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BMJ Open
The association between childhood cognitive ability and
adult long term sickness absence in 3 British birth cohorts
Journal:
BMJ Open
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Manuscript ID:
Article Type:
Date Submitted by the Author:
Complete List of Authors:
bmjopen-2011-000777
Research
20-Dec-2011
<b>Primary Subject
Heading</b>:
Keywords:
Occupational and environmental medicine
Public health, Epidemiology
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Secondary Subject Heading:
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HENDERSON, MAX; INSTITUTE OF PSYCHIATRY, KINGS COLLEGE
LONDON, PSYCHOLOGICAL MEDICINE
Richards, Marcus; MRC Unit for Lifelong Health and Aging,
Stansfeld, Stephen; Barts and the London, Queen Marys School of Medicine
and Dentistry, Neurology
Hotopf, Matthew; King's College London (Institute of Psychiatry),
OCCUPATIONAL & INDUSTRIAL MEDICINE, EPIDEMIOLOGY, PUBLIC
HEALTH
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Page 1 of 28
The association between childhood cognitive ability and adult long term sickness absence in 3 British
birth cohorts
Dr Max Henderson *
Senior Lecturer in Epidemiological & Occupational Psychiatry
Institute of Psychiatry, Kings College London
Department of Psychological Medicine
Weston Education Centre, Cutcombe Road
London SE5 9RJ
UK
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Professor Marcus Richards
Programme Leader
MRC Unit for Lifelong Health and Aging
33 Bedford Place
London WC1B 5JU
UK
Professor Stephen Stansfeld
Professor of Psychiatry
Centre for Psychiatry
Wolfson Institute for Preventive Medicine
Barts and the London School of Medicine and Dentistry
London EC1M 6BQ
UK
020 3228 8564
F:
020 7848 5408
E:
[email protected]
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* corresponding author
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Professor Matthew Hotopf
Professor of General Hospital Psychiatry
Institute of Psychiatry, Kings College London
Department of Psychological Medicine
Weston Education Centre, Cutcombe Road
London SE5 9RJ
UK
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BMJ Open
ABSTRACT
Objectives
We aimed to test the relationship between childhood cognitive function and long term sick leave in
adult life, and to examine whether any relationship was mediated by educational attainment, adult
social class or adult mental ill health.
Design, setting, and participants
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We used data from the 1946, 1958 and 1970 British birth cohorts. We examined the association
between cognitive function assessed at age 10/11 with long term sick leave at age 53, 42 and 34
respectively.
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Results
After adjusting for sex and parental social class lower cognitive function was associated with greater
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odds of being long term sick in all three cohorts with evidence of a dose-response effect. Educational
attainment appeared to partly mediate the associations in all cohorts; adult social class appeared to
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have a mediating role in the 1946 cohort. Adjusting for depression had little effect.
Conclusions
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Long term sick leave is a complex outcome with many risk factors beyond health. Cognitive abilities
might impact on the way individuals are able to develop strategies to maintain their employment or
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rapidly find new employment when faced with a range of difficulties. Education should form part of
the policy response to long term sick leave such that young people are better equipped with skills
needed in a flexible labour market.
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(word count = 211)
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SUMMARY
ARTICLE FOCUS
[1] The association between disease severity and long term sick leave is weak; individual risk factors
including those identifiable before starting work are under-researched
[2] Lower IQ may be one such risk factor and we used data from the 3 British birth cohorts now if
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working age to look at the association between cognitive ability in childhood and long term sick leave
in adult life
[3] We also looked at the extent to which any such association could be mediated by educational
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attainment, adult social class, or adult mental ill health
KEY MESSAGES
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[1] After adjusting for sex and parental social class lower cognitive function was associated with
greater odds of being long term sick in all three cohorts (OR= approx 2 in all 3 cohorts, with clear
dose:response effect)
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[2] Educational attainment appeared to partly mediate the associations in all cohorts
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[3] The effect of lower cognitive ability is independent of mental ill health and adult social class
STRENGTHS & LIMITATIONS
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Strengths
[1] We have used data from 3 well established birth cohorts and used imputation to deal with missing
data
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[2] our data includes those born in the 40s, 50s and 70s who were in their 50s, 40s and 30s at the point
the outcome was measured - our results transcend age and period effects
Weaknesses
[1] There is likely to be some effect from residual confounding from unmeasured variables acting in
early life which might influence both childhood cognitive ability and adult ill-health.
[2] the outcome was assessed by receipt of incapacity benefit in the '58 and '70 cohorts but a different
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measure in the '46. different measures of depression are available in each cohort
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BACKGROUND
In the UK over 2.5 million people are in receipt of Incapacity Benefit (IB), most often paid to those
off work for more than 6 months due to ill health 1. The cost to the economy from reduced tax
revenues and payment of benefits is in excess of £50 billion per year2. Reducing long term sick leave
is thus high on the agenda for policy makers3 4. Long term sick leave increases poverty in the sick, and
is associated with premature mortality5-7 . At the individual level long term sick leave means a loss of
income and dignity, and with this a reduced opportunity for social participation2. 50% of those in
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receipt of IB have been claiming for more than 5 years, and those claiming for 2 years are more likely
to die or retire than get another job 8. Long term sick leave increases and sustains poverty and social
disadvantage.
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Mental and musculoskeletal disorders are the most common reasons to be awarded IB2 9 10. Much of
the policy response to sickness absence has focussed on reducing occupational risk factors for these
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disorders. However there is a disconnect between the increase in incapacity benefit certifications and
the distribution of risk factors in the workplace. Musculoskeletal disorders rose at a time when the
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physical demands of work decreased11, and workplaces became increasingly safe12. Similarly the
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increase in IB awards due to psychiatric disorders was not associated with a concomitant rise in the
prevalence of these disorders within the working age population. Further, the relationship between
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health and occupational function is unclear - whilst there are 2.5 million people in the UK on IB, over
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3 million people with a range of disabilities manage to remain in paid work 13.
Relatively few studies have examined individual, as opposed to occupational, risk factors for long
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term sick leave14. Some difficulties apparent in childhood are associated: data from the Aberdeen
Children of the Nineteen Fifties Cohort 15 indicated that emotional or behavioural difficulties were
associated with being permanently sick or disabled nearly 40 years later. Similar findings have been
shown for adolescent mental disorders in a Swedish cohort16. Another early risk factor might be
cognitive ability: the Aberdeen study indicated that low cognitive ability independently predicted
being permanently sick or disabled in adult life. Work by Gravseth found that low birth weight and a
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failure to complete secondary education predicted the award of a disability pension in a cohort of
Norwegians born between 1967 and 1976 17 . The same author has shown that lower intellectual
performance at age 18 or 19, and educational attainment at age 23 were each independently associated
with the award of a disability pension to Norwegian men between the ages of 24 and 36 18.
Low IQ might explain the association of both childhood behavioural problems and poor educational
attainment with long term sickness absence in adult life. If this were the case, a response at policy
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level which emphasised the attributed health reasons for long term sick leave and responded by trying
to improve the health “offer” to this group may be less than successful. By contrast one that looked
beyond a diagnostic label and emphasised skills and training, especially tailored to the needs of the
least cognitively able, might produce better results.
