Tuesday 26 May 2020

Is deterioration in adult mental health linked to worsening childhood conditions?

A paper I have recently come across (and tweeted a link to) has showed us that mental health in their early 40s is quite a bit worse among members of the 1970 British Birth Cohort than it was at the same age in the 1958 birth cohort. This was a very welcome analysis. Many years ago, in response to a request from the old Health Education Authority and the Department of Employment (now DWP) our ESRC Resilience Network team set about a similar task in a rather rushed manner and I always wondered about the results.

The DWP was very worried about the large & increasing numbers of young-ish working age people who were on long term sickness benefits because of mental health issues. At a meeting we had agreed this might happen in (at least) 2 ways: 1. young people were arriving at school leaving and labour market entry with a heavier burden of mental health problems in 1986 (when 1970 cohort would be 16) than they did in the mid 1970s; 2. something was different in the lives of early labour market entrants .

I personally was quite sure that changes for the worse in childhood, such as higher levels of divorce and single parenthood, would have produced a less mentally fit cohort of labour market entrants. How wrong I was! To our surprise the data gave absolutely no sign of this. So we went on, in an even greater rush, to have a quick look (using different data from the BHPS youth boost survey) to look for a mismatch between job aspirations before age 16 and destinations at the time when adult mental health was measured. I was sorry to have too little time to go further into this and arguably we should have when we started work as the ESRC International Centre for Life Course Studies (ICLS). But at the time we wrote the research application for ICLS, 2006-7, funders' priorities had shifted away from unemployment & non-employment (don't laugh).

In thsi paper "Psychological distress in mid-life: evidence from the 1958 and 1970 British birth cohorts" Psychological Medicine Volume 47, Issue 2January 2017 , pp. 291-30, Ploubidis et al. take great care to make sure their measures of adult distress are truly comparable between the 2 cohorts. They also did a far more sophisticated analysis, by considering a lot more mediating and confounding factors than we did. But their analysis did not indicate that childhood factors such as parental divorce, maaternal employment or childhood behavioural maladjustment accounted to any large extent for the higher distress scores in the later cohort. They comment:

The 1958 cohort are part of the ‘Lucky Generation’ of post-war baby boomers, who experienced high absolute levels of social mobility, and lower levels of social inequality, whereas the 1970 cohort are part of ‘Generation X’, who have experienced greater uncertainty and insecurity over the whole of their adult lives and a more individualistic ideological climate (Sullivan et al., 2015). If these generational changes lie behind the increase in psychological distress, then we would predict that future generations will be worse off still if such trends were to continue
This is a sobering conclusion. Even more so when one considers that the study participants who suffered the worst from mental distress are likely to be  found among people "sanctioned" by today's workfare policies.

SULLIVAN, A., BROWN, M. & BANN, D. 2015. Guest Editorial: Generation X enters
middle age. Longitudinal and Life Course Studies, 6, 120-130.

Access to the paper:
Printed version, paywalled at

and for free preprint:

Wednesday 26 February 2020

Looking back at The Black Report

The publication of the latest in Michael Marmot's reports on health inequality has aroused the curiosity of people who either don't remember the original Black report on heath inequality published in 1980, or only vaguely remember it.

At the time I was working as a clerical assistant on the British Regional Heart Study (BRHS) (my 1st experience of epidemiology), but also hanging out with various left wing people who were into the politics of health. I had studied for the Bedford College MSc in Medical Sociology between 1971-2 and so had an initiation into the fact that health and life expectancy varied according to social class. It was pretty stunning to think that social inequality could actually influence your chances of a long life. The BRHS also studied some aspects of what would now be called "social determinants of health" although only as a side issue. The main hypothesis of the study was that heart disease had something to do with how hard the water was and the policy implications would be whether measures should be taken to harden water in the areas where water was softest. So social conditions and even behaviours were not the main focus, altough the study did concentrate mainly on health behaviour eventually. But it meant that both friends and colleagues were informed observers of the publication of the Black Report.

The Black Report had been commissioned by a Labour Secretary of State at the Department of Health and Social Security (DHSS) , David Ennals, after he had read an article in New Society by Richard Wilkinson. It happened at the time that the DHSS had become disillusioned with the fact that the Medical Research Council (MRC) spent too much money on obscure diseases and genetics (yes, already) and so removed 30% of the MRC budget to be spent on "cinderella specialties" such as the social factors in health and illness. The rumour was that Sir Douglas Black, a very senior medical figure, had been given the funding for the Black Report to make up for the loss of power of the medical royal colleges over the health budget.

