but there’s a reason why they perform tests like these; I have no way of knowing myself if there’s a problem here.
Anyway, a few quotes from the paper:
“Fibrotic changes, especially in the basal area of the left ventricle, have frequently been observed in diabetic patients, even when cardiac involvement is clinically not yet evident. [...] The EURODIAB Insulin-Dependent Diabetes Mellitus Complications Study (EURODIAB IDDM)9 investigated 3250 type 1 diabetes patients with an average diabetes duration of >30 years; the prevalence of left ventricular hypertrophy was found to be 3 times greater than that reported in the general population of similar age. [...] Baroreflex dysfunction and disturbed heart rate variability are the most commonly used methods to assess CAN [Cardiovascular autonomic neuropathy, US]. [...]
Ong et al14 found the QTc to be shorter if patients had signs of neuropathy, although these patients’ heart rate was higher and their circadian patterns seemed to be preserved. Valensi et al15 found an unchanged QTc in mild neuropathy, although the circadian day/night QTc pattern was reversed. Pappachan et al16 expressed the view that the QTc interval can be used to diagnose CAN with reasonable sensitivity, specificity, and positive predictive value. Grossmann et al17 observed a prolonged QTc only in diabetic patients with CAN; late potentials were not recorded in any of these patients with CAN. CAN patients with prolonged variability in QTc, QT, or both had high incidence of sudden death.18 [...]
Myocardial ischemia is more often painless in patients with diabetes mellitus.19 Resting ECG abnormalities20 as well as cardiac autonomic dysfunction21 were found to be predictors of silent ischemia in asymptomatic persons with T1D.
In otherwise healthy diabetic men during an average follow-up of 16 years, an abnormal and even an equivocal exercise ECG response was associated with a statistically significant high risk for all-cause and cardiac mortality and morbidity, independently of physical fitness and other traditional risk factors; fit men had a higher survival rate than did unfit men.22 [One more reason why I shouldn't have that much trouble motivating myself to stay in shape.] [...]
The early stage of diabetic cardiomyopathy may already be associated with a range of metabolic abnormalities and even with abnormalities in diastolic function. Frequently, no structural cardiac abnormalities can be identified at this stage; the often subtle ECG alterations may be our only way to diagnose early diabetic cardiomyopathy. [...]
Conclusions
Even early in the course of diabetes mellitus, ECG alterations such as sinus tachycardia, long QTc, QT dispersion, changes in heart rate variability, ST-T changes, and left ventricular hypertrophy may be observed. ECG alterations help evaluate cardiac autonomic neuropathy and detect signs of myocardial ischemia even in asymptomatic patients. Prolonged myocardial fibrosis leads to diabetic cardiomyopathy, with peculiar ECG presentation. Electrocardiographic changes are already present in fetuses, children, and adolescents. The resting ECG, frequently complemented by exercise ECG, assists in cardiac screening of diabetic individuals and helps detect silent ischemia, assess prognosis, and predict mortality”
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iii. Boredom Proneness: Its Relationship to Psychological- and Physical-Health Symptoms, by Sommers and Vodanovich.
“The relationship between boredom proneness and health-symptom reporting was examined. Undergraduate students (N 5 200) completed the Boredom Proneness Scale and the Hopkins Symptom Checklist. A multiple analysis of covariance indicated that individuals with high boredomproneness total scores reported significantly higher ratings on all five subscales of the Hopkins Symptom Checklist (Obsessive–Compulsive, Somatization, Anxiety, Interpersonal Sensitivity, and Depression). The results suggest that boredom proneness may be an important element to consider when assessing symptom reporting. Implications for determining the effects of boredom proneness on psychological- and physical-health symptoms, as well as the application in clinical settings, are discussed.”
