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:

Divorce 1

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:

Divorce 2

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.

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.

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.

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):

Computer and internet
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:

Active internet users


Internet subscribers
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…).

June 12, 2013 Posted by | data, demographics, statistics | Leave a comment


I have a paper deadline approaching, so I’ll be unlikely to blog much more this week. Below some links and stuff of interest:

i. Plos One: A Survey on Data Reproducibility in Cancer Research Provides Insights into Our Limited Ability to Translate Findings from the Laboratory to the Clinic.

“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.”

ii. The development in the number of people killed in traffic accidents in Denmark over the last decade (link):

Traffic accidents
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.

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…

iv. Some Khan Academy videos of interest:

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:

Anderson et al

“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.”

May 22, 2013 Posted by | data, demographics, economics, Khan Academy, marriage, medicine, papers | Leave a comment

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:

Support for sharia

Sharia apply only to muslims

What do sharia supporters want

Right to choose veil and wife must obey

Religious freedom

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.


Honour killings

May 2, 2013 Posted by | data, demographics, islam | Leave a comment


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).

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.

iii. A couple of Khan Academy videos:

iv. PlosOne: Sex Differences in Mathematics and Reading Achievement Are Inversely Related: Within- and Across-Nation Assessment of 10 Years of PISA Data.

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.”

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.”

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.

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.”

viii. I’m very surprised they did not already know this.

April 3, 2013 Posted by | data, demographics, diabetes, genetics, Khan Academy, papers, personal | Leave a comment

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.

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%.

February 24, 2013 Posted by | data, demographics, immigration | Leave a comment

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.”

January 23, 2013 Posted by | books, data, demographics, Psychology | 4 Comments

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.”

January 21, 2013 Posted by | books, data, demographics, diabetes, health, marriage, Psychology | Leave a comment

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.”

January 20, 2013 Posted by | books, data, demographics, marriage, Psychology | Leave a comment

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 of the book. 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 they’ve covered this stuff 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.

December 18, 2012 Posted by | biology, books, data, demographics, health, statistics | Leave a comment

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.”

December 6, 2012 Posted by | books, data, demographics, health, health care, medicine | Leave a comment


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. […]


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”

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.”

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.

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:

media expo

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.

December 4, 2012 Posted by | data, demographics, diabetes, papers, personal, Psychology, random stuff | Leave a comment

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.

November 14, 2012 Posted by | data, demographics, health | Leave a comment

Danish education – some numbers

The data included in this post are from Statistics Denmark, Statistikbanken – “KRHFU1: Befolkningens højeste fuldførte uddannelse (15-69 år) efter område, herkomst, uddannelse alder og køn.” I had a look at the documentation and most of the data are registry data, but the data on immigrants are survey-based (and thus less reliable) – no surveys have been conducted since 2006, so all immigrants who’ve arrived since then have an ‘unknown education level’ in the data. If you’re more curious about that subject I presented some other, much more detailed, data on the same topic a while ago here. If you disaggregate the data on immigrants and descendants, the image looks worse than it does here because descendants of Western immigrants have a different age profile than do descendants of non-Western immigrants – one third of descendants of Western immigrants are above the age of 30, whereas only 6% of non-Western descendants are that old (also, only 10% of all descendants in Denmark have reached the age of 30). Another aspect adding to the confusion is the fact that Western immigrants are quite well educated, which contributes to the confusion about the numbers – if you look at ‘Danish immigrants’, you’re basically mixing data drawn from two completely different distributions.

If you want to know more about the Danish education system this link may be of some use (note that there’s a lot of additional stuff in the sidebar there). Regarding the higher education stuff, a short-cycle higher education is at most two years long, a medium-cycle higher education is from 2-4 years long. The latter differs from a ‘standard’ Danish bachelor’s degree: “Professionally oriented higher education programmes are offered at colleges. Whereas in other countries, similar programmes may be offered by universities, in Denmark they have traditionally been offered by specialised colleges” (from the link). Long-cycle higher education corresponds to a Master’s degree. Click to view graphs in full size. All data reported are from the 2012 data sets. There aren’t all that many data included in this post, but part of the reason is that the source only gave the raw data – not percentage stuff (which is much more informative) – and variable transformations take time. Anyway…

So, let’s have a look at the data… I figured it’d be interesting to look at the first cohort of ‘young people’ (30-34) consisting of people about whom we can say with relative certainty that almost all of them have completed their formal education. I’ll start out with the males:

Descendant n is not that high compared to the other groups, but I think it’s ‘high enough to draw conclusions’ from the data (n=3041). Descendants are more than twice as likely to not get any education aside from grundskole than are people of Danish origin. What about the females?

Females are more likely to get an education so the numbers generally look better. When including all groups, 17,7% of males and 12,9% of females end up with only grundskole – it’s a significant difference, but it’s not actually that high compared to some of the variation we see in these data. The female descendants (n=2873) are roughly twice as likely to only have a grundskole education (22.8% vs 11,9%) as are people of Danish origin. Male immigrants were much less likely to have attended vocational school than were males of Danish origin; that difference is almost gone when we’re looking at the females. As I’ve mentioned elsewhere, do have in mind that a lot of those ‘unknown education level’ immigrants are people with very little education, and/or education which is not worth a lot on the Danish labour market – immigrants who’ve studied here have known education levels, and most of the people with an unknown education level aren’t highly educated foreigners who love the Danish weather and our marginal tax rates.

