Health Online 2013 (Pew)

“Thirty-five percent of U.S. adults say that at one time or another they have gone online specifically to try to figure out what medical condition they or someone else might have.

These findings come from a national survey by the Pew Research Center’s Internet & American Life Project. Throughout this report, we call those who searched for answers on the internet “online diagnosers”.

When asked if the information found online led them to think they needed the attention of a medical professional, 46% of online diagnosers say that was the case. Thirty-eight percent of online diagnosers say it was something they could take care of at home and 11% say it was both or in-between.

When we asked respondents about the accuracy of their initial diagnosis, they reported:
41% of online diagnosers say a medical professional confirmed their diagnosis. An additional 2% say a medical professional partially confirmed it.
35% say they did not visit a clinician to get a professional opinion.
18% say they consulted a medical professional and the clinician either did not agree or offered a different opinion about the condition.
1% say their conversation with a clinician was inconclusive.

Women are more likely than men to go online to figure out a possible diagnosis. Other groups that have a high likelihood of doing so include younger people, white adults, those who live in households earning $75,000 or more, and those with a college degree or advanced degrees.”

The quotes above are from a Pew report, Health Online 2013, published earlier this year. Below I’ve added some more data from the report, as well as a few comments. You can click the tables to view them in a higher resolution.

“Looking more broadly at the online landscape, 72% of internet users say they looked online for health information of one kind or another within the past year. […] 77% of online health seekers say they began at a search engine such as Google, Bing, or Yahoo. Another 13% say they began at a site that specializes in health information, like WebMD. Just 2% say they started their research at a more general site like Wikipedia […] 39% of online health seekers say they looked for information related to their own situation. Another 39% say they looked for information related to someone else’s health or medical situation. […] As of September 2012, 81% of U.S. adults use the internet and, of those, 72% say they have looked online for health information in the past year. [Incidentally, according to this Pew report, the number of online Americans is actually 85%, but it’s in that neighbourhood… Note that 72% of 81% is just 58% (they say 59% in the report later, probably due to rounding) – so almost half of all Americans don’t look for health information online. That’s a lot of people.] […]

Online diagnosis and follow-up

Females are more likely to be online diagnosers, as are young people, whites, rich people, and college-educated individuals (when we compare the females with males, the young people with the old, the white people with the non-white, etc. See also the remarks in the update..). Note that education is basically a step-function here; the more education you get, all else equal the more likely you are to try to diagnose yourself online. Note also that some of these differences are really huge; roughly 10 percent of people without a HS diploma answered that they’d looked online to diagnose a condition during the last year, whereas half of all college-educated individuals answered in the affirmative.

Insured vs uninsured

A potentially important thing to have in mind when comparing the numbers for insured and uninsured individuals is that internet usage and health insurance status probably covary; I believe it’s likely that uninsured people are also less likely to use the internet. Low-income individuals with short educations are much less likely to be online, independent of age (see the link above).

“Twenty-six percent of internet users who look online for health information say they have been asked to pay for access to something they wanted to see online. […] Of those who have been asked to pay, just 2% say they did so. [I was very surprised that that number was strictly larger than zero…] Fully 83% of those who hit a pay wall say they tried to find the same information somewhere else. Thirteen percent of those who hit a pay wall say they just gave up. […] Respondents living in lower-income households were significantly more likely than their wealthier counterparts to say they gave up at that point. Wealthier respondents were the likeliest group to say they tried to find the same information elsewhere.”

Educ in detail

Do remember when looking at the numbers above that health status and education are related variables; lower educated people are more likely to be in poorer health than are higher educated people on average, in part because of lifestyle choices (I’ve written about these differences before – see e.g. this post (and note that there’s a lot of stuff in those links – and that I have a lot more links for you if you don’t find them satisfactory, as I’ve done academic work in this field and am quite familiar with the literature on the links between education and health.)). Yet even when conditioning on online status (low-educated individuals are less likely to be online), individuals with low educations are still, all other things being equal, much less likely than are the college educated to look online for many types of health information.

Update: To illustrate how much trouble you might get into if you don’t have in mind the differences in internet adoption rates across social strata, I decided to add a few more numbers. The numbers are from the Offline Adults report, to which I also link above:

Offline demographics

People without a high school diploma are roughly 10 times as likely not to use the internet as are people with a college degree; 41% of people without a HS diploma don’t use the internet – 4% of college-educated don’t. For individuals with an income below $30k, one in four don’t use the internet, whereas roughly 5% of those with an income north of $50k don’t. It’s very safe to say that not all subgroups included in some of the specific types of response data above are equally representative of the groups from which they are derived. Note also that potential drivers of the relevant intragroup differences here may be very important if one were to try to find ways to ‘bridge the information gap’; for example if some of the low-educated individuals who don’t use the internet can’t read, finding ways to provide them with internet access may not make much difference.

I should point out here that based just on the observations above it’s impossible to say anything about the details of what drives these results. It’s not clear e.g. how big a role the age variable plays when it comes to the contribution from income and education; old people on a pension have much lower incomes (but higher net savings) than most people who’re still active in the labour market (link), and older people are also significantly less likely to have college degrees and more likely to not have a high school diploma. The significance tests they report which are meant to indicate whether or not e.g. the results for people with an income of $30-50k are different from the results for people with incomes below $30k don’t take stuff like that into account, they’re just of a ‘let’s ignore everything else and compare the numbers’-kind and so can’t really be trusted. Maybe income doesn’t matter once you’ve taken age and education into account. I’m not saying this is the case, but given the data you can’t say if that’s true or not. Disentangling the ‘pure partial effects’ would be nice, but that’s likely to be a lot harder than it looks; multicollinearity is likely a problem, and some of the correlated regressors display non-linear relationships (e.g. income-age – see the link above). Be careful about which conclusions you draw.


October 14, 2013 Posted by | Data, Demographics, health | Leave a comment


i. I’ve played some good chess over the last few weeks. I’m currently participating in an unrated chess tournament –  the format is two games per evening (one with the white pieces and one with the black), with 45 minutes per person per game. The time control means that although the games aren’t rated, they’re at least long enough to be what I’d consider ‘semi-serious’.

Here’s a recent game I played, from that tournament – I was white. It wasn’t without flaws on my part but it was ‘good enough’ as he was basically lost out of the opening. I wasn’t actually sure if 7.Qd4 could be played (this should tell you all you need to know about how much I know about the Pirc…) but I was told after the game that it was playable – my opponent had seen it in a book before, but he’d forgotten how the theory went and so he made a blunder. It was the second game that evening, played shortly after I’d held my opponent, a ca. 2000 FIDE rated player, to a draw in the first game. I mention the first game also because I think it’s quite likely that the outcome of that game played a role in the mistake he made in the second game. The average rating of my opponents so far has been 1908 (I’ve also drawn a 2173 FIDE guy along the way, though the chess in that case was not that great), and I’m at +1 after six games. I’ve beaten FMs before in bullet and blitz, but as mentioned these games are a tad more serious than, say, random 3 minute games online, and this is one of the first times I’ve encountered opponents as strong as this in a ‘semi-serious’ setting. And I’m doing quite well. It probably can’t go on, but I’m enjoying it while it lasts.

ii. An interesting medical lecture about vaccines:

iii. Estimating Gender Disparities in Federal Criminal Cases.

“This paper assesses gender disparities in federal criminal cases. It finds large gender gaps favoring women throughout the sentence length distribution (averaging over 60%), conditional on arrest offense, criminal history, and other pre-charge observables. Female arrestees are also significantly likelier to avoid charges and convictions entirely, and twice as likely to avoid incarceration if convicted. Prior studies have reported much smaller sentence gaps because they have ignored the role of charging, plea-bargaining, and sentencing fact-finding in producing sentences. Most studies control for endogenous severity measures that result from these earlier discretionary processes and use samples that have been winnowed by them. I avoid these problems by using a linked dataset tracing cases from arrest through sentencing. Using decomposition methods, I show that most sentence disparity arises from decisions at the earlier stages, and use the rich data to investigate causal theories for these gender gaps.”

Here’s what she’s trying to figure out: “In short, I ask: do otherwise-similar men and women who are arrested for the same crimes end up with the same punishments, and if not, at what points do their fates diverge?”

Some stuff from the paper:

“The estimated gender disparities are strikingly large, conditional on observables. Most notably, treatment as male is associated with a 63% average increase in sentence length, with substantial unexplained gaps throughout the sentence distribution. These gaps are much larger than those estimated by previous research. This is because, as the sequential decomposition demonstrates, the gender gap in sentences is mostly driven by decisions earlier in the justice process—most importantly sentencing fact-finding, a prosecutor-driven process that other literature has ignored.

But why do these disparities exist? Despite the rich set of covariates, unobservable gender differences are still possible, so I cannot definitively answer the causal question. However, several plausible theories have testable implications, and I take advantage of the unusually rich dataset to explore them. I find substantial support for some theories (particularly accommodation of childcare responsibilities and perceived role differences in group crimes), but that these appear only to partially explain the observed disparities.” […]

“Columns 11-12 of Table 5 show that the gender gap is substantially larger among black than non-black defendants (74% versus 51%). The race-gender interaction adds to our understanding of racial disparity: racial disparities among men significantly favor whites,29 but among women, the race gap in this sample is insignificant (and reversed in sign). The interaction also offers another theory for the gender gap: it might partly reflect a “black male effect”—a special harshness toward black men, who are by far the most incarcerated group in the U.S. […] This theory only goes so far, however — the gender gap even among non-blacks is over 50%, far larger than the race gap among men.”

iv. Low glycaemic index, or low glycaemic load, diets for diabetes mellitus?

“Nutritional factors affect blood glucose levels, however there is currently no universal approach to the optimal dietary strategy for diabetes. Different carbohydrate foods have different effects on blood glucose and can be ranked by the overall effect on the blood glucose levels using the so-called glycaemic index. By contributing a gradual supply of glucose to the bloodstream and hence stimulating lower insulin release, low glycaemic index foods, such as lentils, beans and oats, may contribute to improved glycaemic control, compared to high glycaemic index foods, such as white bread. The so-called glycaemic load represents the overall glycaemic effect of the diet and is calculated by multiplying the glycaemic index by the grammes of carbohydrates.

