Yesterday I gave some of the reasons I had for disliking the book; in this post I’ll provide some of the reasons why I kept reading. The book had a lot of interesting data. I know I’ve covered some of these topics and numbers before (e.g. here), but I don’t mind repeating myself every now and then; some things are worth saying more than once, and as for the those that are not I must admit I don’t really care enough about not repeating myself here to spend time perusing the archives in order to make sure I don’t repeat myself here. Anyway, here are some number from the coverage:
“Twenty-two high-burden countries account for over 80 % of the world’s TB cases […] data referring to 2011 revealed 8.7 million new cases of TB [worldwide] (13 % coinfected with HIV) and 1.4 million people deaths due to such disease […] Around 80 % of TB cases among people living with HIV were located in Africa. In 2011, in the WHO European Region, 6 % of TB patients were coinfected with HIV […] In 2011, the global prevalence of HIV accounted for 34 million people; 69 % of them lived in Sub-Saharan Africa. Around five million people are living with HIV in South, South-East and East Asia combined. Other high-prevalence regions include the Caribbean, Eastern Europe and Central Asia . Worldwide, HIV incidence is in downturn. In 2011, 2.5 million people acquired HIV infection; this number was 20 % lower than in 2001. […] Sub-Saharan Africa still accounts for 70 % of all AIDS-related deaths […] Worldwide, an estimated 499 million new cases of curable STIs (as gonorrhoea, chlamydia and syphilis) occurred in 2008; these findings suggested no improvement compared to the 448 million cases occurring in 2005. However, wide variations in the incidence of STIs are reported among different regions; the burden of STIs mainly occurs in low-income countries”.
“It is estimated that in 2010 alone, malaria caused 216 million clinical episodes and 655,000 deaths. An estimated 91 % of deaths in 2010 were in the African Region […]. A total of 3.3 billion people (half the world’s population) live in areas at risk of malaria transmission in 106 countries and territories”.
“Diarrhoeal diseases amount to an estimated 4.1 % of the total disability-adjusted life years (DALY) global burden of disease, and are responsible for 1.8 million deaths every year. An estimated 88 % of that burden is attributable to unsafe supply of water, sanitation and hygiene […] It is estimated that diarrhoeal diseases account for one in nine child deaths worldwide, making diarrhoea the second leading cause of death among children under the age of 5 after pneumonia”
“NCDs [Non-Communicable Diseases] are the leading global cause of death worldwide, being responsible for more
deaths than all other causes combined. […] more than 60 % of all deaths worldwide currently stem from NCDs .
In 2008, the leading causes of all NCD deaths (36 million) were:
• CVD [cardiovascular disease] (17 million, or 48 % of NCD deaths) [nearly 30 % of all deaths];
• Cancer (7.6 million, or 21 % of NCD deaths) [about 13 % of all deaths]
• Respiratory diseases (4.2 million, or 12 % of NCD deaths) [7 % of all deaths]
• Diabetes (1.3 million, 4 % of NCD deaths) .” [Elsewhere in the publication they report that: “In 2010, diabetes was responsible for 3.4 million deaths globally and 3.6 % of DALYs” – obviously there’s a lot of uncertainty here. How to avoid ‘double-counting’ is one of the major issues, because we have a pretty good idea what they die of: “CVD is by far the most frequent cause of death in both men and women with diabetes, accounting for about 60 % of all mortality”].
“Behavioural risk factors such as physical inactivity, tobacco use and unhealthy diet explain nearly 80 % of the CVD burden”
“nearly 80 % of NCD deaths occur in low- and middle-income countries , up sharply from just under 40 % in 1990 […] Low- and lower-middle-income countries have the highest proportion of deaths from NCDs under 60 years. Premature deaths under 60 years for high-income countries were 13 and 25 % for upper-middle-income countries. […] In low-income countries, the proportion of premature NCD deaths under 60 years is 41 %, three times the proportion in high-income countries . […] Overall, NCDs account for more than 50 % of DALYs [disability-adjusted life years] in most counties. This percentage rises to over 80 % in Australia, Japan and the richest countries of Western Europe and North America […] In Europe, CVD causes over four million deaths per year (52 % of deaths in women and 42 % of deaths in men), and they are the main cause of death in women in all European countries.”
“Overall, age-adjusted CVD death rates are higher in most low- and middle-income countries than in developed countries […]. CHD [coronary heart disease] and stroke together are the first and third leading causes of death in developed and developing countries, respectively. […] excluding deaths from cancer, these two conditions were responsible for more deaths in 2008 than all remaining causes among the ten leading causes of death combined (including chronic diseases of the lungs, accidents, diabetes, influenza, and pneumonia)”.
“The global prevalence of diabetes was estimated to be 10 % in adults aged 25 + years […] more than half of all nontraumatic lower limb amputations are due to diabetes [and] diabetes is one of the leading causes of visual impairment and blindness in developed countries .”
“Almost six million people die from tobacco each year […] Smoking is estimated to cause nearly 10 % of CVD […] Approximately 2.3 million die each year from the harmful use of alcohol. […] Alcohol abuse is responsible for 3.8 % of all deaths (half of which are due to CVD, cancer, and liver cirrhosis) and 4.5 % of the global burden of disease […] Heavy alcohol consumption (i.e. ≥ 4 drinks/day) is significantly associated with an about fivefold increased risk of oral and pharyngeal cancer and oesophageal squamous cell carcinoma (SqCC), 2.5-fold for laryngeal cancer, 50 % for colorectal and breast cancers and 30 % for pancreatic cancer . These estimates are based on a large number of epidemiological studies, and are generally consistent across strata of several covariates. […] The global burden of cancer attributable to alcohol drinking has been estimated at 3.6 and 3.5 % of cancer deaths , although this figure is higher in high-income countries (e.g. the figure of 6 % has been proposed for UK  and 9 % in Central and Eastern Europe).”
“At least two million cancer cases per year (18 % of the global cancer burden) are attributable to chronic infections by human papillomavirus, hepatitis B virus, hepatitis C virus and Helicobacter pylori. These infections are largely preventable or treatable […] The estimate of the attributable fraction is higher in low- and middle-income countries than in high-income countries (22.9 % of total cancer vs. 7.4 %).”
“Information on the magnitude of CVD in high-income countries is available from three large longitudinal studies that collect multidisciplinary data from a representative sample of European and American individuals aged 50 and older […] according to the Health Retirement Survey (HRS) in the USA, almost one in three adults have one or more types of CVD [11, 12]. By contrast, the data of Survey of Health, Ageing and Retirement in Europe (SHARE), obtained from 11 European countries, and English Longitudinal Study of Aging (ELSA) show that disease rates (specifically heart disease, diabetes, and stroke) across these populations are lower (almost one in five)”
“In 1990, the major fraction of morbidity worldwide was due to communicable, maternal, neonatal, and nutritional disorders (47 %), while 43 % of disability adjusted life years (DALYs) lost were attributable to NCDs. Within two decades, these estimates had undergone a drastic change, shifting to 35 % and 54 %, respectively”
“Estimates of the direct health care and nonhealth care costs attributable to CVD in many countries, especially in low- and middle-income countries, are unclear and fragmentary. In high-income countries (e.g., USA and Europe), CVD is the most costly disease both in terms of economic costs and human costs. Over half (54 %) of the total cost is due to direct health care costs, while one fourth (24 %) is attributable to productivity losses and 22 % to the informal care of people with CVD. Overall, CVD is estimated to cost the EU economy, in terms of health care, almost €196 billion per year, i.e., 9 % of the total health care expenditure across the EU”
“In the WHO European Region, the Eastern Mediterranean Region, and the Region of the Americas, over 50 % of women are overweight. The highest prevalence of overweight among infants and young children is in upper-to-middle-income populations, while the fastest rise in overweight is in the lower-to-middle-income group . Globally, in 2008, 9.8 % of men and 13.8 % of women were obese compared to 4.8 % of men and 7.9 % of women in 1980 .”
“In low-income countries, around 25 % of adults have raised total cholesterol, while in high-income countries, over 50 % of adults have raised total cholesterol […]. Overall, one third of CHD disease is attributable to high cholesterol levels” (These numbers seem very high to me, but I’m reporting them anyway).
“interventions based on tobacco taxation have a proportionally greater effect on smokers of lower SES and younger smokers, who might otherwise be difficult to influence. Several studies suggest that the application of a 10 % rise in price could lead to as much as a 2.5–10 % decline in smoking [20, 45, 50, 56].”
“The decision to allocate resources for implementing a particular health intervention depends not only on the strength of the evidence (effectiveness of intervention) but also on the cost of achieving the expected health gain. Cost-effectiveness analysis is the primary tool for evaluating health interventions on the basis of the magnitude of their incremental net benefits in comparison with others, which allows the economic attractiveness of one program over another to be determined [More about this kind of stuff here]. If an intervention is both more effective and less costly than the existing one, there are compelling reasons to implement it. However, the majority of health interventions do not meet these criteria, being either more effective but more costly, or less costly but less effective, than the existing interventions [see also this]. Therefore, in most cases, there is no “best” or absolute level of cost-effectiveness, and this level varies mainly on the basis of health care system expenditure and needs .”
“The number of new cases of cancer worldwide in 2008 has been estimated at about 12,700,000 . Of these, 6,600,000 occurred in men and 6,000,000 in women. About 5,600,000 cases occurred in high-resource countries […] and 7,100,000 in low- and middle-income countries. Among men, lung, stomach, colorectal, prostate and liver cancers are the most common […], while breast, colorectal, cervical, lung and stomach are the most common neoplasms among women […]. The number of deaths from cancer was estimated at about 7,600,000 in 2008 […] No global estimates of survival from cancer are available: Data from selected cancer registries suggest wide disparities between high- and low-income countries for neoplasms with effective but expensive treatment, such as leukaemia, while the gap is narrow for neoplasms without an effective therapy, such as lung cancer […]. The overall 5-year survival of cases diagnosed during 1995– 1999 in 23 European countries was 49.6 % […] Tobacco smoking is the main single cause of human cancer worldwide […] In high-income countries, tobacco smoking causes approximately 30 % of all human cancers .”
“Systematic reviews have concluded that nutritional factors may be responsible for about one fourth of human cancers in high-income countries, although, because of the limitations of the current understanding of the precise role of diet in human cancer, the proportion of cancers known to be avoidable in practicable ways is much smaller . The only justified dietary recommendation for cancer prevention is to reduce the total caloric intake, which would contribute to a decrease in overweight and obesity, an established risk factor for human cancer. […] The magnitude of the excess risk [associated with obesity] is not very high (for most cancers, the relative risk (RR) ranges between 1.5 and 2 for body weight higher than 35 % above the ideal weight). Estimates of the proportion of cancers attributable to overweight and obesity in Europe range from 2 %  to 5 % . However, this figure is likely to be larger in North America, where the prevalence of overweight and obesity is higher.”
“Estimates of the global burden of cancer attributable to occupation in high-income countries result in the order of 1–5 % [9, 42]. In the past, almost 50 % of these were due to asbestos alone […] The available evidence suggests, in most populations, a small role of air, water and soil pollutants. Global estimates are in the order of 1 % or less of total cancers [9, 42]. This is in striking contrast with public perception, which often identifies pollution as a major cause of human cancer.”
“Avoidance of sun exposure, in particular during the middle of the day, is the primary preventive measure to reduce the incidence of skin cancer. There is no adequate evidence of a protective effect of sunscreens, possibly because use of sunscreens is associated with increased exposure to the sun. The possible benefit in reducing skin cancer risk by reduction of sun exposure, however, should be balanced against possible favourable effects of UV radiation in promoting vitamin D metabolism.”
In my review of the book on goodreads I did not have many nice things to say about this book, but I do note that the book had some interesting data. I’ll save those for another post – in this post I’ll provide some of the reasons why the book got a one star rating. Given the format of the book I thought I should clarify a bit what I didn’t like about it, because both the title and actually also the basic structure maked the book seem quite promising; they cover a lot of review articles and a lot of studies, so how could I possibly dislike a book like that? Well…
The main issue: If I thought the Psychology of Lifestyle book was bad in terms of implicit political assumptions etc., this book takes this to a whole different level. Outright bans and severe restrictions on behaviours harming health are repeatedly described as either cost-effective or ‘best buys’, and many chapters don’t even touch upon potential problems associated with such policies, making you start wondering along the way why policies such as national bans on alcohol and tobacco and special police forces armed with automatic weapons coming to your house during the night and throwing you in jail if you’re found smoking a cigarette aren’t already implemented worldwide, if the research looks that way. The political agenda here seems so apparent in many chapters that you start questioning the reporting because you figure these people would not be above lying to you to get the sort of policies they’d like. Faulty assumptions throughout the coverage don’t help – as a rule you don’t get significant health effects by simply providing information about healthy behaviours and behavioural risk factors to the population; we know this from a large number of studies – and I know this because I just read a book about this research – so the fact that some authors assume such interventions to be ‘cost-effective’, and that they can point to one very old example where there does seem to have been some measurable effects, does not convince me. Some of the authors point to interventions involving primary care physicians lecturing people about healthy lifestyle behaviours being cost effective, without at all going into the many issues related to even evaluating the long-run health effects of such interventions. That effects might not persist over time is not the impression you get from this kind of coverage:
“The evidence suggests that counseling by physicians to reduce intake of total fat, saturated fat intake, and daily salt, and to increase fruit and vegetable intake, is very cost-effective, leading to dietary changes, improved weight control, and increased physical activity [64–69].” (p. 55).
Compare with for example this quote from Thirlaway and Upton:
“Hundreds of interventions to combat the obesity epidemic are currently being introduced worldwide, but there are significant gaps in the evidence base for such interventions and few been evaluated in a way that enables any definitive conclusions to be drawn about their effectiveness. Those that have shown an impact are limited to easily controlled settings and it remains unclear how promising small-scale initiatives would be scaled up for whole population impact”.
What people compare when doing the CEAs in the book is occasionally/often unclear, which tends to make that sort of reporting close to worthless. I had the impression in some parts of the coverage that what was driving cost-effectiveness in some of the studies was a combination of large health impacts of disease + assumed but unproven/speculative health impacts of the interventions; an impression probably partly a result of the intervention study coverage provided in Thirlaway & Upton.
‘Implicit assumptions’ and more or less overtly politicizing comments along the way spoiled the reading experience. Below I have added some examples of sentences I for various reasons did not like:
“Several countries have explored fiscal measures such as increased taxation on foods that should be consumed in lower quantities and decreased taxation, price subsidies or production incentives for foods that are encouraged.” (‘foods that should be consumed…’).
“Restriction of alcohol drinking to the limits indicated by the European Code Against Cancer  (20 g/day for men and 10 g/day for women) would avoid about 90 % of alcohol-related cancers and cancer deaths in men and over 50 % of cancers in women, i.e. about 330/360,000 cancer cases and about 200/220,000 cancer deaths. Avoidance or moderation of alcohol consumption to 2 drinks/day in men and 1 drink/day in women is therefore a global public health priority” [The idea that men might not want to avoid 90% of alcohol-related cancers doesn’t seem to cross the minds of these authors – they want them to not get cancer, and they’re going to get their way one way or the other, dammit!]
“Nowadays, obesity is the most frequently encountered metabolic disease” [Disease? Disease???]
“T2D is the most common type of diabetes, representing 90 % of cases worldwide and it is named non-insulin-dependent diabetes mellitus (NIDDM)” [My comment in the margin: “No, it’s actually not. No longer. Because this is a terrible name. A majority of diabetics on insulin treatment are type 2 diabetics.” (see also my comments in the last paragraph here if you’re curious to know more about this topic)]
“The difficulty of communicating is, however, exactly the major obstacle in this communion of responsibility. In this regard, we shall analyze the dynamics of interpersonal communication based on the scheme proposed by Slama-Cazacu . According to this model the elements of a communicative act are: (1) the transmitter, who produces the message, (2) the message conveyed according to the rules provided by code; (3) the code according to which the message is produced; (4) the transmission channel; (5) the context in which the message is found and to which it refers; and (6) the receiver” [To be frank, the chapter from which this quote is taken – Some Ethical Reflections in Public Health – had almost nothing but problematic sentences, despite actually addressing a few issues I’d had with the coverage elsewhere in the publication. I thought the quote illustrated how rambling and besides-the-point that coverage was; recall that this is a chapter about ethics. The quote was used to provide context so that you’d understand e.g. that people sometimes don’t understand health messages. Incidentally you should not be fooled by the quote into assuming that the author actually covered any data about how sensitive people are to health data in this coverage (how information impacts behaviour). She of course did not.]