Education rates have increased over time. Below I’ve compared the numbers for males at the age of 65-69 with the 30-34 year old cohort. I didn’t really see why I should care about the education levels of immigrants or descendants in that age group, so I only included people of Danish origin:

Note here that the mandatory education level back then was lower than it is now (7 years vs 9 years), so most of the people in this graph with only grundskole education have spent less time in school than have the groups in the sections above. The numbers are not identical, but they’re not that different given how much the educational system changed over that 35 year period. I think it’s interesting that ‘only high school’ (or technical/trade high school) was a less likely scenario for people in this group than for the younger generation, but on the other hand it’s not surprising.

How about the females?

The difference is significant. The number of uneducated women has been reduced dramatically and the number of females who are highly educated has gone up a lot. The proportion of 30-34 year old females of Danish origin with a long-cycle higher education is higher than the proportion of males of Danish origin with a long-cycle higher education (15.6% vs 13.2%). The same pattern is seen in the younger 25-29 year old cohort: In that age group, 6,86% of males of Danish origin (n=8791) have completed a long-cycle higher education, whereas the corresponding number for females of Danish origin (n=10168) is 8,22% (which is a 20% difference). Here’s a mapping of all relevant cohorts included in the data set:

It’s well known that females are more likely to get a medium-cycle higher education than are males (n=34921 or 25,6% of females and n=14750 or 10,6% of males at the ages of 30-34 have such an education), so I decided to also look at the proportion of the genders with any type of higher education (short-cycle, medium-cycle, bachelor, long-cycle or PhD) and condition on age. A lot of people would probably be surprised to learn that it looks this way:

In case you want to argue that the short-cycle ones are roughly equivalent to vocational schooling (‘females take short-cycle higher educations where males take vocational schooling’), it’s worth noting that for all age groups males are more likely to get a short-cycle higher education than are females. No, the difference derives from the other categories. It seems that females are better educated than males on average and have been for decades – I did not expect that.

The dataset also includes some information about geographical variation. The percentage of people with a long-cycle higher education varies a lot:

(Wikipedia can help you if you don’t know anything about the Danish regions). If you meet a random person above the age of 30 on the street, he or she is more than three times as likely to have a long-cycle higher education if the person is from Copenhagen than if the person is from the Region of Southern Denmark. If you restrict your search to include only people drawn from the younger cohorts, the differences become even larger. If you scale down further and look at the differences at the municipal level, they are just huge; to take but one example, 3,1% of Danes above 30 years of age from the Jammerbugt municipality have a long-cycle higher education, whereas the corresponding number for people living in the Gentofte municipality is 29,6%.

November 8, 2012 Posted by | data, demographics, education | 2 Comments


i. Contradictory Messages: A Content Analysis of Hollywood-Produced Romantic Comedy Feature Films.

“This study analyzed the romantic content of a sample of 40 romantic comedy films using a basic grounded theory methodology. Analyses revealed that such films appear to depict romantic relationships as having qualities of both new and long-term relationships; that is, to be both novel and exciting, yet emotionally significant and meaningful. Furthermore, relationships were shown to have both highly idealistic and undesirable qualities but, for any problems or transgressions experienced to have no real negative long-term impact on relationship functioning. The potential for viewer interpretations is discussed and the need for future research highlighted. […]

Of the 107 [romantic] gestures coded, male characters performed 90, they gave 35 of 37 gifts, performed 14 of 17 favors, and took more steps to initiate relationships (63 of 84). Such a proportion of effort could lead to the distinguishing of gender roles, identifying the man’s role to ‘‘take the lead’’ when it comes to relationships. A further implication could be female adolescent viewers’ forming of somewhat idealized relationship expectations. With films depicting male characters as frequently performing exaggeratedly romantic gestures […], female adolescents may be led to believe that such behaviors are the norm. Furthermore, by preferring to focus on behaviors between couples such as the aforementioned, it is possible that such films may make these gestures more salient to adolescents as an indication of the extent of partners’ feelings for them and the quality of the relationship itself over factors such as communication and trust.

Although there were 61 coded instances of ‘‘open about feelings and intentions,’’ there were only 4 incidents coded pertaining to trust, with 3 of these demonstrating a character’s lack of trust in their partner. […] The lack of depiction of trust becomes particularly notable when looking at the number of incidents of ‘‘deception’’ coded. There were 82 such incidents, occurring across all 40 films, ranging from white lies so as to spare partners’ feelings, to more serious acts of deception such as ulterior motives and direct lying for personal gains. These far outweighed characters confessing their lies and deceptive acts to their partners (9), with lies being discovered by partners typically by chance or indeed not at all. […]

Another category to emerge at this stage of coding that may have the potential to influence viewer perceptions was ‘‘being single.’’ Although this was one of the smaller categories, each coded incident (15) was consistently negative. Individuals who were single were depicted as either lonely and miserable […], frustrated […], or made to feel insecure […]. Two films […] even suggested that being single might interfere with career progression. Such a consistently negative representation of being single could, therefore, have the potential to negatively influence viewers’ feelings toward being single themselves. […]