We identified eleven relevant randomised controlled trials, lasting 1 to 12 months, involving 402 participants. Metabolic control (measured by glycated haemoglobin A1c (HbA1c), a long-term measure of blood glucose levels) decreased by 0.5% HbA1c with low glycaemic index diet, which is both statistically and clinically significant. Hypoglycaemic episodes significantly decreased with low glycaemic index diet compared to high glycaemic index diet. No study reported on mortality, morbidity or costs.”

v. I started reading Dinosaurs Past and Present a few days ago. It’s actually a quite short and neat book, but I haven’t gotten very far as other things have gotten in the way. I just noticed that a recently published PlosOne study deals with some of the same topics covered in the book – I haven’t read it yet but if you’re curious you can read the article on Forearm Posture and Mobility in Quadrupedal Dinosaurs here.

September 25, 2013 Posted by | Chess, Data, Diabetes, Immunology, Lectures, Medicine, Paleontology, Personal, Studies | Leave a comment


i. More U.S. Men Are Living Alone:

“The share of one-person households in the U.S. maintained by men ages 15 to 64 rose to 34% in 2012, up from 23% in 1970, according to a Census report on the status of families released Tuesday. For women of the same age, this figure actually dropped slightly, to 30% in 2012 from 31% in 1970.

The findings may reflect, in part, the sharp increase in divorce rates in the U.S. throughout the 1970s, Census said. The dominant living arrangement for children following their parents’ divorce is custody by mothers.”

I would have preferred to read the actual Census report and I did go have a look for it; but when I click the pdf link to the report in question at the census site all I get is an error message (link) – they seem to have put up a corrupt link. Annoying. Here are some related Danish numbers which I blogged a while ago. Although the 2012 report doesn’t seem to be available, there’s a lot of 2009-2011 data on related matters here. I messed around a little with that data – below some stuff from that source:

Naturally there’s a big gender disparity; at the age range of 24-29, 89.1% of males have never married whereas only 80,7% of the females have never married. For people in the 25-29 year age range 64% of males and 50,1% of females have never married. You’d expect the numbers to converge somewhat ‘over time’ (/as people get older) and they do, but not until we reach the age group of 55-64 year olds do the proportion of females who have never married surpass the proportion of males who have not (and these numbers are quite small – less than 9% have never married at that age, both when looking at males and females).

Higher earnings seem to confer an advantage when it comes to minimizing the risk of never getting married, which is of course a big surprise. For example, of the 45-49 year old people with a reported income of $25,000 to $39,999 17,6% of them have never married, whereas the corresponding number for people with an income of $40,000-75,000 is 11,5%. For people with incomes in the $75,000-$100,000 range the number is 5.5%, and incidentally the number of 45-49 year olds with incomes above $100k who’ve never married is also 5,5%. The relationship is not perfectly linear, but it’s clear that people with higher earnings have a higher likelihood of getting married. Incidentally almost a third of people in that age range who reported annual earnings less than $5000 have never married (29.2%).

The numbers above are from the first third of the first document. There’s a lot of data available here if you’re curious.

ii. Global Reality of Type 1 Diabetes Care in 2013. Not much to see here – here’s why I bookmarked it:

“from a global perspective, the most common cause of death for a child with type 1 diabetes is lack of access to insulin (2). Yet, this is not just a problem for low-income countries, with one recent study in the U.S. noting that discontinuation of insulin therapy represents the leading precipitating cause of diabetic ketoacidosis (3). Indeed, lack of insulin explained 68% of such episodes in people living in an inner-city setting, with approximately one-third of people reporting a lack of financial resources to buy insulin and eking out their insulin supplies.”

We’re talking about the United States of America, a very rich country – and in fact the country in the world with the highest health care expenditures. And still you have type 1 diabetics who go into ketoacidosis because they can’t afford their drugs. That’s messed up. Note that low medical subsidies to type 1s may not necessarily be cost saving at a systemic level as hospital admissions are very expensive; based on the average estimates at the link and these length of stay estimates, a back of the envelope estimate of the average cost of a DKA-related hospital admission would be $5.500. This estimate is probably too low as this study (which I may blog in more detail later) estimated non-compliance-related DKA-admissions to cost on average roughly $7.500 (and the non-compliance admissions were actually significantly cheaper than the other admissions on a per-case basis). To put this estimate into perspective, the mean annual cost of intensive diabetes care per diabetic patient in the U.S. is $4,000 (same link).

iii. Related to i., but I figured it deserved to be linked to separately: A theory of marriage, by Gary Becker.

iv. Some maps illustrating racial segregation patterns in the US. Don’t miss the sixth map of Detroit. The one of Saint Louis is also…

v. I haven’t used it much yet, so I don’t really know if it’s any good – but it looks interesting and I’ve missed such a resource. I sometimes feel a bit guilty about not working harder on improving my vocabulary, especially on account of the fact that I’ve basically ended up only speaking two languages – I used to speak French reasonably well, but that’s many years ago and at this point I’d rather spend time improving my English than spend a lot of effort on a third language which most likely will only be of very limited use to me.

vi. PLOS ONE: What Are You or Who Are You? The Emergence of Social Interaction between Dog and an Unidentified Moving Object (UMO). Here’s the abstract:

“Robots offer new possibilities for investigating animal social behaviour. This method enhances controllability and reproducibility of experimental techniques, and it allows also the experimental separation of the effects of bodily appearance (embodiment) and behaviour. In the present study we examined dogs’ interactive behaviour in a problem solving task (in which the dog has no access to the food) with three different social partners, two of which were robots and the third a human behaving in a robot-like manner. The Mechanical UMO (Unidentified Moving Object) and the Mechanical Human differed only in their embodiment, but showed similar behaviour toward the dog. In contrast, the Social UMO was interactive, showed contingent responsiveness and goal-directed behaviour and moved along varied routes. The dogs showed shorter looking and touching duration, but increased gaze alternation toward the Mechanical Human than to the Mechanical UMO. This suggests that dogs’ interactive behaviour may have been affected by previous experience with typical humans. We found that dogs also looked longer and showed more gaze alternations between the food and the Social UMO compared to the Mechanical UMO. These results suggest that dogs form expectations about an unfamiliar moving object within a short period of time and they recognise some social aspects of UMOs’ behaviour. This is the first evidence that interactive behaviour of a robot is important for evoking dogs’ social responsiveness.”

From the discussion:

“The aim of this study was to investigate whether dogs are able to differentiate agents on the basis of their behaviour and show social behaviours toward an UMO (Unidentified Moving Object) if the agent behaves appropriately in an interactive situation. In order to observe such interaction we modelled an experimental situation in which the dog is faced with inaccessible food. Miklósi et al [21] showed that in this case dogs increase their looking time at a human helper and show gaze alternation between the inaccessible food and the human. These observations have been replicated by Gaunet [23] and Horn et al [26], and the authors implicated that the dogs’ behaviour reflects communicative intentions. The present experiment showed that these behaviour features also emerge in the dogs while they are interacting with an UMO, moreover the onset of these behaviours is facilitated by the social features of the UMO: Dogs look longer and show more gaze alternation if the UMO carries eyes, shows variations in its path of movement, displays goal-directed behaviour and contingent reactivity (reacts to the looking action of the dog by retrieving the inaccessible food item).”

If you’re curious about how they actually did this stuff, don’t miss the neat video towards the end.

September 4, 2013 Posted by | Data, Demographics, Diabetes, marriage, Papers | Leave a comment

Handbook of critical care (1)

Here’s a link. From the description:

“Written as a teaching aid for residents and fellows in intensive care and emergency medicine, this revised edition of the Handbook of Critical Care is also a valuable reference for all medical professionals in the critical care team. The 15 chapters in this pocket-sized basic intensive care manual include eight substantial sections covering the major organ systems, as well as infection, nutrition, physical injury and toxicology, and brief chapters on scoring systems and obstetrics. The chapters feature numerous pictures, comparative tables, diagrams and lists, and provide essential information for juniors training in intensive care medicine. The definitions, etiology, clinical features and differential diagnoses are well covered, while extensive use of bullet points and numbering increases the clarity of presentation enabling readers to quickly get to the key learning points.”

I’m not a medical professional who’s part of a critical care team (surprise!) and so I don’t understand everything that’s going on in this book, but I still feel like I’m learning quite a bit. I think it’s an interesting book, but I certainly wouldn’t recommend it to someone who’s not spent more time than most obtaining an understanding of the human body, pathophysiology, some pharmacology, etc. – if you’re new to the field of medicine I think you’ll simply get blown away here and you’ll have little clue what’s going on most of the time. Khan Academy has a lot of stuff about the heart, and I’ve watched a lot of the videos dealing with this kind of stuff, though far from all of them – but a couple of textbooks plus learning all the material covered in the lectures I link to above is probably the bare minimum you need in order to understand everything that’s going on in chapter 3 alone. So, yeah…

As pointed out, even though I don’t understand everything doesn’t mean I don’t learn a lot by reading this stuff – that’s not how it works. So so far I’m enjoying this – if I could have been bothered to look up all the new terms I’ve come across here so far, I’d have learned more than I did, but that would have been too much work. I did rewatch a few Khan Academy videos to brush up on some of the concepts, but that’s pretty much all I’ve done, aside from an occasional visit to wikipedia. So I’ve read and understood some of it, and I’ve read and not fully understood other parts. That’s okay.

One thing that I’ve achieved a greater understanding of is how stuff like adverse drug reactionsnosocomial infections etc. may be much harder to avoid and deal with than I’ve tended to believe in the past. All drugs have side effects, and as a general rule I don’t think it’d be wrong to say that the more sick you are, the more extensive health interventions are required to make you better (or simply stop you from getting worse). A patient in the ICU who develops pneumonia as a (more or less direct) consequence of having been on a mechanical ventilator for an extended period of time and dies from it would most likely have died even sooner if he had not been put on a ventilator – he was so sick in the first place that he couldn’t even satisfy his own body’s oxygen demands through breathing… Many treatment options critically ill patients have to choose from (or their medical proxy has to choose from) are quite risky, but it should be kept in mind that the risks associated with not treating the conditions in question are usually much worse. Adding to all of this is the fact that quite a few diseases progress much too fast for treatment to follow diagnosis chronologically; in such cases you need to engage in treatment before you’re even certain what’s wrong. Some drugs will work one way when dosed in a specific manner, but will have more or less the opposite effect if given in a higher dose; now add interpersonal differences in drug metabolism, absorption rates, measurement problems, etc. to the mix… This is not to say that attempts to minimize errors and treatment-associated complications should not be undertaken, far from it, but I think I understand a little better at this point why these problems may sometimes be very hard to address satisfactorily, and why some of these problems are probably even best perceived of as inherent risks which simply cannot be avoided.