In those days, scientists interestd in health inequality had to contend with 2 major strands of thought whose implications were that it did not exist at all (you might say it was fake news). One of these held that health inequality was a normal part of a kind of Darwinian process of selection: fitter people found themselves in the more advantaged social classes because they were fitter & more intelligent, and it was this fitness that also made them healthier (nowadays we might draw a DAG for this). The 2nd was the "artefact explanation", which held that the appearance of health inequality in the official statistics was due to statistical artefacts which I wont go into unless anyone asks me.

So it was really quite an achievement that the Black Report did result in the widespread acceptance that health inequality was real and had something to do with social conditions (although some health economists continued to argue against this, even to this day). And the explanations that Black et al. accepted were (1) "behavioural cultural", i.e. there was something in the culture of the social groups with worse paid, more arduous jobs that encouraged unhealthy behavour (2) "material" explanations, which focused on the actual biological effects of poverty, poor housing, arduous working conditions and stress.

But I know what many people are interested in is the reception of the Black Report. . It was published soon after the election of a Tory government. Only 260 copies were produced, in a kind of cyclostyled typescript form not even properly printed, released on the Friday before an August Bank Holiday.  It is a huge doorstep of a thing, and those of us who managed to get our hands on a copy still treasure it greatly. There was little fanfare. I don't remember Sir Douglas going on the TV though I hardly watched any in those days. A great account of the emergence of the Black Report can be read in the Introduction to

P Townsend, N Davidson , M Whitehead "Inequalities in Health" (Penguin 1988)

A good summary is:

D Blane "An assessment of the Black Report's 'explanations of health inequality'" Sociology of Health and Illness 1985 7; 3: 423-445.

The subsequent story of the inter relationship between research and policy in this area is documented in :
K Smith "Beyond Evidence Based Policy in Public Health :The Interplay of Ideas" (Palgrave, 2013)

The Black Report itself had a lot more influence on research than on policy. Especailly after it was updated as Margaret Whitehead's "The Health Divide". But unfortunately health inequality then became a kind of bandwagon where anything that seemed to show the importance of health behaviours of or "Selection" got published in high impact journals and other papers showing a bigger influence of material factors, often more methodologically complex due to defensiveness, went unremarked.

Partly as a result of this, all the well meaning hype that followed the Health Divide  and the subsequent Acheson Report just fizzled out into "lifestyle drift", that is, in the end, more preaching to poorer people about their "behaviour".

This was where I started from early this morning, as I noticed (& tweeted) that this time round only a single journalist no one ever heard of had written that the recent plateau in life expectancy (with falls in the poorest women) was due to their fact that they are too fat and in any case live quite long enough. It has become quite unrespectable, both for academics and for informed opinion leaders, to blame health inequality on behaviour. I was impressed by this and thought, well, maybe those of us who have worked on this stuff for the last 40 years didnt totally waste our time.

Friday 17 January 2020

The functionalist theory of health inequality

It took me a long time to realize that the implicit theory underlying a lot of work on health inequality was the classic American idea of Structural-Functionalism, developed by people like Talcott Parsons and Robert Merton. This was dozy of me, as decades ago Gordon Marshall had pointed out that the Registrar-General's Social Class schema used in research on health inequality in UK was based on, as he saw it, outdated functionalist and eugenic notions.
When the national statistics office for England & Wales adopted a new measure of social class for the 2001 Census and all other official statistics from then onward, I did notice that people had trouble using it. There seemed to be a constant attempt to drag the meaning of the measure away from "employment relations and conditions", which was its theoretical basis, back toward something like "manual/ non-manual". I have already written about this all over the place, including in previous blogs. So I won't bind on about it too much more here.