I had no idea there was such a thing as a ‘Boredom Proneness Scale’! I found the literature overview in the beginning of the paper much more interesting than the study itself (one word: WEIRD). Judging from the reported results there, if you’re bored a lot and/or have a really boring job you may be well advised to do something about that – because being bored is associated with a lot of bad stuff:
“To date, the work on boredom proneness has focused on its association with negative affect, as well as problems in academic and work settings. For instance, significant positive relationships have been found between the tendency to experience boredom and depression, anxiety, hostility, anger, loneliness, and hopelessness (e.g., Ahmed, 1990; Farmer & Sundberg, 1986; Rupp & Vodanovich, 1997; Vodanovich, Verner, & Gilbride,
1991; Watt & Davis, 1991). Other researchers have reported boredom proneness to be related significantly to lower educational achievement, truancy rate, and poor work performance (e.g., Branton, 1970; Drory, 1982; Gardell, 1971; Maroldo, 1986; O’Hanlon, 1981; Robinson, 1975; Smith, 1981).
Limited work, however, has been devoted to investigating the association between boredom and psychological- and physical-health symptoms. Evidence for such a relationship can be inferred from studies reporting significant, positive correlations between boredom and substance abuse and eating disorders (e.g., Abramson & Stinson, 1977; Ganley, 1989; Johnston & O’Malley, 1986; Martin, 1989; Pascale & Sylvester, 1988).
Other researchers have established a connection between boredom and detrimental health effects in organizational settings. For instance, Smith, Cohen, and Stammerjohn (1981) found that workers in monotonous jobs reported more visual, musculoskeletal, and emotional-health complaints than those performing non-monotonous work. Samilova (1971) found that female Russian workers employed in repetitive tasks experienced higher incidence of health problems, including gastritis, peripheral neurological disorders, and joint, tendon, muscle, and cardiovascular disease, than workers in less-repetitive jobs. Ferguson (1973) found that telegraphists who complained of task monotony indicated a greater occurrence of physical-health problems, such as asthma, bronchitis, trunk myalgia, and hand tremors, as compared to other workers in less-monotonous positions.”
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iv. Ideology, Motivated Reasoning, and Cognitive Reflection: An Experimental Study. I haven’t actually gotten around to reading this yet, but I bookmarked it for a reason; I probably will later during the week.
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v. Media Use Among White, Black, Hispanic, and Asian American Children, by Rideout, Lauricella and Wartella. I’ve written about that stuff before but I haven’t written about this data. It’s survey data so it should be taken with a grain of salt. Even if it is, however, I think there’s some interesting information here. Some stuff from the report:
“Historically, scholars have been aware of differences in the amount of time that White and minority children spend with media, especially TV. But last year’s Generation M2 study indicated a large increase in the amount of time both Black and Hispanic youth are spending with media, to the point where they are consuming an average of 13 hours worth of media content a day (12:59 for Blacks and 13:00 for Hispanics), compared with about eight and a half hours (8:36) for White youth, a difference of about four and a half hours a day.” [my emphasis] [...]
The biggest differences are in the amount of time spent with a TV (a difference of about one to two hours of TV a day between White and minority youth), music (a difference of about an hour a day), computers (up to an hour and a half difference), and video games (from 30 to 40 minutes difference).”
Here’s the ‘big picture’, click to view full size:
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vi. I really, truly dislike (and that’s putting it mildly) the new format for the discover magazine blogs, but I really liked this post by Razib Khan. Then again it was posted before the switch. I like a lot of his stuff so I tend not to link to individual posts (I’d have to link to a lot of stuff…) but I figure I should remind you now and then that you should be reading his blog. Even if the new format sucks.
Absolute Risk of Suicide After First Hospital Contact in Mental Disorder
This new article is rather awesome, if for no other reason then because it involves so many people and follow them over such a long time-frame:
“Objective To estimate, in a national cohort, the absolute risk of suicide within 36 years after the first psychiatric contact.
Design Prospective study of incident cases followed up for as long as 36 years. Median follow-up was 18 years.
Setting Individual data drawn from Danish longitudinal registers.
Participants A total of 176 347 persons born from January 1, 1955, through December 31, 1991, were followed up from their first contact with secondary mental health services after 15 years of age until death, emigration, disappearance, or the end of 2006. For each participant, 5 matched control individuals were included.”