I decided to add a few quotes below from the first four chapters (95 pages) of the book. I’ve only added quotes from the stuff I understand. I added some wikipedia links along the way in order to make the stuff a little easier to read.

“Several types of sedative available are commonly used in the ICU […] Drug regimens should of course be matched to the particular needs of individual patients; however, generally speaking, no single drug is ideal and what follows is a summary of the advantages and disadvantages of each drug. […] All sedatives can accumulate in critically ill patients, leading to a prolonged sedative effect. This may increase the duration of mechanical ventilation, length of stay in the ICU, and length of stay in the hospital, and lead to complications such as ventilator-associated pneumonia. A strategy to reduce drug accumulation should be implemented […]

“studies that have failed to demonstrate an improved outcome in critical patients have cast doubt on the clinical value of PACs. [PAC: Pulmonary Artery Catheter, US] Nevertheless, traditional indications include the following: [Long list omitted here] […] To date, the use of PAC monitoring has not been shown to confer a clinical benefit in any of these settings.”

“A wide range of inotropes and vasopressors is available to help support CO [cardiac output] or blood pressure (BP). […] Inotropes that vasodilate and vasoconstrict are known as inodilators and inoconstrictors, respectively. Vasoconstrictors should always increase blood pressure, but may have a variable effect on CO. Many of these drugs have the potential to cause myocardial ischemia due to increases in cardiac workload, tachycarrhythmias, etc, and thus as electrocardiogram (EKG) and (preferably direct) arterial pressure monitoring are mandatory during their use. Vasoconstrictor drugs must be given into a central vein.”

“Hypertension is not uncommon in critically ill patients and may worsen myocardial ischemia and increase oxygen requirements. […] Injudicious use of hypotensive drugs reduces perfusion pressure (eg, kidney, brain, myocardium) and may lead to organ dysfunction.”

Heart failure occurs when the heart fails to maintain a CO sufficient for the metabolic needs of the body, or when it can only do so at the expense of abnormally elevated end-diastolic pressures. Heart failure is not a diagnosis as such, but a clinical syndrome; consequently the underlying disease must always be sought and treated.
Chronic heart failure has increased in incidence due to a decline in mortality from acute myocardial infarction, and an increase in the elderly population. It carries a significant mortality risk, with a 5-year survival rate of approximately 30%.
Acute cardiac failure is a medical emergency with a high mortality rate […] in which diagnosis of the cause and empirical treatment may have to be carried out simultaneously.”

“Pathogenesis of AMI
Rupture of an atheromatous plaque within the lumen of a coronary artery, and the subsequent formation of fresh thrombus, leads to vascular occlusion and (total) cessation of blood flow to the region of the myocardium supplied by that artery. Hypotension, hypoxemia, and local vasospasm may extend the size of the resulting infarct by compromising the blood supply of surrounding ischemic muscle. […] There is ischemic pain, typically retrosternal, spreading across the chest, and possibly radiating to the arms, throat, jaw, and back. The pain lasts for more than 20 min and may be atypical (eg, epigastric) which may confuse the diagnosis. A silent (ie, painless) infarction is more common in elderly people and those with diabetes. […] Less than 10% of patients with enzyme-proven infarcts will have two normal EKGs performed 30 min apart in the hyperacute phase. This establishes electrocardiography as an important initial investigation in the patient with a history suggestive of AMI. […] Aspirin combined with streptokinase improves the reduction in mortality rate from 25% to 42% by preventing reocclusion of thrombolyzed arteries. A dose of 150–300 mg should be given as soon as possible after the onset of symptoms […] The in-hospital mortality rate from AMI is now less than 10%, with most deaths occurring within the first few hours, often due to ventricular fibrillation (VF).”

Cardiogenic shock is a low-cardiac output state with clinical evidence of inadequate blood flow. It has been defined clinically as a syndrome characterized by hypotension (eg, systolic blood pressure

“The lungs have two major functions: to provide adequate arterial oxygenation for tissue needs and to eliminate CO2. These two functions are largely independent of each other. Respiratory failure can be classified according to the underlying pathophysiologic derangement. All types of respiratory failure may present with arterial hypoxemia and/or arterial hypercapnia.”

“In the normal resting state, 1–5% of the cardiac output is delivered to the respiratory muscles. This can increase up to tenfold in patients with shock and respiratory distress. Mechanical ventilation allows resting of the respiratory muscles.”

“Patients who have been ventilated for brief periods of time (eg, overnight ventilation following major surgery) may be liberated from mechanical ventilation rapidly […] This is in marked contrast to patients who have been critically ill for long periods of time (days), in whom the process of withdrawing ventilatory support is often protracted. Day-to-day changes in the patient’s condition during this period of respiratory convalescence often necessitate the temporary reintroduction of more substantial mechanical ventilatory support.”

“ARDS is a syndrome causing acute respiratory failure characterized by severe hypoxemia, poorly compliant (‘stiff ’) lungs, and diffuse patchy infiltration on the chest X-ray in patients in whom cardiogenic pulmonary edema has been excluded. Rather than being an isolated condition, it is recognized as the pulmonary manifestation of systemic inflammation. ARDS is now recognized as the extreme end of a spectrum of ALI [Acute Lung Injury, US – though see also this], and is defined in terms of the severity of the gas exchange defect […] The mortality rate of ARDS ranges from 30% to 40%, and has improved significantly in recent years with the advent of new ventilator strategies.”

“Pneumonia can be defined as an acute lower respiratory tract illness, which is associated with fever, symptoms and signs in the chest, and abnormalities on the chest X-ray. In patients admitted to the hospital, it carries an overall mortality of about 10%. Mortality is strongly correlated with age, chronic comorbidities, severely abnormal vital signs upon presentation, and laboratory abnormalities (eg, pH, blood urea nitrogen, Na+, glucose, hemoglobin, and PaO2).”

“[Hospital-acquired (nosocomial) pneumonia] is defined as pneumonia developing more than 2 days after admission to hospital. It is particularly common in the ICU and postoperative patients, and carries a mortality rate of up to 50%. […] Diagnosis often proves difficult, particularly in ventilated patients, because features are nonspecific and may be confused with other conditions ”

“Pulmonary embolism (PE) occurs in 15–20 patients per 1,000 of the general hospital population, of which 2–5 cases are fatal. At least 50% of patients who die from PE have had some indication of thromboembolism within the preceding 7 days. Failure to diagnose PE has adverse consequences, since 30% of patients with untreated PE die compared with 8% of treated PE. […] Pulmonary emboli usually result from the formation of asymptomatic deep vein thromboses (DVTs) in deep veins of the lower limbs, pelvis, and abdomen. Upper extremity DVTs are usually associated with indwelling catheters and may account for up to 15% of DVTs. […] Factors promoting the formation of thrombi are described by Virchow’s triad of venous stasis, abnormal vessel walls, and increased coagulability […] Thrombolytic therapy is indicated for massive PE with associated shock. Its role in massive PE, with echocardiographic evidence of right heart failure or massive PE with severe pulmonary hypertension, has demonstrated improved secondary outcomes compared with heparin, though no survival benefit has been noted. Allergic reactions and hemorrhage are the principal complications of thrombolytics, and restrict their use considerably.”

August 25, 2013 Posted by | Books, Cardiology, Data, Infectious disease, Medicine, Pharmacology | Leave a comment

Gender, Physical Activity, and Aging (2)

I’ve finished the book. I gave it four stars. There’s a lot of research covered here, lots of ground covered, and most of it is well written. When findings are conflicting we are told so, and the reasons for discrepancies across studies are often investigated in some detail. Conclusions drawn are often of a tentative nature, and the uncertainties involved are often emphasized. Given the amount of material covered, detailed coverage of specific studies and their limitations is somewhat limited, but stuff like differences in study design across studies and consequences of these are occasionally emphasized; the lack of longitudinal studies in specific areas of research covered are for example a few times highlighted as a potential problem regarding which causal inferences to draw from the research. Sometimes the controls included in a specific study are mentioned, sometimes they’re not, and that bothered me a little a few times as it was for example unclear in some cases whether a specific study had controlled for initial health status or not; the inclusion of this variable might not deal completely with the endogeneity problem (exercise affects health status, but health status also affects exercise ability – or at the very least perceived exercise ability), but without including it in some specific cases you’re quite likely to get into trouble, and it seems very probably that some older studies have overlooked this problem. In the book the results of quite a few RCTs are covered, which is nice – but there are also a lot of cross-sectional studies, epidemiological studies of various kinds, survey-based stuff… Natural experiments are almost (? can’t remember now if the proper word is ‘completely’…) absent in this work, but then again I guess this book was written before IV estimation really took off, and besides such methods would be most useful in areas which although related to the areas covered in the book are still sufficiently different in scope for it to (arguably) make sense not to include that kind of stuff in the book.

In general the stuff’s not easy to read if you don’t know a lot of stuff about biology, physiology and related fields, and I felt more than a few times that I was in over my head (though some chapters were a lot easier than others; because of my knowledge of diabetes and the physiological consequences of adiposity chapter 10 was an easy read) – but stuff like study methodology should not cause you problems as most of the -designs applied are quite uncomplicated. The stuff included about health impacts of health interventions (e.g. exercise) deals mainly with ‘idealized’ high-compliance settings; they do talk a bit about the adherence-/compliance problems which are observed when doing intervention studies, but more focus on this aspect might have been a good idea – at least I think the book sells the idea that exercise is good for the individual much better than it does the idea that large-scale policy interventions undertaken in order to improve health that way might be a good idea. I believe quite a bit of work has been done in that area since then, so you can find out about that stuff elsewhere.

I haven’t ‘punished’ the authors for not defining all terms applied in the work and for including stuff I was supposed to know but didn’t – it’s not their fault I’m an ignorant fool. But you should have in mind when interpreting my rating that a person like me is borderline too ignorant about stuff like immunology, microbiology, and cardiology to read and understand all the stuff in the book, despite having, among other things, read textbooks dealing with all three areas before. I got a lot of stuff out of this book, but I’d have gotten more out of it if I’d have known more about some of the things they cover.