“The distal risk factors of ethnic groups thus explain why a certain proximal risk factor is unevenly distributed across ethnic groups. If, for example, a certain ethnic minority group has an increased prevalence of smoking, this may be due to the fact that the group is exposed to discrimination in the host country (relational), or to specific sociocultural values characteristic for that group (attributional).” [My comment in the margin: “Discrimination => smoking? Seriously? Stop being stupid.” I was close to losing my patience at this point…]
“metabolic control is poor among migrant groups with diabetes, and HbA1c in migrants is generally higher than in the local-born population [3, 32]. These findings suggest shortfalls in diabetes health care among migrant populations.” [“Or some of the immigrants are stupid and irresponsible.” As mentioned, I was losing patience fast… (In the margin the words ‘some of’ were of course not included, but I live in a wonderful country where omitting such qualifiers in texts like this one run you the risk of getting thrown in jail for ‘racism’..)]
“For European health care contexts, empirical research on inequalities in healthcare outcomes is scarce. For some diseases or care contexts, ethnic inequalities in outcomes, attributable to deficient care, have been shown.” [Stuff like this was also part of the reason for the outburst above – I got really annoyed in this chapter, because the author repeatedly seemed to assume/implicitly assert that anything less than equal coverage for all individuals living in a country was a state that was really morally unjustifiable – later talk about ‘diversity-responsive care’ did not help. I don’t understand how anyone would consider it to be fair that a guy getting sick after paying taxes into the cost-sharing mechanism financing his care for 30 years do not get better health care coverage than some poor immigrant who just arrived yesterday and haven’t paid anything into the scheme, but anyway this is politics and so I shouldn’t bother.]
“In developing countries, the prevalence of some form of depression among urban adults ranges from 12 to 51 %” [No, it probably doesn’t…]
“Of course, in a millennium in which next to the advancement of health technologies (digital, with the development of nanotechnology; social and cultural, with the emergence of new values that should be conjugated with the old; scientific and medical, through imaging and the study of genomics, proteomics, and metabolomics; etc.) there is a global crisis of the world economy, it is fundamental to strengthen and use the assets of individual and community resilience (most definitions of resilience refer to notions—derived from physics—of rebound, or bouncing back, from deformation or distress), also because action to improve community health requires the coordination and the cooperation of decision makers in many sectors responsible for shaping wider determinants, and also because the traditional management of policy may be ineffective to address the problems of the “future cities” and requires an institutional change, given the discrepancy that can exist between technological innovation, scientific evolution, and adaptive flexibility of governance systems.” [This was around the point where I decided that no matter what happened in the last couple of chapters, this book is going to get one star]
“The National Institute for Public Health and the Environment was committed to analyze opportunities to address health inequalities through the HiAP strategy. On the basis of data derived from the document analysis, 38 out of 153 policy resolutions were identified to have a potential impact on determinants of health inequalities. Resolutions often consisted of a combination of policy measures, projects, and programs and were mostly released by the Ministry of Housing, Communities, and Integration and by the Ministry of the Education, Culture, and Science. Fifteen resolutions were on the enhancement of socioeconomic position; 4 on striving participation of people with health problems; 19 on improving living and working environment and lifestyle; and 4 on accessibility and quality of care. Interestingly, only 11 were inter-sectoral collaboration between the Ministry of Health and other ministries. This aspect allows us to conclude that even though HiAP is officially recognized as a strategic approach to be followed in setting policies and programs, further efforts are needed at European and global levels in order to implement in a practical manner.” [I’m pretty sure if this stuff had not been located in the last chapter of the book, I’d never have finished the book.]
I haven’t really blogged this book in anywhere near the amount of detail it deserves even though my first post about the book actually had a few quotes illustrating how much different stuff is covered in the book.
This book is technical, and even if I’m trying to make it less technical by omitting the math in this post it may be a good idea to reread the first post about the book before reading this post to refresh your knowledge of these things.
Quotes and comments below – most of the coverage here focuses on stuff covered in chapters 3 and 4 in the book.
“Tests of null hypotheses and information-theoretic approaches should not be used together; they are very different analysis paradigms. A very common mistake seen in the applied literature is to use AIC to rank the candidate models and then “test” to see whether the best model (the alternative hypothesis) is “significantly better” than the second-best model (the null hypothesis). This procedure is flawed, and we strongly recommend against it […] the primary emphasis should be on the size of the treatment effects and their precision; too often we find a statement regarding “significance,” while the treatment and control means are not even presented. Nearly all statisticians are calling for estimates of effect size and associated precision, rather than test statistics, P-values, and “significance.” [Borenstein & Hedges certainly did as well in their book (written much later), and this was not an issue I omitted to talk about in my coverage of their book…] […] Information-theoretic criteria such as AIC, AICc, and QAICc are not a “test” in any sense, and there are no associated concepts such as test power or P-values or α-levels. Statistical hypothesis testing represents a very different, and generally inferior, paradigm for the analysis of data in complex settings. It seems best to avoid use of the word “significant” in reporting research results under an information-theoretic paradigm. […] AIC allows a ranking of models and the identification of models that are nearly equally useful versus those that are clearly poor explanations for the data at hand […]. Hypothesis testing provides no general way to rank models, even for models that are nested. […] In general, we recommend strongly against the use of null hypothesis testing in model selection.”
“The bootstrap is a type of Monte Carlo method used frequently in applied statistics. This computer-intensive approach is based on resampling of the observed data […] The fundamental idea of the model-based sampling theory approach to statistical inference is that the data arise as a sample from some conceptual probability distribution f. Uncertainties of our inferences can be measured if we can estimate f. The bootstrap method allows the computation of measures of our inference uncertainty by having a simple empirical estimate of f and sampling from this estimated distribution. In practical application, the empirical bootstrap means using some form of resampling with replacement from the actual data x to generate B (e.g., B = 1,000 or 10,000) bootstrap samples […] The set of B bootstrap samples is a proxy for a set of B independent real samples from f (in reality we have only one actual sample of data). Properties expected from replicate real samples are inferred from the bootstrap samples by analyzing each bootstrap sample exactly as we first analyzed the real data sample. From the set of results of sample size B we measure our inference uncertainties from sample to (conceptual) population […] For many applications it has been theoretically shown […] that the bootstrap can work well for large sample sizes (n), but it is not generally reliable for small n […], regardless of how many bootstrap samples B are used. […] Just as the analysis of a single data set can have many objectives, the bootstrap can be used to provide insight into a host of questions. For example, for each bootstrap sample one could compute and store the conditional variance–covariance matrix, goodness-of-fit values, the estimated variance inflation factor, the model selected, confidence interval width, and other quantities. Inference can be made concerning these quantities, based on summaries over the B bootstrap samples.”
“Information criteria attempt only to select the best model from the candidate models available; if a better model exists, but is not offered as a candidate, then the information-theoretic approach cannot be expected to identify this new model. Adjusted R2 […] are useful as a measure of the proportion of the variation “explained,” [but] are not useful in model selection […] adjusted R2 is poor in model selection; its usefulness should be restricted to description.”
“As we have struggled to understand the larger issues, it has become clear to us that inference based on only a single best model is often relatively poor for a wide variety of substantive reasons. Instead, we increasingly favor multimodel inference: procedures to allow formal statistical inference from all the models in the set. […] Such multimodel inference includes model averaging, incorporating model selection uncertainty into estimates of precision, confidence sets on models, and simple ways to assess the relative importance of variables.”
“If sample size is small, one must realize that relatively little information is probably contained in the data (unless the effect size if very substantial), and the data may provide few insights of much interest or use. Researchers routinely err by building models that are far too complex for the (often meager) data at hand. They do not realize how little structure can be reliably supported by small amounts of data that are typically “noisy.””
“Sometimes, the selected model [when applying an information criterion] contains a parameter that is constant over time, or areas, or age classes […]. This result should not imply that there is no variation in this parameter, rather that parsimony and its bias/variance tradeoff finds the actual variation in the parameter to be relatively small in relation to the information contained in the sample data. It “costs” too much in lost precision to add estimates of all of the individual θi. As the sample size increases, then at some point a model with estimates of the individual parameters would likely be favored. Just because a parsimonious model contains a parameter that is constant across strata does not mean that there is no variation in that process across the strata.”
“[In a significance testing context,] a significant test result does not relate directly to the issue of what approximating model is best to use for inference. One model selection strategy that has often been used in the past is to do likelihood ratio tests of each structural factor […] and then use a model with all the factors that were “significant” at, say, α = 0.05. However, there is no theory that would suggest that this strategy would lead to a model with good inferential properties (i.e., small bias, good precision, and achieved confidence interval coverage at the nominal level). […] The purpose of the analysis of empirical data is not to find the “true model”— not at all. Instead, we wish to find a best approximating model, based on the data, and then develop statistical inferences from this model. […] We search […] not for a “true model,” but rather for a parsimonious model giving an accurate approximation to the interpretable information in the data at hand. Data analysis involves the question, “What level of model complexity will the data support?” and both under- and overfitting are to be avoided. Larger data sets tend to support more complex models, and the selection of the size of the model represents a tradeoff between bias and variance.”
“The easy part of the information-theoretic approaches includes both the computational aspects and the clear understanding of these results […]. The hard part, and the one where training has been so poor, is the a priori thinking about the science of the matter before data analysis — even before data collection. It has been too easy to collect data on a large number of variables in the hope that a fast computer and sophisticated software will sort out the important things — the “significant” ones […]. Instead, a major effort should be mounted to understand the nature of the problem by critical examination of the literature, talking with others working on the general problem, and thinking deeply about alternative hypotheses. Rather than “test” dozens of trivial matters (is the correlation zero? is the effect of the lead treatment zero? are ravens pink?, Anderson et al. 2000), there must be a more concerted effort to provide evidence on meaningful questions that are important to a discipline. This is the critical point: the common failure to address important science questions in a fully competent fashion. […] “Let the computer find out” is a poor strategy for researchers who do not bother to think clearly about the problem of interest and its scientific setting. The sterile analysis of “just the numbers” will continue to be a poor strategy for progress in the sciences.
Researchers often resort to using a computer program that will examine all possible models and variables automatically. Here, the hope is that the computer will discover the important variables and relationships […] The primary mistake here is a common one: the failure to posit a small set of a priori models, each representing a plausible research hypothesis.”
“Model selection is most often thought of as a way to select just the best model, then inference is conditional on that model. However, information-theoretic approaches are more general than this simplistic concept of model selection. Given a set of models, specified independently of the sample data, we can make formal inferences based on the entire set of models. […] Part of multimodel inference includes ranking the fitted models from best to worst […] and then scaling to obtain the relative plausibility of each fitted model (gi) by a weight of evidence (wi) relative to the selected best model. Using the conditional sampling variance […] from each model and the Akaike weights […], unconditional inferences about precision can be made over the entire set of models. Model-averaged parameter estimates and estimates of unconditional sampling variances can be easily computed. Model selection uncertainty is a substantial subject in its own right, well beyond just the issue of determining the best model.”
“There are three general approaches to assessing model selection uncertainty: (1) theoretical studies, mostly using Monte Carlo simulation methods; (2) the bootstrap applied to a given set of data; and (3) utilizing the set of AIC differences (i.e., ∆i) and model weights wi from the set of models fit to data.”
“Statistical science should emphasize estimation of parameters and associated measures of estimator uncertainty. Given a correct model […], an MLE is reliable, and we can compute a reliable estimate of its sampling variance and a reliable confidence interval […]. If the model is selected entirely independently of the data at hand, and is a good approximating model, and if n is large, then the estimated sampling variance is essentially unbiased, and any appropriate confidence interval will essentially achieve its nominal coverage. This would be the case if we used only one model, decided on a priori, and it was a good model, g, of the data generated under truth, f. However, even when we do objective, data-based model selection (which we are advocating here), the [model] selection process is expected to introduce an added component of sampling uncertainty into any estimated parameter; hence classical theoretical sampling variances are too small: They are conditional on the model and do not reflect model selection uncertainty. One result is that conditional confidence intervals can be expected to have less than nominal coverage.”
“Data analysis is sometimes focused on the variables to include versus exclude in the selected model (e.g., important vs. unimportant). Variable selection is often the focus of model selection for linear or logistic regression models. Often, an investigator uses stepwise analysis to arrive at a final model, and from this a conclusion is drawn that the variables in this model are important, whereas the other variables are not important. While common, this is poor practice and, among other issues, fails to fully consider model selection uncertainty. […] Estimates of the relative importance of predictor variables xj can best be made by summing the Akaike weights across all the models in the set where variable j occurs. Thus, the relative importance of variable j is reflected in the sum w+ (j). The larger the w+ (j) the more important variable j is, relative to the other variables. Using the w+ (j), all the variables can be ranked in their importance. […] This idea extends to subsets of variables. For example, we can judge the importance of a pair of variables, as a pair, by the sum of the Akaike weights of all models that include the pair of variables. […] To summarize, in many contexts the AIC selected best model will include some variables and exclude others. Yet this inclusion or exclusion by itself does not distinguish differential evidence for the importance of a variable in the model. The model weights […] summed over all models that include a given variable provide a better weight of evidence for the importance of that variable in the context of the set of models considered.” [The reason why I’m not telling you how to calculate Akaike weights is that I don’t want to bother with math formulas in wordpress – but I guess all you need to know is that these are not hard to calculate. It should perhaps be added that one can also use bootstrapping methods to obtain relevant model weights to apply in a multimodel inference context.]
“If data analysis relies on model selection, then inferences should acknowledge model selection uncertainty. If the goal is to get the best estimates of a set of parameters in common to all models (this includes prediction), model averaging is recommended. If the models have definite, and differing, interpretations as regards understanding relationships among variables, and it is such understanding that is sought, then one wants to identify the best model and make inferences based on that model. […] The bootstrap provides direct, robust estimates of model selection probabilities πi , but we have no reason now to think that use of bootstrap estimates of model selection probabilities rather than use of the Akaike weights will lead to superior unconditional sampling variances or model-averaged parameter estimators. […] Be mindful of possible model redundancy. A carefully thought-out set of a priori models should eliminate model redundancy problems and is a central part of a sound strategy for obtaining reliable inferences. […] Results are sensitive to having demonstrably poor models in the set of models considered; thus it is very important to exclude models that are a priori poor. […] The importance of a small number (R) of candidate models, defined prior to detailed analysis of the data, cannot be overstated. […] One should have R much smaller than n. MMI [Multi-Model Inference] approaches become increasingly important in cases where there are many models to consider.”
“In general there is a substantial amount of model selection uncertainty in many practical problems […]. Such uncertainty about what model structure (and associated parameter values) is the K-L [Kullback–Leibler] best approximating model applies whether one uses hypothesis testing, information-theoretic criteria, dimension-consistent criteria, cross-validation, or various Bayesian methods. Often, there is a nonnegligible variance component for estimated parameters (this includes prediction) due to uncertainty about what model to use, and this component should be included in estimates of precision. […] we recommend assessing model selection uncertainty rather than ignoring the matter. […] It is […] not a sound idea to pick a single model and unquestioningly base extrapolated predictions on it when there is model uncertainty.”
Despite not actually having reading all that many books this year I’m way behind on blogging the books I’ve read, so I thought I might as well try to catch up a bit. You can find my previous coverage of the book here and here.
In this post I’ll cover the chapters about the musculoskeletal system, the endocrine system, and the breast.