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We tested the hypothesis that lower cognitive ability is a risk factor for long term sickness absence in
three British birth cohorts. We further aimed to determine whether such an association is mediated by
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educational attainment, adult social class, or adult mental health.
METHODS
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We used data from the 3 British birth cohorts whose participants are now working age 19.
The National Survey of Health and Development
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The 1946 National Survey of Health and Development (NSHD) obtained information on all singleton
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births to married women in England Scotland and Wales in a single week in March 1946 20. An initial
sample of 5362 were then followed up, comprising all those with fathers in non-manual and
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agricultural employment and a 1:4 sample of those with fathers in manual employment. The cohort is
described in detail elsewhere20. In 1999, 3760 of the 5362 were alive, living in the UK and were not
permanent refusals. Of these 3035 (81%) provided data to the study. This group (weighted to adjust
for the sampling procedure) are broadly representative of the population born in 1946 in the UK,
although there was over-representation among non-responders of the never married and the least
advantaged in terms of cognitive ability, educational attainment, and social class21.
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The National Child Development Study
The 1958 National Childhood Development Study (NCDS) included all surviving children born in
England Scotland and Wales in a single week in March 1958. During follow-up ‘sweeps’ immigrant
children who would have been part of the study had they been born in the UK were added. The cohort
is described in detail elsewhere 22. In 2000, 16147 were still eligible to take part and 11419 (71%)
contributed data.
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The British Cohort Study
The 1970 British Cohort Study (BCS) included all live births in one week in April 1970 in the whole
United Kingdom. Children born in Northern Ireland were subsequently dropped from follow-up. The
cohort is described in detail elsewhere 23. In 2004, excluding those who had died, emigrated, been
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born in Northern Ireland or were permanent refusals 16875 were eligible to take part of whom 9656
(59%) contributed data.
Outcome
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In all cohorts data on the outcome, long term sick leave, were extracted from the most recent dataset
at the time the present project began: for the 1946 cohort this was in 1999 when participants were
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aged 53 years; for the 1958 cohort in 2000, when participants were aged 42, and in the 1970 cohort in
2004, when participants were aged 34.
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In both the 1958 and 1970 cohort, participants were asked if they were in receipt of any benefit
payments. Individuals reporting receipt of Incapacity Benefit (IB) or Severe Disablement Allowance
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were identified as being on long term sick leave. Typically these participants were off work for health
reasons for more than 6 months. Data on benefit receipt were not available for the 1946 birth cohort in
1999. Instead participants were asked (yes/no) if they were in a job. Those who responded ‘No’ were
asked (yes/no) if they were looking for work. Those who also replied ‘No’ to this question were asked
why and asked to select a response from 6 options, one of which was “Permanently sick or disabled”.
Individuals reporting this option as the reason they were not looking for work were identified as being
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on long term sick leave. We have previously described research using this category in the Aberdeen
Children of the Nineteen Fifties cohort 15.
Exposures of interest
The 1946 and 1958 cohorts contain data on participants’ cognitive ability at age 11; the 1970 cohort
has a measure at age 10. 1946 cohort members were tested at age 11 on verbal and non-verbal
intelligence, arithmetic, word pronunciation, and vocabulary. Scores were summed to represent
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overall cognitive ability. The cognitive ability of the 1958 cohort members was assessed using the
General Ability Test 24. 1970 cohort members completed a modified version of the British Ability
Scales (BAS) 25. A principal components analysis was performed on the four subscales of the BAS
and the first factor was taken as a general measure of cognitive ability 26. For all cohorts cognitive
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ability scores were divided into quartiles and the first (lowest cognitive ability) used as the reference
group.
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In all three cohorts occupation of the father at the time of the participants’ birth was coded according
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to the Registrar General’s classification. For these analyses social class was categorised as Class I/II,
Class III (non-manual and manual) and Class IV/V. Participants were asked about their current or
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most recent job, and these were similarly coded. Common mental disorders are the most common
reason for sick leave9. All cohorts contained a measure of depression or psychological distress. 1946
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cohort members were administered the Present state Examination 27 at age 36 years, and depression in
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the preceding year was derived from the CATEGO algorithm 27. 1958 cohort members were
administered the Malaise Inventory 28in 1991. Those scoring 8/24 or more were identified as ‘cases’
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of depression 29. 1970 cohort members were administered the 12-item General Health Questionnaire 30
in 2000. Participants scoring 4 or more were identified as cases of psychological distress/depression
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The highest level of educational qualification was available in the 1946, 1958 and 1970 cohorts at
ages 26, 33 and 26 years, respectively. All 3 cohorts categorised this information differently and thus
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all data were re-coded into degree; A level or equivalent; O level or equivalent; CSE grade 2-5; no
qualifications.
Risk set
At any time-point the workless population is a heterogeneous one, comprising individuals on shortterm sick leave, individuals on long-term sick leave and some individuals who, for whatever reason,
have never worked. Many of this latter group will have substantial health difficulties such as severe
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physical disabilities or learning disabilities. Our outcome was long term sick leave, and therefore in
all 3 cohorts analyses were restricted to those participants who described themselves as either in
employment or full-time education, or caring for a family in the sweep immediately prior to that from
which the outcome was derived.
Statistical Analyses
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All data were analysed using STATA version 9.2 32. As with all longitudinal studies, partial data
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collection and loss to follow-up meant that there were incomplete data on participants in all 3 cohorts.
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To minimise the impact of missing data multiple imputation using chained equations (ICE) 33was
carried out 32. All variables were included in the imputation model 34. 10 iterations were completed.
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The MICOMBINE function was used to calculate average regression estimates across the 10 imputed
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datasets.
For each cohort the prevalence of each of the exposures of interest was calculated. The unadjusted
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association between childhood cognitive ability and long term sickness absence was estimated and
shown as odds ratios (OR), with 95% confidence intervals, for each of the four quartiles of childhood
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cognition compared to the reference, and for the overall trend. These were then adjusted for the
potential confounders of sex and social class at birth. Finally, to examine the potential mediating
effects of covariables measured in adult life, adult social class, educational attainment and history of
recent depression or psychological distress were each added to the model.
RESULTS
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In 1999 2894 members of the 1946 cohort were eligible for this study, of whom 159 (5.5%) reported
themselves as permanently sick or disabled. In 2000 there were 15 053 eligible members of the 1958
cohort, of whom 431(2.9%) were in receipt of long term sickness benefits. In 2004 there were 14 713
eligible members of the 1970 cohort, of whom 153 (1.04%) were in receipt of long term sickness
benefits. The distribution of the covariables in each of the birth cohorts is shown in table 1.
[Table 1 about here].
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The associations between childhood cognitive ability and long term sickness absence, adjusted for the
covariables are shown in Table 2. This shows that for each cohort there is a strong impact of cognitive
ability measured in childhood on the outcome several decades later. The top quartile showed between
one quart and one half the odds of long term sickness absence depending upon the cohort studied. The
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effect was present after adjusting for sex and paternal social class (model 2). When potential
mediating variables were added, effects were reduced. Adding social class in adulthood diminished
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effect sizes, particularly in the 1946 birth cohort. The overall impact of cognition on the outcome was
statistically significant in two of the three cohorts. Adjusting for educational attainment also led to a
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reduction in effect sizes, with one cohort (the 1958) showing a significant trend of cognition on the
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outcome, whereas the others showed a marginally statistically significant effect, although the ORs for
the lowest quartile were still of the order of two. Adjusting for prior mental disorder had little impact,
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with all three of the cohorts showing an independent effect of cognition on long term sickness
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absence. Finally, a full model controlling for all covariates simultaneously, showed a reduction in the
effect of cognition on long term sickness, with one of the three cohorts (1958) remaining significant.