But recent exhaustive international comparative research has given the idea new legs. It turns out that over the last 30-40 years, Italy and Spain have stubbornly retained the smallest differences in mortality and life expectancy between those in the most and the least advantaged social circumstances, whether these were measured by income, education or social class. I well remember the total shock 25 years ago when this was first discovered. Italy & Spain don't have the lowest income inequality for example, or the most egalitarian welfare states. In fact, health inequality in most studies is higher in the egalitarianNordic nations. For many years the standard explanation was that the smoking epidemic was delayed in these Mediterranean nations: smoking was slow to become concentrated among people with lower income and less advantaged occupations.
However, as the years rolled by, it began to seem less likely that the narrower health gaps in the Mediterranean nations could be purely due to smoking. So an alternative explanation began to emerge.
According to this idea, the size of the differences in health & life expectancy between more & less socially advantaged groups might be due to the ways in which their home nations allocate people into these groups. Accroding the the Functionalist theory, societies like the Norway & Sweden are more meritocratic. Education is available to everyone up to an advanced level. This helps to make sure that the fittest & most able people are channeled into those jobs that are most essential for the "functioning" of society, like senior management, judges, military and political leaders.  Regardless of origin family, the fittest and most intelligent people will be channelled through the schools and universities into these important positions. In order to motivate the fittest people to aspire to these destinations, salaries & status are high. As fitness for high position is only partly determined by genetic inheritance from the parents, this process is important to make sure that "good functioning" is ensured. A society cannot just rely on allocating the sons (and it would be sons) of the powerful into powerful positions themselves. There will have to be a turnover such that the less fit sons of more advantaged families in one generation are filtered out by the education system and replaced by the fitter sons of the less advantaged. So the less fit fall down the social ladder and contribute to worse health in the less advantaged social groups, and vice versa. Michael Young wrote about this many decades ago in his book "The Rise of the Meritocracy", depicting an eventual dystopia in which society was divided into extremes of health, intelligence, and income.
There is some evidence in favour of this idea


In addition, there were large increases in health inequality in England and Wales duriing the 1950s-1980s, a time when the numbers of middle class jobs increased enormously, with an associated increase in social mobility (although this mobility took place during the work career, not through the educaiton system). One might argue that the increase in mortality among older working men in unskilled manual jobs (which was the main source of the rising inequality) resulted from an unfit group being left behind.


On the other hand, extensive sociological research has documented a pretty hefty role for the social class, income and education level of the parents in determining those of the children, even after taking coognitive variables ("intelligence") into account. If anything, the expansion of higher education in the UK, for example, has mainly benefited middle class children. Almost 100% of middle class children now go to University and get degrees, which must therefore cover a wide spectrum of the ability range.

So there is a certain amlunt of evidence out there that can be used to test this idea further. But a lot remains to be done.

Wednesday 23 October 2019

Eugenic thinking is not dead if you know where to look

There has recently been a lot of dicussion about the award of a prestigious fellowship at Cambridge University to Dr Noah Carl. I am not at all familiar with Dr Carl's work so not in a position to make any comment at all on whether it give comfort and succour to racists or eugenicists at the expense of scientific accuracy. Agreement broke out, at least on my Twitter time line, that critics have every opportunity to test rigorously his work as he uses openly available data. Which is an excellent argument for open data, but that is another story (see my earlier blog "In God we trust, the rest must bring data").

One direction in which the Twitter exchange led, however, resulted in me feelinig that a lot of sociologits have been leading somewhat sheltered live in terms of their familiarity with the influence of eugenic ideas in neighbouring disciplines. I work with epidemiologists. And the first thing one notices turning back to sociological literature is that no sociologist has used the Registrar General's Social Class schema (RG) for, oh, 30 years at least. Long ago, Gordon Marshall wrote of the "eugenic assumptions" that underlie this classification and I have also written a couple of blogs about this ("What is wrong with "SES""). But in social epidemiology, after a move in a different drection up to about 10 years ago , the use of measures and thinking that is based on the same ideas as the RG classification has come roaring back.

All this has coincided with the rise and rise of genetic epidemiology. Let me give a couple of quotes from recent papers. Here is one from a paper in a high ranked journal called "Intelligence in youth and all-cause-mortality: systematic review with meta-analysis" published in 2011:

"Twin studies to determine the extent to which intelligence shares genetic and environmental causes with health, education, and social class, in predicting mortality, will also help to inform this issue. With evidence of associations between cognitive performance and education showing substantial heritability, it is possible that these variables may share some genetic effects in predicting death."

Perhaps the recent paper that is being most discussed is called “Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals” published in Nature Genetics this year. Here is a quote from its Conclusions

For  research  in  social  science  and  epidemiology,  the polygenic scores that we construct—which explain 11–13% and 7–10% of the variance in educational attainment and cognitive performance, respectively—will prove useful across at least three types of applications. First,  by  examining  associations  between  the  scores  and  high-quality  measures  of  endophenotypes,  researchers  may  be  able  to  disentangle the mechanisms by which genetic factors affect educational attainment and cognitive phenotypes.”