“Disorders of the musculoskeletal system make up 20–25 per cent of a general practitioner’s workload and account for significant disability in the general population. […] The chief symptoms to identify in the musculoskeletal assessment are: *pain *stiffness *swelling *impaired function *constitutional [regarding constitutional symptoms, “Patients with arthritis may describe symptoms of fatigue, fever, sweating and weight loss”]. […] As a rule mechanical disorders (e.g. OA [Osteoarthritis], spondylosis, and tendinopathies) are worsened by activity and relieved by rest. In severe degenerative disease the pain may, however, be present at rest and disturb sleep. Inflammatory disorders tend to be painful both at rest and during activity and are associated with worsened stiffness after periods of prolonged rest. The patient may note that stiffness is relieved somewhat by movement. Both mechanical and inflammatory disorders may be worsened by excessive movement.”
“The lifetime incidence of lower back pain is about 60 per cent and the greatest prevalence is between ages 45 and 65 years. Over 90 per cent of low back pain is mechanical and self-limiting. […] Indicators of serious pathology in lumbar pain: ‘red flags’ of serious pathology that requires further investigation […] are: *presenting under age 20 and over age 55 years *prolonged stiffness (>6 weeks) *sudden onset of severe pain *pain that disturbs sleep (>6 weeks) *thoracic pain *nerve root symptoms – including spinal claudication (pain on walking resolved by rest), saddle numbness, and loss of bladder or bowel control *chronic persistent pain (>12 weeks) *weight loss *history of carcinoma.”
“Osteoarthritis is a chronic degenerative and mechanical disorder characterized by cartilage loss. It is the most common form of arthritis, estimated to affect 15 per cent of the population of the UK over the age of 55 years. It is second only to cardiovascular disease as a cause of disability. Weight-bearing joints are chiefly involved (e.g. facets in the spine, hip and knee). […] There is little evidence to link OA with repetitive injury from occupation, except perhaps knee bending in men. Dockers and miners have a higher incidence of knee OA.”
“Rheumatoid arthritis […] is the most common ARD [Autoimmune Rheumatic Diseases] and is characterized by the presence of a symmetrical destructive polyarthritis with a predisposition for the small joints of the hands, wrists and feet. It is more common in women than men and may present at any age though most often in the third to fourth decade. […] Onset is typically insidious and progressive pain, stiffness and symmetrical swelling of small joints occurs. Up to a third of patients may have a subacute onset with symptoms of fatigue, malaise, weight loss, myalgia, morning stiffness and joint pain without overt signs of swelling. A mono- or bilateral arthropathy of the shoulder or wrist may account for up to 30–40 per cent of initial presentations”
“[Osteoporosis] remains a significant cause of morbidity and mortality. Peak bone mass is usually achieved in the third decade and is determined by both genetic and environmental factors. After the age of 35 the amount of bone laid down is less than that reabsorbed during each remodelling cycle. The net effect is age-related loss of bone mass. Up to 15 per cent of bone mass can also be lost over the 5-year period immediately post menopause. Symptomless reduction in bone mass and strength results in an increased risk of fracture; it is the resulting fractures that lead to pain and morbidity. Major risk factors to be considered in osteoporosis are: *race (white or Asian > African Caribbean) *age *gender *family history of maternal hip fracture *previous low trauma fracture (low trauma defined as no greater than falling from standing height) *long-term use of corticosteroids *malabsorption disorders *endocrinopathies […] *inflammatory arthritis […] Other risk factors include: *low body mass index […] *late menarche and early menopause *nulliparity *reduced physical activity *low intake of calcium (below 240 mg daily) *excess alcohol intake *smoking *malignancy (multiple myeloma).”
“Infection may give rise to systemic inflammatory arthritis or vasculitis. The condition ‘reactive arthritis’ is also recognized. […] It is usually triggered by sexually transmitted infection such as with Chlamydia trachomatis. The acute inflammatory reaction is treated with NSAIDs and corticosteroids and often ‘burns out’ after 6–18 months [Had to read that one twice: 18 months…]. It may leave lasting joint damage. […] Septic arthritis constitutes an acute emergency. The presentation is usually one of a rapid onset of severe pain in a hot swollen joint, the pain so severe that the patient cannot bear for it to be touched or moved.”
“Focal pain, swelling, or a low trauma fracture in the spine or long bones should alert suspicion [of neoplasia]. Primary tumours of bone include the benign (but often very painful) osteoid-osteoma, chondromas, and malignant osteosarcoma. Metastatic carcinoma may be secondary to a primary lesion in the lung, breast, prostate, kidney or thyroid. Haematological malignancies including lymphomas and leukaemias may also lead to diffuse bone involvement.”
“Diabetes mellitus is becoming a major public health problem. This is particularly true for type 2 diabetes, the prevalence of which is increasing rapidly due to the association with obesity and physical inactivity. Much of the morbidity, and cost, of diabetes care is due to the associated complications, rather than directly to hyperglycaemia and its management. Thyroid disease and polycystic ovarian syndrome are also prevalent [endocrine] conditions. Most other endocrine disorders are uncommon”
“The classic triad of symptoms associated with diabetes mellitus consists of: *thirst *polyuria (often nocturia) *weight loss.
Many patients will also experience pruritus or balanitis, fatigue and blurred vision. Some people, particularly those with newly presenting type 1 diabetes diabetes mellitus (T1DM) or with marked hyperglycaemia in type 2 diabetes mellitus (T2DM), may have a ‘full house’ of symptoms, in which case it is generally not difficult to suspect the diagnosis. However, other patients, particularly those with only modestly elevated blood glucose concentrations in T2DM, will have fewer, milder symptoms, and some may be entirely asymptomatic. […] symptoms potentially suggestive of diabetes may have alternative causes, particularly in elderly people, for example, frequency and nocturia in an older man may be due to bladder outflow obstruction, and many medical disorders are associated with weight loss. The symptom complex of thirst, polydipsia and polyuria most commonly suggests a diagnosis of uncontrolled diabetes mellitus but can occur in other settings. Some patients taking diuretics will experience similar symptoms. A dry mouth, perhaps associated with drug usage (e.g. tricyclic antidepressants) or certain medical conditions (e.g. Sjögren’s syndrome), may lead to increased fluid intake in an attempt at symptom relief.”
“The blood glucose concentration at diagnosis is not useful as a guide to whether an individual patient has T1DM or T2DM. Patients with T1DM can be in severe ketoacidosis with a blood glucose less than 20 mmol/L, and even below 10 mmol/L on occasions, whereas T2DM can present with a hyperosmolar state with blood glucose levels over 50 mmol/L.”
“30–50 per cent of patients with newly diagnosed T2DM will already have tissue complications at diagnosis due to the prolonged period of antecedent moderate and asymptomatic hyperglycaemia. […] Diabetes mellitus is much more than a disorder of glucose metabolism. The complications of diabetes can affect many of the organ systems leading to associated cardiac, vascular, renal, retinal, neurological and other disorders.”
“Pain is one of the commonest presenting disorders in the female breast, occurring in both pre-and postmenopausal women. […] In most women, there is no obvious or serious underlying breast pathology present […] In males, pain is not uncommon in gynaecomastia (swelling of male breast). […] A discrete lump, nodularity or thickening is the next most common mode of presentation. Size may vary (frequently ‘pea-sized’), but can be large. Onset may be acute (several days) or longstanding (several months). Fluctuation with the menstrual cycle is common in young women. Pain and tenderness are features of cysts, less common with fibroadenomas (unless rapidly growing or phylloides tumours), uncommon with cancer, except with rapidly expanding, aggressive (grade 3) and inflammatory tumours. The commonest lump in women below 30 years is a fibroadenoma; in women 30–45 years, a cyst and those over 45 years, cancer. […] Careful assessment of a lump can indicate whether the breast lesion is benign or malignant: *if it is rounded, smooth, mobile, tense and tender it is most likely to be a cyst (30 to 45 years of age) *if it is rounded, smooth, mobile, firm and non-tender it is most likely to be a fibroadenoma (under 30 years of age) *malignant lumps are rare in women under 30 years and uncommon under 40 years (4 per cent of breast cancers). Cancers are usually irregular, firm or hard, with variable involvement of overlying skin or deeper structures.”
“Retraction (intermittent, partial or chronic) is often a concern to women. It can be idiopathic or associated with malignancy in the retroareolar region, but usually is seen in the postmenopausal breast and is secondary to glandular atrophy and replacement by fibrosis and major duct ectasia. Congenital absence is very rare, whereas accessory nipples are seen in 2 per cent of women.” [Again, I had to read that one twice. 2 %! Who knew! Also, this condition seems to be even more common in males (see the link above).]
“Five to 10 per cent of women will, at some stage, present with a macrocyst. Microcysts are more common but tend to be occult. Breast cysts are commonest between the ages of 35 and 50, but can occur outside this age range, particularly in women who have been taking HRT. […] Patients present with a palpable lump or nodularity. When acute and large, the lump can be tender and the patient complains of pain. Typically cysts are well-circumscribed, smooth, mobile and, on occasion, tender lumps.”
“Nipple discharge in premenopausal women is likely to be associated with, or be due to, benign disease. It is the predominant clinical feature in up to 10 per cent of women presenting with breast cancer. […] *Purulent and coloured discharges are usually indicative of benign disease (infection and fibrocystic disease, respectively). *Spontaneous bilateral milky discharge (multiple ducts) most commonly occurs in women of reproductive age and is called galactorrhoea. […] *Clear, serous or bloodstained discharges are not infrequently associated with neoplastic disease”
“Carcinoma of the breast is one of the most common cancers (23 per cent of all female malignancies in the developed world) […]. One in 10 women develops breast cancer during her lifetime. […] Breast cancer is very rare in women under the age of 25. About 4 per cent occur under the age of 40. There is a plateau in incidence between the ages of 45 and 55, and beyond 55 years it continues to increase steadily into the 80s. […] The most common (70 per cent) presentation is a palpable lump, nodularity or thickening in the breast, usually detected by the patient. Typically the lump is firm or hard, well defined, with an irregular surface. […] About 25 per cent of women in the UK present with large primary tumours […], or locally advanced breast cancers […]. In some cases, particularly elderly patients, the tumour may have been present for some time, but hidden by the patient from her relatives due to fear and anxiety […]. Occasionally patients may even deny the presence of a tumour as a psychological coping strategy. […] Breast cancer is the most common malignant condition occurring during pregnancy. The incidence is approximately 1 in 2500 pregnancies, and poses many medical and psychological problems, both for the woman and her relatives.”
“This report shows trends and group differences in current marital status, with a focus on first marriages among women and men aged 15–44 years in the United States. Trends and group differences in the timing and duration of first marriages are also discussed. […] The analyses presented in this report are based on a nationally representative sample of 12,279 women and 10,403 men aged 15–44 years in the household population of the United States.”
“In 2006–2010, […] median age at first marriage was 25.8 for women and 28.3 for men.”
“Among women, 68% of unions formed in 1997–2001 began as a cohabitation rather than as a marriage (8). If entry into any type of union, marriage or cohabitation, is taken into account, then the timing of a first union occurs at roughly the same point in the life course as marriage did in the past (9). Given the place of cohabitation in contemporary union formation, descriptions of marital behavior, particularly those concerning trends over time, are more complete when cohabitation is also measured. […] Trends in the current marital statuses of women using the 1982, 1995, 2002, and 2006–2010 NSFG indicate that the percentage of women who were currently in a first marriage decreased over the past several decades, from 44% in 1982 to 36% in 2006–2010 […]. At the same time, the percentage of women who were currently cohabiting increased steadily from 3.0% in 1982 to 11% in 2006– 2010. In addition, the proportion of women aged 15–44 who were never married at the time of interview increased from 34% in 1982 to 38% in 2006–2010.”
“In 2006–2010, the probability of first marriage by age 25 was 44% for women compared with 59% in 1995, a decrease of 25%. By age 35, the probability of first marriage was 84% in 1995 compared with 78% in 2006–2010 […] By age 40, the difference in the probability of age at first marriage for women was not significant between 1995 (86%) and 2006–2010 (84%). These findings suggest that between 1995 and 2006– 2010, women married for the first time at older ages; however, this delay was not apparent by age 40.”
“In 2006–2010, the probability of a first marriage lasting at least 10 years was 68% for women and 70% for men. Looking at 20 years, the probability that the first marriages of women and men will survive was 52% for women and 56% for men in 2006–2010. These levels are virtually identical to estimates based on vital statistics from the early 1970s (24). For women, there was no significant change in the probability of a first marriage lasting 20 years between the 1995 NSFG (50%) and the 2006–2010 NSFG (52%)”
“Women who had no births when they married for the first time had a higher probability of their marriage surviving 20 years (56%) compared with women who had one or more births at the time of first marriage (33%). […] Looking at spousal characteristics, women whose first husbands had been previously married (38%) had a lower probability of their first marriage lasting 20 years compared with women whose first husband had never been married before (54%). Women whose first husband had children from previous relationships had a lower probability that their first marriage would last 20 years (37%) compared with first husbands who had no other children (54%). For men, […] patterns of first marriage survival […] are similar to those shown for women for marriages that survived up to 15 years.”
“These data show trends that are consistent with broad demographic changes in the American family that have occurred in the United States over the last several decades. One such trend is an increase in the time spent unmarried among women and men. For women, there was a continued decrease in the percentage currently married for the first time — and an increase in the percent currently cohabiting — in 2006–2010 compared with earlier years. For men, there was also an increase in the percentage unmarried and in the percentage currently cohabiting between 2002 and 2006–2010. Another trend is an increase in the age at first marriage for women and men, with men continuing to marry for the first time at older ages than women. […] Previous research suggests that women with more education and better economic prospects are more likely to delay first marriage to older ages, but are ultimately more likely to become married and to stay married […]. Data from the 2006–2010 NSFG support these findings”
ii. Involuntary Celibacy: A life course analysis (review). This is not a link to the actual paper – the paper is not freely available, which is why I do not link to it – but rather a link to a report talking about what’s in that paper. However I found some of the stuff interesting:
“A member of an on-line discussion group for involuntary celibates approached the first author of the paper via email to ask about research on involuntary celibacy. It soon became apparent that little had been done, and so the discussion group volunteered to be interviewed and a research team was put together. An initial questionnaire was mailed to 35 group members, and they got a return rate of 85%. They later posted it to a web page so that other potential respondents had access to it. Eventually 60 men and 22 women took the survey.”
“Most were between the ages of 25-34, 28% were married or living with a partner, 89% had attended or completed college. Professionals (45%) and students (16%) were the two largest groups. 85% of the sample was white, 89% were heterosexual. 70% lived in the U.S. and the rest primarily in Western Europe, Canada and Australia. […] the value of this research lies in the rich descriptive data obtained about the lives of involuntary celibates, a group about which little is known. […] The questionnaire contained 13 categorical, close-ended questions assessing demographic data such as age, sex, marital status, living arrangement, income, education, employment type, area of residence, race/ethnicity, sexual orientation, religious preference, political views, and time spent on the computer. 58 open-ended questions investigated such areas as past sexual experiences, current relationships, initiating relationships, sexuality and celibacy, nonsexual relationships and the consequences of celibacy. They started out by asking about childhood experiences, progressed to questions about teen and early adult years and finished with questions about current status and the effects of celibacy.”
“78% of this sample had discussed sex with friends, 84% had masturbated as teens. The virgins and singles, however, differed from national averages in their dating and sexual experiences.”
“91% of virgins and 52 % of singles had never dated as teenagers. Males reported hesitancy in initiating dates, and females reporting a lack of invitations by males. For those who did date, their experiences tended to be very limited. Only 29% of virgins reported first sexual experiences that involved other people, and they frequently reported no sexual activity at all except for masturbation. Singles were more likely than virgins to have had an initial sexual experience that involved other people (76%), but they tended to report that they were dissatisfied with the experience. […] While most of the sample had discussed sex with friends and masturbated as teens, most virgins and singles did not date. […] Virgins and singles may have missed important transitions, and as they got older, their trajectories began to differ from those of their age peers. Patterns of sexuality in young adulthood are significantly related to dating, steady dating and sexual experience in adolescence. It is rare for a teenager to initiate sexual activity outside of a dating relationship. While virginity and lack of experience are fairly common in teenagers and young adults, by the time these respondents reached their mid-twenties, they reported feeling left behind by age peers. […] Even for the heterosexuals in the study, it appears that lack of dating and sexual experimentation in the teen years may be precursors to problems in adult sexual relationships.”