[Table 2 about here]
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DISCUSSION
Summary of findings
We examined associations between cognitive ability measured in childhood and long term sickness
absence in adult life across three British birth cohorts. In all three cohorts the effects after adjustment
for sex and social class at birth were similar, and all three demonstrated a clear dose-response effect
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whereby lower childhood cognitive ability was more strongly associated with long-term sick leave. In
each cohort there was little attenuation when previous history of depression was included. There was
some attenuation of the effect when adult social class and, particularly, educational attainment was
included, and this attenuation was greater for those of lower cognitive ability. This suggests that some
of the effect of lower cognitive ability is mediated by educational attainment. For example low
educational attainment might lead to more insecure jobs or more manual jobs that could be more
difficult to sustain in the context of disability. However educational attainment does not fully explain
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the association.
Strengths and weaknesses
Strengths of this study include the use of data from three British cohorts across half a century, with
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outcome data from both early (age 34) and late career (age 53), thus these results seem to transcend
period effects. These cohorts are broadly representative of the population born in UK in the years of
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their inception. Those relatively disadvantaged were more likely to be under-represented, but we
have no reason to believe that this would have altered the pattern of results reported here. Exposures
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were measured long before the outcomes occurred, and cognitive ability was assessed using well
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recognised tools. Exposures in adult life were assessed independently of the research question,
limiting the impact of reporting bias.
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Weaknesses include the different assessment tools used to measure childhood cognitive ability in each
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cohort which raises questions of comparability of results between cohorts. Paternal social class at
birth was assessed by asking the participant’s mother. There is likely to be a degree of
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misclassification here, most notable in the 1946 cohort as many fathers were just returning from the
war. We believe any such misclassification is likely to be random. Although the associations between
lower cognitive ability and long term sick leave remain after adjustment for parental social class we
are mindful of the possibility of residual confounding from unmeasured variables acting in early life
which might influence both childhood cognitive ability and adult ill-health. Depression or
psychological distress was measured using different self-report tools in all three cohorts. Only recent
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difficulties were asked for and as with all cohort studies the data are silent as to what happens
between ‘sweeps’. A more robust measure of depression which identified episodes of illness between
sweeps would have been preferable.
There is no accepted definition of long term sick leave. Although available in the 1958 and 1970
cohorts, receipt of Incapacity Benefit was not available in the 1946 cohort and this is a limitation.
Nonetheless we believe the population captured under the heading “permanently sick or disabled” at
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age 53 to be very similar to those indentified as being in receipt of IB. Most IB recipients have been
away from work for over 6 months. There are other routes in to incapacity benefit but the median time
spent on IB is 5 years and the advantages of using this outweigh any limitations. The population we
have studied represents the persistent and severe long term absentees. IB receipt is a binary question,
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asked relatively context free and this will minimise any recall, reporting or observer bias, and any
misclassification is likely to be random. Furthermore we believe our findings have greater salience for
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policy makers as notwithstanding the introduction of Employment and Support Allowance they can be
mapped straight onto the existing UK benefits framework.
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The effect sizes we have demonstrated are noticeably similar between the cohorts despite the
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differences in the cohorts and the methods used to assess cognitive ability. The impact of cognitive
ability on later long term sickness absence attained conventional statistical significance in all three
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cohorts though most strongly for the 1958 cohort. The higher P value in the 1946 cohorts reflects the
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smaller size of the cohort (less than half that of the other two). In the 1970 cohort the outcome was
rare (1%) and hence statistical power was greatest in the 1958 cohort. Our results cannot be accounted
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for by the people with very low cognitive ability never entering the labour force as we restricted our
analyses to only those were either working or fulfilling other social roles (caring for a family or
studying) at the previous sweep.
There are no data on the cognitive abilities of people claiming Incapacity Benefit. Our study shows
that the bottom two quartiles of cognitive ability are responsible for a considerable proportion of the
IB recipient population. We present regression models showing the impact of controlling for a
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number of variables on these associations. It is worth noting that we do not consider these factors
predominantly as confounders – in other words, although the association between cognition is
attenuated and becomes non-significant in two of the three cohorts when educational attainment, adult
social class, and depression are controlled, this does not indicate that the univariate association
between cognition and long term sickness absence is merely a result of confounding. Rather, we
consider it probable that these variables are mediators of the association. Thus the association
between lower cognitive status and long term sickness absence is in part explained by a pathway via
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educational attainment and adult social class.
There is an extensive literature on the health implications of low cognitive ability35-37. However we
think it unlikely that the association we gave described between low cognitive ability in childhood and
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adult occupational outcomes is simply because these individuals are more likely to become unwell.
First, we have deliberately not attempted to ascertain the clinical labels as to why an individual is in
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receipt of IB – the effect of cognitive ability is substantial enough to be observed at cohort level.
Second, the very limited attenuating effect of depression in all three cohorts suggests that the
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mechanism behind this association is largely independent of mental health, the most common reason
for long term sick leave. This is also suggested by the consistency of results across the three cohorts
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as the health difficulties suffered by those in their thirties are likely to be different to those suffered by
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people in their fifties. Last, whilst previous work on the 1946 cohort38, replicating work on the 1958
and 1970 cohorts26 39-41, has shown an association between cognitive ability and adult chronic physical
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diseases, these associations were mediated by education and to a lesser degree socioeconomic status,
both of which are included in our analyses.
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In trying to understand how childhood cognitive function affects adult occupational function it is
important to recognise that long term sick leave is the result of a process rather than an event10. These
data are unable to tell us if lower cognitive ability makes it more likely that an individual with a
particular disorder or set of symptoms is more likely to go off work sick, or less able to get
appropriate support when they are ill, or find it more difficult to negotiate a successful return to work
after a period of ill health. Cognitive ability might impact on any or all of these, possibly in “soft”
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BMJ Open
ways such as by directing responses to illness or by facilitating the recruitment of support from health
professionals, line managers, colleagues and friends. Such a model has previously been proposed for
the association between IQ and mortality42. The important role of education, identified in all three
cohorts, is consistent with this idea. Low cognitive ability and/or low educational attainment are likely
to be associated with a limited ability to transfer skills. So, for example, if an individual with few
skills goes off sick from a labouring job, the options with regard to alternative employment are few.
The change in last 40 years from a manufacturing economy to a service-based economy makes such a
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lack of flexibility all the more problematic.
Our findings suggest that health is only one factor in understanding long term sickness absence. We
suggest that education should form part of the policy response to long term sickness absence: for
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future generations equipping children with skills necessary for labour market flexibility may inoculate
them from the risk of long term sickness absence. For the present cohorts of individuals on incapacity
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benefits it is important to recognise that their cognitive abilities may be below average and that the
most fruitful approach to rehabilitation may be to improve skills. More broadly the devastating
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outcome of long term worklessness for those with health problems needs to be seen as having its roots
as much in a combination of individual risk factors as in the health and workplace factors which have
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been the basis for much of the policy response to date.