I have included some observations from the book below. I’ve mostly stayed clear of the technical stuff:

“It has been suggested that declines in functional capacity with age reflect age-related reductions in physical activity. Inactivity has been estimated to account for 50% of the age-related loss in function. […]

The ability to move with purpose and to remain independent with increasing age depends to a large degree on retaining an adequate functional capacity in the neuromuscular system. This system, which governs the generation and control of muscle force, typically undergoes a substantial decline in functional capacity with age […] Beginning at approximately 30 years of age, human muscular strength declines at a rate of 10 to 15% per decade1 […] Because the activities of daily living usually do not require maximal muscular efforts, the gradual loss of strength for most individuals does not become functionally significant until after 55 to 60 years of age. […]

Evidence is accumulating that progressive resistance exercise is an efficacious, nonpharmacological treatment for age-related losses in muscle mass, quality, and function. The benefits of regular physical activity throughout the life span have been a major focus of exercise physiologists for many decades. […] Taken together, these results suggest that, if sustained over a lifetime, regular physical activity has a significant protective effect on muscle strength, function, and oxidative capacity. Benefits appear to relate not only to function, but also to longevity.9,10 […]

Evidence from both animal and human models suggests that there are age-related differences in the susceptibility of skeletal muscle to exercise-induced damage and ability for post-damage repair. One such difference is in the amount of work required to induce muscle damage. […] Human studies have […] tended to demonstrate a greater degree of exercise-induced muscle damage in elderly than in younger adults. […] Most animal and human studies agree that recovery from acute exercise-induced muscle damage is impaired in older subjects. […]

evidence is mounting that estrogen may be a key hormone for maintaining muscle strength in women.96 […] although gender differences in tissue antioxidant potential, partially due to estrogen, may exist, their importance in influencing exercise-induced peroxidative muscle damage is still undefined. […] whether females are afforded greater protection from postexercise muscle inflammatory damage and/or are delayed in muscle healing rates as a consequence of their higher estrogen levels is not yet firmly established. […]

The elderly appear to be more susceptible to exercise-induced muscle damage than younger adults. In addition, following such damage, there seems to be a relative impairment in muscle repair and adaptation in the sedentary elderly. Nevertheless, evidence suggests that the ability of older muscle to adapt to a resistance training program remains robust, and the physiological mechanisms associated with muscle repair and hypertrophy are still able to function even in older adults. […] regular resistance exercise may be one of the best intrinsic methods of protecting muscles from exercise-induced muscle damage and helping to normalize the rate and quality of muscle repair processes and adaptation to muscular activity in older individuals. […]

Over half of the older population is afflicted by arthritis, and approximately one-third of postmenopausal women will experience an osteoporotic fracture in their lifetime.1 […] distinguishing between disease processes and disease consequences of arthritis and normal aging is complex. […] More than 80% of people over the age of 75 years have clinical osteoarthritis and more than 80% of people over the age of 50 have radiologic evidence of the condition. Before the age of 50 years, the prevalence of osteoarthritis in most joints is higher in men than in women. […] The prevalence of rheumatoid arthritis increases with age and is found in about 10% of adults older than 65 years of age. […] The association between obesity and osteoarthritis has been evident for many years, but whether obesity was a cause or a consequence of the disease was unclear. It now appears that obesity not only predates osteoarthritis, but also increases the rate of disease progression, especially in women and in those with osteoarthritis of the knee.26,27 […] Occupational or recreational activities associated with excessive, repetitive, or high-impact joint loads are risk factors for osteoarthritis. In contrast, moderate physical activity such as running decreases the risk for osteoarthritis, at least in men.28 […] General exercise and physical activities are not harmful to the arthritic process, as was once thought. […] Despite many interstudy differences of methodology, there is consistent support for the notion that exercise and physical activity can and should play a role in both prevention and rehabilitation. […]

The one fairly robust finding across studies of exercise adherence is past exercise behavior. […] The fact that current exercise behavior appears to be best predicted by past exercise behavior is not surprising, but it is disconcerting, given that those individuals who most need to exercise are also those who are least likely to exercise. […]

Based upon […] systematic reviews of randomized investigations, the effect of exercise on bone mass appears to be a gain of approximately 1% per year, regardless of menopausal status. Data comparing male and female subjects are limited […]

Aging, per se, appears to have only a small effect on glucose intolerance and insulin resistance. The majority of insulin resistance that develops in older women and men is explained by increased adiposity, particularly in the abdominal region. […] life style appears to be a much stronger determinant of insulin resistance than aging per se. […]

Overall, exercise training in later life reduces the magnitude of catecholamine and pituitary hormone responses to a given bout of exercise, and increases the resistance to physical stress. Given that stress hormones are in general immunosuppressive, appropriate exercise training may be beneficial for the aging immune system, raising the threshold level of immunosuppressive (i.e., strenuous and/or prolonged) physical exercise. […] Strenuous exercise increases concentrations of various proinflammatory and anti-inflammatory cytokines, naturally occurring cytokine inhibitors, and chemokines.43 Given that aging is associated with increased inflammatory activity, strenuous exercise may induce the cytokine cascade more markedly in aging adults than in young peers. […] The results seem to imply that older adults should adopt a more cautious approach to strenuous exercise. […]

Human immune function undergoes adverse changes with aging. The T cells, which have a central role in cellular immunity, show the largest age-related differences in distribution and function. The underlying causes include thymus involution and continuous attrition caused by chronic antigenic overload. Immune function is apparently sexually dimorphic; women have more vigorous immunologic activity than do men, thus reducing their risks of infection. However, the same mechanisms make women more susceptible to various autoimmune diseases. The sexual dimorphism in immune function may become less apparent with aging, although it persists into later life […]

In Canada, by the age of 65 years, 37% of women and 31% of men have noted some limitations in their physical activity.28 As early as 55 years of age, 2% of men and 10% of women are unable to carry their groceries, and in those over the age of 80 years, the prevalence of this particular handicap rises to 20% of men and 30% of women.81 […] When interpreting functional changes, it is often difficult to disentangle what is a consequence of normal aging from the effects of disuse and chronic disease. One U.S. study estimated that as much as half of age-related decline in functional capacity was self-imposed, due to an accumulation of body fat and a failure to take adequate physical activity.32 […] in Denmark, Avelund et al.5 noted a substantial inverse relationship between levels of habitual physical activity and the loss of functional capacity. […]

Although an age-related loss of function can in itself cause disability, chronic disease is the usual source of impairment. […] A major part of the age-related loss of functional capacity, with the associated social and economic costs of prolonged disability, is due to adoption of an inappropriate lifestyle. […] The apparent prevalence of various disease conditions varies according to the diagnostic criteria applied. For example, aging is inevitably associated with a progressive increase in blood pressure, but when a certain arbitrary level of pressure is surpassed, hypertension is diagnosed […] Similarly, when the age-related decrease in bone mineral content reaches an arbitrary figure, clinical osteoporosis is diagnosed. […]

Many elderly people have multiple disorders, and it is then difficult to assess the contribution of specific conditions to the reported level of disability. In young and middle old age, the main causes of disability are chronic disease and a restriction of mobility, but in the oldest old mental deterioration and a loss of the special senses become important sources of impairment.62 […]

the main social costs associated with aging are incurred in the final year of life, as heroic attempts are made to prolong the survival of sedentary and severely disabled individuals.9,17 Regular physical activity decreases the risk of chronic disease and thus the scope for heroic treatment; it increases healthy life expectancy.17 […] there is little evidence that regular physical activity prolongs survival into advanced old age. What it does is to avert premature death, at a time when an individual is contributing to society rather than drawing upon its resources. The survival curves for active and sedentary individuals converge around the age of 80 years […]

The muscle force and aerobic power required to undertake many of the tasks important to the independence of an elderly person (for example, rising from a chair or climbing a flight of stairs) are almost directly proportional to an individual’s body mass. Thus, a 10% reduction in body mass will effectively increase muscle strength and maximal aerobic power by some 10%, equivalent to a 10-year reversal of the effects of aging.”

August 4, 2013 Posted by | Books, Data, Demographics, Epidemiology, Immunology, Medicine | 2 Comments

Gender, Physical Activity, and Aging

“In the past few years, research on age-related changes in biological function, physical capacity, and the training responses of women has grown. The time is thus opportune to present a succinct summary of these investigations, exploring the interesting issues of potential gender differences in both the course of aging and responses of the elderly to physical activity. This book undertakes this task, drawing upon the knowledge of leading experts in exercise gerontology.”

I’ve read books dealing with related stuff before, but from different angles not involving much stuff about gender differences.

The book spends a lot of time on gender-differences related to the aging process and how this stuff relates to stuff like physical activity and other environmental factors as well as genetics. Some of the chapters are quite easy to read, others are significantly more technical – chapter four occasionally contained stuff which was at least borderline beyond me (unless you’ve learned by heart stuff like what’s covered here and here you’ll either be at least somewhat lost or you’ll need to look up some stuff along the way), but I read on anyway (occasionally rewatching a Khan video…) and even if some of the finer details sometimes elude you you’ll probably learn some stuff. I thought the first parts of chapter 3 were quite weak compared to the stuff on those topics I’ve read elsewhere (can’t remember where – Whitbourne perhaps? Razib Khan?). On a general note I believe I’m leaning towards a 3 star goodreads rating at this point – I’ve read roughly half the book. There’s a lot of stuff and it’s a well documented book (aside from the intro chapter and chapter 5, all chapters so far have had more than 100 references – chapter 3 e.g. has more than 250 references), but some of the topics covered I don’t find to be very interesting, and e.g. the stuff on motivation in chapter 2 is way too theoretical to be of any use in an applied setting (so why are they wasting time writing about it?). I added a ‘pure speculation’ note in the margin at one point. But again, there’s a lot of good stuff – some stuff from the first half of the book:

“On average, a larger fraction of total body mass is fat and bone structure is lighter in women than in men; likewise, most older individuals accumulate body fat […] Gender differences in muscle strength and maximal aerobic power become much smaller if values are expressed per unit of lean body mass. A lean mass adjustment may be appropriate when comparing specific aspects of muscle and cardiac function between women and men, young and old, or indigenous and modern populations. But during most activities of normal daily life a person must displace the entire body mass rather than just lean tissue; if the type of activity to be performed requires a size adjustment, then total body mass is the most appropriate unit of reference.25 […] Fat is a poor conductor of heat, and if the layer of subcutaneous fat is increased […] then the person concerned must direct an increased fraction of total cardiac output to skin rather than working muscles when carrying out heavy physical work in a warm environment.27 This reduces the external power output for a given maximal oxygen intake […]