“Many of the virgins reported that becoming celibate involved a lack of sexual and interpersonal experience at several different transition points in adolescence and young adulthood. They never or rarely dated, had little experience with interpersonal sexual activity, and had never had sexual intercourse. […] In contrast, partnered celibates generally became sexually inactive by a very different process. All had initially been sexually active with their partners, but at some point stopped. At the time of the survey, sexual intimacy no longer or very rarely occurred in their relationships. The majority of them (70%) started out having satisfactory relationships, but they slowly stopped having sex as time went on.”
“shyness was a barrier to developing and maintaining relationships for many of the respondents. Virgins (94%) and singles (84%) were more likely to report shyness than were partnered respondents (20%). The men (89%) were more likely to report being shy than women (77%). 41% of virgins and 23% of singles reported an inability to relate to others socially. […] 1/3 of the respondents thought their weight, appearance, or physical characteristics were obstacles to attracting potential partners. 47% of virgins and 56% of singles mentioned these factors, compared to only 9% of partnered people. […] Many felt that their sexual development had somehow stalled in an earlier stage of life; feeling different from their peers and feeling like they will never catch up. […] All respondents perceived their lack of sexual activity in a negative light and in all likelihood, the relationship between involuntary celibacy and unhappiness, anger and depression is reciprocal, with involuntary celibacy contributing to negative feelings, but these negative feelings also causing people to feel less self-confident and less open to sexual opportunities when they occur. The longer the duration of the celibacy, the more likely our respondents were to view it as a permanent way of life. Virginal celibates tended to see their condition as temporary for the most part, but the older they were, the more likely they were to see it as permanent, and the same was true for single celibates.”
It seems to me from ‘a brief look around’ that not a lot of research has been done on this topic, which I find annoying. Because yes, I’m well aware these are old data and that the sample is small and ‘convenient’. Here’s a brief related study on the ‘Characteristics of adult women who abstain from sexual intercourse‘ – the main findings:
“Of the 1801 respondents, 244 (14%) reported abstaining from intercourse in the past 6 months. Univariate analysis revealed that abstinent women were less likely than sexually active women to have used illicit drugs [odds ratio (OR) 0.47; 95% CI 0.35–0.63], to have been physically abused (OR 0.44, 95% CI 0.31–0.64), to be current smokers (OR 0.59, 95% CI 0.45–0.78), to drink above risk thresholds (OR 0.66, 95% CI 0.49–0.90), to have high Mental Health Inventory-5 scores (OR 0.7, 95% CI 0.54–0.92) and to have health insurance (OR 0.74, 95% CI 0.56–0.98). Abstinent women were more likely to be aged over 30 years (OR 1.98, 95% CI 1.51–2.61) and to have a high school education (OR 1.38, 95% CI 1.01–1.89). Logistic regression showed that age >30 years, absence of illicit drug use, absence of physical abuse and lack of health insurance were independently associated with sexual abstinence.
Prolonged sexual abstinence was not uncommon among adult women. Periodic, voluntary sexual abstinence was associated with positive health behaviours, implying that abstinence was not a random event. Future studies should address whether abstinence has a causal role in promoting healthy behaviours or whether women with a healthy lifestyle are more likely to choose abstinence.”
Here’s another more recent study – Prevalence and Predictors of Sexual Inexperience in Adulthood (unfortunately I haven’t been able to locate a non-gated link) – which I found and may have a closer look at later. A few quotes/observations:
“By adulthood, sexual activity is nearly universal: 97 % of men and 98 % of women between the ages of 25-44 report having had vaginal intercourse (Mosher, Chandra, & Jones, 2005). […] Although the majority of individuals experience this transition during adolescence or early adulthood, a small minority remain sexually inexperienced far longer. Data from the NSFG indicate that about 5% of males and 3% of females between the ages of 25 and 29 report never having had vaginal sex (Mosher et al., 2005). While the percentage of sexually inexperienced participants drops slightly among older age groups, between 1 and 2% of both males and females continue to report that they have never had vaginal sex even into their early 40s. Other nationally representative surveys have yielded similar estimates of adult sexual inexperience (Billy, Tanfer, Grady, & Klepinger, 1993)”
“Individuals who have not experienced any type of sexual activity as adults […] may differ from those who only abstain from vaginal intercourse. For example, vaginal virgins who engage in “everything but” vaginal sex – sometimes referred to as “technical virgins” […] – may abstain from vaginal sex in order to avoid its potential negative consequences […]. In contrast, individuals who have neither coital nor noncoital experience may have been unable to attract sexual partners or may have little interest in sexual involvement. Because prior analyses have generally conflated these two populations, we know virtually nothing about the prevalence or characteristics of young adults who have abstained from all types of sexual activity.”
“We used data from 2,857 individuals who participated in Waves I–IV of the National Longitudinal Study of Adolescent Health (Add Health) and reported no sexual activity (i.e., oral-genital, vaginal, or anal sex) by age 18 to identify, using discrete-time survival models, adolescent sociodemographic, biosocial, and behavioral characteristics that predicted adult sexual inexperience. The mean age of participants at Wave IV was 28.5 years (SD = 1.92). Over one out of eight participants who did not initiate sexual activity during adolescence remained abstinent as young adults. Sexual non-attraction significantly predicted sexual inexperience among both males (aOR = 0.5) and females (aOR = 0.6). Males also had lower odds of initiating sexual activity after age 18 if they were non-Hispanic Asian, reported later than average pubertal development, or were rated as physically unattractive (aORs = 0.6–0.7). Females who were overweight, had lower cognitive performance, or reported frequent religious attendance had lower odds of sexual experience (aORs = 0.7–0.8) while those who were rated by the interviewers as very attractive or whose parents had lower educational attainment had higher odds of sexual experience (aORs = 1.4–1.8). Our findings underscore the heterogeneity of this unique population and suggest that there are a number of different pathways that may lead to either voluntary or involuntary adult sexual inexperience.”
“Breastfeeding has clear short-term benefits, but its long-term consequences on human capital are yet to be established. We aimed to assess whether breastfeeding duration was associated with intelligence quotient (IQ), years of schooling, and income at the age of 30 years, in a setting where no strong social patterning of breastfeeding exists. […] A prospective, population-based birth cohort study of neonates was launched in 1982 in Pelotas, Brazil. Information about breastfeeding was recorded in early childhood. At 30 years of age, we studied the IQ (Wechsler Adult Intelligence Scale, 3rd version), educational attainment, and income of the participants. For the analyses, we used multiple linear regression with adjustment for ten confounding variables and the G-formula. […] From June 4, 2012, to Feb 28, 2013, of the 5914 neonates enrolled, information about IQ and breastfeeding duration was available for 3493 participants. In the crude and adjusted analyses, the durations of total breastfeeding and predominant breastfeeding (breastfeeding as the main form of nutrition with some other foods) were positively associated with IQ, educational attainment, and income. We identified dose-response associations with breastfeeding duration for IQ and educational attainment. In the confounder-adjusted analysis, participants who were breastfed for 12 months or more had higher IQ scores (difference of 3,76 points, 95% CI 2,20–5,33), more years of education (0,91 years, 0,42–1,40), and higher monthly incomes (341,0 Brazilian reals, 93,8–588,3) than did those who were breastfed for less than 1 month. The results of our mediation analysis suggested that IQ was responsible for 72% of the effect on income.”
This is a huge effect size.
iv. Grandmaster blunders (chess). This is quite a nice little collection; some of the best players in the world have actually played some really terrible moves over the years, which I find oddly comforting in a way..
v. History of the United Kingdom during World War I (wikipedia, ‘good article’). A few observations from the article:
“In 1915, the Ministry of Munitions under David Lloyd-George was formed to control munitions production and had considerable success. By April 1915, just two million rounds of shells had been sent to France; by the end of the war the figure had reached 187 million, and a year’s worth of pre-war production of light munitions could be completed in just four days by 1918.”
“During the war, average calories intake [in Britain] decreased only three percent, but protein intake six percent.“
“Energy was a critical factor for the British war effort. Most of the energy supplies came from coal mines in Britain, where the issue was labour supply. Critical however was the flow of oil for ships, lorries and industrial use. There were no oil wells in Britain so everything was imported. The U.S. pumped two-thirds of the world’s oil. In 1917, total British consumption was 827 million barrels, of which 85 percent was supplied by the United States, and 6 percent by Mexico.”
“In the post war publication Statistics of the Military Effort of the British Empire During the Great War 1914–1920 (The War Office, March 1922), the official report lists 908,371 ‘soldiers’ as being either killed in action, dying of wounds, dying as prisoners of war or missing in action in the World War. (This is broken down into the United Kingdom and its colonies 704,121; British India 64,449; Canada 56,639; Australia 59,330; New Zealand 16,711; South Africa 7,121.) […] The civilian death rate exceeded the prewar level by 292,000, which included 109,000 deaths due to food shortages and 183,577 from Spanish Flu.”
vi. House of Plantagenet (wikipedia, ‘good article’).
vii. r/Earthp*rn. There are some really nice pictures here…
“92 per cent of men and 86 per cent of women in Britain drink alcohol (DoH 2002a).”
I sort of liked the chapter about alcohol more than I did at first after I’d yesterday read some stuff in Boccia et al. dealing with the same topic (their coverage is much poorer in regards to some key issues). When thinking about how to blog this chapter I was considering including a table from the book, table 5,1, in full, even if it’s rather large, but I decided against it as I might as well report what it’s talking about myself here. The observation that addiction and physical dependence should be treated as separate entities is not included in the coverage, although Clark & Treisman considered this to be a very important point to keep in mind (see also this post: “It is very important to realize that addiction and physical dependence are different phenomena with different underlying brain substrates”), but the coverage is still much more detailed than the public health review text alluded to above. It should be noted that some of the shortcomings of the chapter is presumably due to the intended scope of the coverage which makes the omission of some of the important distinctions seem understandable, sort of; the authors note early on that they mostly focus on volitional rather than dependent drinking, because the book deals with lifestyle behaviours over which individuals have some level of control (but if you’re covering smoking and illegal substance abuse in your book, why not cover dependent drinking as well? I still find their coverage of some of these issues sort of puzzling…). Anyway, table 5,1 includes the ICD-10 diagnostic criteria for alcohol dependence, and these criteria include (my bold):
Evidence of tolerance (need more alcohol to get the same effect); physiological withdrawal when alcohol use is reduced or ceased (or use of a closely related substance with the intention of relieving or avoiding withdrawal symptoms); persisting with alcohol use despite clear evidence of harmful consequences; preoccupation with alcohol use (important other pleasures/interests given up or reduced because of alcohol, much time spent on activities such as procuring alcohol, consuming it, or recovering from its effects); difficulty controlling drinking behaviour in terms of onset-, termination or level of use – evidenced by alcohol being consumed in larger amounts or over a longer period than intended, or by any unsuccessful effort or persistent desire to cut down; and lastly a strong desire or compulsion to use alcohol.
“The majority of people who drink alcohol have not been diagnosed as dependent drinkers. Orton (2001) reported that 7.5 per cent of men and 2.1 per cent of women in Britain in the 1990s could be classified as dependent on alcohol. […] Nonresponse bias is a particular problem in drinking surveys. […] Issues of response bias are a common concern and one that afflicts many of the lifestyle surveys reported throughout this text. […] An important issue for measurement of drinking is the validity and reliability of the instrument in question and unfortunately many widely used measures of alcohol consumption have not been tested for such psychometric properties. […] Probably the most convincing evidence that self-report measures of drinking in any one study do, at the very least, place people in an appropriate place on the drinking continuum compared to their peers is the relationship between self-reported drinking and proven increased risk for a number of alcohol related conditions (Room et al. 2005).”
“Men drink more alcohol than women and they are more likely to exceed their daily and/or weekly guidelines, even though those guidelines are higher than those recommended for women […]. This gender difference in alcohol consumption is consistently reported in the national surveys and elsewhere […] and furthermore is similar to the gendered drinking patterns of previous decades […] There are few clear socio-economic trends in alcohol consumption evident from the National Surveys”
“People under the influence of alcohol are more likely to behave aggressively and this can lead to physical violence that can harm themselves and others […]. Offenders are believed to be under the influence of alcohol in 46 per cent of incidents of domestic violence and 44 per cent of acquaintance violence. […] 15 per cent of rape victims recorded by the 2001 British Crime Survey were raped when they were under the influence of alcohol [I was actually really surprised the number was that low…] […] People under the influence of alcohol are also more likely to have accidents. […] The World Health Organisation (2002) estimates that 20 per cent of motor vehicle accidents worldwide are alcohol related.”
“Alcohol has been implicated in more than 60 medical conditions, predominantly with negative, but occasionally with positive, consequences […] the relationship between alcohol consumption and health is not always linear. […] Episodic heavy drinking, even when the overall volume of alcohol intake is low, has been found to increase the risk for a number of cardiovascular conditions. […] This association is physiologically consistent with the increased clotting, lower threshold for ventricular fibrillation and elevation of low density lipoproteins that occur after heavy drinking (Room et al. 2005). […] Breast cancer risk increases linearly with increased alcohol consumption: 10 grams of alcohol a day (an average UK unit) increases the relative risk of breast cancer by 9 per cent. A daily consumption of between 30 and 60 grams a day increases the relative risk by 41 per cent […] In England and Wales alcohol-related injury or illness accounts for 180,000 hospital admissions a year (HM Government 2007).”
“Alcohol serves an important social function. It enhances social integration and facilitates the development of relationships (Kuther and Timoshin 2003). It is hardly surprising that people drink most at a period in their lives [teen-age years, early twenties] which is normally associated with the development of stable adult relationships (Paglia and Room 1999). Increased levels of drinking in newly divorced people may be in part due to the breakdown of stable relationships and the desire to establish new relationships (HM Government 2007). Social isolation is a key factor in poor health outcomes […] so the positive social function of alcohol in enabling people to develop social relationships should not be overlooked.”
“In contrast to other lifestyle behaviours where social norms have been argued to play little or no part in the explanation for variations in behaviour, social norms are consistently reported to be useful in explaining variations in drinking behaviour”
“it is well established that the earlier a person starts to drink, smoke or use illegal drugs the higher the risk of later abuse […] There is evidence that people drink less if the price of alcohol increases […] and that those of particular concern, heavy drinkers and young people, both respond to price increases by drinking less […] Many interventions to encourage sensible drinking are aimed at adolescents and young people with the goal of preventing the establishment of unhealthy drinking habits. The rationale for a predominance of interventions for this age group includes the indisputable fact that young people are the heaviest drinkers in society […] Many early drinking interventions are educational in nature. In essence these are risk communication messages and the evidence from psychological research is that improving risk perceptions will have little impact on levels of drinking. Unsurprisingly then, there is little evidence that alcohol education and health promotion have any positive effect on drinking habits in Britain […] These campaigns are heard and understood because knowledge increases in targeted populations […] so it is not that the message is failing to reach the designated audience, rather the message has no impact on behaviour. […] Foxcroft et al. (2003) reviewed the effectiveness of programmes designed to prevent excessive drinking in young people. Worryingly, [they] found very little evidence that any of these programmes were effective. Among the studies with medium-term followup that met the methodological guidelines the majority, 19 studies, found no evidence of intervention effectiveness. Several of these studies had previously reported short-term effectiveness which demonstrates the importance of longer term follow-up. […] There are two concerns from these studies on early drinking interventions. First, there are a wealth of studies that report no reduction in any measure of drinking. Second, research has failed to consistently test and tease out what is effective.”