The authors of this study were eager to avoid misinterpretation of their findings. On the website of the Social Science Genetic Consortium https://www.thessgac.org/ (stongly recommended) are a large number of "FAQs" that had been raised about the study, with associated sensible comments for example:

"it is important to keep in mind that the score fails to predict the vast majority (89%) of variation in years of education across individuals. Many of those with low polygenic scores go on to achieve high levels of education, and a large proportion of those with high polygenic scores do not complete college.
Thus, an important message of this paper and our earlier papers is that DNA does not “determine” an individual’s level of education, for multiple reasons: First, it is estimated that, at least in the environments in which we have been measuring it, the additive effects of common genetic variants will only ever predict about 20% of the variance in educational attainment across individuals. Second, today’s polygenic score is only able to predict a little more than half of that 20% (11 percentage points). 

Thus it seemed that “social genetics” (a term I hate) are too fascinating for many researchers to avoid, is being carried out by responsible people. And indeed, the GWAS studies have revealed important differences to the twin studies that have been carried on for many years .

But I guess it was never going to stop there. And in the last week or so a new paper has appeared: Genetic consequences of social stratification in Great Britain by Abdel Abdellaoui and colleagues, available at http://dx.doi.org/10.1101/457515 . In their words:
We show that the geographic clustering of genome-wide trait-associated alleles is related to recent geographic movement of people and that the resulting regional genetic patterns are associated with regional socioeconomic and cultural outcomes...... The strongest clustering was observed for Educational Attainment (EA). Among the rest of the geographically clustered traits are body dimensions, personality dimensions, and physical and mental health traits. ... Our results show that people with a genetic predisposition for higher cognitive abilities are leaving these (deprived) regions, likely attracted by better educational or occupational opportunities in other regions. In fact, the people who were born in coal mining areas and migrated to better neighbourhoods have higher average EA polygenic scores than people born outside of these regions. The regional clustering of cognitive abilities that follows may further affect the economic development of neighbourhoods.

The authors do go on to speculate that social policies might need to be devised to lower the tendency of geographical mobility to increase differences in deprivation between areas. If those with higher genetic scores for educational attainment did not have to travel to more prosperous areas in order to get better jobs and increase their income, the argument goes, this might slow down the tendency of health inequalities between areas to widen over time.

A clearly written cautionary commentary has also appeared in Nature at https://www.nature.com/articles/d41586-019-03171-6
But it is hard to escape the impression of an element of dog-whistling in this literature. At the very least, sociologists need to be on their toes in respect of it.

Monday 21 October 2019

An interesting papear has recenty appeared in the Journal of Epidemology and Community Health by Murray et al, entitled  Inequalities in time from stopping paid work to death: findings from the ONS Longitudinal Study, 2001 to 2011

open access version at  https://discovery.ucl.ac.uk/id/eprint/10082463/1/Murray%2020190821_JECH_R2_manuscript_CLEAN%20copy.pdf

At first sight it might appear puzzling that the bottom line of the paper is that people who had worked in less advantaged, lower skilled & lower status jobs (defined by the Registrar General's class schema, which is conceptually based on skills and status) actually lived longer after leaving the labour force than those whose jobs were of higher skill and status. To cite the paper itself:

"LS members who had worked in lower social classes lived a greater number of years after they stopped work, with more time per decreasing social class."

How to make sense of this? Actually, a similar issue was also a big puzzle for the authors of the first book that decribed the contribution of the LS to the study of health inequality. To the amazement of almost everyone involved, the earliest analysis showed no social class gradient in health, or even a hint of a reverse gradient. Did this mean that all the previous research on social class differences in health including those in the Black Report, had been biased by either artefact or selection?

And what does this have to do with Murray et al.'s paper?

To cut a long story short, it turned out that high status, high skilled jobs also benefit from less arduous working conditions. Just think about the difference between a building worker and a university lecturer. Lets say both of them start to get angina pectoris. The lecturer, first of all, will probably not be affected by narowing of her coronary arteries as soon because she does not need to do much heavy lifting, digging, or other activities that equire increaed cardiac output. And when she does start to notice, it is not too hard to keep her job if she also needs to do less of these kinds of things (moving furniture, lifting large piles of books or files...).  By the time she even notices that her cardiovascular function is declining, let alone has to give up her job, her disease is far more advanced. Contrast to the building worker whose daily work activities will cause pain earlier in the natural history of the disease, and incapacitate her (or him) more quickly. Let's say the disease process is exactly the same in them both. The building worker will not die sooner than the lecturer but will have had to give up work earlier.