176.347 people followed for roughly two decades on average. That’s a lot of data. What did they find? Some of the main results:
“Results Among men, the absolute risk of suicide (95% confidence interval [CI]) was highest for bipolar disorder, (7.77%; 6.01%-10.05%), followed by unipolar affective disorder (6.67%; 5.72%-7.78%) and schizophrenia (6.55%; 5.85%-7.34%). Among women, the highest risk was found among women with schizophrenia (4.91%; 95% CI, 4.03%-5.98%), followed by bipolar disorder (4.78%; 3.48%-6.56%). In the nonpsychiatric population, the risk was 0.72% (95% CI, 0.61%-0.86%) for men and 0.26% (0.20%-0.35%) for women. Comorbid substance abuse and comorbid unipolar affective disorder significantly increased the risk. The co-occurrence of deliberate self-harm increased the risk approximately 2-fold. Men with bipolar disorder and deliberate self-harm had the highest risk (17.08%; 95% CI, 11.19%-26.07%).”
As mentioned they of course they didn’t just limit themselves to following ‘the sick people’ – they also needed people to compare them with… So:
“To estimate the cumulative incidence of suicide among people with no history of mental illness, we adopted a slightly alternative strategy. For each person with a history of any mental illness (as defined in the“Assessment of Suicide and Mental Illness” subsection), we randomly selected 5 people of the same sex and same birth date who had no history of mental illness (time matched). Using the described strategy, we followed up this healthy population (881 735 persons) to provide absolute suicide risks. Because this healthy population was selected at random among all 2.46 million people included in the study population, the estimates obtained represent the absolute risk of suicide among all 2.46 million people without a mental disorder.”
Again, that’s a lot of data – representativeness really is unlikely to be an issue here (at least when dealing with the situation in Denmark). As they put it in the paper: “This is the first analysis of the absolute risk of suicide in a total national cohort of individuals followed up from the first psychiatric contact, and it represents, to our knowledge, the hitherto largest sample with the longest and most complete follow-up.”
Results in a bit more detail:
(click to view full size). I’ve previously seen it argued in papers on anorexia that it’s the phychiatric disorder with the highest mortality rate, so I was a bit surprised by the relatively low numbers here. On the other hand that may be related to the fact that they tend to starve themselves to death rather than take their own lives in the traditional sense, which means that a lot of those excess deaths are not considered suicides. Note that a big majority of all suicides committed are committed by people with a mental illness and that the risk increase from a diagnosis is really quite significant; given the estimates, females with a mental illness are more than 8 times as likely to kill themselves than females without a mental illness, and males are 6 times more likely. Schizophrenic females are almost 20 times as likely to commit suicide than are females without a mental illness. Add substance abuse as well and these females are more than 30 times as likely to commit suicide (the absolute risk is around 7% in that case). The risk is substantially increased for almost all groups when you add substance abuse.
Do also note that not all people in the ‘mental illness’ group are actually people with a mental illness; personality disorders are not usually considered mental illnesses by health professionals, but the study includes in the group of people with mental illnesses people with: “any mental illness (any ICD-8 or ICD-10 code) if they had been admitted to a psychiatric hospital or had been in outpatient care with one of these diagnoses.” (The “any ICD-8 or ICD-10 code” means that people with personality disorders are included in the group as well). This is probably ‘fair enough’ given that at least some of these groups clearly have elevated suicide levels, but it’s worth having in mind that it should change the interpretation slightly. How about people who’ve attempted suicide?
The deliberate self-harm/attempted suicide group is obviously a high-risk group. The follow-up period is shorter than for the other estimates (30 years, rather than 36) so these estimates are perhaps best thought of as lower bounds. There’s some uncertainty regarding the estimates because the sample sizes aren’t that big (which is a good thing I think…), but roughly 1 in 6 Danish males with bipolar affective disorder killed themselves during the period. The absolute risks here are substantial; for the ‘any mental illness’ group, one in 12 committed suicide during the period. Although the female numbers are substantially lower for the group as a whole, for some illnesses the absolute risk is comparable to that of the males (and the excess risk much, much higher). More than one in ten females with schizophrenia and a suicide attempt in the past committed suicide during the follow-up period.
I should perhaps mention here that there may be some significant tail risk unaccounted for in the data, despite the long follow-up period which might lead you to think these are good estimates of the ‘lifetime probability of suicide’. The suicide-rate of Danish males above the age of 85 is the highest of all age groups, and it’s five times as high as the suicide risk of males at the age of 25-29 (Danish link). This is not just a Danish thing – similar dynamics have been observed elsewhere. Age matters a lot here, but people tend to care less when old people kill themselves than when young people do.