From a physiological point of view, there is an important gender difference in average blood hemoglobin concentration. […] The lower average figure in females reflects mainly physiologic influences […] Given the predominantly biological basis of the hemoglobin
differential, the gender gap seems likely to be small after menopause;37 at this stage, values remain relatively constant in women, but tend to decrease in men. […] The maximal oxygen content of unit volume of blood is stoichiometrically related to the hemoglobin concentration.20 Thus, for each liter of blood pumped by the heart, a woman necessarily transports approximately 10% less oxygen than a man, at least prior to menopause. […]

Over a 3-month period, even a moderate training program can augment muscle strength and maximal aerobic power by 20% or more, 25,26 — equivalent to a reversal of approximately 20 years of normal aging.26 It is thus important that any gender comparisons of the aging process be based on individuals who begin with a similar initial training status and are pursuing similar patterns of habitual physical activity. […] laboratory-measured indices of physical fitness (such as treadmill endurance time) bear a closer relationship to health outcomes than do questionnaire assessments [my emphasis, US] […]

One U.S. study attributed as much as a half of variance in the age-linked decrease in relative aerobic power to a combination of a decrease in habitual physical activity and an increase in body mass.12 In order to see the true influences of gender and aging upon the primary variable, it is thus desirable to focus attention on a population sample where habitual physical activity and body fat content have remained constant over the individual’s life span. […]

it has […] been recognized for many years that the aging process actually shows some curvilinearity. […] For example, women show a sharp acceleration in the rate of bone mineral loss during the five years around the age of menopause;18 in men, there is an accelerating loss of lean tissue after retirement […] In women, functional losses accelerate with the distinct end point of menopause, but in men the process begins at a later age, and develops more gradually […]

Two robust findings from population-based surveys are that older adults are less active than younger adults, and older women are less active than older men. […] Physical activity is associated with physical function, even in those living with chronic disease52 and is inversely related to disability in women.53 A low level of physical activity is considered a risk factor for functional decline in older adults.54,55 […]

Older adults have an average of 11.4 contacts per year with a physician or health care provider,1 […]

randomized controlled exercise trials with older adults have shown that exercise adherence is comparable or superior for home-based compared to group-based exercise.122-124 […] older adults are more likely to cite the health benefits of physical activity as a motivation for exercise than are younger adults. […] perceived exercise benefits or outcome expectations are positively associated with physical activity participation in older women.82,96,98,109,128 […]

Official statistics show that women have had a substantially longer average survival than men in all countries of the world throughout the past century […] Lifestyle and other environmental factors plainly modulate any underlying effect of constitution, since gender discrepancy increased very substantially in almost all countries during the first two thirds of the 20th century (Table 3.1). In the U.S., for example, the gender differential increased from 5.8% in 1900 to 9.6% in 1990. […] Gains in life expectancy during the present century have been much larger in women than in men.206,236 Thus, a large fraction of the elderly population and an even larger fraction of those who are very old are now women. […] Although women currently have a much longer average survival than men, many aspects of function such as aerobic power and muscular strength deteriorate at a similar absolute rate in the two sexes […] Thus, women face a substantially longer period than men when their level of function is insufficient to undertake instrumental and other activities of daily living43,210,224 […] Indeed, their active life expectancy112 may be no greater than that of their male counterparts. […] In the U.S., the total number of disabled life years averages 10.8 years for men and 14.0 years for women,223 and in some countries the gender discrepancy in chronic disability is even larger.” […]

“the major effect of genotype is probably in terms of increasing an individual’s susceptibility to various causes of disability and
premature death. […] In general, women have fewer material resources than men during old age.132 They are much more likely to be living on their own,16 and thus tend to receive less psychological support than men.42,149,167 They are also more likely to be disabled. In general, disability increases social isolation […] Growing evidence suggests that physical activity helps to maintain social contacts, enhances mental health, and sustains cognitive ability in the very old.210 […]

Gender differences in the prevalence of cigarette smoking have in the past explained much of the shorter average life span of the male. Indeed, after allowing for a somewhat greater incidence of traumatic deaths among men, there is almost no gender difference in life expectancy among nonsmokers.155 Now that the prevalence of smoking also shows little sex difference, a progressive equalization of average life span between men and women can be anticipated.173 [my emphasis, US] […]

Particularly in the final years of life, the greatest dividend from regular physical activity may be an increase in the individual’s functional capacity and thus quality of life […] rather than an extension of life span.209 […] Because women generally have a smaller functional margin than men, they are likely to show a larger gain in quality of life as a result of participating in a regular physical activity program […]

Specific genes can now be identified that increase the risk of various chronic diseases, affecting an individual’s quality of life and survival prospects. Furthermore, the frequency of occurrence of such genes in some instances differs between the two sexes. Nevertheless, various environmental challenges exert a powerful influence, both in their own right and as the reason why adverse genetic characteristics become manifest. The gender difference in survival thus seems determined almost entirely by environmental factors, with cigarette smoking playing a dominant role. […]

there is typically a ten-year delay in the onset of coronary symptoms for women compared to men […]

Here’s a quote from chapter 4 I picked because I figured it’d convey part of why this chapter may be hard to understand for some readers:

“With advancing age, strategies used to augment cardiac output during exercise shift from codependence on catecholamine-mediated inotropic, chronotropic, and volumetric means, to greater dependence on changes in ventricular end-diastolic volume via the Frank–Starling mechanism. […] The key signaling proteins involved in both the amplification and integration of extracellular signals in the myocyte (from the sarcoplasmic reticulum to the intracellular effectors) include β-adrenergic receptors, G proteins, and adenyl cyclase. […] Variability in the R-R interval, used as an index of parasympathetic tone, is augmented with aerobic training …”

Back to the ‘not-that-hard-to-understand-stuff’:

Exercise training which increases and augments the ventilation threshold by 10 to 15% may increase the time to fatigue by as much as 180% when exercising at a fixed intensity. Improvement in submaximal aerobic exercise performance is believed to result in part from change in skeletal muscle metabolism. These changes in submaximal performance have a profound effect on the ability of older people to function in daily life.99 [my emphasis, US] […] Aging of the cardiorespiratory system is not due to breakdown in a single step of oxygen conductance from the atmosphere to exercising muscles. Rather, there are physiological changes in each of the series of resistors. […] it is apparent that aging affects each step in the delivery of oxygen, often with differing effects across genders. Many of these changes are slowed or reversed by exercise training […]

It has been widely demonstrated that greater physical activity is associated with a reduced all-cause mortality in men. However, this relationship has been studied less frequently in women. […] Physical activity and longevity were investigated by Paffenbarger et al.1 in 17,000 male Harvard alumni aged 35 to 74 years. With physical activity assessed by questionnaire in the follow up, it was estimated that those expending greater than 8.4 megajoules per week in exercise (walking, stair climbing, sports play) had a 25 to 30% lower mortality rate than those with lower weekly energy expenditures. Paffenbarger and colleagues2,3 also showed that physical activity participation (in the form of moderately vigorous sports play) initiated in middle-age was independently associated with a 23% lower all-cause death rate …”

August 1, 2013 Posted by | Biology, Books, Data, Demographics, Medicine | Leave a comment

A few Cochrane reviews and links

I’ve spent the last few days at my parents’ place and haven’t had much time for blogging due to social obligations. I read The Murder on the Links the day before yesterday and I’ll finish Lord Edgware Dies later today – I’ll probably blog the books tomorrow. For now I’ll just post a few Cochrane reviews and a couple of links:

i. Abstinence-only programs for preventing HIV infection in high-income countries (as defined by the World Bank). (link to the full paper here)

“Abstinence-only programs are widespread and well-funded, particularly in the United States and countries supported by the US President’s Emergency Plan for AIDS Relief. On the premise that sexual abstinence is the best and only way to prevent HIV, abstinence-only interventions aim to prevent, stop, or decrease sexual activity. These programs differ from abstinence-plus designs: abstinence-plus programs promote safer-sex strategies (e.g., condom use) along with sexual abstinence, but abstinence-only programs do not, and instead often highlight the limitations of condom use. An up-to-date review suggests that abstinence-only programs do not affect HIV risk in low-income countries; this review examined the evidence in high-income countries.

This review included thirteen randomized controlled trials comparing abstinence-only programs to various control groups (e.g., “usual care,” no intervention). Although we conducted an extensive international search for trials, all included studies enrolled youth in the US (total baseline enrollment=15,940 participants). Programs were conducted in schools, community centers, and family homes; all were delivered in family units or groups of young people. We could not conduct a meta-analysis because of missing data and variation in program designs. However, findings from the individual trials were remarkably consistent.

Overall, the trials did not indicate that abstinence-only programs can reduce HIV risk as indicated by behavioral outcomes (e.g., unprotected vaginal sex) or biological outcomes (e.g., sexually transmitted infection). Instead, the programs consistently had no effect on participants’ incidence of unprotected vaginal sex, frequency of vaginal sex, number of sex partners, sexual initiation, or condom use.”

ii. Healthcare financing systems for increasing the use of tobacco dependence treatment.

The short version:

“Apart from providing counselling and drug treatment, strategies that reduce or cover the costs of accessing or providing these treatments could help smokers quit.

We found eleven trials, eight of which involve financial interventions directed at smokers and three of which involve financial interventions directed at healthcare providers.

Covering all the costs of smoking cessation treatment for smokers when compared to providing no financial benefits increased the proportion of smokers attempting to quit, using smoking cessation treatments, and succeeding in quitting. Although the absolute differences in quitting were small, the costs per person successfully quitting were low or moderate. Financial incentives directed at healthcare providers did not have an effect on smoking cessation.”

From the paper:

Summary of main results:

With very high to modest levels of consistency, we detected a statistically significant positive effect of full financial interventions targeting smokers with regard to abstinence from smoking compared to provision of no financial intervention at six months follow-up or more (all abstinence measures: RR 2.45, 95% CI 1.17 to 5.12). The effect of full financial interventions was also extended to favourable outcomes on the use of smoking cessation treatments: the pooled effect of full coverage compared with no financial intervention on the use of smoking cessation treatments was highly significant for each treatment type (NRT, bupropion, and behavioural interventions).Despite the observation of multiple favourable effects of full as compared to no financial intervention, when full coverage was compared to partial coverage, results showed no significant effect on smoking cessation or quit attempts. […]

Five studies presented data on cost effectiveness. When full benefit was compared with partial or no benefit, the costs per quitter ranged from $119 to $6,450. [the $6,450 estimate is an outlier in that group; the other estimates are all much lower, at or below $1500/quitter – US] […]

In this review, covering the full cost to smokers of using smoking cessation treatment increased the number of successful quitters, the number of participants making a quit attempt, and the use of smoking cessation treatment when compared with no financial coverage. As the majority of the studies were rated at high or unclear risk of bias in three or more domains, and there was variation between the settings, interventions and participants of the included studies, the results should be interpreted cautiously. The differences in self-reported abstinence rate, number of participants making a quit attempt and use of smoking cessation treatments were modest.”

iii. Psychosocial and pharmacological treatments for deliberate self harm.