In other words, it is not that the people in the less skilled, lower status jobs died later, but that they had to give up work earlier in the disease process.

This phenomenon eventually resulted in a convention when analyzing social class differences in health in longitudinal follow up such as that in the LS, to allow several years to pass to "allow selection to wear off" before comparing the death rates in the different classes. After the 1st 5 years, the sicker people in the more advantaged social positions died and the social class inequalities in mortality risk re-appeared. All subsequent papers using the LS have used this adjustment, but often explain it in a rather abbreviated way (let me know if anyone wants references). With this adjustment, the class differences in mortality look about the same as in the previous, cross sectional ("unlinked") studies from 1951 onwards.

These comments are no criticism of the JECH paper, whose objectives were to show that extending the pension age is less fair to people in more advantaged social classes. But it does show the dangers in assuming that the nominal definitions of social position need to be taken with care. The social forces at work here are not derived from status or skills but from working conditions, which, while collinear to each other, do not measure the same thing.

Monday 19 March 2018

Understanding the research-policy relationship: the role of "technical interests"

In their excellent LSE Impact blog, on the relationship between research and policy

 Christina Boswell & Kat Smith talk about "mutual constitution" of the 2 spheres. This is a huge step forward in the present understanding.

Many years ago, in a differently labelled social-scientific enterprise, scholars proposed the notion of "partisan mutual adjustment" as a guide to understanding this relationship. That was why the title of my book on thetopic was "Authorities and Partisans". The findings of the project that gave rise to the book were totally at odds with any of my hypotheses. Scientists (the "Authorities") often behaved like partisans and participants in policy debate played a very important role in the consititution of knoowledge claims as facts. As Boswell & Smith point out, this kind of thinking can help us to a much more sophisticated understanding of  a present day obsession: "Impact". It is in fact rather coounter producitve to work with an image of science as a hammer having "impact" on policy in any simple way.

There was in my opinion one element left out from the blog, however. Of course there is not space to go through everything in a short article. But I am gonig to try & fill this out, using a lot of extracts from my paper "Do we need a Strong Programme in Medical Sociology" I wont give the URL because it is still paywalled about 100 years after it was published. Oe reason I want to do this is that since both my research and even Kat's great PhD work was done, genetic research has risen to much greater prominance and I believe that "technical interests" are very much in play here. For example, there are no clear policy implications to, for example, finding such as educational attainment being partly due to a bunch of genes. In general, genetic research has little potential for impact and yet it received massive funding and gets published in the highest impact (i  the other sense) journals. Interestingly, private biotech companies have been withdrawing fundinig from genetic research as they realise how ittle infleunce genes actually have on health conditions. This leaves, of course, the massive ideological  benefiit of allowing governments to cut back on (obviously) educational spending, or indeed to implement policies that discourage childbearing in poorer people. I dont want to play this down at all. But the "technical interest", that centres on those who build the large expensive machinery needed to sequence genes and those who develop methods to make sense of the resulting data, are aso I think very important and somewhat neglected.

By technical interest is meant the interest of occupational subgroups in creating a continuing market for the specific techniques and forms of expertise of which they can claim 'ownership'. For example, experts in the anatomy of plants were threatened, as Nicolson (1984; 1989) has shown, by a move towards the use of plant ecology as the most important form of classifying plants and understanding soil fertility. Another example, not yet studied systematically"*, might be drawn from the recent history of reproductive technology. Obstetrics has faced some degree of crisis due to the compression of childbearing into women's healthiest years. The resulting decline in the amount of medical intervention required is arguably one reason for the rapid growth of interest in infertility. Although far fewer women are affected, those who see their infertility as a problem that doctors can solve require a great deal of medical intervention over an extended period of time.

The model for studying how the production of scientific knowledge is influenced by technical interests is one which regards scientists as actively 'doing interest-work', that is, mobilising a variety of other social groups (and being mobilised by them). These processes of enrolment and alliance profoundly influence the knowledge claims made by scientists. Some of these claims go on to become facts.