“There is considerable variation in the prevalence of smoking worldwide. In sub-Saharan Africa less than 10 per cent of the population smoke, whereas in Japan this figure rises to above 50 per cent, and in Indonesia 69 per cent, with almost three-quarters of the Vietnamese population smoking (Edwards 2004).” [I had no idea the numbers were that high anywhere… (and I’m perhaps slightly skeptical, in particular about the Japanese estimate; a 50+% smoking prevalence seems to not fit very well with the very high Japanese life expectancy)]
“Despite the health effects of smoking being known since the 1960s, and the health impact being publicised, some 12 million individuals still smoke in the UK: 25 per cent of men and 23 per cent of women (ONS 2007). These figures have shown a substantial decrease since the early 1970s: for example in the 1970s the comparable figures were 51 per cent of men and 41 per cent of women smoking.” [If you’re curious about Danish figures, I blogged some Danish alcohol and smoking stats some years back here (the post is in Danish)] […] smoking is the highest in the 20–24 year age group (about 36 per cent) and the lowest in the over 65 years (about 15 per cent). This reflects both the fact that many former smokers will have quit and also that about a quarter of smokers die before reaching retirement age (ONS 2007). […] in the UK it is suggested that annually some 120,000 people die as a result of their smoking habit (440,000 in the United States). Every year, tobacco smoking kills 5 million people worldwide (Perkins et al. 2008) […] Deaths caused by tobacco smoking in the UK are higher than the number of deaths caused by road traffic accidents (3,500), other accidents (8,500), poisoning and overdose (900), alcoholic liver disease (5,000), suicide (4,000) and HIV infection (250). Almost a half of all regular smokers will be killed by their habit. A man who smokes cuts short his life by 13.2 years and female smokers lose 14.5 years (ASH 2008).”
“It is usually teenagers who experiment with smoking, with very few smokers starting after the age of 25 years […]. There are a number of reasons why people start smoking, but these are mainly related to psychosocial motives […] One of the major reasons for experimenting with cigarettes is social pressure from peers or older siblings […] adolescents are more likely to smoke cigarettes if their parents smoke […] Research has also indicated that teenagers underestimate the health risk of smoking […] and they also believe that they will quit before they do themselves serious damage […]. Hence, they smoke in spite of knowing the health damage effects of smoking: they know of them, they just don’t think it will impact upon them. […] of all the lifestyle behaviours discussed in this book smoking has the simplest relationship with social class and is the only behaviour to demonstrate a totally linear relationship with class.”
“One of the major attempts to reduce smoking has been the introduction of graphic warning labels on cigarette packets or on posters and billboards. […] there is very little evidence of the success of this form of approach. When politicians are asked for the evidence of such approaches there is much filibustering and some reference to dated research which does not stand up to scrutiny (Ruiter and Kok 2005). […] the evidence can be described as, at best, insubstantial. […] there are a large number of studies that highlight that some type of in-person or telephone behavioural support with NRT [nicotine replacement therapy] increases quit rates, especially those using nicotine gum […]. This support works by increasing motivation for quitting and remaining tobacco-free. However, most quitters attempt to stop smoking by use of NRTs alone and overlook the behavioural and psychological support required to enhance and maintain the necessary motivation”
The stuff below is from the smoking chapter, but might easily have been found in a very different chapter (or even in a different book?):
“Motivational interviewing can be defined as ‘a client-centred, directive method for enhancing intrinsic motivation to change by exploring and resolving ambivalence’ (Miller and Rollnick 2002). Motivational interviewing has as its goal the simple expectation that increasing an individual’s motivation to consider change rather than showing them how to change should be the key step. If a person is not motivated to change then it is irrelevant if they know how to do it or not. […] Motivational interviewing (MI) is a technique based on cognitive-behavioural therapy which aims to enhance an individual’s motivation to change health behaviour. The whole process aims to help the patient understand their thought processes and to identify how their thought processes help produce the inappropriate behaviour and how their thought processes can be changed to develop alternative, health-promoting behaviours. Motivational strategies include eight components that are designed to increase the level of motivation the person has towards changing a specific behaviour. […] The eight components are: *giving advice (about specific behaviours to be changed) *removing barriers (often about access to particular help) *providing choice (making it clear that if they choose not to change that is their right and it is their choice […] *decreasing desirability (of the ambivalence towards change or the status quo) *practising empathy *providing feedback […] *clarifying goals (feedback should be compared with a standard (an ideal) *active helping”.
“The definition of ‘lapse’ and ‘relapse’ has been debated in various forums […] but simply a ‘lapse’ is a slip into smoking behaviour, whereas ‘relapse’ refers to long-term failure. Most smokers who attempt to quit do so through self-quitting […] but the rates of success are very low with reports suggesting that only about 3–5 per cent of those self-quitting attain long-term abstinence at 6–12 months (Hughes et al. 2004). More recently, self-quitters have been aided by being able to purchase over the counter NRT and although this can double the rate of success this is still a paltry 6–10 per cent success rate. […] Although the majority of smokers want to stop smoking and predict that they will have stopped in twelve months, only 2–3 per cent actually stops permanently a year (Taylor et al. 2006).”
“In London, the area with the highest prevalence of HIV in the UK, 30 per cent of people did not know HIV could be transmitted through unprotected sex (National AIDS Trust 2006; UNAIDS 2006). [first thought: Some of these have got to be joke responses] […] [in the UK] the number of women diagnosed with HIV has increased in recent years and in 2007 it was some 40 per cent of the total (compared to 10 per cent of all diagnoses in 1990). […] 95 per cent of 16–24 year olds who use a condom do so in order to prevent pregnancy whereas only 71 per cent report using a condom in order to prevent infection. Furthermore, less than half (48 per cent) of men and only 37 per cent of women report using a condom ‘always’. […] At least 50 per cent of sexually active men and women acquire genital HPV infection at some point in their lives […] Regarding HIV it is estimated that one-quarter of people living with the disease do not know that they have it and are therefore at risk of transmitting the virus to others (CDC 2006e).”
“The pharmacological effects of alcohol and various other non-prescription substances tend to have the effect of reducing inhibitions, boosting confidence, intensifying emotions and increasing the importance of immediate cues such as sexual desire, at the expense of more future-oriented considerations such as STIs. As a result, users have been shown to engage in more risky sexual behaviours [related link (well, sort of related – if you skip the first paragraph and see link i. and ii…)] […] Alcohol use and sexual activity often co-occur and more than one-quarter of sexually active teens used alcohol or drugs during their last sexual experience […] However, not only does the condom have to be used, but also it has to be used effectively (i.e. properly). Hatherall et al. (2007) report that a sizeable minority (between 12 and 40 per cent) applied a condom imperfectly. […] it is well documented that the earlier first sex occurs the less likely it is that contraception will be used […] Reviews have shown that school-based sex education leads to improved awareness of risk and knowledge of protection strategies, and increases intention to adopt safer sex behaviours. It has also been found to delay sexual debut (Kirby et al. 2006).”
This evening IM Christof Sielecki, the guy behind the ChessExplained youtube account, gave an online simultaneous display. These are events where a very strong player will take on many opponents at the same time, and then see how well he does against the opposition. According to the original plan he was supposed to play 20 different opponents, but in the end he ended up only playing 18; I was one of the players he played against during the event. He won 17 games and drew one game. I not surprisingly lost my game, but I did hold out for almost three hours and he had some really nice things to say about my play during the game (see comments below). You can watch the entire ‘show’ here if you haven’t got anything better to do (I sort of hope you do…), and you can see my own game against him here (I was black – Christof had the white pieces in all games); it should perhaps be noted that I spent most of my time on the first 25 moves or so and that I got into severe time trouble and was playing basically only on the increment (30 seconds/move) for the last 20 moves of the game.
As mentioned he had nice things to say about my play, and I’m actually quite satisfied with my play even if I lost. A few quotes from his commentary during the game:
“Very solid game here by the black player.” (43 minutes into the game)
“What can I do, this guy is playing very, very solid chess.” (49 minutes…)
“that’s tough, that’s tough business here, it’s not easy at all …this is one of – he’s playing this very, very solidly. […] I have absolutely nothing here.” (after 17…Re7, roughly 1 hour and 13 minutes into the game)
“Ah, yeah, a5 … yeah, what can you do, he’s playing well…” (after 23…a5 – 1 hour, 52 minutes…)
“Ahm, okay. He keeps defending …that guy, he keeps defending very, very well.” (after 35…g6 – 2 hours, 19 minutes)
“I’m kind of trying to win here, maybe in a situation where it’s not justified.” (after 41…d4 – 2 hours, 28 minutes)
“He played a really, really solid defence, this guy” (2 hours 42 minutes in)
“[M]any [children] show fear and avoidance of novel foods. The tendency to reject novel foods has been termed neophobia. Research has begun to reveal how early experience and learning can reduce the neophobic response to new foods, thereby enhancing dietary variety. For example, Birch and Marlin (1982) found that when 2 year olds were given varying numbers of opportunities to taste new fruits or cheeses, their preferences increased with frequency of exposure. Researchers found that between five and ten exposures to a new food were necessary before preference for that food increased. In another study, Gerrish and Mennella (2001) investigated the acceptance of a novel taste (pureed carrot) by infants who had previously experienced a range of tastes that included many vegetables but not carrot. Exposure to fruit, carrots alone or a variety of vegetables resulted in an increased acceptance of pureed carrot. Furthermore, those who had been exposed to a variety of vegetables were also more likely to eat other novel foods. Researchers concluded that familiarity with a variety of flavours increased the acceptance of novel foods. The implication was that parents should expose their children to a wide variety of tastes to encourage the acceptance of novel foods. […] exposure is a major factor in encouraging consumption. […] during childhood, the neophobic response to new foods decreases with age […]. Although repeated opportunities to taste and eat new food has been found to reduce neophobia and enhance acceptance, merely smelling or looking at the food has no such effect (Birch et al. 1987). This finding is consistent with the learned safety hypothesis which suggests that neophobia is only reduced as we learn that the food is safe to eat and does not cause illness […]. Further evidence suggests that watching others consume the food may provide a form of ‘exposure by proxy’ or modelling which could also reduce rejection […] observing a parent eating energy dense food could potentially encourage a child to establish similar food preferences. The effectiveness of the role model has been found to differ depending on the relationship between the child and the model. […] Birch (1980) and Duncker (1938, cited in Birch 1999) report that older children are more effective role models than younger children; Harper and Sanders (1975) report that mothers are more effective than strangers; and for older preschool children, adult heroes are more effective than ordinary adults (Birch 1999).”
“Promise of a reward is a time-honoured parental tactic for promoting consumption of healthy food. Nevertheless, it has been argued that treating food consumption in this way may actually decrease liking for that food. Lepper and Greene’s (1978) overjustification theory argues that offering a reward for an action devalues it for the child. In support of this a number of studies have reported decreased liking for foods when children are rewarded for eating them […] Horne et al. (2004) argue that in order for rewards to be effective, it is important that they are highly desirable and that they indicate to the child that they are for behaviour which is enjoyable and high status. Other studies have investigated the impact of using food as a reward. For example, Birch et al. (1980) presented children with foods either as a reward, a snack or in a non-social situation and found that acceptance increased if the food was presented as a reward. It is easy to generalise this finding to real life situations. High fat and sweet items are used repeatedly in positive contexts, for example on special occasions. The consumption of already pleasurable items in this way is reinforced. If children are given foods as rewards for approved behaviour, preference for those foods is enhanced (Benton 2004).”
“Cognitive models of eating behaviour explore the extent to which cognitions predict and explain behaviour. Most research from a cognitive perspective has drawn on social cognition models and several models have been developed […] All […] share the assumption that attitudes and beliefs are major determinants of eating behaviour, however they vary in terms of the cognitions they include and whether they use behavioural intentions or actual behaviour as their outcome measure […] Some research using the TRA and TPB has focused on predicting behavioural intentions. Research suggests however, that behavioural intentions are not that successful in predicting actual behaviour.”
“Traditionally habit has been measured by the number of times behaviour has been performed in the past […] Nevertheless behavioural recurrence does not constitute direct evidence for habitual processes. Verplanken and Orbell (2003) argue that habit is a psychological construct rather than behavioural recurrence and involves lack of awareness, difficulty to control, mental efficiency and repetition. Although repetition is a necessary requirement for a habit to develop, subsequent research has supported the hypothesis that frequency of past behaviour and habit are separate constructs [I also pointed this out elsewhere recently, but I think it’s an important insight. Revisiting my coverage of Buskirk et al.’s text after posting that comment I incidentally realized that Eysenck and Keane‘s coverage may well in some respects be more relevant/useful than the former.] […] It may be […] useful to conceptualise habits as established patterns of behaviour that may once have been initiated by rational choice but which are now under the control of specific situational cues that trigger the behaviour without cognitive effort. […] Reasoned action as represented in social cognition models and habit can be considered as two extremes of a conscious decision-making continuum. In between may lie a number of heuristic decision-making strategies that involve varying degrees of cognition.”
“Foltin et al. (1988) gave volunteers two cigarettes containing active marijuana or a placebo and found that active marijuana increased total caloric intake by 40 per cent. […] studies exploring the relationship between alcohol and food intake have been contradictory. In a mini-review Gee (2006) found that among eight studies reviewed, only one showed a significant difference in appetite ratings between the alcohol and no alcohol pre-load. […] Gee (2006) concluded that the effect of alcohol on appetite appears to be unsubstantiated; however alcohol’s effect on energy intake does appear significant. As well as recreational drugs, anti-psychotics and antidepressants have also been shown to influence hunger and satiety.” [Of course there are a large number of variables involved, but they don’t actually go into much detail in their coverage. To add to the list, sleep can also be quite important].
“According to Bourn (2001) approximately two-thirds of the UK’s population visit their GP at least annually, so primary care provides an unparalleled opportunity for health promotion and preventive interventions.” (This number is old, but a number like this one seems relevant to a wide variety of topics so even if it’s dated I decided to include it here anyway in order to increase the likelihood that I’ll remember the context of the estimate later).
“Despite considerable efforts over a number of years, there is limited evidence to suggest that educational approaches to dietary change (that is providing basic information about what constitutes a ‘healthy’ diet) alter children’s eating habits […] Hundreds of interventions to combat the obesity epidemic are currently being introduced worldwide, but there are significant gaps in the evidence base for such interventions and few been evaluated in a way that enables any definitive conclusions to be drawn about their effectiveness. Those that have shown an impact are limited to easily controlled settings and it remains unclear how promising small-scale initiatives would be scaled up for whole population impact (Butland et al. 2007). […] NICE recommends that interventions to improve diet should be multicomponent (i.e. including dietary modification, targeted advice, family involvement and goal setting), tailored to the individual, provide ongoing support, include behaviour change strategies and include awareness raising promotional activities as part of a longer term, multicomponent intervention rather than a one off activity.”
“The Office for National Statistics (2003) reported that distances walked annually dropped by 63 miles between 1975 and 2003 [I was actually sort of surprised the number wasn’t higher…]. Similarly, distances cycled dropped by 16 miles in the same period [I must admit part of the reason why I picked out the quote was that I wanted to illustrate once again why I gave this book a low rating on goodreads; the book here clearly gives you the impression that people walk less and bicycle less than they used to do. But try to look at those numbers and divide each of them with 365. There’s no way in hell those 16 miles of bicycling *per year* per person makes any measurable difference on any semi-relevant health variable of interest – this is something like 40 meters per day per person, or 10 seconds of bicycling per day, assuming an average speed of 15 km/hour…]. The proportion of people who travel by walking or cycling has declined by 26 per cent (Department of Health, Physical Activity, Health Improvement and Prevention 2004). [This number on the other hand seems much more likely to have health-relevance. But then you immediately start asking yourself: if that number is true, why are the other numbers so low? And the inclusion of all of the above numbers in the coverage actually illustrates perfectly a recurring issue I had with the coverage; there are a lot of numbers here, and they don’t all tell the same story, and the authors aren’t always making it the least bit easier to make sense of them because they seem to treat many of them quite uncritically. Maybe fewer people cycle, but those that do put in more kilometers – but the authors aren’t suggesting this in the text, so you sort of need to come up with these sorts of explanations for the semi-weird constellation of research results yourself]. Consequently, it has been argued that active transport is a key factor in the achievement of healthy levels of physical activity […] All four national surveys demonstrate the same sex difference in activity levels. Physical activity is the only lifestyle behaviour where men are more likely to achieve government guidelines than women […]. Sport is a traditional male activity which may contribute to this finding.”