“Deliberate self-harm is a major health problem associated with considerable risk of subsequent self-harm, including completed suicide. This systematic review evaluated the effectiveness of various treatments for deliberate self-harm patients in terms of prevention of further suicidal behaviour. […]

Main results:

A total of 23 trials were identified in which repetition of deliberate self-harm was reported as an outcome variable. The trials were classified into 11 categories. The summary odds ratio indicated a trend towards reduced repetition of deliberate self-harm for problem-solving therapy compared with standard aftercare (0.70; 0.45 to 1.11) and for provision of an emergency contact card in addition to standard care compared with standard aftercare alone (0.45; 0.19 to 1.07). The summary odds ratio for trials of intensive aftercare plus outreach compared with standard aftercare was 0.83 (0.61 to 1.14), and for antidepressant treatment compared with placebo was 0.83 (0.47 to 1.48). […]

Authors’ conclusions:

There still remains considerable uncertainty about which forms of psychosocial and physical treatments of self-harm patients are most effective, inclusion of insufficient numbers of patients in trials being the main limiting factor. There is a need for larger trials of treatments associated with trends towards reduced rates of repetition of deliberate self-harm. The results of small single trials which have been associated with statistically significant reductions in repetition must be interpreted with caution and it is desirable that such trials are also replicated.”

A few other links which are not from the Cochrane site:

iv. Plausible indeed!

v. Errors in DCP2 cost-effectiveness estimate for deworming.”Over the past few months, GiveWell has undertaken an in-depth investigation of the cost-effectiveness of deworming, a treatment for parasitic worms that are very common in some parts of the developing world. While our investigation is ongoing, we now believe that one of the key cost-effectiveness estimates for deworming is flawed, and contains several errors that overstate the cost-effectiveness of deworming by a factor of about 100. This finding has implications not just for deworming, but for cost-effectiveness analysis in general: we are now rethinking how we use published cost-effectiveness estimates for which the full calculations and methods are not public. […]we see this case as a general argument for expecting transparency, rather than taking recommendations on trust – no matter how pedigreed the people making the recommendations. Note that the DCP2 was published by the Disease Control Priorities Project, a joint enterprise of The World Bank, the National Institutes of Health, the World Health Organization, and the Population Reference Bureau, which was funded primarily by a $3.5 million grant from the Gates Foundation. The DCP2 chapter on helminth infections, which contains the $3.41/DALY estimate, has 18 authors, including many of the world’s foremost experts on soil-transmitted helminths.”

vi. Evolution, Creationism, Intelligent Design – a Gallup poll from last year. According to that poll a majority of Americans (56%) think creationism should be taught in public school science classes. One of the questions asked were: If the public schools in your community taught the theory of evolution, — that is, the idea that human beings evolved from other species of animals — would you be upset, or not?  A third of the people asked (34%) answered yes to this question. Incidentally in related news it should be noted that in a recent poll of South Korean biology teachers, 40% of them “agreed with the statement that “much of the scientific community doubts if evolution occurs”; and half disagreed that “modern humans are the product of evolutionary processes”.”

In slightly related news, according to an older poll conducted shortly before the turn of the century roughly one in five Americans asked back then didn’t know that the Earth revolves around the Sun. Other countries didn’t do any better:

“Gallup also asked the following basic science question, which has been used to indicate the level of public knowledge in two European countries in recent years: “As far as you know, does the earth revolve around the sun or does the sun revolve around the earth?” In the new poll, about four out of five Americans (79%) correctly respond that the earth revolves around the sun, while 18% say it is the other way around. These results are comparable to those found in Germany when a similar question was asked there in 1996; in response to that poll, 74% of Germans gave the correct answer, while 16% thought the sun revolved around the earth, and 10% said they didn’t know. When the question was asked in Great Britain that same year, 67% answered correctly, 19% answered incorrectly, and 14% didn’t know.”

You do have a potential ‘this is a silly question so I want to mess with the people asking it’-effect lurking in the background, but that’s probably mostly related to people giving the wrong answer deliberately. But even if many of the people asked perhaps gave the wrong answer deliberately, there’s still a substantial number of people answering that they ‘don’t know.’ I found the numbers surprising and I would love to see some updated estimates; a brief googling didn’t turn up anything.

July 28, 2013 Posted by | Data, Demographics, Economics, Evolutionary biology, Health Economics, Infectious disease, Medicine, Psychology, Religion, Studies | 5 Comments

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 cliff 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 satisfied 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 specification […] we find 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 | Cancer/oncology, Chemistry, 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

Patient Compliance – Sweetening the pill

“Compliance is the degree to which a patient is compliant with the instructions that are given by a healthcare professional and written on the medication label (for example, prescribed dose and time schedule).” (p.8 – I didn’t know that definition before reading the book so it made sense to me to start out with this quote, to make sure people are aware of what this book is about.)

It’s an interesting book with a lot of stuff I didn’t know and/or at the very least hadn’t thought about. A couple of the chapters were quite weak and I basically skipped most of chapter 6, which was written by a pharmaceutical marketing consultant who wrote about branding stuff which I couldn’t care less about – but most of the book was quite good. One of the chapters (chapter 8) very surprisingly included undocumented claims which were to some extent proven wrong in a previous chapter (chapter 3) – it seemed as if the authors of that chapter had not read the previous chapter in question. Here’s what they wrote at the very beginning of their chapter (chapter 8):

“Compliance is important. Better adherence to treatment regimes leads to less healthcare resource utilization overall, as fewer illness recurrence or medication errors leading to side-effects take place.” (p.109)

And here’s what Dr. Dyffrig Hughes told us in chapter 3:

From the studies evaluated, the direction and magnitude of the change in costs and consequences resulting from applying sensitivity analysis to the compliance rate was measured and taken as an indicator of the impact of non-compliance. There was consistency among studies, in that as compliance decreased (whatever the measure), the [health] benefits also decreased […] There is no consistency, however, in the direction of change in costs resulting from changes in compliance [my bold, US] […] Whilst some studies show that costs increase as compliance decreases, others showed the opposite trend. This difference did not appear to be related to the nature of the disease, the measure of non-compliance or the assumptions relating to the health benefits experienced by non-compliers.

And here’s even a figure illustrating this point:


A little more from chapter 3 on the same subject: “The economic evaluations described demonstrate that medical expenditures do not always increase because of poor compliance. However, the limitations in the methodology adopted in many of the studies would suggest that the reported changes in healthcare expenditure may not necessarily be observed in practice. It is difficult, therefore, to predict the true economic impact of non-compliance with drug therapy, particularly as evidence relating to discontinuers is often not reported. It is the case, however, that decisions on optimal treatments, based on economic criteria, are influenced by non-compliance […] Health economic evaluations often fail to include non-compliance with medications. As a significant proportion of evaluations are based on efficacy trials, attention should be given to how their findings might be generalized. In particular, as poor compliance is one of the most important elements responsible for the differences that may exist between the effectiveness and efficacy of an intervention, greater consideration should be given to compliance when generalizing from the results of a controlled clinical trial. An optimal cost-effective treatment strategy chosen on the basis of efficacy data may not be so attractive once real-world compliance figures are taken into account.”

I don’t consider this to be an unforgiveable error in a book like this with a lot of authors writing about different aspects of the problem, but it doesn’t help that the authors of chapter 8 repeat the claim that improved compliance will have cost-saving effects in their conclusion of the chapter as well, and at the very least it doesn’t make them look good to me (a more cautious and tentative approach in the introduction and the conclusion of the chapter would have suited me better). A good editor sh(/w)ould probably have caught something like this.

The efficacy/effectiveness difference he talks about relates to the fact that the results of randomized controlled trials (RCTs) could/should be considered estimates of the health effects related to something close to the ideal treatment scenario, whereas real world implementation (effectiveness) of the treatment in question will often provide patients a sometimes significantly lower health benefit in terms of average treatment effect (or similar metrics), because of differences in the composition of the two groups and the settings of the treatment protocols applied, among other things. RCTs often deliberately try to maximize compliance e.g. by excluding patients who are likely to be non-compliers, and that of course will lead to biased estimates if you apply such estimates to the total patient population. There are many variables affecting how big the potential difference between efficacy and effectiveness may be for a particular drug and they cover that stuff, as well as a lot of other stuff, in the book. Non-compliance rates are much bigger than I’d imagined, but there are a lot of reasons for this that I hadn’t considered. The fact that non-compliance is widespread can be inferred even from the definitions applied in clinical trials:

“ultimately it is the outcome that is important. This might not always require that all doses of a drug are taken. Indeed, in short-term efficacy clinical trials patients who take 80 per cent or more of their medication, based upon pill counts, are usually considered ‘compliant’.” (p.14)

You can fail to take one-fifth of the medicine and still be considered compliant. Indeed as Parkinson, Wei and McDonald put it in their chapter:

“As the reader of this chapter it might be informative to reflect on your own behaviour: can you honestly say that you have always complied fully with every tablet of every prescription and have always finished the course? A very few readers will say yes, with honesty. The reality is that nearly everyone is non-compliant; the variable is the degree of non-compliance.”