It should be further noted that of the incidents of affection coded, a vast minority occurred between married couples. Married couples were typically portrayed as either unhappy with their spouse […], or were implied as happy but did little to reflect this […]. Of the depictions of affection between married couples that were coded, many were interspersed with episodes of arguing […], and most were limited to gestures such as brief kisses or standing with an arm around one other. Such a representation of marriage may leave adolescent viewers to see marriage and romance as disparate entities and with affection between married couples as an exception instead of the norm. […]

What is interesting to note about the behaviors comprising this category [‘relationship issues’], however, is that, irrespective of seriousness, there appeared to be no real consequences for characters’ transgressions in their relationships. […] Such depictions do not accurately reflect the actual emotions individuals typically experience in response to acts of deception and betrayal in their relationships, which can involve feelings of hurt, anger, resentment, and relational devaluation (Fitness, 2001). As a result, with characters’ negative behaviors either going undiscovered or having no long-lasting impact on their relationships, adolescent viewers may underestimate the consequences their behaviors can have on their own relationships.”

ii. The burden of knowledge and the ‘death of the renaissance man’: Is  innovation getting harder? by Benjamin Jones.

“This paper investigates, theoretically and empirically, a possibly fundamental aspect of technological progress. If knowledge accumulates as technology progresses, then successive generations of innovators may face an increasing educational burden. Innovators can compensate in their education by seeking narrower expertise, but narrowing expertise will reduce their individual capacities, with implications for the organization of innovative activity – a greater reliance on teamwork – and negative implications for growth. I develop a formal model of this “knowledge burden mechanism” and derive six testable predictions for innovators. Over time, educational attainment will rise while increased specialization and teamwork follow from a sufficiently rapid increase in the burden of knowledge. In cross-section, the model predicts that specialization and teamwork will be greater in deeper areas of knowledge while, surprisingly, educational attainment will not vary across fields. I test these six predictions using a micro-data set of individual inventors and find evidence consistent with each prediction. The model thus provides a parsimonious explanation for a range of empirical patterns of inventive activity. Upward trends in academic collaboration and lengthening doctorates, which have been noted in other research, can also be explained by the model, as can much-debated trends relating productivity growth and patent output to aggregate inventive effort. The knowledge burden mechanism suggests that the nature of innovation is changing, with negative implications for long-run economic growth.”

iii. The Basic Laws of Human Stupidity.

iv. Beyond Guns and God, Understanding the Complexities of the White Working Class in America. I haven’t read it and I don’t think I will, but I thought I should put the link up anyway. The link has a lot of data.

v. Some Danish church membership numbers. The site is in Danish but google translate is your friend and there isn’t much text anyway. Where I live almost 5 out of 6 people are members of the church. Over the last 20 years the national membership rate has dropped by ~0,5 percentage points/year. 4 out of 5 Danes are members of the national church, in 1990 it was 9 out of 10. Approximately 90% of the people who die are members, whereas ‘only’ approximately 70% of children being born get baptized. Children of non-Western immigrants make up less than 10% of all births (9,1% from 2006-2010) – so even though population replacement may be part of the story, there’s likely other stuff going on as well.

vi. Intelligence: Knowns and Unknowns. I may blog this in more detail later, for now I’ll just post the link.

vii. Theodore Dalrymple visited North Korea in 1989. The notes here about his visit to Department Store Number 1 are worth reading.

October 11, 2012 Posted by | culture, data, demographics, IQ, papers, Psychology, religion | Leave a comment

Reading habits of Americans

Here’s Pew’s report on the subject. I’ve included some numbers from the report below. Click to view tables in full size.

When interpreting the numbers in the post, do have in mind that people often lie about their reading habits. Also note that this may be an extremely biased sample; the cooperation rate is around 20% and the combined response rate was around 12,5% (1 in 8). I don’t know what kind of cooperation rate you usually get out of surveys like these, but my first instinct is to be critical seeing numbers like those; there may be a lot of stuff going on behind the scenes (out of sample). Anyway, ‘to the data…’:

About 1 in 5 didn’t read a book over the last 12 months, whereas about a third read 1-5. Approximately two-thirds read less than one book a month on average. But the interesting part to me was how many belonged in the category 11-50; about one in 4. That’s a lot more than I’d have thought. The 5% in the 50+ is also significantly higher than I’d have thought; I read 14 hours yesterday, I’m at maybe 30 hours this week so far (including all book reading, including ‘work book reading’ – though I must hasten to add that not all work is ‘book reading’) and I don’t think I’m even close to reading that many books over the course of a year. Of course ‘not all books are the same’, but even so. Not surprisingly the distribution is somewhat skewed: The mean was 17 books and the median was 8.

Females read more, old people read more and people who’ve been to college read more than people who have not. I thought it was interesting here that if you include education income is insignificant.

They do provide a more detailed picture of the number of books read. Of the people who read at least one book over the last 12 months, 8% had read one book, 17% had read 2-3 books, 16% had read 4-5 books, 19% had read 6-10, 18% had read 11-20 books and  22% had read more than 20 books. This means that 31% read 1-5 books per year (‘infrequent readers’), 28% read 6-20 (‘medium readers’) and only 17% (~1 in 6) of the population read more than 20 books per year (‘frequent readers’).