In his work on biometrics, Mackenzie (1981)  compares biometry in the early 1900s to a new political party which has to build its network of supporters and gain resources for its tasks. In order to do this, biometry, or any other new and/ or struggling discipline, must demonstrate the utility of its ideas and measures to more powerful interest-groups and/or groups or individuals with command of resources. Accordingly, biometry linked itself to the Eugenics movement, as Mackenzie shows.

 A scientific team quite often finds itself in the position of having a solution to a problem no one has, or a product with no market. So as well as translating their products to fit the interests of powerful groups, scientists may work at translating the goals of these groups to fit better with what the scientists have on offer. 'If you give greater priority to this issue' a group of scientists may argue with a struggling sub-profession (for example a medical sub-specialty), 'we have a hot new technique (or machine) which will enable your weak, low-status segment of the profession of medicine to gain far more influence and status.' In such cases it is not only a case of selling one's idea or device as better suited to existing purposes of other groups, but of persuading other groups that they have interests they didn't even know about before. 

Aronson (1982) gives an excellent example of scientists being enrolled by other interest groups and the resultant shaping of knowledge claims in her study of nutrition science in the 1870s and 1880s in the United States. At this time: liberal economists and statisticians hoped to end class conflict by developing objective criteria of the adequacy of wages At the same time, the young discipline of nutrition science was struggling to establish its credentials as a respectable science worthy of funded teaching and research posts in US universities. The upshot of the negotiations between interested groups was that: the alliance between nutrition science and labour statistics gave birth to the definition of nutrition as a "social problem" inextricably tied to labour reform. Accordingly, the first dietary survey conducted in the USA, in 1885, concluded that: 

"existing wages would be adequate if workers learned to eat scientifically" 

Thus the leading exponent of the new science, Atwater, could claim that nutrition: 

"could solve the labour problem . . . within the existing class structure and without decreasing the profits of capital and therefore deserved public support."

Atwater correctly interpreted the interests of various powerful groups involved in both the policy debate on 'the labour problem', the debate on nutritional requirements, and the debate on the status of nutrition as an academic discipline. 

These are just a few examples of the wide range of "technical" and "professional interests" that have linked scientists and political interest groups

Aronson, N. (1982) Nutrition as a social problem: a case study of entrepreneurial

strategy in science. Social Problems, 29, 474-487.

Mackenzie. D. (1981) Statistics in Britain 1865-1930: The Social Construction of

Scientific Knowledge. Edinburgh University Press.

Nicolson. M. (1984) The Development of Plant Ecology. 1790-1960. Unpublished
Ph.D. Thesis, University of Edinburgh.

Nicolson. M. (1989) National styles, divergent classifications: a history of French and
American plant ecology, in L. Hargen. R. A. Jones. A. Pickering (eds.).

Knowledge an

Tuesday 24 October 2017

What have political interference in research & Harvey Weinstein got in common (updated)

I don't suppose anyone will have trouble guessing the answer: neither the existence of sex pests in show business (for heavens sake) nor the existence of political considerations in academic work are anything new.

In the case of abuse in show business, what has changed is the awareness of it as a problem that should not be tolerated. This is a big step forward. Universities, it also turns out, are far from innoocent in this respect. Some senior academics have this weird mixture of power and charisma based on their knowledge and communication skill. In medicine, this "transference" problem is so well known that there are severe sanctions for taking sexual advantage of patients. Even if it might seem like something consensual, the power imbalance makes it abusive. In academe, however, sleeping with your  students seems to be more accepted. At least there is no strict code of ethics, or wasnt the last time I looked. A BSA working group on this issue, 20 or so years ago now, decided not to develop such a code, to the dismay of someone I know with training in medicine who was a member of the working group. This is not to say we thought a lecturer should never develop an emotional relationship with a student, only that it must no take place at the same time as the power relationship of teacher-student. As another friend once said of an academic we both knew "Lets face it dear, if he was the window cleaner you wouldn't look twice".

In the case of academic work, it is to be greatly welcomed that we now have things like "Retraction Watch" working to expose misconduct. And that people are speaking up more about harassment of all kinds. I think this is a similar develoment. It comes at a time when the incentives for misconduct are massively inceasing, but I have remarked on Twitter that it is nothing completely new. So here are some stories about the way things have been over the last 30 years of my career.