A few numbers from the book illustrating the extent of the problem:

“reports (for example, Sung et al., 1998) have suggested that only 37 percent of participants take greater than 90 per cent of all doses of statins over a two-year period. […]

[Astma:] When patients were aware of being monitored a majority (60 per cent) were fully compliant, but when unaware the majority had a compliance rate between 30 and 51 per cent (Yeung et al., 1994). […]

Significant levels of non-redemption [of prescriptions], as seen in this study, have subsequently been confirmed within the large UK general practice databases such as GPRD where there is only about 90 per cent concordance between the prescriptions issued by the GP and those recorded as being redeemed at a pharmacy by the UK Prescription Pricing Authority (Rodriguez et al., 2000). […]

Chapman et al. (2005) recently examined compliance with concomitant antihypertensive and lipid-lowering drug therapy in 8406 enrollees in a US-managed care plan […] Less than half of patients (44.7 per cent) were adherent with both therapies three months after medication initiation, a figure that decreased to 35.8 per cent at 12 months. […]

Despite international clinical guidelines recommending lipid-lowering treatment in patients with clinically evident atherosclerotic vascular disease, study after study has documented low treatment rates in this high-risk patient population, thereby creating a clinical practice and public health dilemma (Fonarow and Watson, 2003).
Only about 30 per cent of patients with established CVD and raised serum lipids, and fewer than 10 per cent of individuals eligible for primary prevention, receive lipidlowering therapy. Target total cholesterol concentrations are then achieved in fewer than 50 per cent of patients who do receive such treatment (Primatesta and Poulter, 2000).
Poor patient compliance to medication regimen is a major factor in the lack of success in treating hyperlipidaemia (Schedlbauer et al., 2004). All of the lipid-lowering drugs must be continued indefinitely; when they are stopped, plasma cholesterol concentrations generally return to pretreatment levels (Anon, 1998). […]

Up to half of the patients treated for hypertension drop out of care entirely within a year of diagnosis (ibid. [WHO, 2003b], Flack et al., 1996). […]

Non-compliance comes in many forms: depending on the disease area, as many as one in five patients fail to take the first step of collecting a prescription from the pharmacy. Many patients on short-term medications depart from recommended doses within a day or two of starting treatment. And many of those on longer-term medication may take a break from their medication or vary their dose depending on how they feel. A review of the evidence (Horne and Weinman, 1999) concluded that compliance overall is approximately 50 per cent but varies across different medication regimens, different illnesses and different treatment settings.”

A little more stuff from the book:

“Compliance depends on many factors, including the study population (better in educated compared to disadvantaged patients) type of intervention, duration of treatment, complexity of treatment, real or perceived side-effects and life circumstances (see Table 8.1). The reasons are often patient-specific, multifaceted and can change over time. Demographically, the very young, the very old, teenagers and those taking very complex treatment regimes are the least likely to comply. […]

asymptomatic and chronic diseases needing long-term treatment […] result in poorer compliance; and […] the longer the remission in chronic diseases, the lower the compliance (Blackwell, 1976). […] patient-controlled non-compliance was lower in treatment for diseases in which the relationship between non-compliance and recurrence is very clear, such as diabetes, compared to treatment for diseases in which this relationship is less clear […] Of course, cognitive deficit, helplessness, poor motivation and withdrawal all lead to forgetfulness and passive or structural noncompliance (Gitlin et al., 1989; Shaw, 1986). […] most non-compliance is intentional and results from conscious choices. […]

As a rule, patients cannot be simply classified as compliers or non-compliers. Rather, the level of compliance ranges from patients who take every prescribed dose precisely as directed to those who never do with the typical patient lying between these two extremes. The degree to which patients intend to comply with a regimen can be subdivided into patient-controlled and structural. Patient-controlled factors can be subdivided further into rational behaviour (as seen in patients with Parkinson’s disease who regulate their own dosing) and irrational behaviours (such as self-induced seizures). Structural factors are those beyond the patient’s control, such as impaired memory or difficulty accessing medication (Leppik, 1990). […]

Compliance and adherence to therapy are complex issues with no obvious ‘one size fits all’ solution available. It appears that actively involving patients in treatment decisions, empowering patients with access to medical information and providing ongoing monitoring all contribute to improved compliance and adherence rates. The challenge for health services, however, is to provide these enhanced levels of support cost-effectively.”

The book is a few years old and sometimes you can tell. I was curious along the way about how much things have changed in the meantime. I’m guessing less than would have been optimal.

I should point out lastly that I have made a goodreads profile. I haven’t added a lot of books to my profile yet, but I may decide to use that site actively in the future. At goodreads I gave the book 3 stars, corresponding to an ‘I liked it’ evalution.

April 22, 2013 Posted by | Books, Data, Diabetes, Economics, Health Economics, Medicine, Pharmacology | 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, Mathematics, Papers, Personal, Physics | Leave a comment


i. Remember ‘the good old days’ of film-making? Here’s a reminder: The Hays Code.

“1. No picture shall be produced that will lower the moral standards of those who see it. Hence the sympathy of the audience should never be thrown to the side of crime, wrongdoing, evil or sin.

2. Correct standards of life, subject only to the requirements of drama and entertainment, shall be presented.

3. Law, natural or human, shall not be ridiculed, nor shall sympathy be created for its violation. […]

The sanctity of the institution of marriage and the home shall be upheld. Pictures shall not infer that low forms of sex relationship are the accepted or common thing.

1. Adultery, sometimes necessary plot material, must not be explicitly treated, or justified, or presented attractively.

2. Scenes of Passion

a. They should not be introduced when not essential to the plot.

b. Excessive and lustful kissing, lustful embraces, suggestive postures and gestures, are not to be shown.

c. In general passion should so be treated that these scenes do not stimulate the lower and baser element. […]

1. No film or episode may throw ridicule on any religious faith.

2. Ministers of religion in their character as ministers of religion should not be used as comic characters or as villains. […]

The reason why ministers of religion may not be comic characters or villains is simply because the attitude taken toward them may easily become the attitude taken toward religion in general. Religion is lowered in the minds of the audience because of the lowering of the audience’s respect for a minister.”

Background etc. here and here.

ii. I’d love to see some corresponding Danish numbers:

“Italians born in 1970, who are about 43 now, will pay 50% more in taxes as a percentage of their lifetime income than those born in 1952, according to research from the Bank of Italy and the University of Verona. The research also found they will receive half the pension benefits that Italy’s 60-somethings are getting or are poised to get.” (link, via MR)

iii. Longevity Among Hunter-Gatherers: A Cross-Cultural Examination. Some main findings and conclusions from the paper:

“Post-reproductive longevity is a robust feature of hunter-gatherers and of the life cycle of Homo sapiens. Survivorship to grandparental age is achieved by over two-thirds of people who reach sexual maturity and can last an average of 20 years.

Adult mortality appears to be characterized by two stages. Mortality rates remain stable and fairly low at around 1 percent per year from the age of maturity until around age 40. After age 40, the rate of mortality increase is exponential (Gompertz) with a mortality rate doubling time of about 6–9 years. The two decades without detectable senescence in early and mid-adulthood appear to be an important component of human life span extension.

The average modal age of adult death for hunter-gatherers is 72 with a range of 68–78 years. This range appears to be the closest functional equivalent of an “adaptive” human life span.

Departures from this general pattern in published estimates of life expectancy in past populations (e.g., low child and high adult mortality) are most likely due to a combination of high levels of contact-related infectiousdisease, excessive violence or homicide, and methodological problems that lead to poor age estimates of older individuals and inappropriate use of model life tables for deriving demographic estimates.

Illnesses account for 70 percent, violence and accidents for 20 percent, and degenerative diseases for 9 percent of all deaths in our sample. Illnesses largely include infectious and gastrointestinal disease, although less than half of all deaths in our sample are from contact-related disease.

Comparisons among hunter-gatherers, acculturated hunter-gatherers, wild chimpanzees, and captive chimpanzees illustrate the interaction of improved conditions and species differences. Within species, improved conditions tend to decrease mortality rates at all ages, with a diminishing effect at older ages. Human and chimpanzee mortality diverge dramatically at older ages, revealing selection for a longer adult period in humans. […]

Our results contradict Vallois’s (1961: 222) claim that among early humans, “few individuals passed forty years, and it is only quite exceptionally that any passed fifty,” and the more traditional Hobbesian view of a nasty, brutish, and short human life (see also King and Jukes 1969; Weiss 1981). The data show that modal adult lifespan is 68–78 years, and that it was not uncommon for individuals to reach these ages”

iv. What is it like when one of your parents gets Alzheimer’s? It’s not fun.

v. Different strategies for screening and prevention of type 2 diabetes in adults: cost effectiveness analysis.

“What is already known on this topic
  • In people with impaired glucose tolerance interventions are clinically and cost effective

  • Screening for type 2 diabetes to allow early detection might be cost effective in certain groups

What this study adds

  • Modelling the whole screening and intervention pathway from screening to death shows that screening for type 2 diabetes and impaired glucose tolerance, followed by interventions, seems to be cost effective compared with no screening

  • Uncertainty still exists concerning the cost effectiveness of screening for type 2 diabetes alone

  • Screening populations with a higher prevalence of glucose intolerance might result in better clinical outcomes, although cost effectiveness seems unaffected”

vi. PLOS-ONE: Minimal Intensity Physical Activity (Standing and Walking) of Longer Duration Improves Insulin Action and Plasma Lipids More than Shorter Periods of Moderate to Vigorous Exercise (Cycling) in Sedentary Subjects When Energy Expenditure Is Comparable.

N is small but even so this is an interesting finding.

vii. “Commercial fishing operations in the past 40 years have precipitated a dramatic change in ocean fish stocks, with tuna and other big predators declining and small fish like anchovies and sardines surging. That’s the conclusion of the most ambitious study ever completed of fish populations in the Earth’s oceans, conducted by Villy Christensen of the University of British Columbia’s Fisheries Centre.In the past 100 years, 80% of the biomass of fish in the world’s oceans has been lost, Christensen says in a AAAS video that coincided with a symposium at the Annual Meeting. “Just in the last 40 years, we have lost 60% of the biomass,” he explained. “So we’ve seen some very serious declines, and there’s no doubt about what the cause is: We’re talking about overfishing—overfishing at the global scale.” […] Christensen’s team of scientists based their conclusions on more than 200 marine ecosystem models and more than 68,000 estimates of fish biomass from 1880 to 2007, the Vancouver Sun reported, citing a University of British Columbia news release.”

Here’s the link.

March 4, 2013 Posted by | Anthropology, Biology, Data, Diabetes, Ecology, Economics, Evolutionary biology, Health Economics, Medicine, Papers, Random stuff, Zoology | 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

More preliminary data on the blood glucose/mental performance ‘study’

Previous posts here and here. I haven’t been very good at gathering data and during the exam period I basically stopped, but I do have 105 observations at this point.