“A fifth of Americans (18%) said they had not read a book in the past year. This group is more likely to be: male than female (23% vs. 14%), Hispanic than white or black (28% vs. 17% and 16%), age 65 or older (27%), lacking a high school diploma (34%), living in households earning less than $30,000 (26%), unemployed (22%), and residents of rural areas 25%. Those who did not read a book last year also tended not to be technology users.”

I found none of those associations to be the least bit surprising.

58% regularly read daily news or newspapers. 48% regularly read magazines or journals. Even though it makes sense I did find it interesting that income becomes significant when looking at those numbers even when you account for education.

“Altogether, 43% of Americans age 16 and older have read long-form writing in digital format as of December 2011 – either e-books or newspaper or magazine material in digital form. We get that figure by combining those in the December survey who have read e-books with the 31% of those who regularly read news content and have read that content in digital format and the 16% who read magazines and journals and have read that content in digital format.
Those who have taken the plunge into reading e-books stand out in almost every way from other kinds of readers. They read more books than other readers. They read more frequently and are more likely than others to read for more purposes. They consume books in all formats, including print and audio: 88% of those who read e-books in the past 12 months also read print books. But they are also more likely than others to have bought their most recent book, rather than borrowed it, and they are more likely than others to say they prefer to purchase books.
Demographically, as of February 2012, the adults age 18 and older who read e-books are disproportionately likely to be under age 50, with higher levels of education and income.”

“64% of those 16 and older said they get book recommendations from family members, friends, or co-workers. […] 28% said they get recommendations from online bookstores or other websites. […] 23% said they get recommendations from staffers in bookstores they visit in person. […] 19% said they get recommendations from librarians or library websites.”

About one in four to one in five got recommendations from staffers in bookstores. I was surprised the number is that high. Some more detail: “Those most likely to get recommendations this way include: college graduates (28%), those living in households earning more than $75,000 (30%), parents of minor children (27%), technology owners and users, urban and suburban residents, and those under age 65.” The ‘college graduates’ really surprised me, as did the income one. The income one can perhaps be explained in terms of higher search costs because of higher opportunity cost of time but that’s not exactly convincing. Maybe it’s a ‘what are smart, rich, successful, educated people like me supposed to be reading these days’-effect?

I didn’t really care about the gadget stuff in the report but some of you may find that interesting.

September 27, 2012 Posted by | books, data, demographics | 5 Comments

Sociosexuality from Argentina to Zimbabwe: A 48-nation study of sex, culture, and strategies of human mating

Real life takes up most of my time these days and I’m only posting this because I haven’t posted in a few days. Anyway, I found this paper and I thought some of you might be interested. Note that the sample sizes are generally very small (# of males from Brazil included? 39. Finland? 28. France? 47) and that “the ISDP samples were primarily college students” (p. 269) – so it’s probably a good idea to be very cautious when interpreting the results. Unfortunately Finland is the only Scandinavian country included in the analysis. Anyway, some stuff from the paper:

“Abstract: The Sociosexual Orientation Inventory (SOI; Simpson & Gangestad 1991) is a self-report measure of individual differences in human mating strategies. Low SOI scores signify that a person is sociosexually restricted, or follows a more monogamous mating strategy. High SOI scores indicate that an individual is unrestricted, or has a more promiscuous mating strategy. As part of the International Sexuality Description Project (ISDP), the SOI was translated from English into 25 additional languages and administered to a total sample of 14,059 people across 48 nations. Responses to the SOI were used to address four main issues. First, the psychometric properties of the SOI were examined in cross-cultural perspective. The SOI possessed adequate reliability and validity both within and across a diverse range of modern cultures. Second, theories concerning the systematic distribution of sociosexuality across cultures were evaluated. Both operational sex ratios and reproductively demanding environments related in evolutionary-predicted ways to national levels of sociosexuality. Third, sex differences in sociosexuality were generally large and demonstrated cross-cultural universality across the 48 nations of the ISDP, confirming several evolutionary theories of human mating. Fourth, sex differences in sociosexuality were significantly larger when reproductive environments were demanding but were reduced to more moderate levels in cultures with more political and economic gender equality. Implications for evolutionary and social role theories of human sexuality are discussed.” […]

“On average, men tend to possess more positive attitudes toward casual, low-investment sex than women do (Carrol et al. 1985; Fisher et al. 1988; Hendrick et al. 1985; Oliver & Hyde 1993; Townsend 1995; Wilson 1987). Men also report that they fantasize about having sex with multiple partners more than women do (Ellis & Symons 1990; Malamuth 1996), and men behaviorally seek short-term mateships more than women do (Blumstein & Schwartz 1994; Eysenck 1976; Laumman et al. 1994; Wiederman 1997). Experimental tests have further confirmed that men are more likely than women to consent to sex with a stranger when approached in a community setting (Clark & Hatfield 1989), even when the stranger is “vouched for” by a participant’s same-sex friend (Clark 1990). […]

This pervasive pattern of sexual differences – across attitudes, fantasy, and behavior – implies that men should be higher or more unrestricted on sociosexuality than women. Indeed, the direct evidence on this point is unequivocal, at least in United States. In every study published to date, American men report higher levels of sociosexuality than American women based on responses to the SOI. […]