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Table 1 Distribution of covariables in 3 British birth cohorts
1946 cohort
Sex
Social class
at birth
Long term
sick leave
Whole
cohort
Long term
sick leave
Whole
cohort
Long term
sick leave
Male
1561 (54%)
72 (45%)
7483 (50%)
190 (44%)
7373 (50%)
62 (41%)
Female
1333 (46%)
89 (55%)
7570 (50%)
241 (55%)
7340 (50%)
91 (59%)
I/II
656 (23%)
18 (11%)
2611 (17%)
37 (8%)
2431 (17%)
20 (13%)
III
1505 (52%)
76 (47%)
8849 (59%)
274 (64%)
10359 (70%)
80 (52%)
67 (42%)
3593 (24%)
120 (28%)
1923 (13%)
53 (35%)
Degree
30 (1%)
1 (0.5%)
1867 (12%)
21 (5%)
2708 (18%)
16 (10%)
A levels
270 (9%)
3 (2%)
1962 (13%)
86 (20%)
2054 (14%)
14 (9%)
O Levels
740 (26%)
17 (10.5%)
5200 (35%)
143 (33%)
6178 (42%)
77 (50%)
CSEs
575 (20%)
25 (16%)
4204 (28%)
79 (18%)
2904 (20%)
34 (22%)
No qualifications
1279 (44%)
115 (71%)
1820 (12%)
103 (24%)
869 (6%)
12 (8%)
I/II
1284 (45%)
40 (25%)
2675 (18%)
55 (13%)
6037 (41%)
47 (31%)
III
1138 (39%)
60 (37%)
7779 (52%)
220 (51%)
6159 (42%)
64 (42%)
IV/V
472 (16%)
61 (38%)
4599 (30%)
156 (36%)
2517 (17%)
42 (27%)
Yes
502 (17%)
37 (23%)
946 (6%)
73 (17%)
3387 (23%)
36 (24%)
No
2392 (83%)
124 (77%)
14107 (94%)
358 (83%)
11326 (77%)
117 (76%
Quartile 1
(least able)
Quartile 2
657 (23%)
76 (47%)
3768 (25%)
175 (41%)
3663 (25%)
49 (32%)
707 (24%)
37 (23%)
ie
Cognitive ability
in childhood
733 (25%)
3776 (25%)
125 (29%)
3758 (26%)
47 (31%)
Quartile 3
757 (26%)
28 (17%)
3907 (26%)
77 (18%)
3722 (25%)
35 (23%)
Quartile 4
(most able)
773 (27%)
20 (13%)
3602 (24%)
54 (12%)
3570 (24%)
22 (14%)
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Previous
depression
IV/V
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Social class at
last sweep
1970 cohort
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Educational
attainment
1958 cohort
Whole
cohort
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Table 2. The association between childhood cognitive ability and long term sickness absence in 3 British birth cohorts
1946
cohort
1958
cohort
1970
cohort
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Adjusted for all covariables
Model 1: Unadjusted
Model 2: Adjusted for sex,
paternal social class
Model 2 + adult social class
Model 2 + educational
attainment
Model 2 + depression
OR (95% CI)
p
OR (95% CI)
p
OR (95% CI)
P
OR (95% CI)
p
OR (95% CI)
P
OR (95% CI)
p
P<0.001
0.70 (0.56,0.86)
P=0.001
0.78 (0.63,0.98)
P=0.04
0.80 (0.63,1.02)
P=0.07
0.69 (0.56,0.86)
P=0.001
0.84
P=0.15
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Cognition
0.66 (0.53,0.82)
Quartile 1
(least able)
1
Quartile 2
0.77 (0.46,1.29)
P=0.32
0.84 (0.50,1.42)
Quartile 3
0.49 (0.27,0.88)
P=0.02
0.54 (0.30,0.96)
Quartile 4
(most able)
0.26 (0.11,0.58)
P=0.001
Cognition
0.68 (0.60,0.76)
P<0.001
Quartile 1
(least able)
1
Quartile 2
0.67 (0.51,0.88)
P=0.004
0.68 (0.52,0.89)
P=0.005
0.68 (0.52,0.90)
P=0.006
Quartile 3
0.43 (0.31,0.59)
P<0.001
0.44 (0.32, 0.61)
P<0.001
0.45 (0.33,0.62)
P<0.001
Quartile 4
(most able)
0.32 (0.22,0.48)
P<0.001
0.35 (0.24,0.52)
P<0.001
0.36 (0.24,0.54)
Cognition
0.78 (0.64,0.94)
P=0.01
0.80 (0.66,0.97)
P=0.03
0.84 (0.69,1.03)
Quartile 1
(least able
1
Quartile 2
0.94 (0.48,1.82)
P=0.85
0.97 (0.50,1.88)
P=0.93
1.03 (0.52,2.03)
P=0.93
1.0 (0.51,1.94)
P=0.99
0.97 (0.50,1.87)
P=0.92
1.03 (0.52,2.02)
P=0.93
Quartile 3
0.71 (0.44,1.15)
P=0.17
0.74 (0.46,1.21)
P=0.24
0.82 (0.50,1.34)
P=0.43
0.80 (0.50,1.29)
P=0.37
0.75 (0.46,1.22)
P=0.24
0.82 (0.50,1.34)
P=0.43
Quartile 4
(most able)
0.44 (0.21,0.90)
P=0.03
0.48 (0.24,0.98)
P=0.04
0.56 (0.26,1.19)
0.13
0.57 (0.28,1.12)
P=0.10
0.48 (0.24,0.98)
P=0.04
0.56 (0.26,1.19)
P=0.13
1
ee
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1
P=0.52
0.98 (0.57,1.67)
P=0.93
0.95 (0.56,1.61)
P=0.84
0.84 (0.50,1.41)
P=0.51
1.02 (0.60,1,74)
P=0.94
P=0.04
0.65 (0.36,1.19)
P=0.17
0.67 (0.36,1.24)
P=0.21
0.52 (0.29,0.95)
P=0.03
0.71 (0.38,1.33)
P=0.29
0.31 (0.13,0.70)
0.45 (0.18,1.11)
P=0.09
0.30 (0.13,0.69)
P=0.005
0.53 (0.21,1.33)
P=0.17
0.69 (0.61,0.77)
P=0.001
0.72 (0.64,0.81)
P<0.001
0.79 (0.68,0.92)
P=0.002
P=0.005
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0.44 (0.18,1.05)
P=0.06
P<0.001
0.69 (0.61,0.78)
P<0.001
1
1
1
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0.77 (0.67,0.90)
1
1
0.78 (0.59,1.03)
P=0.09
0.56 (0.40,0.79)
P=0.001
P<0.001
0.49 (0.30,0.81)
P=0.1
0.85 (0.70,1.02)
1
1
P=0.02
0.81 (0.61,1.07)
P=0.13
0.49 (0.35,0.68)
P<0.001
0.60 (0.42,0.84)
P=0.003
P=0.005
0.72 (0.54,0.94)
0.39 (0.26,0.59)
P<0.001
0.53 (0.32,0.86)
P=0.01
P=0.08
0.80 (0.66,0.98)
P=0.03
0.87 (0.72,1.05)
P=0.15
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WHAT IS ALREADY KNOWN ON THIS SUBJECT
•
Mental ill health and musculoskeletal disorders are the most common diagnoses in people on
long term sick leave.
