The Psychology of Lifestyle (I)
“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)”
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