(click to view full size)

“sex differences in sociosexuality appear to be culturally universal (at least across the spectrum of modern ISDP nations) […] The hypothesis that men should be more unrestricted than women across cultures is fundamental to several evolutionary theories of human mating (e.g., Buss & Schmitt 1993). In support of this perspective, men were more unrestricted than women across all nations of the ISDP. This tended to be true when looking at means, medians, and distributions; when looking at sociosexual attitudes and behaviors; and – most importantly – the magnitude of this difference was moderate to large in size regardless of the moderating effects of culture. Overall, the average mean-level man scored about three-quarters of a standard deviation higher on the SOI than the average mean-level woman – one of the largest and most robust cross-cultural differences ever documented in the sexuality literature (Oliver & Hyde 1994). In addition, based on ANOVA methods, the overall effect size of biological sex is quite large (η^2 =  0.15), more than double the more moderate effect size of nation (η^2 = 0.06).” […]

Among the 48 nations of the ISDP, the five nations with the highest levels of gender equity ratings on the United Nations Gender Development Index are Australia (d = 0.66), Canada (d = 0.75), the United States (d = 0.73), Belgium (d = 0.69), and the Netherlands (d = 0.76). In each nation, sex differences in sociosexuality are conspicuous, ranging from moderate to large in size. Relatively egalitarian sexual standards and gender role beliefs for men and women in modern cultures, therefore, may attenuate sex differences in sociosexuality, but they appear unlikely to reduce them to less than moderately-sized magnitudes of effect. […] The current findings do suggest that women’s sociosexual attitudes and behaviors will get closer to men’s as gender equality becomes more common, but it seems unlikely that men and women would ever possess precisely equal levels of sociosexuality.”

Do note that the study itself is only half or so of the text in the link – the latter half is commentary and criticism provided by other people in the field.

September 12, 2012 Posted by | biology, data, demographics, evolution, Psychology, studies | 2 Comments


i. Population pyramids. Pretty neat. A few examples below. First, the world population pyramid, 2010:

Here’s how it looked like in 1950:

Here’s the population pyramid for Western Africa, 1950:

And here’s how it looks today:

No, I didn’t copy the same image twice. When you’re at the site and click from one version to the other you can spot the difference, but it’s not easy if you’re just comparing the images even if you look carefully. Try to compare that ‘development’ with what happened in Western Europe. First 1950:

Notice the ‘hole’ in the middle? It looks really strange. I wonder what happened 30-35 years before 1950 that might have impacted birth rates so significantly… Here’s how the pyramid looked like in 2010:

The site has more.

ii. The case for personal responsibility?

iii. Vihart has a new cute doodling in math class video up:

iv. I want to play this game at some point (while in the presence of at least one female. Otherwise it’d probably just be weird). Any ideas on how best to implement elo-difference-related handicaps here?

v. I linked to the Vice Guide to North Korea a long time ago. By accident I came across the site again recently, and I liked this video:

vi. The short version of why I may not ‘work blog’ the paper I’m reading right now:

I may decide to blog it anyway and just talk my way around the math, I haven’t decided yet. Much of the stuff the paper covers is also covered to some extent in the paper I linked to earlier today, so that’s certainly a better place to start for people with a time constraint who are curious to know more about these things.

Incidentally while reading the second paper a hidden assumption that had crept into my first work blog post became apparent to me for some reason. I wrote that the article I covered was “an overview article that can be read by pretty much anyone who understands English”. This is not true and I should have known better. I measured the Gunning fog index of my own post about the article and that came out at about 15,2 or so (‘the index estimates the years of formal education needed to understand the text on a first reading’). Surely the article itself has a lower readability level than my blog post about it.

I know that most of you know this, but maybe it’s worth rehashing even so: I’m not a journalist, and I will generally neither think about nor care about how ‘readable’ my stuff, or the stuff I link to, is. That’s not to say I do not try hard to be very precise when it comes to terminology and choice of words and so on.

vii. This is an awesome video:

The future is now.

September 5, 2012 Posted by | blogging, demographics, economics, mathematics, random stuff | 2 Comments


i. I was considering covering this study in a bit more detail, but I decided against it because workplace filters probably would not like it very much – it would contain words such filters do not like (no, I’m not thinking of words like ‘sociodemographic characteristics’ or ‘multiple regression analyses’). I know a few people sometimes read my blog from work and if you’re one of them, let me just say that you should probably not read this while at work.

ii. Population Trends in the Incidence and Outcomes of Acute Myocardial Infarction

“The age- and sex-adjusted incidence of myocardial infarction increased from 274 cases per 100,000 person-years in 1999 to 287 cases per 100,000 person-years in 2000, and it decreased each year thereafter, to 208 cases per 100,000 person-years in 2008, representing a 24% relative decrease over the study period. […]

The proportion of patients who underwent revascularization within 30 days after myocardial infarction increased from 40.7% in 1999 to 47.2% in 2008 (P<0.001 for trend). Among patients with ST-segment elevation myocardial infarction, 49.9% underwent revascularization in 1999 as compared with 69.6% in 2008 (P<0.001 for trend). Among patients with non–ST-segment elevation myocardial infarction, 33.4% underwent revascularization in 1999 as compared with 41.3% in 2008 (P<0.001 for trend) […]