•
However, the associations between objective measures of health and long term sick leave are
weak
•
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Most research has focussed on occupational risk factors for sickness absence, such as the
psychosocial work environment.
•
Relatively little research has examined the role of individual risk factors
WHAT THIS STUDY ADDS
There is a clear dose-response relationship between lower cognitive function in childhood and
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increased odds of being on long term sick leave in adulthood.
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This association applies to younger as well as older workers, and holds true irrespective of the
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decade of birth.
This association is mediated in part by education attainment suggesting improved education,
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especially for those with lower cognitive abilities, may help inoculate them from the risk of
long term sickness absence.
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COPYRIGHT
“The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of
all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats
and media (whether known now or created in the future), to i) publish, reproduce, distribute, display
and store the Contribution, ii) translate the Contribution into other languages, create adaptations,
reprints, include within collections and create summaries, extracts and/or, abstracts of the
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Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all
subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third
party material where-ever it may be located; and, vi) licence any third party to do any or all of the
above.”
COMPETING INTERESTS
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"All authors have completed the Unified Competing Interest form
atwww.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and
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declare: no support from any organisation for the submitted work; no financial relationships with any
organisations that might have an interest in the submitted work in the previous 3 years; no other
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relationships or activities that could appear to have influenced the submitted work."
CONTRIBUTORS
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Page 22 of 28
Henderson, Hotopf and Stansfeld conceived the study. Henderson Hotopf and Richards analysed the
data. Henderson Hotopf Stansfeld and Richards interpreted the results. Henderson drafted the
manuscript. Hotopf Stansfeld and Richards critically revised the manuscript for important intellectual
content.
All authors approved the final version.
Henderson is the guarantor.
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Page 23 of 28
ETHICAL APPROVAL
Not required for this study.
ACKNOWLEDGEMENTS
We are grateful to all the participants of each cohort study. We acknowledge the support of Imran
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Shah at the National Survey of Health and Development in providing us with data.
FUNDING
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Dr Henderson received support from a Medical Research Council Research Training Fellowship in
Health Services and Health of the Public Research. He is now supported by the NIHR Biomedical
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Research Centre BRC Nucleus jointly funded by the Guys and St Thomas’ Charity and the South
London and Maudsley Trustees. Professor Hotopf is supported by the NIHR Biomedical Research
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Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and Institute of
Psychiatry, Kings College London.
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All authors confirm that this research was carried out independent of the funders.
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BMJ Open
RESEARCH CHECKLIST: The association between childhood cognitive ability and long term sickness absence in 3
British birth cohorts
Title and abstract
Introduction
Background/rationale
Objectives
Methods
Study design
Setting
Item
No
1
2
Recommendation
(a) Indicate the study’s design with a commonly used term in the title or the
abstract
2
Explain the scientific background and rationale for the investigation being
reported
3-4
3
State specific objectives, including any prespecified hypotheses
4
4
Present key elements of study design early in the paper
4
5
Describe the setting, locations, and relevant dates, including periods of
recruitment, exposure, follow-up, and data collection
6
(a) Give the eligibility criteria, and the sources and methods of selection of
participants. Describe methods of follow-up
ee
Participants
Page no.
in paper
1
(b) Provide in the abstract an informative and balanced summary of what
was done and what was found
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4-7
4-5
Author note: Our study used data from 3 British birth cohorts, all of which
have been extensively investigated and reported on
rr
(b) For matched studies, give matching criteria and number of exposed and
unexposed
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NA
Variables
7
Clearly define all outcomes, exposures, predictors, potential confounders,
and effect modifiers. Give diagnostic criteria, if applicable
Data sources/
measurement
8*
For each variable of interest, give sources of data and details of methods of
assessment (measurement). Describe comparability of assessment methods
if there is more than one group
5-7
Bias
9
Describe any efforts to address potential sources of bias
9-10
Study size
10
Explain how the study size was arrived at
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Author note: we used data from 3 well established birth cohorts and have
Quantitative
variables
11
Statistical methods
12
cited detailed descriptions of each
Explain how quantitative variables were handled in the analyses. If
applicable, describe which groupings were chosen and why
6-7
(a) Describe all statistical methods, including those used to control for
confounding
7
(b) Describe any methods used to examine subgroups and interactions
n/a
(c) Explain how missing data were addressed
7
(d) If applicable, explain how loss to follow-up was addressed
7
(e) Describe any sensitivity analyses
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Results
Participants
13*
(a) Report numbers of individuals at each stage of study—eg numbers
potentially eligible, examined for eligibility, confirmed eligible, included in
the study, completing follow-up, and analysed
8
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Author note: we cite “About the cohort” papers for all 3 cohorts in addition
to Professor Wadsworth’s book which provides further information. We
would happily include further information in the paper if required but with 3
birth cohorts we felt this was too much
Descriptive data
14*
(a) Give characteristics of study participants (eg demographic, clinical,
social) and information on exposures and potential confounders
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13
(b) Indicate number of participants with missing data for each variable of
interest
(c) Summarise follow-up time (eg, average and total amount)
ee
n/a
Outcome data
15*
Report numbers of outcome events or summary measures over time
8
Main results
16
(a) Give unadjusted estimates and, if applicable, confounder-adjusted
estimates and their precision (eg, 95% confidence interval). Make clear
which confounders were adjusted for and why they were included
13
ev
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(b) Report category boundaries when continuous variables were categorized
NA
(c) If relevant, consider translating estimates of relative risk into absolute
risk for a meaningful time period
NA
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Other analyses
17
Report other analyses done—eg analyses of subgroups and interactions, and
sensitivity analyses
None
Discussion
Key results
18
Summarise key results with reference to study objectives
8-9
Limitations
19
Discuss limitations of the study, taking into account sources of potential bias
or imprecision. Discuss both direction and magnitude of any potential bias
9-10
Interpretation
20
Give a cautious overall interpretation of results considering objectives,
limitations, multiplicity of analyses, results from similar studies, and other
relevant evidence
11-12
Generalisability
21
Discuss the generalisability (external validity) of the study results
11-12
Other information
Funding
22
Give the source of funding and the role of the funders for the present study
and, if applicable, for the original study on which the present article is based
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Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and
published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely
available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is
available at http://www.strobe-statement.org.