“The relationship between [physical] activity and social class as measured by the National Statistics Socio-Economic Classification (NS-SEC) […] is complex. […] The relationship between NS-SEC and physical activity can be described by an inverted U-shaped curve, with those at either end of the NS-SEC scale being the least likely to be active. […] Compared to the general population, South Asian and Chinese men and women were much less likely to participate in physical activity of any kind. Bangladeshi men and women were the most inactive and were almost twice as likely as the general population to be classified as sedentary. […] Physical activity reduces the risk of premature mortality for everyone, regardless of their age, sex or ethnicity […] In England, the Department of Health, Physical Activity, Health Improvement and Prevention (2004) has estimated that adults who are physically active have a 20–30 per cent reduced risk of premature death. Warburton et al. (2006) have suggested that a 50 per cent reduction in risk from death is possible for the physically fit. The effect of physical activity on health manifests itself by its influence on a wide range of diseases. In particular, people who are physically active can achieve up to a 50 per cent reduced risk of developing the major lifestyle diseases: coronary heart disease, stroke, diabetes and cancers […] not only do inactive people face shorter lives, but also they face poor quality of life in the years preceding death. While the relationship of physical activity to each disease is important in its own right, what makes physical activity so important is the strength of its effect over such a wide range of conditions. […] Associations with health are generally stronger for measured cardiorespiratory fitness than for reported physical activity […] but a self-reported physical activity is still convincingly associated with reduced mortality […]. In short, cardiorespiratory fitness will benefit health but levels of physical activity that may not be of an intensity to alter physical fitness parameters may still have health benefits. […] Obesity is the main visible sign of inactivity, yet obesity is just one of possibly 20 chronic diseases and disorders for which low activity levels are a known contributory factor. […] it is easier to influence the energy intake–output balance through diet than through activity […] The evidence suggests that for physical activity to have a significant effect on bodyweight and in particular on weight loss then 30 minutes of moderate activity for five days a week is unlikely to be a high enough level of activity.”
“Social cognition theory has identified self-efficacy and perceived behavioural control as key factors in the practice of healthy levels of physical activity, but at best such models can predict 50 per cent of the variation in physical activity […] Extensive evaluation of social cognition models’ ability to predict uptake of physical activity leads to the conclusion that a perception of the risks of non-activity and the benefits of activity for health has at best a small impact of overall variation in physical activity behaviour. […] Kahn et al. (2002) in their review of informational campaigns found no evidence that informational only media-based campaigns were effective, in line with the theoretically derived conclusion that attempts to inform people of the benefits and costs of activity and inactivity are unlikely to facilitate substantial changes in behaviour. Similarly, Ogilvie et al. (2004) found no evidence that informational campaigns to increase active transport were successful. […] Behavioural interventions are more likely to be at a small group or individual level of intervention. Kahn et al. (2002) found that individually adapted behavioural change programmes were effective in increasing physical activity levels. Ogilvie et al. (2004) found that targeted behavioural change programmes were the most effective way to promote walking and cycling. […] Many public health interventions to increase physical activity in the community are not individualised, do not recognise the role of psychological processes in effective behavioural change and are carried out by professionals with no psychological training”.
“Improving lifestyles is thought to be one of the most effective means of reducing mortality and morbidity in the developed world. However, despite decades of health promotion, there has been no significant difference to lifestyles and instead there are rising levels of inactivity and obesity. The Psychology of Lifestyle addresses the role psychology can play in reversing the trend of deleterious lifestyle choices. It considers the common characteristics of lifestyle behaviours and reflects on how we can inform and improve interventions to promote healthy lifestyles. […] The chapters cover key lifestyle behaviours that impact on health – eating, physical activity, drinking, smoking, sex and drug use – as well as combinations of behaviours.”
I gave the book two stars on goodreads. There are multiple reasons why it did not get a higher rating despite containing quite a lot of material which I consider to be worth blogging. One reason is that the book is really UK-centric; it’s written by British authors for a British audience. Which is fine if you’re from Britain, but it does mean that some of the details included (such as drinking pattern breakdowns for England, Scotland, and Wales) may not be super interesting to the non-British readership. Another reason is that some of the numbers included in the publication are frankly not trustworthy, and the inclusion of those numbers without critical comments on part of the authors occasionally made me question their judgment. To give an example, it is at one point during the coverage noted that: “Women aged 16–19 were least likely to be using contraception despite almost two-thirds of teenagers having had intercourse by age 13 (CDC 2007b).” The problem I have with this quote is that they don’t comment anywhere in the publication upon the fact that this estimate is, if applied to the general population, frankly unbelievable, taking into account other estimates from the literature, including other estimates from US samples (see e.g. this previous post of mine). It’s clear that it’s an estimate derived from a specific sample, but it’s not made clear that the characteristics of the sample were probably very different from the characteristics of the population about which the reader is using the quote to make inferences. To illustrate just how difficult it is to believe that the estimate has much, if any, external validity, according to the estimates reported in fig. 6.2 in the link in the parenthesis above, you don’t get to the point where two-thirds have had sexual intercourse before the age of 19. The estimate they include in the book is not just weird and strange, it’s so weird and strange that anybody who knows anything about that literature would know the estimate is weird and strange, and would at least comment upon why it is perhaps not to be trusted (my guess would be that this estimate is derived from a sample displaying a substantial amount of selection bias due to opportunistic sampling from a very high-risk group). Yet they don’t comment on these things at all, apparently not only taking it to some extent at face value, but also asking the reader to do the same. This was almost an unforgivable error on part of the authors and I was strongly considering not reading on when I got to this point – I don’t really think you can not comment on this kind of thing if you decide to include numbers like those in your coverage in the first place.
Another problem is that there’s also occasionally some sloppy reporting which makes it hard to understand what the research they’re reporting on is actually saying; one example is that they note in the publication (p.185) that: “Young people aged over 15 accounted for 40 per cent of new HIV infections in 2006” – which immediately makes me start wondering whether e.g. a 25-year old would be considered ‘young’, according to this estimate? What about a 30-year old? The publication is silent on the issue of where the right-hand side cut-off is located, making the estimate much less useful than it otherwise would be.
A fourth(?) issue is that a lot of this stuff is correlational research, and there are a lot of cross-section studies and pretty much no longitudinal studies. At a few points do the authors caution against drawing strong conclusions from this kind of research and are frank about the problems which are present, but at other points in the coverage they then to me seem to later on just draw some of those semi-strong conclusions anyway, disregarding the methodological concerns (which are huge).
A fifth issue is that there are some hidden assumptions hidden in the coverage, assumptions which some people might categorize as ‘political’ or something along those lines; these didn’t much bother me because politics and that kind of thing isn’t something I care very much about, as mentioned many times before (though do also see my comments below..), but I’m sure some readers will take issue with what in some sense might be described as ‘the tone’ of the coverage. To be fair they do briefly touch upon e.g. the ethics of smoking bans, but you’re never in doubt where they stand on these issues (bans are fine, most interventions aimed at making the population healthier seem to be fine with the authors), and readers who find government interventions less desirable/justifiable than the authors do may take issue with specific recommendations and implicit assumptions in the coverage. The coverage in the last chapter is sort of a counter-weight to much of the rest of the coverage in the sense that ‘the case against bans and regulation’ gets reasonable coverage here, but I’d say the rest of the book is not really written in a manner which would lead most readers to believe it’s not a good idea to regulate *a lot*.
A sixth personal issue I have with the book is that the book is written in a manner I personally consider to be somewhat disagreeable. It’s a really classic textbook with stuff like a section in the beginning of the chapter outlining ‘what you’ll learn from this chapter’. These kinds of things perhaps wouldn’t be as much of an issue to me if I actually agreed with the authors about what you might be argued to be learning, or not learning, from the coverage in a given chapter. To take an example of what I’m talking about, at the beginning of chapter 7 you learn that: “At the end of this chapter you will: […] understand the nature of sexually transmitted diseases and their health consequences, along with their extent nationwide”. This is just one of 6 learning goals presented. Having read roughly the first third of Holmes et al., I can safely say that reading that book instead would be a lot more helpful than reading the chapter in this book in terms of achieving the learning goal presented, and I might add that if an author of a textbook thinks that you’ll ‘understand the nature of sexually transmitted diseases and their health consequences’ after having read a chapter in a textbook like this one, maybe that author shouldn’t be writing textbooks. This isn’t really fair because the chapter has a lot of useful stuff (and because I have a nagging suspicion that such silly learning goals may well be (politically?) mandated, and that this is probably part of the explanation for why they’re included in books like this one in the first place), but I hate interacting with clueless people with delusions of competence/knowledge, and if people are writing textbooks this way you’ll end up with a lot of people like that coming out the other end.
Despite the above-mentioned problems (and a few others) there’s also a lot of nice stuff in the book, and I’ll share some of that stuff below and in future posts about the book.
“One of the problems with attempting to arrive at a conclusion about what constitutes a lifestyle disease is the myriad of definitions under which diseases are categorised. […] Interestingly, few authors would include sexually transmitted diseases under the lifestyle umbrella, although they could be argued to be entirely under behavioural control, with none of the genetic component that plays a part in aetiology of the six major lifestyle diseases as identified by Doyle (2001). […] In between an ‘imprudent lifestyle’ (Doyle 2001) and the development of a chronic life-threatening or life-foreshortening condition lie a number of precursors of disease. High cholesterol, high blood pressure and obesity are risk factors for the development of a number of the aforementioned lifestyle diseases. The distinction between these precursors, the diseases they predict and the behaviours that are associated with them is often blurred. They are often presented as diseases per se”.
Even though there’s some disagreement about whether or not risk factors are actually Diseases or not, I would caution against the idea that they’re somehow ‘less severe’ than ‘an actual Disease’, unless they actually are; high blood pressure increases the risk of e.g. stroke substantially, so in some ways it’s actually quite a bit worse than some ‘agreed-upon Diseases’ which have less significant health impacts and may not actually kill anybody. I was reminded of this stuff (the blurring of diseases and risk factors) and some related problems very recently during a conversation with a friend, and I’ll allow myself to digress a bit to talk about this stuff in a little more detail here even though it’s only marginally related to the book coverage. Anyway, it seems to me that a lot of people who’d prefer a more ‘fair’ health care resource allocation (‘less money for people who caused their own health problems and more for the others’), a goal towards which I feel sympathetically inclined, are not really aware of how complicated these things are and how difficult it may be to make anything even resembling ‘fair’ distinctions between conditions which are/may be caused by behaviour and conditions which are not, to take but one of many issues. I can usually easily see the impetus for ‘changing things in the direction suggested’, but new problems pop up at every junction and it seems perfectly obvious to me that you’re not going to get rid of unfairness by not giving fat people any money to pay for their insulin. Some of the politically feasible solutions may conceivably make matters worse, e.g. because restricting access to (some types of) medical care may just shift expenditures and perhaps lead to higher expenditures on other treatments to which coverage is maintained (and you’d expect coverage to be maintained to some degree – alternatives are not politically viable). I’m aware that the role of preventative care is from a ‘pure cost standpoint’ probably somewhat overblown (usually preventative care does not save money in the long run, as they tend to cost more money than they save – see e.g. Glied and Smith’s coverage), but this stuff is complicated for many reasons. Some of the current disease treatment modalities in widespread use might well be conceived of as preventative medicine as well, and it’d probably make sense to think of them that way in the case of major changes to insurance coverage profiles. Let’s for example try to compare two models. In the first one insulin for type 2 diabetes is covered, and acute hospitalizations as a result of hypo- and hyperglycemia (DKA, HHS) are also covered. Assume now that the coverage for insulin is removed, but acute hospitalizations would still be covered. It would be quite easy for this change to result in an increase in the total costs incurred by the insurance provider, because hospitalizations are a lot more expensive than insulin, and it’s easy to see why excluding coverage of insulin might lead to more acute hospitalizations among type 2 diabetics (I’m too lazy to look up the numbers, but to people who have no idea about the magnitudes involved here one number which I seem to recall and which should illustrate the issues quite nicely is that in terms of the costs involved, one diabetes-related hospitalization corresponds to something like 8 months of treatment – not insulin, all treatment, including doctor’s visits, blood tests, etc., etc.). Evaluating efficiency in such a context would be really difficult because the conclusion drawn would also depend upon how a third factor, long-term complications, are managed. On the margin, a lot of patients face a tradeoff between the risk of hospitalization from hypoglycemia and the risk of developing chronic health complications such as kidney disease (many patients could decrease their risk of e.g. diabetic retinopathy, -neuropathy or -nephropathy by lowering their Hba1c, but this could easily lead to an increased risk of hypoglycemic episodes – which is part of why patients don’t), and if insurance companies are only expected to care about short-term complications/acute stuff then that may lead to some interesting dynamics, e.g. insurers offering cheaper contracts to diabetics with poor (and known to be sub-optimal, from a health standpoint) glycemic control. Another problem/complication is that even if preventative care-interventions tend to cost more money than they save by decreasing the need for other interventions long-term, they may easily cost less money (sometimes substantially less) per unit of health than a lot of other stuff we’re willing to have cost-sharing mechanisms, whether public or private, pay for – which means that if you’re very strongly in favour of ‘not subsidizing the unhealthy’, you may end up rejecting cost-sharing mechanisms promoting interventions which could potentially add a lot of health on the cheap and might be considered no-brainers in any other context. One could also talk about genes and how the impact of life-style is probably highly heterogeneous, so that some people have a lot more leeway in terms of living unhealthily than do others, making a ‘nobody gets insurance coverage if it might be their own fault’ perhaps just as unfair as the converse position where everybody gets covered. I don’t know, I haven’t added it all together and done the math, but I’m willing to bet that neither have the people who may suggest that sort of thing, and I’d be skeptical about assuming you even can ‘do the math’ given the amount of knowledge required to make sense of all the complications. I’m reasonably certain the system most people would evaluate as optimal through a Rawlsian veil of ignorance would not be at either end of the extremes of what might be termed ‘the responsibility axis’ (‘if there’s any chance it might be your own fault, you don’t get any money from us’ being at one end, and ‘it doesn’t matter how you’ve behaved during your life – of course we’ll cover all your treatment costs related to those five chronic, very expensive, and completely preventable diseases you seem to have contracted’-being at the other end), even assuming the proposed model would be the only one available (thus sidestepping the problem that both models would certainly be outcompeted by alternatives in an actual insurance market where different options might be available to health care consumers). Tradeoffs are everywhere, and they’re not going away. I could probably add another related rant here about how many of the issues private insurance market decision-makers have to deal with are identical to the ones confronting public sector decisions-makers, but I think I’ll stop here as the post is quite long enough as it is – back to the book coverage:
“The behaviours that are usually cited as being involved in the aetiology of lifestyle diseases are poor diet, lack of physical activity, cigarette smoking […] and, increasingly, excess drinking […] The taking of illegal drugs is also lifestyle behaviour with health consequences […] Sexual practices are also often described as health and/or lifestyle behaviours by public health professionals […] Major lifestyle diseases are coronary heart disease, stroke, lung cancer, colon cancer, diabetes and chronic obstructive pulmonary disease. […] health-related lifestyles can be defined as behavioural choices made by individuals about eating, physical activity, drinking alcohol, smoking tobacco, taking drugs and sexual practices. […] lifestyle behaviours are all chronic rather than acute behaviours. Usually individuals will practise regular patterns of these behaviours and their future behaviour will be best predicted by the choices they have made in the past. […] lifestyle behaviours have the majority of their positive consequences in the present and the majority of their negative outcomes in the future. Any lifestyle behavioural change intervention consequently requires individuals to be future orientated.”
“Measuring any type of behaviour creates a number of challenges for psychologists. Instruments need to be valid, reliable, practical, non-reactive (that is to say they should not alter the behaviour they seek to measure) and have the appropriate degree of specificity […]. Few methods of measurement meet all these requirements. For none of the lifestyle behaviours identified by this text is there a single accepted ‘gold standard’ measurement tool. Methods of behavioural assessment can be categorised as observational, self report or physiological. Observational and self-report methods are often not validated effectively, whereas physiological methods are often valid but impractical or unacceptable to the study population. […] The variation in methods available to measure lifestyle behaviours creates problems in interpreting research and survey data. First, researchers differ in what they choose to measure and second, even if they choose to measure the same aspect of behaviour, they can differ widely in the method they choose to collect their data and the way they choose to present their findings. Throughout the research literature on lifestyle behaviours, different methods of measurement confuse and hinder direct comparisons.”