The proportion of patients with myocardial infarction who were known to have undergone troponin I testing increased from 53% in 1999 to 84% in 2004, with stable testing rates between 2004 and 2008. […]

The age- and sex-adjusted 30-day mortality after myocardial infarction decreased from 10.5% in 1999 to 7.8% in 2008 (P<0.001 for linear trend). This decrease was driven by the case fatality rate for non–ST-segment elevation myocardial infarction, which decreased from 10.0% to 7.6% (P<0.001 for trend); there was no significant change over time for ST-segment elevation myocardial infarction (P = 0.81). The multivariable adjusted odds ratio for death at 30 days after myocardial infarction was 0.76 (95% confidence interval [CI], 0.65 to 0.89) in 2008 as compared with 1999.”

Short version: Fewer people got a(n ST-segment elevation) myocardial infarction even though more people were subjected to fancy testing, more people got access to fancy treatment, and the people in the sample who got a non-ST-segment MI during the study period were less likely to die from it. But…

“observed reductions in case fatality rates could be attributable to secular trends in ascertainment of myocardial infarction and decreased severity on presentation, as well as any improvements in management of acute myocardial infarction.44 The observation that mortality after ST-segment elevation myocardial infarction (which is less influenced by the use of highly sensitive biomarkers) did not decrease over time provides support for this hypothesis.”

This could still be considered good news because if decreased severity on presentation reduces mortality it’s probably a good idea to at least have a closer look at that variable; on the other hand it’s bad news because fancy testing is expensive. Another thing:

“given the integrated medical care delivery structure in the health system that we studied and the magnitude of recent improvements in the control of risk factors within our population, our results may not be fully generalizable to other health care settings.”

Good luck finding MSM-coverage of the study including this part. I’d probably have removed the word ‘fully’. The population risk factor development during the period is a major confound.

iii. International migration: A panel data analysis of the determinants of bilateral flows by Anna Maria Mayda.

Click to view full size. From the paper:

“According to the international migration model, pull and push factors have either similarsized effects (with opposite signs), when migration quotas are not binding, or they both have no (or a small) effect on emigration rates, when migration quotas are binding. It is not clear, ex ante, which one of the two scenarios characterizes actual flows. Migration policies in the majority of destination countries are very restrictive, which should imply binding constraints on the number of migrants. On the other hand, even countries with binding official immigration quotas often accept unwanted (legal) immigration.8 Restrictive immigration policies are often characterized by loopholes, that leave room for potential migrants to take advantage of economic incentives. […]

My empirical analysis also finds that inequality in the source and host economies is related to the size of emigration rates as predicted by Borjas (1987) selection model. An increase in the origin country’s relative inequality has a non-monotonic effect on the size of the emigration rate: the impact is estimated to be positive if there is positive selection, negative if there is negative selection. Among the variables affecting the costs of migration, distance between destination and origin countries appears to be the most important one: Its effect is negative, significant and steady across specifications. On the other hand, there is no evidence that cultural variables related to each country pair play a significant role. Demographics – in particular, the share of the origin country’s population who is young – shape bilateral flows as predicted by the theory. Since the effect of geography and demographics works through the supply side of the model, their impact should be even stronger when migration quotas are relaxed, which is what I find in the data. […]

Since immigrants are likely to receive support from other immigrants from the same origin country already established in the host country, they will have an incentive to choose destinations with larger communities of fellow citizens. Network effects imply that bilateral migration flows are highly correlated over time, which is what the data shows.”

iv. Via npr:

“It’s a sound you would never want to hear in real life, but this a safe way to eavesdrop. Just one warning: For the first two minutes of this video, nothing happens, nothing I could hear, anyway. Then there’s a countdown, and at 2:24 from the top … the bomb bursts; at 2:54 the blast hits.”

v. Does Thinking Really Hard Burn More Calories? Interesting piece. Unfortunately(?), “for most people, the body easily supplies what little extra glucose the brain needs for additional mental effort.”

I would be very interested in seeing a study on this including type 1 diabetics. Hard thinking for extended periods of time – like, say, a four-hour chess game or an exam – impacts my blood glucose in a very significant way; it drops like a stone if I don’t take precautions. This is despite the fact that hard thinking under such circumstances is often, as mentioned in the article, linked to stress and the release of cortisol, one of the primary functions of which is to increase blood sugar.

vi. TV from a different world:

August 3, 2012 Posted by | biology, data, demographics, immigration, science, studies | Leave a comment

How couples meet

Click to view full-size (the same goes for the data posted below). The figure is from Searching for a Mate: The Rise of the Internet as a Social Intermediary, by Rosenfeld and Thomas.

“we show that gays, lesbians, and middle aged heterosexuals- three groups who inhabit thin markets for romantic partners- are particularly likely to have found their partners online. Individuals are in a thin market for potential partners when the cost of identifying multiple potential partners who meet minimum criteria may be large enough to present a barrier to relationship formation. We propose that for single adults in thin dating markets, improvements in the efficiency of Internet search may be especially useful and important. Conversely, single people (college students, for example) who are fortunate enough to inhabit an environment full of eligible potential partners may not need to actively search for partners at all.”