Stuff
i. Temporal view of the costs and benefits of self-deception, by Chance, Nortona, Ginob, and Ariely. The abstract:
“Researchers have documented many cases in which individuals rationalize their regrettable actions. Four experiments examine situations in which people go beyond merely explaining away their misconduct to actively deceiving themselves. We find that those who exploit opportunities to cheat on tests are likely to engage in self-deception, inferring that their elevated performance is a sign of intelligence. This short-term psychological benefit of self-deception, however, can come with longer-term costs: when predicting future performance, participants expect to perform equally well—a lack of awareness that persists even when these inflated expectations prove costly. We show that although people expect to cheat, they do not foresee self-deception, and that factors that reinforce the benefits of cheating enhance self-deception. More broadly, the findings of these experiments offer evidence that debates about the relative costs and benefits of self-deception are informed by adopting a temporal view that assesses the cumulative impact of self-deception over time.”
A bit more from the paper:
“People often rationalize their questionable behavior in an effort to maintain a positive view of themselves. We show that, beyond merely sweeping transgressions under the psychological rug, people can use the positive outcomes resulting from negative behavior to enhance their opinions of themselves—a mistake that can prove costly in the long run. We capture this form of self-deception in a series of laboratory experiments in which we give some people the opportunity to perform well on an initial test by allowing them access to the answers. We then examine whether the participants accurately attribute their inflated scores to having seen the answers, or whether they deceive themselves into believing that their high scores reflect new-found intelligence, and therefore expect to perform similarly well on future tests without the answer key.
Previous theorists have modeled self-deception after interpersonal deception, proposing that self-deception—one part of the self deceiving another part of the self—evolved in the service of deceiving others, since a lie can be harder to detect if the liar believes it to be true (1, 2). This interpersonal account reflects the calculated nature of lying; the liar is assumed to balance the immediate advantages of deceit against the risk of subsequent exposure. For example, people frequently lie in matchmaking contexts by exaggerating their own physical attributes, and though such deception might initially prove beneficial in convincing an attractive prospect to meet for coffee, the ensuing disenchantment during that rendezvous demonstrates the risks (3, 4). Thus, the benefits of deceiving others (e.g., getting a date, getting a job) often accrue in the short term, and the costs of deception (e.g., rejection, punishment) accrue over time.
The relative costs and benefits of self-deception, however, are less clear, and have spurred a theoretical debate across disciplines (5–10). [...]
As we had expected, social recognition exacerbated self-deception: those who were commended for their answers-aided performance were even more likely to inflate their beliefs about their subsequent performance. The fact that social recognition, which so often accompanies self-deception in the real world, enhances self-deception has troubling implications for the prevalence and magnitude of self-deception in everyday life.”
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ii. Nonverbal Communication, by Albert Mehrabian. Some time ago I decided that I wanted to know more about this stuff, but I haven’t really gotten around to it until now. It’s old stuff, but it’s quite interesting. Some quotes:
“The work of Condon and Ogston (1966, 1967) has dealt with the synchronous relations of a speaker’s verbal cues to his own and his addressee’s nonverbal behaviors. One implication of their work is the existence of a kind of coactive regulation of communicator-addressee behaviors which is an intrinsic part of social interaction and which is certainly not exhausted through a consideration of speech alone. Kendon (1967a) recognized these and other functions that are also served by implicit behaviors, particularly eye contact. He noted that looking at another person helps in getting information about how that person is behaving (that is, to monitor), in regulating the initiation and termination of speech, and in conveying emotionality or intimacy. With regard to the regulatory function, Kendon’s (1967a) findings showed that when the speaker and his listener are baout to change roles, the speaker looks in the direction of his listener as he stops talking, and his listener in turn looks away as he starts speaking. Further, when speech is fluent, the speaker looks more in the direction of his listener than when his speech is disrupted with errors and hesitations. Looking away during these awkward moments implies recognition by the speaker that he has less to say, and is demanding less attention from his listener. It also provides the speaker with some relief to organize his thoughts.