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RESEARCH CHECKLIST: The association between childhood cognitive ability and long term sickness absence in 3
Downloaded from http://bmjopen.bmj.com/ on May 20, 2016 - Published by group.bmj.com
British birth cohorts
Item
No
1
Title and abstract
Recommendation
(a) Indicate the study’s design with a commonly used term in the title or the
Page no.
in paper
1
abstract
(b) Provide in the abstract an informative and balanced summary of what
2
was done and what was found
Introduction
Background/rationale
2
Explain the scientific background and rationale for the investigation being
3-4
reported
Objectives
3
State specific objectives, including any prespecified hypotheses
Fo
Methods
Study design
Setting
4
Present key elements of study design early in the paper
5
Describe the setting, locations, and relevant dates, including periods of
4
4
4-7
recruitment, exposure, follow-up, and data collection
Participants
6
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(a) Give the eligibility criteria, and the sources and methods of selection of
4-5
participants. Describe methods of follow-up
Author note: Our study used data from 3 British birth cohorts, all of which
ee
have been extensively investigated and reported on
(b) For matched studies, give matching criteria and number of exposed and
unexposed
Variables
7
NA
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Clearly define all outcomes, exposures, predictors, potential confounders,
and effect modifiers. Give diagnostic criteria, if applicable
ev
5-7
Bias
9
Describe any efforts to address potential sources of bias
9-10
Study size
10
Explain how the study size was arrived at
Data sources/
8*
measurement
For each variable of interest, give sources of data and details of methods of
assessment (measurement). Describe comparability of assessment methods
if there is more than one group
iew
Author note: we used data from 3 well established birth cohorts and have
cited detailed descriptions of each
Quantitative
11
variables
Explain how quantitative variables were handled in the analyses. If
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12
(a) Describe all statistical methods, including those used to control for
confounding
n/a
(c) Explain how missing data were addressed
7
(e) Describe any sensitivity analyses
13*
7
(b) Describe any methods used to examine subgroups and interactions
(d) If applicable, explain how loss to follow-up was addressed
Results
Participants
6-7
applicable, describe which groupings were chosen and why
Statistical methods
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BMJ Open
(a) Report numbers of individuals at each stage of study—eg numbers
potentially eligible, examined for eligibility, confirmed eligible, included in
the study, completing follow-up, and analysed
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Author note: we cite “About the cohort” papers for all 3 cohorts in addition
to Professor Wadsworth’s book which provides further information. We
would happily include further information in the paper if required but with 3
1
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7
None
8
BMJ Open
birth cohorts we felt this was too much
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Descriptive data
14*
(a) Give characteristics of study participants (eg demographic, clinical,
13
social) and information on exposures and potential confounders
(b) Indicate number of participants with missing data for each variable of
interest
(c) Summarise follow-up time (eg, average and total amount)
n/a
Outcome data
15*
Report numbers of outcome events or summary measures over time
8
Main results
16
(a) Give unadjusted estimates and, if applicable, confounder-adjusted
13
estimates and their precision (eg, 95% confidence interval). Make clear
which confounders were adjusted for and why they were included
(b) Report category boundaries when continuous variables were categorized
NA
(c) If relevant, consider translating estimates of relative risk into absolute
NA
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risk for a meaningful time period
Other analyses
17
Report other analyses done—eg analyses of subgroups and interactions, and
None
sensitivity analyses
18
Limitations
19
Summarise key results with reference to study objectives
8-9
Discuss limitations of the study, taking into account sources of potential bias
9-10
ee
Discussion
Key results
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or imprecision. Discuss both direction and magnitude of any potential bias
Interpretation
20
Give a cautious overall interpretation of results considering objectives,
11-12
limitations, multiplicity of analyses, results from similar studies, and other
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relevant evidence
Generalisability
21
Other information
Funding
22
Discuss the generalisability (external validity) of the study results
ev
Give the source of funding and the role of the funders for the present study
11-12
19
and, if applicable, for the original study on which the present article is based
iew
*Give information separately for exposed and unexposed groups.
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and
published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely
l
on
available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is
available at http://www.strobe-statement.org.
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BMJ Open
The association between childhood cognitive ability and
adult long term sickness absence in 3 British birth cohorts:
a cohort study
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Journal:
Manuscript ID:
Article Type:
Date Submitted by the Author:
Complete List of Authors:
BMJ Open
bmjopen-2011-000777.R1
Research
22-Feb-2012
<b>Primary Subject
Heading</b>:
Keywords:
Occupational and environmental medicine
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Secondary Subject Heading:
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HENDERSON, MAX; INSTITUTE OF PSYCHIATRY, KINGS COLLEGE
LONDON, PSYCHOLOGICAL MEDICINE
Richards, Marcus; MRC Unit for Lifelong Health and Aging,
Stansfeld, Stephen; Barts and the London, Queen Marys School of Medicine
and Dentistry, Neurology
Hotopf, Matthew; King's College London (Institute of Psychiatry),
Public health, Epidemiology
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OCCUPATIONAL & INDUSTRIAL MEDICINE, EPIDEMIOLOGY, PUBLIC
HEALTH
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Page 1 of 28
RESEARCH CHECKLIST: The association between childhood cognitive ability and long term sickness absence in 3
Downloaded from http://bmjopen.bmj.com/ on May 20, 2016 - Published by group.bmj.com
British birth cohorts
Item
No
1
Title and abstract
Recommendation
(a) Indicate the study’s design with a commonly used term in the title or the
Page no.
in paper
1
abstract
(b) Provide in the abstract an informative and balanced summary of what
2
was done and what was found
Introduction
Background/rationale
2
Explain the scientific background and rationale for the investigation being
3-4
reported
Objectives
3
State specific objectives, including any prespecified hypotheses
Fo
Methods
Study design
Setting
4
Present key elements of study design early in the paper
5
Describe the setting, locations, and relevant dates, including periods of
4
4
4-7
recruitment, exposure, follow-up, and data collection
Participants
6
rp
(a) Give the eligibility criteria, and the sources and methods of selection of
4-5
participants. Describe methods of follow-up
Author note: Our study used data from 3 British birth cohorts, all of which
ee
have been extensively investigated and reported on
(b) For matched studies, give matching criteria and number of exposed and
unexposed
Variables
7
NA
rr
Clearly define all outcomes, exposures, predictors, potential confounders,
and effect modifiers. Give diagnostic criteria, if applicable
ev
5-7
Bias
9
Describe any efforts to address potential sources of bias
9-10
Study size
10
Explain how the study size was arrived at
Data sources/
8*
measurement
For each variable of interest, give sources of data and details of methods of
assessment (measurement). Describe comparability of assessment methods
if there is more than one group
iew
Author note: we used data from 3 well established birth cohorts and have
cited detailed descriptions of each
Quantitative
11
variables
Explain how quantitative variables were handled in the analyses. If
l
on
12
(a) Describe all statistical methods, including those used to control for
confounding
n/a
(c) Explain how missing data were addressed
7
(e) Describe any sensitivity analyses
13*
7
(b) Describe any methods used to examine subgroups and interactions
(d) If applicable, explain how loss to follow-up was addressed
Results
Participants
6-7
applicable, describe which groupings were chosen and why
Statistical methods
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BMJ Open
(a) Report numbers of individuals at each stage of study—eg numbers
potentially eligible, examined for eligibility, confirmed eligible, included in
the study, completing follow-up, and analysed
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Author note: we cite “About the cohort” papers for all 3 cohorts in addition
to Professor Wadsworth’s book which provides further information. We
would happily include further information in the paper if required but with 3
1
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
7
None
8
BMJ Open
birth cohorts we felt this was too much
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Descriptive data
14*
(a) Give characteristics of study participants (eg demographic, clinical,
13
social) and information on exposures and potential confounders
(b) Indicate number of participants with missing data for each variable of
interest
(c) Summarise follow-up time (eg, average and total amount)
n/a
Outcome data
15*
Report numbers of outcome events or summary measures over time
8
Main results
16
(a) Give unadjusted estimates and, if applicable, confounder-adjusted
13
estimates and their precision (eg, 95% confidence interval). Make clear
which confounders were adjusted for and why they were included
(b) Report category boundaries when continuous variables were categorized
NA
(c) If relevant, consider translating estimates of relative risk into absolute
NA
Fo
risk for a meaningful time period
Other analyses
17
Report other analyses done—eg analyses of subgroups and interactions, and
None
sensitivity analyses
18
Limitations
19
Summarise key results with reference to study objectives
8-9
Discuss limitations of the study, taking into account sources of potential bias
9-10
ee
Discussion
Key results
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or imprecision. Discuss both direction and magnitude of any potential bias
Interpretation
20
Give a cautious overall interpretation of results considering objectives,
11-12
limitations, multiplicity of analyses, results from similar studies, and other
rr
relevant evidence
Generalisability
21
Other information
Funding
22
Discuss the generalisability (external validity) of the study results
ev
Give the source of funding and the role of the funders for the present study
11-12
19
and, if applicable, for the original study on which the present article is based
iew
*Give information separately for exposed and unexposed groups.