The last part of that sentence had me laughing, but it’s an interesting paper. Of course in general they’re probably right – in the discussion they note that:

“Young heterosexual adults, who we presume to be among the most technologically savvy people in society, are among the least likely to meet partners online. Young adults have single others all around them which renders the search advantages of the Internet mostly irrelevant. In environments rich with potential partners, old fashioned face-to-face socializing still trumps online search.”

Here’s another interesting observation:

“Searching the personal advertisements in the pre-Internet era meant thumbing through the newspaper classified section by hand. Print advertisements could only be examined one issue at a time. Perhaps that is why only 4 out of 3,009 couples in the dataset reported meeting through the newspaper classifieds (even though a majority of the sample met before the Internet era).”

Lastly, some tables from the paper:

(there’s basically no difference)

Note that there’s again pretty much no difference. Only the ‘met-through-friends’-variable was significant for the adjusted odds ratio measure and maybe that’s just a fluke. The raw ‘met-in-church’ odds ratio is highly significant, but once you control for relationship duration, children, race, religion and other stuff, the effect disappears completely.

July 4, 2012 Posted by | data, dating, demographics, papers | 4 Comments


i. From The future of infectious diseases. Watch it.:

“Take home messages:

  • You can watch evolution in progress in quickly-reproducing organisms, like malaria
  • Over 100,000 Americans die of infections that were easily treated 30 years ago due to the evolution of resistance (twice the number of people who will die in car crashes).
  • In an arms race between us and infectious diseases, we lose.
  • We need to understand the evolutionary forces unleashed by medicine before we can manage infectious disease
  • We need to ask, “Will (this drug) STAY safe, and CONTINUE to work”, not just if it is safe and whether it will work.
  • The Lancet (a high impact medical journal) rejected an evolutionary paper addressing malaria because, “a good understanding of evolutionary biology is beyond most of our readers.””

Point 3 is one I try to remember to bring up every time I find myself in a discussion about matters related to how the future development of medicine will look like. Unless you do not agree with that one, it’s very hard to be an optimist about the future of medicine.

ii. I discussed this subject briefly yesterday, and I later started thinking about whether I’d actually blogged this (pdf) publication (in Danish, sorry), PISA København 2010, which deals with the educational achievements of Danish children in Copenhagen who left the 9th grade in 2010. I don’t think I have (I couldn’t find anything in the archives), so I decided to add a link here as well as a few observations from the paper:

“Opdeles eleverne efter andelen af indvandrerelever på deres skoles niende klassetrin, finder man generelt, at jo større andel af indvandrere, des lavere gennemsnitlig læsetestscore.” (a (loose) translation: ‘If the students are distributed according to the proportion of immigrant-pupils in the 9th grade, a general finding is that the larger the share of immigrants, the lower the average reading test score’).

Immigrant groups perform worse than non-immigrant groups, and the proportion of immigrants also affects the performance of the non-immgrant pupils (negatively) for some, though not all, specifications. The ‘Danish’ pupils enrolled in schools where the proportion of immigrant pupils exceeds 50% do significantly worse than do Danish pupils who are enrolled in schools where the immigrant pupil proportion is below 25% (p.11). Immigrant pupils also do better in schools with less than 25% immigrants than they do in schools where the proportion of immigrant pupils exceeds that number (p.11).

A table from the report (p.31), click to view full size:

The above table contains some numbers related to PISA’s reading test, with a special focus on the proportion of pupils in the sample who are functionally illiterate, corresponding to a reading performance of less than level 2 on the PISA scale (which is described in more details in the Appendix, p. 82-83 – I will not go into details here unless asked). In 2010, 14% of ‘Danish’ pupils and 42% of ‘immigrant pupils’ from schools in Copenhagen were functionally illiterate judging from the PISA reading test. There’s a big gender gap – 17% of the girls and 30% of the boys were functionally illiterate. The difference between the performances of first (44%) and second (41%) generation immigrant pupils is not statistically significant. Almost half of all 9th grade immigrant pupils in the public school system – 48% of first generation immigrant pupils in public schools and 46% of second generation immigrant pupils in public schools – were functionally illiterate.

There’s a lot of hidden variation in the immigrant numbers and not all immigrant groups do equally badly. It’s worth having in mind that these results are actually averages. Taking not-insignificant heterogeneity in the immigrant sample into account, it’s surely the case that some immigrant groups do even worse than these numbers might imply. If you look at the school level, some of the numbers probably get much worse. The Rockwool Foundation found in 2007 that 64% of pupils of Arab origin in the 9th grade were functionally illiterate (Danish link). In the PISA report they don’t go into much details, but they do note that pupils of Lebanese (/Palestinians), Iraqi and Turkish origin do worse than do pupils of Pakistani origin (also from p. 11).

iii. Another paper, Moral Hypocrisy, Power and Social Preferences, by Rustichini and Villeval (via Robin Hanson):

“Abstract: We show with a laboratory experiment that individuals adjust their moral principles to the situation and to their actions, just as much as they adjust their actions to their principles. We first elicit the individuals’ principles regarding the fairness and unfairness of allocations in three different scenarios (a Dictator game, an Ultimatum game, and a Trust game). One week later, the same individuals are invited to play those same games with monetary compensation. Finally in the same session we elicit again their principles regarding the fairness and unfairness of allocations in the same three scenarios.