In the 1980s there was a lively debate on whether or not unemployment (during the Thatcher recession) was harmful to health. Could it be that sicker or less "fit" people were more likely to become and remain unemployed? Any apparent association between the two wold then be "confounded" by pre-existing poor health. A series of 3 studies seemed to show that this was not true, that unemployment itself was harmful.  There were not many holds barred in this competition between what you might say were more versus less politically sophisticated groups and individuals. I was told during this time that one way an academic could get research money was to say "Dear Minister, we can prove that unemployment does not cause ill health or mortality". Other people admitted to having taken up the topic because it made it easier to get published. The topic was a bandwagon. There is more detail on this story in my book "Authorities and Partisans". But the denoument was remarkable: an MRC programme grant that had produced some of these findings was cut from 5 years to 2. That had never happened before and I don't think it ever happened again. This was in 1987.

Most people may not remember that Thatcher commissioned a review of the (then ) Social Science Research Council. The result was a change in title of the UKs major social science funding body to "Economic and Social Research Council" (the ESRC of today). In this way the title of the funding did not contain the word "Science". Political interference? Naaahhh.

Some colleagues set out to try & make me understand that a lot of interference in research was not "Political", it was small-p stuff that was done by  those who sat on powerful funding bodies. There were funding bodies, and indeed, journals, that one just did not bother with during the incumbency of certain people on their governing board or editoria committees, because you knew it would be a waste of time. A Scottish Office civil servant admitted duriing a seminar I attended that during the Thatcher years there were some eminent Profs who just would never be granted funding from government sources. But other eminent figures would vote down research projects or papers because their own results might be threatened, which had nothing to do with Politics.

When I applied for money to do my own first project on unemployment & health, I had come to a more subtle understanding of this kind of thing. I included a good-ish chunk of text about how, now that we had longitudinal data, we could investigate more closely the selection processes that might produce the appearance of poor health among the unemployed (sicker people being "selected" for unemployment). We knew the health status of participants in these studies from birth, and we knew their hisotires of employment and unemployment. But silly me! I had not anicipated that there would be assessors of the proposal who were very much outside this ideological camp. One fair minded senior colleague, who was asked to be a referee on the proposal, was a little shocked at my approach (he had supervised my PhD, I was mortified). But being fair minded, he did not turn it down. This was around 1993. We got all our papers published, which began to show that the association between unemployment and health needs to be seen not as "either selection or causation" but rather that many unemployed people had had previously more adverse life courses, which could increase their propensity to both illness and unemployment. This work met with very little response, either hostile or friendly. At that time (mid 1990s) Cox regression with time  varying co-ordinates was a bit heavy going for the average reader . More important perhaps was that there was a change of government in 1997. When, during the mid 2000s, I went to present some of the results at the Social Exclusion Unit I was asked why all our models adjusted for the height of the parents. I explained this was the only way we had to control for any genetic influences on who became unemployed. The politicans present, to their everlasting credit, were absolutely horrifed at the notion anyone would think unemployment was genetic. I do wonder if members of the present government would have the same reaction.

Which brings me to the last story I have energy to talk about today. I am privileged to be involved in a large EU funded project on health inequality during the life course . One of the "work packages" concerns policy implications and policy impact. So the project leader, a distinguished public health academic, who also knows a lot about "omics" (genomics, proteoics etc), invited a participant from a very well known health policy institute to help the project with policy impact. At our last meeting our policy expert was critical of the little genetic work that had yet been done (it will be, it just takes awhile) and of the strong social justice theme in the project overall. "All the policy makers want to hear is about genetic influences" we were told. This story illustrates the importance that has to be given to things like a totally oversimplified view of genetics now in the age of Impact. Admittedly 20 years ago we had to show we had "taken account " of genetic influences in order to get past referees, but our Unemployment & Health project was not assessed on Impact .It got the highest possible grade in the assessment of its Final Report to the ESRC, which it would not today because we were pretty conservative in drawing media attention to it. And what will happen to the EU projects Impact when it does publish results of proper genetic research on health inequality, which will show miniscule influences? We shall see.

Oh, yes, cant resist one last tale. Around 1997, someone I had worked with for years was a speaker at a workshop in Manchester on Health Inequality, to talk about the genetics of health inequality. I had been invited to this but didn't feel like going to Manchester (tilting trains make me sick). So I phoned my long term colleague to ask if he would like me to turn up & give some moral support. "You misunderstand" he responded "I am talking in favour of a genetic effect". I was stunned. "If I get an OR of 1.4 for some social determinant" he explained" I only get that paper in JECH. If I get that same result for a gene, I get it in Nature". Go figure.