The concept of regulation has also been studied by Scheflen (1964, 1965). According to him, a communicator may use changes in posture, eye contact, or position to indicate that (1) he is about to make a new point, (2) he is assuming an attitude relative to several points being made by himself or his addresse, or (3) he wishes to temporarily remove himself from the communication situation, as would be the case if he were to select a great distance from the addressee or begin to turn his back on him. There are many interesting aspects of this regulative function of nonverbal cues that have been dealt with only informally. [...]
One of the first attempts for a more general characterization of the referents of implicit behavior and, therefore, possibly of the behaviors themselves, was made by Schlosberg (1954). He suggested a three-dimensional framework involving pleasantness-unpleasantness, sleep-tension, and attention-rejection. Any feeling could be assigned a value on each of these three dimensions, and different feelings would correspond to different points in this three-dimensional space. This shift away from the study of isolated feelings and their corresponding nonverbal cues and toward a characterization of the general referents of nonverbal behavior on a limited set of dimensions was seen as beneficial. It was hoped that it could aid in the identification of large classes of interrelated nonverbal behaviors.
Recent factor-analytic work by Williams and Sundene (1965) and Osgood (1966) provided further impetus for characterizing the referents of implicit behavior in terms of a limited set of dimensions. Williams and Sundene (1965) found that facial, vocal, or facial-vocal cues can be categorized primarily in terms of three orthogonal factors: general evalution, social control, and activity.
For facial expression of emotion, Osgood (1966) suggested the following dimensions as primary referents: pleasantness (joy and glee versus dread and anxiety), control (annoyance, disgust, contempt, scorn, and loathing versus dismay, bewilderment, surprise, amazement, and excitement), and activation (sullen anger, rage, disgust, scorn, and loathing versus despair, pity, dreamy sadness, boredom, quiet pleasure, complacency, and adoration). [...]
Scheflen (1964, 1965, 1966) provided detailed observations of an informal quality on the significance of postures and positions in interpersonal situations. Along similar lines, Kendon (1967a) and Exline and his colleagues explored the many-faceted significance of eye contact with, or observation of, another [...] These investigations consistently found, among same-sexed pairs of communicators, that females generally had more eye contact with each other than did males; also, members of both sexes had less eye contact with one another when the interaction between them was aversive [...] In generally positive exchanges, males had a tendency to decrease their eye contact over a period of time, whereas females tended to increase it (Exline and Winters, 1965). [...]
extensive data provided by Kendon (1967a) showed that observation of another person duing a social exchange varied from about 30 per cent of 70 per cent, and that corresponding figures for eye contact ranged from 10 per cent to 40 per cent. [...]
Physical proximity, touching, eye contact, a forward lean rather than a reclining position, and an orientation of the torso toward rather than away from an addressee have all been found to communicate a more positive attitude toward him. A second set of cues that indicates postural relaxation includes asymmetrical placement of the limbs, a sideways lean and/or reclining position by the seated communicator, and specific relaxation measures of the hands or neck. This second set of cues relates primarily to status differences between the communicator and his addressee: there is more relaxation with an addressee of lower status, and less relaxation with one of higher status. [...]
In sum, the findings from studies of posture and position and subtle variations in verbal statements [...] show that immediacy cues primarily denote evaluation, and postural relaxation ues denote status or potency in a relationship. It is interesting to note a weaker effect: less relaxation of one’s posture also conveys a more positive attitude toward another. One way to interpret this overlap of the referential significance of less relaxation and more immediacy in communicating a more positive feeling is in terms of the implied positive connotations of higher status in our culture. A respectful attitude (that is, when one conveys that the other is of higher status) does indeed have implied positive connotations. Therefore it is not surprising that the communication of respect and of positive attitude exhibits some similarity in the nonverbal cues that they require. However, whereas the communication of liking is more heavily weighted by variations in immediacy, that of respect is weighted more by variations in relaxation.”
I should probably note here that whereas it makes a lot of sense to be skeptical of some of the reported findings in the book, simply to get an awareness of some of the key variables and some proposed dynamics may actually be helpful. I don’t know how deficient I am in these areas because I haven’t really given body language and similar stuff much thought; I assume most people haven’t/don’t, but I may be mistaken.
…
iii. A friend let me know about this ressource and I thought I should share it here. It’s a collection of free online courses/lectures provided by Yale University.