“Since the late 1970s regular travel by foot or by bicycle has declined by 26 per cent (Department of Health, Physical Activity, Health Improvement and Prevention 2004).”
“emotional reactions to risky situations can often diverge from cognitive assessments of the same situation. If division occurs emotional reactions usually override cognitive reactions and drive behaviour. One reason for the domination of emotional responses over cognitive assessment is that emotional responses are rapid and rational analyses usually take time […] Many researchers investigating the role of emotion in risk perception conceptualise it as inferior to analytical responses. Indeed it is often dismissed as a source of lay error […] The emotion most usually associated with risk is anxiety (Joffe 2003). Dismissing anxiety as a biasing factor in ‘accurate’ risk perception is problematic. Anxiety is the intermediate goal of many risk communications, particularly public health communications. The primary goal is preventative behaviour but anxiety is considered an essential initiating motivation. Many health promotions are based on this fear drive hypothesis […]. The fear-drive model is generally considered outdated in academic health psychology […] but it is worth considering as it remains a central, if unacknowledged, tenet of many health promotion campaigns. […] The fear-drive model principally proposes that fear is an unpleasant emotion and people are motivated to try to reduce their state of fear. Health promotion has taken this notion and applied it to communication. If a communication evokes fear or anxiety then the fear drive model suggests that the recipient will be motivated to reduce this unpleasant emotive state. If the communication also contains behavioural advice, either implicitly or explicitly, then individuals may follow this advice […] Fear is intuitively appealing as a means of promoting behavioural change but the role it plays in initiating behavioural change is not clear cut or consistent […]. However, this has been effectively denied […] by health professionals for over half a century.”
“Self-efficacy is the belief that one can carry out specific behaviours in specified situations […]. Self-efficacy has been extensively studied [and] has been argued to be enhanced by personal accomplishment or mastery, vicarious experience or verbal persuasion […]. Self-efficacy is not unrealistic optimism as it is based on experience […]. Self-efficacy is similar to the broader construct of self-esteem but can be distinguished by three aspects: self-efficacy implies a personal attribution; it is prospective, referring to future behaviours and finally it is an operative construct in that the cognition is proximal to the behaviour […]. Self-efficacy is one of the best predictors of behavioural change whereas self-esteem has been found to be a poor predictor of behavioural change […]. Ajzen (1988, 1998) has consistently argued that behaviour-specific constructs fare better than generalised dispositions in predicting behaviour. The success of self-efficacy and the failure of self-esteem in predicting a range of behaviours adds considerable weight to this principle of compatibility [I remember an analogous argument being made in Leary et al.]. […] Perceived self-efficacy has been found to be the major instigating force in both intentions to change lifestyle behaviours and actual behavioural change […] Outcome expectancies, goals and perceived impediments have also been found to be predictive in some studies”
“Stage theories have become increasing popular in recent years […]. Many theorists have argued that different cognitions may be important at different stages in promoting health behaviour […] According to all stage theories a person can move through a series of stages in the process of behavioural change […] Different factors are important at different stages, although the theory allows for some overlap. […] interpreting whether the data supports a stage theory of behaviour is fraught with difficulties. […] Regardless of the method of analysis there appears [however] to be little empirical evidence for the existent of discrete stages that could not equally well be explained as categorisation of a continuum […].”
“There are differences in the level of obesity between the different UK countries. In Northern Ireland, some 64 per cent of men and 53 per cent of women are overweight or obese (NISRA 2006). Similarly, in Scotland 64 per cent of men and 57 per cent of women are so classified (Scottish Executive 2005) […] In England, 65.2 per cent of men and 57 per cent of women were reported as being at least overweight. The results from the Health Survey for England show that the proportion of adults with a desirable BMI decreased between 1993 and 2005, from 41.0 per cent to 32.2 per cent among men and from 49.5 per cent to 40.7 per cent among women. There was no significant change in the proportion of adults who were overweight. The proportion who were categorised as obese (BMI 30+) increased from 13.2 per cent of men in 1993 to 23.1 per cent in 2005 and from 16.4 per cent to 24.8 per cent of women (Information Centre 2006).”
“The National Diet and Nutrition Survey (DoH/FSA 2002) reported on a range of socio-demographic factors related to diet and obesity. For example, those in the low working-class group consumed more calories, considerably more fat, more salt and non-milk extrinsic sugars than those in the middle and upper classes. Furthermore those on low income eat a less varied diet compared to those in the upper classes. […] people living on state benefits and reduced income eat less fruit and vegetables, less fish and less high-fibre foods […] children of semi-skilled and unskilled manual workers are more likely to eat fatty food, less fruit and vegetables, and more sweets than those children of professionals and managers. […] research suggests that nearly 20 per cent of those aged between 4 and 18 years eat no fruit at all during a typical week […] Rayner and Scarborough (2005) estimated that food related ill-health is responsible for about 10 per cent of morbidity and mortality in the UK. […] They estimated that food accounts for costs of £6 billion a year (9 per cent of the NHS budget).”
“the amount of sedentary time spent watching TV by children in the UK has doubled since the 1960s (Reilly and Dorosty 1999)”
Reading this short note made me sad, even if I’ve never met the guy. Picking just one author as my ‘favourite author’ would be an unfair and impossible undertaking, but I’m pretty sure I would often pick Pratchett if asked to do so anyway. His Discworld books are funny, thought-provoking, wonderful, and unique, and fortunately they are still around and will remain so for a long time to come. If you have not already read him, now might be a good time to give his books a shot. A few samples here, here, and here.
I’ve shared this lecture of his before here on the blog, but it may be worth doing it again today, given the circumstances.
People who’re keeping up to date with my reading on the book list or on goodreads would have noticed that I have not read much stuff (especially not non-fiction) lately, and that I’m mostly covering books I read a while back. I assume most people don’t (keep up), but now the rest of you know as well. There are two principal reasons for this recent change: a) I’ve been busy with ‘real work’, and b) (significantly more important) I have been bothered by noise from another flat in the building in which I live for some time. It has become dramatically worse in the last week or two. My impression is that me moving someplace else would be easier to accomplish than having those neighbours kicked out, but I’m conflicted about doing this both because of the time and costs involved, but also because I know it’s a temporary problem as the people causing problems are renters and their contract will expire in August. I’m strongly considering at the moment to move to live at my parents’ place for some time (they have room for me, and they wouldn’t mind); not permanently, but several days each week. At the moment I’m more or less permanently angry and frustrated, and lately I’ve been more or less completely unable to focus. My knowledge of the physiological responses to stress is telling me that my blood pressure is probably through the roof. My roommate is also annoyed by the behaviour of my neighbours and have asked me multiple to complain about their behaviour (so it’s not just me), which I have done; but having Asperger’s and being very sensitive to noise does not help. There’s no way to reach an agreement with these people; diplomacy was of course my first approach, until I realized they just don’t give a shit and just do whatever they want anyway. I told them a few days ago that the noise they were making was not acceptable (it was angering both me and my roommate), and their response to this was to keep making noise for another 3 hours after I’d talked to them, into late in the evening; you can’t reason with people like that.
I’m hoping to find some sort of workable solution to these issues soon. It’s not that I’ve stopped finding blogging or reading/learning stuff interesting, but these problems are seriously impacting both my work and activities related to my blogging. Lately I’ve mostly tried to spend the available hours during which I was able to actually focus on the material on my work, and not on blogging or blogging-related activities, so blogging has been light. The noise doesn’t just encroach upon my work hours, but also upon the hours I have for myself; for example there was audible music coming through the floor yesterday evening until almost 11 PM (on a Monday).
Christof Sielecki has started a new and, it seems to me, very promising video series where he analyzes the games of people who’ve sent in their games to him. I think the videos might be useful to a lot of players, perhaps even including players who are relatively new to the game.
I have posted the first three videos in the series below:
“The extinction of the arboreal primates and the reduction or extinction of several browsing groups […] are strong evidence for the retreat of the forests during the early Oligocene and their replacement by open woodlands or even drier biotopes. […] Among the most distinctive species to enter Europe after the “Grande Coupure” were the first true rhinoceroses [which] achieved a high diversity and were going to characterize the mammalian faunas of Europe for millions of years, until the extinction of the last woolly rhinos during the late Pleistocene. […] the evolution of this group produced the largest terrestrial mammals of any time. The giant Paraceratherium […] was 6 m tall at the shoulders and had a 1.5-m-long skull […]. The males of this animal weighed around 15 tons, while the females were somewhat smaller, about 10 tons.” [Wikipedia has a featured article about these things here].
“One of the most significant features of the early Oligocene small-mammal communities was the first entry of lagomorphs into Europe. The lagomorphs — that is, the order of mammals that includes today’s hares and rabbits — originated very early on the Asian continent and from there colonized North America. The presence of the Turgai Strait prevented this group from entering Europe during the Eocene. […] the most characteristic immigrants during the early Oligocene were the cricetids of the genus Atavocricetodon. The cricetids are today represented in Europe by hamsters, reduced to three or four species […] These cricetids are typical inhabitants of the cold steppes of eastern Europe and Central Asia, and their limited representation in today’s European ecosystems does not reflect their importance in the history of the Cenozoic mammalian faunas of Eurasia. After its first entry following the “Grande Coupure,” this group experienced extraordinary success, diversifying into several genera and species. Even more significantly, the cricetids gave rise to the rodent groups that were going to be dominant during the Pliocene and Pleistocene — that is, the murids (the family of mice and rats) and arvicolids (the family of voles). […] In addition, new carnivore families, like the nimravids, appeared […]. The nimravids were once regarded as true felids (the family that includes today’s big and small cats) because of their similar dental and cranial adaptations. […] one of the more distinctive attributes of the nimravids was their long, laterally flattened upper canines, which were similar to those of the Miocene and Pliocene saber-toothed cats […]. However, most of these features have proved to be the result of a similar adaptation to hypercarnivorism, and the nimravids are now placed in a separate family of early carnivores whose evolution paralleled that of the large saber-toothed felids.” [Actually some of the nimravids were in some sense ‘even more sabertoothed’ than the (‘true’) saber-toothed cats which came later: “Although [the nimravid] Eusmilus bidentatus was no larger than a modern lynx, the adaptations for gape seen on its skull and mandible are more advanced than in any of the felid sabertooths of the European Pliocene and Pleistocene.”]
“About 30 million years ago, a new glacial phase began, and for 4 million years Antarctica was subjected to multiple glaciation episodes. The global sea level experienced the largest lowering in the whole Cenozoic, dropping by about 150 m […]. A possible explanation for this new glacial event lies in the final opening of the Drake Passage between Antarctica and South America, which led to the completion of a fully circumpolar circulation and impeded any heat exchange between Antarctic waters and the warmer equatorial waters. A second, perhaps complementary cause for this glacial pulse is probably related to the final opening of the seaway between Greenland and Norway. The cold Arctic waters, largely isolated since the Mesozoic, spread at this time into the North Atlantic. The main effect of this cooling was a new extension of the dry landscapes on the European and western Asian lands. For instance, we know from pollen evidence that a desert vegetation was dominant in the Levant during the late Oligocene and earliest Miocene […] This glacial event led to the extinction of several forms that had persisted from the Eocene”.
“Among the carnivores, the late Oligocene saw the decline and local extinction of the large nimravids [Key word: local. They came back to Europe later during the early Miocene, and “the nimravids maintained a remarkable stability throughout the Miocene, probably in relation to a low speciation rate”]. In contrast, the group of archaic feloids that had arisen during the early Oligocene […] continued its evolution into the late Oligocene and diversified into a number of genera […] The other group of large carnivores that spread during the late Oligocene were the “bear-dog” amphicyonids, which from that time on became quite diverse, with many different ecological adaptations. […] The late Oligocene saw, in addition to the bearlike amphicyonids, the spread of the first true ursids […]. The members of this genus did not have the massive body dimensions of today’s bears but were medium-size omnivores […] Another group of carnivores that spread successfully during the late Oligocene were the mustelids, the family that includes today’s martens, badgers, skunks, and otters. […] In contrast to these successes, the creodonts of the genus Hyaenodon, which had survived all periods of crisis since the Eocene, declined during the late Oligocene. The last Hyaenodon in Europe was recorded at the end of the Oligocene […], and did not survive into the Miocene. This was the end in Europe of a long-lived group of successful carnivorans that had filled the large-predator guild for millions of years. However, as with other Oligocene groups, […] the hyaenodonts persisted in Africa and, from there, made a short incursion into Europe during the early Miocene”.
“After a gradual warming during the late Oligocene, global temperatures reached a climatic optimum during the early Miocene […] Shallow seas covered several nearshore areas in Europe […] as a consequence of a general sea-level rise. A broad connection was established between the Indian Ocean and both the Mediterranean and Paratethys Seas […] Widespread warm-water faunas including tropical fishes and nautiloids have been found, indicating conditions similar to those of the present-day Guinea Gulf, with mean surface-water temperatures around 25 to 27°C. Important reef formations bounded most of the shallow-water Mediterranean basins. […] Reef-building corals that today inhabit the Great Barrier Reef within a temperature range of 19 to 28°C became well established on North Island, New Zealand […] The early Miocene climate was warm and humid, indicating tropical conditions […]. Rich, extensive woodlands with varied kinds of plants developed in different parts of southern Europe […] The climatic optimum of the early Miocene also led to a maximum development of mangroves. These subtropical floras extended as far north as eastern Siberia and Kamchatka”.
“Despite the climatic stability of the early Miocene, an important tectonic event disrupted the evolution of the Eurasian faunas during this epoch. About 19 million years ago, the graben system along the Red Sea Fault, active in the south since the late Oligocene, opened further […] Consequently, the Arabian plate rotated counterclockwise and collided with the Anatolian plate. The marine gateway from the Mediterranean toward the Indo-Pacific closed, and a continental migration bridge (known as the Gomphothere Bridge) between Eurasia and Africa came into existence. This event had enormous consequences for the further evolution of the terrestrial faunas of Eurasia and Africa. Since the late Eocene, Africa had evolved in isolation, developing its own autochthonous fauna. Part of this fauna consisted of a number of endemic Oligocene survivors, such as anthracotheres, hyaenodonts, and primates, for which Africa had acted as a refuge […] The first evidence of an African–Eurasian exchange was the presence of the anthracothere Brachyodus in a number of early Miocene sites in Europe […] a second dispersal event from Africa, that of the gomphothere and deinothere proboscideans, had much more lasting effects. […] Today we can easily identify any proboscidean by its long proboscis and tusks. However, the primitive proboscideans from the African Eocene had a completely different appearance and are hardly recognizable as the ancestors of today’s elephants. Instead, they were hippolike semiamphibious ungulates with massive, elongated bodies supported by rather short legs. […] The first proboscideans entering Europe were the so-called gomphotheres […] which dispersed worldwide during the early Miocene from Africa to Europe, Asia, and North America […]. Gomphotherium was the size of an Indian elephant, about 2.5 m high at the withers. Its skull and dentition, however, were different from those of modern elephants. Gomphotherium’s skull was long […] and displayed not two but four tusks, one pair in the upper jaw and the other pair at the end of the lower jaw. […] Shortly after the entry of Gomphotherium and Zygolophodon [a second group of mastodons], a third proboscidean group, the deinotheres, successfully settled in Eurasia. Unlike the previous genera, the deinotheres were not elephantoids but represented a different, now totally extinct kind of proboscidean.”
“The dispersal of not only the African proboscideans but also many eastern immigrants contributed to a significant increase in the diversity of the impoverished early Miocene terrestrial biotas. The entry of this set of immigrants probably led to the extinction of a number of late Oligocene and early Miocene survivors, such as tapirids, anthracotherids, and primitive suids [pigs] and moschoids. In addition to the events that affected the Middle East area, sea-level fluctuations enabled short-lived mammal exchanges across the Bering Strait between Eurasia and North America, permitting the arrival of the browsing horse Anchitherium in Eurasia […] Widely used for biostragraphic purposes, the dispersal of Anchitherium was the first of a number of similar isolated events undergone by North American equids that entered Eurasia and rapidly spread on this continental area.”