Our results show that individuals adjust abstract norms to fit the game, their role and the choices they made. First, norms that appear abstract and universal take into account the bargaining power of the two sides. The strong side bends the norm in its favor and the weak side agrees: Stated fairness is a compromise with power. Second, in most situations, individuals adjust the range of fair shares after playing the game for real money compared with their initial statement. Third, the discrepancy between hypothetical and real behavior is larger in games where real choices have no strategic consequence (Dictator game and second mover in Trust game) than in those where they do (Ultimatum game). Finally the adjustment of principles to actions is mainly the fact of individuals who behave more selfishly and who have a stronger bargaining power.
The moral hypocrisy displayed (measured by the discrepancy between statements and actions chosen followed by an adjustment of principles to actions) appears produced by the attempt, not necessarily conscious, to strike a balance between self-image and immediate convenience.”

iv. False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant, by Simmons, Nelson and Simonsohn. A pretty neat paper:

In this article, we accomplish two things. First, we show that despite empirical psychologists’ nominal endorsement of a low rate of false-positive findings (! .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates. In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not. We present computer simulations and a pair of actual experiments that demonstrate how unacceptably easy it is to accumulate (and report) statistically significant evidence for a false hypothesis. Second, we suggest a simple, low-cost, and straightforwardly effective disclosure-based solution to this problem. The solution involves six concrete requirements for authors and four guidelines for reviewers, all of which impose a minimal burden on the publication process.”

v. Cognitive Sophistication Does Not Attenuate the Bias Blind Spot, by West, Meserve & Stanovich:

“The so-called bias blind spot arises when people report that thinking biases are more prevalent in others than in themselves. Bias turns out to be relatively easy to recognize in the behaviors of others, but often difficult to detect in one’s own judgments. Most previous research on the bias blind spot has focused on bias in the social domain. In 2 studies, we found replicable bias blind spots with respect to many of the classic cognitive biases studied in the heuristics and biases literature (e.g., Tversky & Kahneman, 1974). Further, we found that none of these bias blind spots were attenuated by measures of cognitive sophistication such as cognitive ability or thinking dispositions related to bias. If anything, a larger bias blind spot was associated with higher cognitive ability. Additional analyses indicated that being free of the bias blind spot does not help a person avoid the actual classic cognitive biases. We discuss these findings in terms of a generic dual-process theory of cognition.”

I’ll just repeat part of that abstract: “none of these bias blind spots were attenuated by measures of cognitive sophistication such as cognitive ability or thinking dispositions related to bias. If anything, a larger bias blind spot was associated with higher cognitive ability.

A few other remarks from the paper (but do read all of it if you find the result interesting):

“the bias blind spot joins a small group of other effects such as myside bias and noncausal base-rate neglect (Stanovich & West, 2008b; Toplak & Stanovich, 2003) in being unmitigated by increases in intelligence. That cognitive sophistication does not mitigate the bias blind spot is consistent with the idea that the mechanisms that cause the bias are quite fundamental and not easily controlled strategically — that they reflect what is termed Type 1 processing in dual-process theory (Evans, 2008; Evans & Stanovich, in press). Two of the theoretical explanations of the effect considered by Pronin (2007)—naive realism and defaulting to introspection—posit the bias as emanating from cognitive mechanisms that are evolutionarily and computationally basic. Much research on the bias blind spot describes the asymmetry in bias detection in self compared to others as being spawned by a belief in naive realism—the idea that one’s perception of the world is objective and thus would be mirrored by others who are open-minded and unbiased in their views (Griffin & Ross, 1991; Pronin et al., 2002; Ross & Ward, 1996). Naive realism is developmentally primitive (Forguson & Gopnik, 1988; Gabennesch, 1990) and thus likely to be ubiquitous and operative in much of our basic information processing.

[rereading this, it reminded me of this quote, from a recent lesswrong article: “if you aren’t treating humans more like animals than most people are, then you’re modeling humans poorly. You are not an agenty homunculus “corrupted” by heuristics and biases. You just are heuristics and biases. And you respond to reinforcement, because most of your motivation systems still work like the motivation systems of other animals.”]

It is likewise with self-assessment based on introspective information, rather than behavioral information (Pronin & Kugler, 2007). The bias blind spot arises, on this view, because we rely on behavioral information for evaluations of others, but on introspection for evaluations of ourselves. The biases of others are easily detected in their overt behaviors, but when we introspect we will largely fail to detect the unconscious processes that are the sources of our own biases (Ehrlinger et al., 2005; Kahneman, 2011; Pronin et al., 2004; Wilson, 2002). When we fail to detect evidence of bias, we are apt to decide no bias has occurred and that our decision-making process was indeed objective and reasonable. This asymmetry in bias assessment information has as its source a ubiquitous and pervasive processing tendency— introspective reliance — that again is developmentally basic (Dennett, 1991; Sterelny, 2003).”

vi. Via Gwern, a meta-analysis on depression and exercise. There seems to be a short-term positive effect, but “there is little evidence of a long-term beneficial effect of exercise in patients with clinical depression.”

June 22, 2012 Posted by | data, demographics, education, papers, Psychology | 2 Comments