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iv. Prevalence, Heritability, and Prospective Risk Factors for Anorexia Nervosa. It’s a pretty neat setup: “During a 4-year period ending in 2002, all living, contactable, interviewable, and consenting twins in the Swedish Twin Registry (N = 31 406) born between January 1, 1935, and December 31, 1958, underwent screening for a range of disorders, including AN. Information collected systematically in 1972 to 1973, before the onset of AN, was used to examine prospective risk factors for AN.”
“Results The overall prevalence of AN was 1.20% and 0.29% for female and male participants, respectively. The prevalence of AN in both sexes was greater among those born after 1945. Individuals with lifetime AN reported lower body mass index, greater physical activity, and better health satisfaction than those without lifetime AN. [...]
[...]
This study represents, to our knowledge, the largest twin study conducted to date of individuals with rigorously diagnosed AN. Our results confirm and extend the findings of previous studies on prevalence, risk factors, and heritability.
Consistent with several studies, the lifetime prevalence of AN identified by all sources was 1.20% in female participants and 0.29% in male participants, reflecting the typically observed disproportionate sex ratio. Similarly, our data show a clear increase in prevalence of DSM-IV AN (broadly and narrowly defined) with historical time in Swedish twins. The increase was apparent for both sexes. Hoek and van Hoeken3 also reported a consistent increase in prevalence, with a leveling out of the trajectory around the 1970s. Future studies in younger STR participants will allow verification of this observation.
Several observed differences between individuals with and without AN were expected, ie, more frequent endorsement of symptoms of eating disorders. Other differences are noteworthy. Consistent with previous observations, individuals with lifetime AN reported lower BMIs at the time of interview than did individuals with no history of AN. Although this could be partially accounted for by the presence of currently symptomatic individuals in the sample, our results remained unchanged when we excluded individuals likely to have current AN (ie, current BMI, ≤17.5). Previous studies have shown that, even after recovery, individuals with a history of AN have a low BMI.59 Although perhaps obvious, a history of AN appears to offer protection against becoming overweight. The protective effect also holds for obesity (BMI, ≥30), although there were too few individuals in the sample with histories of AN who had become obese for meaningful analyses. Despite the obvious nature of this observation, the mechanism whereby protection against overweight is afforded is not immediately clear. Those with a history of AN reported greater current exercise and a perception of being in better physical health. One possible interpretation of this pattern of findings is that individuals with a history of AN continue to display subthreshold symptoms of AN (ie, excessive exercise and caloric restriction) that contribute to their low BMIs. Alternatively, symptoms that were pathologic during acute phases of AN, such as excessive exercise and decreased caloric intake, may resolve over time into healthy behaviors, such as consistent exercise patterns and a healthful diet, that result in better weight control and self-rated health.
Regardless of which of these hypotheses is true, another intriguing difference is that individuals with lifetime AN report a lower age at highest BMI, although the magnitude of the highest lifetime BMI does not differ in those with and without a history of AN. Those with AN report their highest lifetime BMIs early in their fourth decade of life on average, whereas those without AN report their highest BMIs in the middle of their fifth decade of life (close to the age at interview). On a population level, adults tend to gain on average 2.25 kg (5 lb) per decade until reaching their eighth decade of life.60 Although more detailed data are necessary to make definitive statements about different weight trajectories, our results suggest not only that individuals with AN may maintain low BMIs but also that they may not follow the typical adult weight gain trajectories. These data are particularly intriguing in light of recent reports of AN being associated with reduced risk of certain cancers61 - 62 and protective against mortality due to diseases of the circulatory system.63 - 64 Energy intake is closely related to fat intake and obesity, both of which have also been related to cancer development65 - 66 and both of which are reduced in AN. Further detailed studies of the weight trajectories and health of individuals with histories of AN are required to explicate the nature and magnitude of these intriguing findings.
Of the variables assessed in 1972 to 1973, neuroticism emerged as the only significant prospective predictor of AN. This is notable because there have been few truly prospective risk factor studies of AN.”
…
v. The music is a bit much for me towards the end, but this is just an awesome video. I think I’d really have liked to know that guy:
…
vi. Political Sorting in Social Relationships: Evidence from an Online Dating Community, by Huber and Malhotra.