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and
published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely
l
on
available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is
available at http://www.strobe-statement.org.
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Page 3 of 28
The association between childhood cognitive ability and adult long term sickness absence in 3 British
birth cohorts: a cohort study
Dr Max Henderson*
Senior Lecturer in Epidemiological & Occupational Psychiatry
Institute of Psychiatry, Kings College London
Department of Psychological Medicine
Weston Education Centre, Cutcombe Road
London SE5 9RJ
UK
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Professor Marcus Richards
Programme Leader
MRC Unit for Lifelong Health and Aging
33 Bedford Place
London WC1B 5JU
UK
Professor Stephen Stansfeld
Professor of Psychiatry
Centre for Psychiatry
Wolfson Institute for Preventive Medicine
Barts and the London School of Medicine and Dentistry
London EC1M 6BQ
UK
020 3228 8564
F:
020 7848 5408
E:
[email protected]
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* corresponding author
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Professor Matthew Hotopf
Professor of General Hospital Psychiatry
Institute of Psychiatry, Kings College London
Department of Psychological Medicine
Weston Education Centre, Cutcombe Road
London SE5 9RJ
UK
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ABSTRACT
Objectives: We aimed to test the relationship between childhood cognitive function and long term sick leave in adult
life, and whether any relationship was mediated by educational attainment, adult social class or adult mental ill health
Design: Cohort study
Setting: We used data from the 1946, 1958 and 1970 British birth cohorts. Initial study populations included all live
births in one week in that year. Follow-up arrangements have differed between the cohorts.
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Participants: We included only those alive, living in the UK, and not permanent refusals at the time of the outcome.
We further restricted analyses to those in employment, full-time education, or caring for a family in the sweep
immediately prior to the outcome. 2894 (1946), 15 053 (1958) and 14 713 (1970) cohort members were included.
Primary and secondary outcome measures: Receipt of health-related benefits (e.g. incapacity benefit) in 2000 and
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2004 for the 1958 and 1970 cohorts respectively; individuals identified as "permanently sick or disabled" in 1999 for
1946 cohort.
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Results: After adjusting for sex and parental social class better cognitive function at age 10/11 was associated with
reduced odds of being long term sick (1946: 0.70(0.56,0.86) p=0.001; 1958 (0.69 (0.61,0.
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77)p<0.001; 1970 0.80 (0.66,0.97) p=0.003). Educational attainment appeared to partly mediate the associations in
all cohorts; adult social class appeared to have a mediating role in the 1946 cohort.
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Conclusions: Long term sick leave is a complex outcome with many risk factors beyond health. Cognitive abilities
might impact on the way individuals are able to develop strategies to maintain their employment or rapidly find new
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employment when faced with a range of difficulties. Education should form part of the policy response to long term
sick leave such that young people are better equipped with skills needed in a flexible labour market.
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BACKGROUND
In the UK over 2.5 million people are in receipt of health-related benefits (HRBs) including
Incapacity Benefit and Employment and Support allowance , most often paid to those off work for
more than 6 months due to ill health 1. The cost to the economy from reduced tax revenues and
payment of benefits is in excess of £50 billion per year2. Reducing long term sick leave is thus high
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on the agenda for policy makers3 4. Long term sick leave increases poverty in the sick, and is
associated with premature mortality5-7 . At the individual level long term sick leave means a loss of
income and dignity, and with this a reduced opportunity for social participation2. 50% of those in
receipt of an HRB have been claiming for more than 5 years, and those claiming for 2 years are more
likely to die or retire than get another job 8. Long term sick leave increases and sustains poverty and
social disadvantage.
Mental and musculoskeletal disorders are the most common reasons to be awarded an HRB2 9 10.
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Much of the policy response to sickness absence has focussed on reducing occupational risk factors
for these disorders. However there is a disconnect between the increase in incapacity benefit
certifications and the distribution of risk factors in the workplace. Musculoskeletal disorders rose at a
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time when the physical demands of work decreased11, and workplaces became increasingly safe12.
Similarly the increase in awards of HRBs due to psychiatric disorders was not associated with a
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concomitant rise in the prevalence of these disorders within the working age population. Further, the
relationship between health and occupational function is unclear - whilst there are 2.5 million people
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in the UK on IB, over 3 million people with a range of disabilities manage to remain in paid work 13.
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Relatively few studies have examined individual, as opposed to occupational, risk factors for long
term sick leave14. Some difficulties apparent in childhood are associated: data from the Aberdeen
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Children of the Nineteen Fifties Cohort 15 indicated that emotional or behavioural difficulties were
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associated with being permanently sick or disabled nearly 40 years later. Similar findings have been
shown for adolescent mental disorders in a Swedish cohort16. Another early risk factor might be
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cognitive ability: the Aberdeen study indicated that low cognitive ability independently predicted
being permanently sick or disabled in adult life. Work by Gravseth found that low birth weight and a
failure to complete secondary education predicted the award of a disability pension in a cohort of
Norwegians born between 1967 and 1976 17 . The same author has shown that lower intellectual
performance at age 18 or 19, and educational attainment at age 23 were each independently associated
with the award of a disability pension to Norwegian men between the ages of 24 and 36 18.
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Low IQ might explain the association of both childhood behavioural problems and poor educational
attainment with long term sickness absence in adult life. If this were the case, a response at policy
level which emphasised the attributed health reasons for long term sick leave and responded by trying
to improve the health “offer” to this group may be less than successful. By contrast one that looked
beyond a diagnostic label and emphasised skills and training, especially tailored to the needs of the
least cognitively able, might produce better results.
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We tested the hypothesis that lower cognitive ability is a risk factor for long term sickness absence in
three British birth cohorts. We further aimed to determine whether such an association is mediated by
educational attainment, adult social class, or adult mental health.
METHODS
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We used data from the 3 British birth cohorts whose participants are now working age 19.
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The National Survey of Health and Development
The 1946 National Survey of Health and Development (NSHD) obtained information on all singleton
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births to married women in England Scotland and Wales in a single week in March 1946 20. An initial
sample of 5362 were then followed up, comprising all those with fathers in non-manual and
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agricultural employment and a 1:4 sample of those with fathers in manual employment. The cohort is
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described in detail elsewhere20. In 1999, 3760 of the 5362 were alive, living in the UK and were not
permanent refusals. Of these 3035 (81%) provided data to the study. This group (weighted to adjust
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for the sampling procedure) are broadly representative of the population born in 1946 in the UK,
although there was over-representation among non-responders of the never married and the least
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advantaged in terms of cognitive ability, educational attainment, and social class21.