The R-squared and the estimated effect size in a simple linear model both look almost identical at this point in time as they did 55 observations ago – I’ve posted both the old scatterplot (first) and an updated version (second) below – click to view the full size versions:


105 obs

I have however been a little suspicious about a few data-points which were collected around the time of the London Chess Classics tournament last year – I spent a significant amount of time on chess during that week and my playing strength when playing blitz games went up a lot those days too (I gained ~150 elo points over 4-5 days, which is a lot – I’ve lost that rating again at this point). Here’s what the image looks like without those observations:

without London days

I am not convinced that ‘blood glucose has no effect on tactics trainer performance’ is the conclusion to draw from this data-set, so I’m still collecting data at this point. The true data generating process of course includes many variables not included above – you may want to reread the first article if you want to know more about the ‘true’ DTG.

I wrote in my first post that: “I know myself well enough to know that I don’t want to bother with non-linear models when I look at this stuff later; it’s a poor and underspecified model to begin with.” If I actually have to work with methods which prove useful when analysing this type of dataset during my statistics course this semester (do remember that I have not included all the data I’ve gathered in the above plots), I may change my mind about how much work I’ll do on this dataset. Maybe I’ll be reminded of useful ways to handle stuff like this during the course; stuff that I’ve forgotten about at this point. We’ll see how it goes.

If anyone else would like to have a look at the data, just leave a comment below – I’d be happy to send you a copy of the data.

February 16, 2013 Posted by | Data, Diabetes, Personal | Leave a comment


i. PLOS ONE: Till Death (Or an Intruder) Do Us Part: Intrasexual-Competition in a Monogamous Primate.

“Polygynous animals are often highly dimorphic, and show large sex-differences in the degree of intra-sexual competition and aggression, which is associated with biased operational sex ratios (OSR). For socially monogamous, sexually monomorphic species, this relationship is less clear. Among mammals, pair-living has sometimes been assumed to imply equal OSR and low frequency, low intensity intra-sexual competition; even when high rates of intra-sexual competition and selection, in both sexes, have been theoretically predicted and described for various taxa. Owl monkeys are one of a few socially monogamous primates. Using long-term demographic and morphological data from 18 groups, we show that male and female owl monkeys experience intense intra-sexual competition and aggression from solitary floaters. Pair-mates are regularly replaced by intruding floaters (27 female and 23 male replacements in 149 group-years), with negative effects on the reproductive success of both partners. Individuals with only one partner during their life produced 25% more offspring per decade of tenure than those with two or more partners. The termination of the pair-bond is initiated by the floater, and sometimes has fatal consequences for the expelled adult. The existence of floaters and the sporadic, but intense aggression between them and residents suggest that it can be misleading to assume an equal OSR in socially monogamous species based solely on group composition. Instead, we suggest that sexual selection models must assume not equal, but flexible, context-specific, OSR in monogamous species.”

You sort of want to extrapolate out of sample (/…out of species?) here, but be careful:

“Our findings differ from those reported for some monogamous birds, where remaining life-time reproductive success (i.e., the expected future gains) of the individual that initiates or tolerates a ‘divorce’ was higher than if it remained with its initial partner. For example, in kittiwakes (Rissa tridactyla) and many other pair-living birds, but also in some human societies, it is sometimes advantageous to ‘divorce’, if partners prove incompatible [25], [27], [35]. In contrast, our data strongly indicate that break-ups were associated with factors extrinsic to the pair, and that partners did not voluntarily leave or “divorce” as it has been reported for birds, gibbons, and (in at least one case) brown titi monkeys (Callicebus brunneus) [25][27], [36], [37]. On the other hand, in some species (oystercatchers, Haematopus ostralegus), the reproductive success of stable pairs is not only higher, but there are also accrued benefits with increased duration of the pair-bond, independent of effects of age or experience [38]. This was not the case for owl monkeys, since the number of offspring produced did not change with increased duration of the pair-bond (Fig. 2).”

ii. Smbc (click to watch in a higher resolution):

2868 societal complexity
Just to remind you that SMBC is still awesome. Here are a couple of related comics from the site.

iii. PNAS: Microstratigraphic evidence of in situ fire in the Acheulean strata of Wonderwerk Cave, Northern Cape province, South Africa:

“The ability to control fire was a crucial turning point in human evolution, but the question when hominins first developed this ability still remains. Here we show that micromorphological and Fourier transform infrared microspectroscopy (mFTIR) analyses of intact sediments at the site of Wonderwerk Cave, Northern Cape province, South Africa, provide unambiguous evidence—in the form of burned bone and ashed plant remains—that burning took place in the cave during the early Acheulean occupation, approximately 1.0 Ma. To the best of our knowledge, this is the earliest secure evidence for burning in an archaeological context.”

[Another reminder that SMBC is awesome: Here’s a recent comic which is very handy here – it explains what a Fourier transform is, in case you don’t know… (If you actually want to know there’s always wikipedia…)]

iv. I never covered this here and though some of you may already have read it I thought I might as well link to Ed Yong’s write-up on replication studies in Nature published last year. A few quotes from the article:

“Positive results in psychology can behave like rumours: easy to release but hard to dispel. They dominate most journals, which strive to present new, exciting research. Meanwhile, attempts to replicate those studies, especially when the findings are negative, go unpublished, languishing in personal file drawers or circulating in conversations around the water cooler. “There are some experiments that everyone knows don’t replicate, but this knowledge doesn’t get into the literature,” says Wagenmakers. The publication barrier can be chilling, he adds. “I’ve seen students spending their entire PhD period trying to replicate a phenomenon, failing, and quitting academia because they had nothing to show for their time.

These problems occur throughout the sciences, but psychology has a number of deeply entrenched cultural norms that exacerbate them. It has become common practice, for example, to tweak experimental designs in ways that practically guarantee positive results. And once positive results are published, few researchers replicate the experiment exactly, instead carrying out ‘conceptual replications’ that test similar hypotheses using different methods. This practice, say critics, builds a house of cards on potentially shaky foundations.

These problems have been brought into sharp focus by some high-profile fraud cases, which many believe were able to flourish undetected because of the challenges of replication. Now psychologists are trying to fix their field.”

Good luck with that. I don’t see a fix happening anytime soon. A few numbers:

“In a survey of 4,600 studies from across the sciences, Daniele Fanelli, a social scientist at the University of Edinburgh, UK, found that the proportion of positive results rose by more than 22% between 1990 and 2007 (ref. 3). Psychology and psychiatry, according to other work by Fanelli4, are the worst offenders: they are five times more likely to report a positive result than are the space sciences, which are at the other end of the spectrum […]. The situation is not improving. In 1959, statistician Theodore Sterling found that 97% of the studies in four major psychology journals had reported statistically significant positive results5. When he repeated the analysis in 1995, nothing had changed6.”

But maybe other fields are just as bad? Well, as already mentioned the space sciences do better – and that goes for other fields too (though I’d say there seems to be major problems in many areas besides psychology and psychiatry):


A major problem here is that unless you’re actually a researcher in the field or know whom to ask, the file drawer effect can be completely invisible to you.

v. Globalization of Diabetes – The role of diet, lifestyle, and genes. A new publication in Diabetes Care. As usual when they say ‘diabetes’ they mean ‘type 2 diabetes’. Some numbers from the article:

“According to the International Diabetes Federation (1), diabetes affects at least 285 million people worldwide, and that number is expected to reach 438 million by the year 2030, with two-thirds of all diabetes cases occurring in low- to middle-income countries. The number of adults with impaired glucose tolerance will rise from 344 million in 2010 to an estimated 472 million by 2030.
Globally, it was estimated that diabetes accounted for 12% of health expenditures in 2010, or at least $376 billion—a figure expected to hit $490 billion in 2030 (2). […] Asia accounts for 60% of the world’s diabetic population. [Do note that this does not mean that Asian countries are on average overrepresented in the diabetes statistics. Asia also has roughly 60% of the World’s population. – US] […] In 1980, less than 1% of Chinese adults had the disease. By 2008, the prevalence had reached nearly 10% […] in urban areas of south India, the prevalence of diabetes has reached nearly 20% […] Compared with Western populations, Asians develop diabetes at younger ages, at lower degrees of obesity, and at much higher rates given the same amount of weight gain […]

If current worldwide trends continue, the number of overweight people (BMI >25 kg/m^2) is projected to increase from 1.3 billion in 2005 to nearly 2.0 billion by 2030 (6). […] the prevalence of overweight and obesity in Chinese adults increased from 20% in 1992 to 29.9% in 2002 (8) […]

In the NHS (26), each 2-h/day increment of time spent watching television (TV) was associated with a 14% increase in diabetes risk. […] Each 1-h/day increment of brisk walking was associated with a 34% reduction in risk […] Cigarette smoking is an independent risk factor for type 2 diabetes. A meta-analysis found that current smokers had a 45% increased risk of developing diabetes compared with nonsmokers (29). Moreover, there was a dose-response relationship between the number of cigarettes smoked and diabetes risk. [That one I did not know about!] […] Light-to-moderate alcohol consumption is associated with reduced risk of diabetes. A meta-analysis of 370,000 individuals with 12 years of follow-up showed a U-shaped relationship, with a 30–40% reduced risk of the disease among those consuming 1–2 drinks/day compared with heavy drinkers or abstainers (37). […]

common variants of the TCF7L2 gene that are significantly associated with diabetes risk are present in 20–30% of Caucasian populations but only 3–5% of Asians […] Conversely, a variant in the KCNQ1 gene associated with a 20–30% increased risk of diabetes in several Asian populations (43,44) is common in East Asians, but rare in Caucasians […]

Several randomized clinical trials have demonstrated that diabetes is preventable. One of the first diabetes prevention trials was conducted in Daqing, China (58). After 6 years of active intervention, risk was reduced by 31, 46, and 42% in the diet-only, exercise-only, and diet-plus-exercise groups, respectively, compared with the control group. In a subsequent 14-year follow-up study, the intervention groups were combined and compared with control subjects to assess how long the benefits of lifestyle change can extend beyond the period of active intervention (59). Compared with control subjects, individuals in the combined lifestyle intervention group had a 51% lower risk of diabetes during the active intervention period, and a 43% lower risk over a 20-year follow-up.”

vi. Why chess sucks.

vii. If you think your life sucks

February 3, 2013 Posted by | Archaeology, Biology, Data, Diabetes, Genetics, Papers, Psychology, Random stuff, Zoology | 2 Comments

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, Epidemiology, marriage, Medicine, 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, History, Medicine, Statistics | Leave a comment