“A new marine transgression, known as the Langhian Transgression, characterized the beginning of the middle Miocene, affecting the circum-Mediterranean area. Consequently, the seaway to the Indo-Pacific reopened for a short time, restoring the circum-equatorial warm-water circulation. […] tropical conditions became established as far north as Poland in marine coastal and open-sea waters. After the optimal conditions of the early Miocene, the middle Miocene was a period of global oceanic reorganization, representing a major change in the climatic evolution of the Cenozoic. Before this process began, high-latitude paleoclimatic conditions were generally warm although oscillating, but they rapidly cooled thereafter, leading to an abrupt high-latitude cooling event at about 14.5 million years ago […] Increased production of cold, deep Antarctic waters caused the extinction of several oceanic benthic foraminifers that had persisted from the late Oligocene–early Miocene and promoted a significant evolutionary turnover of the oceanic assemblages from about 16 to 14 million years ago […] This middle Miocene cooling was associated with a major growth of the Eastern Antarctic Ice Sheets (EAIS) […] Middle Miocene polar cooling and east Antarctic ice growth had severe effects on middle- to low-latitude terrestrial environments. There was a climatic trend to cooler winters and decreased summer rainfall. Seasonal, summer-drought-adapted schlerophyllous vegetation progressively evolved and spread geographically during the Miocene, replacing the laurophyllous evergreen forests that were adapted to moist, subtropical and tropical conditions with temperate winters and abundant summer rainfalls […] These effects were clearly seen in a wide area to the south of the Paratethys Sea, extending from eastern Europe to western Asia. According to the ideas of the American paleontologist Ray Bernor, this region, known as the Greek-Iranian (or sub-Paratethyan) Province, acted as a woodland environmental “hub” for a corridor of open habitats that extended from northwestern Africa eastward across Arabia into Afghanistan, north into the eastern Mediterranean area, and northeast into northern China. The Greek-Iranian Province records the first evidence of open woodlands in which a number of large, progressive open-country mammals—such as hyaenids, thick-enameled hominoids, bovids, and giraffids — diversified and dispersed into eastern Africa and southwestern Asia […] the peculiar biotope developed in the Greek-Iranian Province acted as the background from which the African savannas evolved during the Pliocene and Pleistocene.”
“The most outstanding effect of the Middle Miocene Event is seen among the herbivorous community, which showed a trend toward developing larger body sizes, more-hypsodont teeth, and more-elongated distal limb segments […]. Increasing body size in herbivores is related to a higher ingestion of fibrous and low-quality vegetation. Browsers and grazers have to be large because they need long stomachs and intestines to process a large quantity of low-energy food (this is why they have to eat almost continuously). Because of the mechanism of rumination, ruminants are the only herbivores that can escape this rule and subsist at small sizes. Increasing hypsodonty and high-crowned teeth are directly related to the ingestion of more-abrasive vegetation […] Finally, the elongation of the distal limb segments is related to increasing cursoriality. The origin of cursoriality can be linked to the expansion of the home range in open, low-productive habitats. […] At the taxonomic level, this habitat change in the low latitudes involved the rapid adaptive radiation of woodland ruminants (bovids and giraffids). […] Gazelles dispersed into Europe at this time from their possible Afro-Arabian origins […] Not only gazelles but also the giraffids experienced a wide adaptive radiation into Africa after their dispersal from Asia. […] Among the suids [pigs], the listriodontines evolved in a peculiar way in northern Africa, leading to giant forms such as Kubanochoerus, with a weight of about 500 kg, which in some species may have reached 800 kg.”
Haughty, persiflage, assignation, curdle, tousle, gabble, decamp, varmint, trumpery, efflorescence, brim, bedizen, rostrum, peroration, farrago, vernal, expiate, astringent, prepossessing, dowdy, niggle, vainglorious, veneer, abnegation, horology, ignoble, fulcrum, skein, acidulous, syncretism, exultant, peremptory, cognomen, debonair, lachrymose, subservience, commiseration, equipoise, animadversion, diffidence, reprobate, martinet, garret, superannuate, asseverate, gravamen, saunter, lassitude, verisimilar, appurtenance, oenophile, lambent, welt, churlish, ingenue, plait, inundate, scamper, incontrovertible, abscond, requite, milliner, caboose, …
The words above are all words I’ve encountered over the last few days, either in novels or during my vocabulary-building exercises on vocabulary.com. The site is a really nice learning tool, though I prefer Webster’s dictionary to theirs (which should explain the links above). I know I’ve mentioned the site before and there’s also a link to it in the sidebar, but as I recently ‘revived’ my account after some period of relative inactivity I assumed there was some positive probability that others reading along here may also have been using the site in the past and then forgot about it/given up on it.
I was wondering about whether or not I should make word-posts like these, with lists of some of the words I’ve been ‘working on’, a regular feature of the blog; it seems nice to get words you’ve come across and would like to remember, and/or words you’re actively learning/reviewing, refreshed here on the blog, and posts like this one might also provide motivation for others to have a go at this kind of stuff. The only real downside I can think of at the moment is that if I start posting stuff like this, there’s a small risk people who come across my blog might get confused and start thinking I’m an intellectual or something along those lines.
Here’s a link to a previous post in the series about the book. Before proceeding to the coverage of the textbook, I thought I should mention that I yesterday read another novel by Wodehouse, and started on a third one. His stuff is awesome – if you’re having trouble finding fiction which is fun and enjoyable to read, you should definitely check out Wodehouse if you haven’t already.
Okay, back to the textbook. When I started out writing this post I thought it would be my last post about the book, but in the end I decided that the post would get too long if I covered all the remaining chapters in this post. So I may or may not cover the rest of the book later. The first topic I’ll cover in this post is intimacy. Some observations from the chapter on that topic:
“Individuals can influence the evolution of an emerging relationship by adjusting the breadth (the number of topics disclosed) and the depth of their self-disclosure (the degree of personal relevance). In addition, nonverbal behaviors (e.g., gaze, touch, body orientation) are expressions that can augment and interact with verbal self-disclosures to influence intimacy in a relationship […] Self-disclosure has been found to account for just below half of the variance in ratings of couples’ level of intimacy […] To contribute to the development of intimacy in a relationship, an individual’s responses have to demonstrate concern for the discloser. A response must be sincere and immediate, capture the content of the original communication, and meet the need of the discloser […]. Responsiveness has been found to play an important role in disclosure reciprocity, liking, and closeness in relationships […]. Recently, researchers have conceptualized responsiveness as a process whereby a person communicates understanding, validation, and caring in response to a partner’s self-disclosure […] In personal relationships, receiving validation and acceptance can often take on a self-esteem maintaining or protective function, in that individuals often seek to confirm their self-concept through the responses of others […]. Reis and Shaver (1988) argued that the speaker’s perception and judgment of the listener’s response as understanding, validating, and caring are important factors in the experience of intimacy, above and beyond the listener’s actual responsiveness. […] According to Reis and Shaver (1988), intimacy is an interpersonal, transactional process with two principal components: self-disclosure and partner responsiveness. Intimacy can be initiated when one person communicates personally relevant and revealing information to another person. […] For the intimacy process to continue, the listener must emit emotions, expressions, and behaviors that are both responsive to the specific content of the disclosure and convey acceptance, validation, and caring toward the individual disclosing. For the interaction to be experienced as intimate by the discloser, he or she must perceive both the descriptive qualities (understanding of content) and evaluative qualities (validation and caring) of the response. […] a consistent finding is that individuals with an insecure attachment style are less responsive than more securely attached individuals according to both objective third-party ratings and subjective reports”.
“A notable tenet of existing models of intimacy […] is that intimacy is achieved when Partner A self-discloses and feels validated, cared for, and understood by Partner B’s attempts at responsiveness. Although we agree that this model describes the intimacy process, we believe that in many ways it is decidedly one-sided. Is the experience of intimacy only achieved when one feels that a relationship partner is responding to one’s needs? We argue that an individual may experience intimacy while providing understanding, care, and validation, as well as while receiving it. In other words, Partner B’s feelings of intimacy may match Partner A’s, even though A is the one being validated.” (I should note that I have made a similar argument during conversations with a good friend, and that I share the opinion of the authors that this aspect is important as well).
“Nonverbal cues have been thought to contribute to intimacy in two ways. First, they communicate specific emotional messages, which may stand alone or be considered along with concurrent verbal messages. Second, nonverbal cues may intensify emotions that are experienced during intimate interactions […] nonverbal cues can increase the likelihood of an intimate outcome, whereas others may decrease the possibility. Specifically, smiling, eye contact, and physical proximity tend to engross the listener, especially if the behaviors amplify the speaker’s words […] Observational studies have shown that husbands and wives use different nonverbal behaviors when delivering positive and negative messages” [I’ll again remind people reading along here that ‘observational studies’ in this context means studies where they’ve actually observed people interacting with each other, instead of e.g. relying on self-reports].
“Self-disclosures have been classified into two types: factual–descriptive (e.g., personal information, such as the number of one’s siblings) versus emotional–evaluative (e.g., feelings about those siblings […]). Emotional disclosures have been shown to be more important to intimate interactions […] Research has shown that more emotional information is transmitted nonverbally than verbally […] Nonverbal cues are often better indicators of feelings, emotions, and attitudes than are words […] when there is a discrepancy between verbal and nonverbal messages, people tend to believe the nonverbal ones […] There is evidence that nonverbal communication affects the outcomes of a wide variety of relationships. In married couples nonverbal behavior is more likely than verbal behavior to distinguish between distressed and undistressed pairs […]. Poor nonverbal skills have been shown to be associated with less satisfying relationships for married couples […], romantic partners […], roommates […], children’s peer relationships […], and adults in general […] To create intimacy in an interaction, several nonverbal processes must occur. First, the discloser must display appropriate emotional nonverbal cues. Second, the listener must be able to decode them accurately. Third, the listener must then respond with appropriate nonverbal expressiveness. Finally, the original discloser must perceive these expressive cues accurately. In any interaction, this process is repeated continuously, and thus there is substantial room for error. […] A wealth of literature supports the conclusion that nonverbal skills are essential to relationship outcomes. Few studies, however, have focused on issues related to mechanism: How do nonverbal behaviors and skills affect relationship outcomes and processes?”
The next chapter is about ‘Social Networks and Personal Communities’. A few observations from the chapter:
“Generally, there is a shortage of longitudinal material on what might be termed the routine natural history of personal communities – the ways in which different relationships unremarkably alter over time, some becoming more central in people’s lives and others becoming of lesser consequence. Importantly, too, the studies there have been have tended to be short rather than long term. […] [A few exceptions exist, and what] these studies indicate, not surprisingly, is that social change routinely occurs across the life course, affecting people’s social location and in turn the sets of relationships they sustain. Although based on a shorter term study, Morgan and his colleagues […] made the important point that although the personnel making up an individual’s network may alter over time, the properties of the network itself can be more stable. In this study of widows, a core segment of key relationships remained relatively constant over the course of the research, whereas relationships that were more peripheral waxed and waned. Thus, as Morgan, Neal, et al. (1997) expressed it, “the stability of the aggregate properties in personal networks is much greater than the stability of the membership in these networks” (p. 22).”
The next chapter, on ‘Relationships in home and community environments’, is terrible, so I won’t talk about that here. Instead I’ll end the coverage here with some observations from the chapter about ‘Relationships, Culture, and Social Change’:
“There are several theoretical reasons for studying relationships across cultures. First, there may be variation in the relative magnitude of different relationship phenomena. […] Second, culture can have a moderating impact on the association between individual-level factors (such as personality) and various relationship phenomena. […] Finally, even when there are strong universal relational phenomena consistent across cultures, the ways in which these influence actual behaviors may differ. As we note later, individuals may feel passionately for each other in some cultures, but their passion may have relatively little impact on who they end up with as partners. Instead, pragmatic considerations (family pressures, but also basic economic realities) may have a far more significant role in partner choice.”
“In the last 2 decades a number of major international studies have sought to differentiate cultures empirically on the basis of their scores on key values. The most influential of these has been the dimensions that arose from Hofstede’s (1980) seminal study of IBM employees of 50 nations and more than one hundred thousand respondents. In this study, Hofstede (1980) concluded that cultures vary along four dimensions: power distance (deference to authority), masculinity–femininity (relative emphasis on achievement or interpersonal harmony), uncertainty avoidance (stability and “planning ahead”) and individualism–collectivism (which concerns the relationship between the individual and the group). Individualism–collectivism has been the most widely researched of these dimensions”
“Most research into PR assumes that close relationships partners are chosen rather in the manner of an individual shopping in a supermarket, with individuals free to choose from a wide variety of products, in a multiplicity of shapes and sizes, from a range of different origins. […] In reality, this image is unlikely to be accurate even in the most individualistic of societies. Personal reputation, availability of social networks, and even opportunities to travel and shop around are basic limiters of choice in most cultures. However, in some cultures there is little opportunity to form any kind of romantic relationship outside of the most tightly restricted range. Indeed, we can plot a continuum ranging from those cultures in which partner choice is rarely restricted (usually those cultures where mate selection studies are conducted) to those cultures where partner choice might be prescribed as early as birth […]. Across the world, the majority of marriages are by arrangement, usually with the aid of matchmakers or relatives (Ingoldsby, 1995). [I dislike having to rely on a 20-year old study here, but I would caution people who think that just because it’s 20 years old, it’s probably obsolete and the results worthless. For example the relationship between ‘modernization’ and marriage is, complicated – see e.g. this paper (“No empirical support was found for any of our hypotheses which link the level of modernization to the risk of divorce”).] Marriage in such cultures is not regarded as a union of two individuals but of two families, with the families likely to be similar in terms of values, customs, and norms. […] Arranged relationships can be seen as invaluable in cementing family liaisons, helping build new economic ties, and maintaining the influence of the extended network on the new couple. Because such arrangements are of such significance to the wider family, opportunities for Western-style dating and partner choice outside of those approved as eligible is likely to be highly restricted”.
“Because partner choice is restricted among some cultures and cultural groups, the role of love in the choice of marital partner is also likely to vary across the world. There is strong evidence that Western beliefs in the significance of love for marriage may not be universal […]. In cultures where marriages are arranged, love is often assumed to grow out of marriage, rather than to be a motivator for the formation of a particular relationship […] because of the importance to family honor and economic success of an “appropriate” relationship match, in societies where marriage is arranged love is most likely to be sanctioned between only certain partners.”
“In those societies in which arranged marriages dominate, divorce or even separation are often difficult or impossible […]. Although marital dissatisfaction undoubtedly exists here as elsewhere, it is important not to exaggerate the unhappiness felt in many more traditional cultures. Instead, in such societies, different expectations about marriage may lead to different kinds of expectations as to what is – and is not – to be obtained from a marital relationship. […] One enduring debate has been the extent to which free-choice matches are happier than arranged marriages. This is difficult to assess because expectations for marriage differ, and in those societies in which arranged marriages predominate divorce is often difficult. To address this issue Xiaohe and Whyte (1990) tested a representative probability sample of 586 ever-married women in the Sichuan Province of mainland China. Their data suggested that women in arranged marriages were consistently less satisfied than those that had chosen their own partners. Controlling for a large number of measures (including age at marriage and family income), their study did suggest that freedom of mate choice was the strongest predictor of marital quality.”
“There are significant culture differences not only in network size and sources of support but also in network utilization. In the West, individuals are expected to solicit help from others actively […], whereas in Eastern cultures a greater sensitivity to others’ needs and feelings may make help seeking less necessary […]. In collectivists cultures where social connectedness is high, help is expected to be voluntarily provided, and asking for help may be regarded as socially demeaning”.
“Buss, Shackleford, Kirkpatrick, and Larsen (2001) reviewed partner preferences over a more than 50-year period using the same instrument (1939, 1956, 1967, 1977, 1984, and 1996). Over this time period, they found important generational shifts in mate preferences. Both men and women increasingly valued mutual attraction and love, education and intelligence, sociability and good looks, and decreased their stress on refinement, neatness, and chastity. Men increasingly valued similar educational background and good financial prospects and decreasingly valued a woman being a good cook and housekeeper, whereas women placed less value on ambition and industriousness. Partner preferences across genders became generally similar over this time period, with men’s preferences moving toward those of women.”