I found these data surprising (and I’m skeptical about the latter finding):
“Among paid content, online dating is the third largest driver of Internet traffic behind music and games (Jupiter Research 2011).A substantial number of marriages also result from interactions started online. For instance, a Harris Interactive study conducted in 2007 found that 2% of U.S. marriages could be traced back to relationships formed on eHarmony.com, a single online dating site (Bialik 2009).”
Anyway I’ll just post some data/results below and leave out the discussion (click to view tables in full size). Note that there are a lot of significant results here:
The last few figures are also interesting (people really care about that black/white thing when they date (online)…). but you can go have a look for yourself. As I’ve already mentioned there are a lot of significant results – they had a huge number of data to work with (170,413 men and 132,081 women).
…
Some data on life expectancy variation
From this WHO paper. It has 254 pages and I haven’t read them all – neither should you, a lot of them are just pages of data. Anyway, some more stuff from the paper (click to view graphs and tables in full size):
“37 of the 40 countries with the lowest life expectancy are in Sub-Saharan Africa. HIV/AIDS is a major cause of the poor performance of many Africa countries in terms of health gains over the last decade or so. Overall, life expectancy in Sub-Saharan Africa has declined by 3-5 years in the 1990s due to increasing mortality from HIV/AIDS, with the estimated loss reaching 15-20 years in countries such as Botswana, Zimbabwe and Zambia.” [my emphasis] [...]
“Of the 10.5 million deaths below age 5 estimated to have occurred in 1999, 99% of them were in developing regions (3). The probability of child death (5qo) is typically less than 1% in industrialized countries classified into the A Regional Strata (and 0.5% in Japan), but rises to 300-350 per 1000 in Niger and Sierra Leone. Levels of child mortality well in excess of 10% (100 per 1000) are still common throughout Africa and in parts of Asia (Mongolia, Cambodia, Laos, Afghanistan, Bhutan, Myanmar, Bangladesh and Nepal).
However, perhaps the widest disparities in mortality occur at the adult ages 15-59 years. In some Southern African countries such as Zimbabwe, Zambia and Botswana, where HIV/AIDS is now a major public health problem, 70% or more of adults who survive to age 15 can be expected to die before age 60 on current mortality rates [in the late 80es, the number for Zimbabwe was 15-20%, see p.25 - US]. In several others (e.g. Malawi, Namibia and Uganda) the risk exceeds 60%. The dramatic increase in 45q15 in South Africa is also noteworthy, with estimated levels of 601 per 1000 and 533 per 1000 for males and females respectively in 1999. At the other extreme, 45q15 levels of 90-100 per 1000 are common in most developed countries for men, with risks as low as half this again for women. [...] HIV/AIDS was the cause of about 2.2 million deaths in Africa in 1999, making it by far the leading cause of death on the continent.”
There’s a lot of variation in mortality rates:
…and Africa is not the only region that’s doing badly: “The extraordinary risks of premature adult death among men in Eastern Europe is also clear from the Figure, (EUR C Region) with more than 1 in 3 who survive to age 15 in this Region likely to die before reaching age 60, at current risks compared with 10-12% in Western Europe, Japan and Australia.”
…
“Globally, some 56 million people are estimated to have died in 1999, 10.5 million below age five years. More males (29million) then females (27million) died, reflecting the systematically higher death rates for males at all ages in almost all countries. [...] Worldwide, deaths at ages 15-59 in 1999 amounted to an estimated 15.5 million, (9 million males, 6.5 million females), but with wide uncertainty. By any definition, these deaths (28% of the total over all ages) must be considered premature.”
…
The Danish life tables are at page 112 and I decided to post them below. The US life tables are at page 245. More fine-grained and newer US data are also available here.
Which variables are reported above? Well: “For each age, estimates of central death rates (nMx), the probability of dying (nqx), number of survivors (lx), and expectation of life (ex) are shown.” (p. 19) I didn’t have a clue what the ‘central death rate’ is but luckily one can look that kind of stuff up:
“For a given population or cohort, the central death rate at age x during a given period of 12 months is found by dividing the number of people who died during this period while aged x (that is, after they had reached the exact age x but before reached the exact age x+1) by the average number who were living in that age group during the period.”
Do remember when looking at numbers such as these that it’s not just about how long you live – how you die matters a great deal.
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