The National Child Development Study
The 1958 National Childhood Development Study (NCDS) included all surviving children born in
England Scotland and Wales in a single week in March 1958. During follow-up ‘sweeps’ immigrant
children who would have been part of the study had they been born in the UK were added. The cohort
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is described in detail elsewhere 22. In 2000, 16147 were still eligible to take part and 11419 (71%)
contributed data.
The British Cohort Study
The 1970 British Cohort Study (BCS) included all live births in one week in April 1970 in the whole
United Kingdom. Children born in Northern Ireland were subsequently dropped from follow-up. The
cohort is described in detail elsewhere 23. In 2004, excluding those who had died, emigrated, been
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born in Northern Ireland or were permanent refusals 16875 were eligible to take part of whom 9656
(59%) contributed data.
Outcome
In all cohorts data on the outcome, long term sick leave, were extracted from the most recent dataset
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at the time the present project began: for the 1946 cohort this was in 1999 when participants were
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aged 53 years; for the 1958 cohort in 2000, when participants were aged 42, and in the 1970 cohort in
2004, when participants were aged 34.
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In both the 1958 and 1970 cohort, participants were asked if they were in receipt of any benefit
payments. Individuals reporting receipt of Incapacity Benefit (IB) or Severe Disablement Allowance
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were identified as being on long term sick leave. Typically these participants were off work for health
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reasons for more than 6 months. Data on benefit receipt were not available for the 1946 birth cohort in
1999. Instead participants were asked (yes/no) if they were in a job. Those who responded ‘No’ were
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asked (yes/no) if they were looking for work. Those who also replied ‘No’ to this question were asked
why and asked to select a response from 6 options, one of which was “Permanently sick or disabled”.
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Individuals reporting this option as the reason they were not looking for work were identified as being
on long term sick leave. We have previously described research using this category in the Aberdeen
Children of the Nineteen Fifties cohort 15.
Exposures of interest
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The 1946 and 1958 cohorts contain data on participants’ cognitive ability at age 11; the 1970 cohort
has a measure at age 10. 1946 cohort members were tested at age 11 on verbal and non-verbal
intelligence, arithmetic, word pronunciation, and vocabulary. Scores were summed to represent
overall cognitive ability. The cognitive ability of the 1958 cohort members was assessed using the
General Ability Test 24. 1970 cohort members completed a modified version of the British Ability
Scales (BAS) 25. A principal components analysis was performed on the four subscales of the BAS
and the first factor was taken as a general measure of cognitive ability 26. For all cohorts cognitive
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ability scores were divided into quartiles and the first (lowest cognitive ability) used as the reference
group.
In all three cohorts occupation of the father at the time of the participants’ birth was coded according
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to the Registrar General’s classification. For these analyses social class was categorised as Class I/II,
Class III (non-manual and manual) and Class IV/V. Participants were asked about their current or
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most recent job, and these were similarly coded. Common mental disorders are the most common
reason for sick leave9. All cohorts contained a measure of depression or psychological distress. 1946
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cohort members were administered the Present state Examination 27 at age 36 years, and depression in
the preceding year was derived from the CATEGO algorithm 27. 1958 cohort members were
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administered the Malaise Inventory 28in 1991. Those scoring 8/24 or more were identified as ‘cases’
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of depression 29. 1970 cohort members were administered the 12-item General Health Questionnaire 30
in 2000. Participants scoring 4 or more were identified as cases of psychological distress/depression
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The highest level of educational qualification was available in the 1946, 1958 and 1970 cohorts at
ages 26, 33 and 26 years, respectively. All 3 cohorts categorised this information differently and thus
all data were re-coded into degree; A level or equivalent; O level or equivalent; CSE grade 2-5; no
qualifications.
Risk set
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At any time-point the workless population is a heterogeneous one, comprising individuals on shortterm sick leave, individuals on long-term sick leave and some individuals who, for whatever reason,
have never worked. Many of this latter group will have substantial health difficulties such as severe
physical disabilities or learning disabilities. Our outcome was long term sick leave, and therefore in
all 3 cohorts analyses were restricted to those participants who described themselves as either in
employment or full-time education, or caring for a family in the sweep immediately prior to that from
which the outcome was derived (1946 cohort - 1989; 1958 cohort - 1991; 1970 cohort - 2000). This
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restriction removed 23%, 7% and 13% of the participants respectively. Post-hoc analysis showed
these participants had very high rates of HRB receipt.
Statistical Analyses
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All data were analysed using STATA version 9.2 32. As with all longitudinal studies, partial data
collection and loss to follow-up meant that there were incomplete data on participants in all 3 cohorts.
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To minimise the impact of missing data multiple imputation using chained equations (ICE) 33was
carried out 32. All variables were included in the imputation model 34. 10 iterations were completed.
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The MICOMBINE function was used to calculate average regression estimates across the 10 imputed
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datasets.
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For each cohort the prevalence of each of the exposures of interest was calculated. The unadjusted
association between childhood cognitive ability and long term sickness absence was estimated and
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shown as odds ratios (OR), with 95% confidence intervals, for each of the four quartiles of childhood
cognition compared to the reference, and for the overall trend. These were then adjusted for the
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potential confounders of sex and social class at birth. Finally, to examine the potential mediating
effects of covariables measured in adult life, adult social class, educational attainment and history of
recent depression or psychological distress were each added to the model.
RESULTS
In 1999 2894 members of the 1946 cohort were eligible for this study, of whom 159 (5.5%) reported
themselves as permanently sick or disabled. In 2000 there were 15 053 eligible members of the 1958
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cohort, of whom 431(2.9%) were in receipt of long term sickness benefits. In 2004 there were 14 713
eligible members of the 1970 cohort, of whom 153 (1.04%) were in receipt of long term sickness
benefits. The distribution of the covariables in each of the birth cohorts is shown in table 1.
[Table 1 about here].
The associations between childhood cognitive ability and long term sickness absence, adjusted for the
covariables are shown in Table 2. This shows that for each cohort there is a strong impact of cognitive
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ability measured in childhood on the outcome several decades later. The top quartile showed between
one quart and one half the odds of long term sickness absence depending upon the cohort studied. The
effect was present after adjusting for sex and paternal social class (model 2). When potential
mediating variables were added, effects were reduced. Adding social class in adulthood diminished
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effect sizes, particularly in the 1946 birth cohort. The overall impact of cognition on the outcome was
statistically significant in two of the three cohorts. Adjusting for educational attainment also led to a
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reduction in effect sizes, with one cohort (the 1958) showing a significant trend of cognition on the
outcome, whereas the others showed a marginally statistically significant effect, although the ORs for
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the lowest quartile were still of the order of two. Adjusting for prior mental disorder had little impact,
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with all three of the cohorts showing an independent effect of cognition on long term sickness
absence. Finally, a full model controlling for all covariates simultaneously, showed a reduction in the
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effect of cognition on long term sickness, with one of the three cohorts (1958) remaining significant.
[Table 2 about here]
Summary of findings
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DISCUSSION
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We examined associations between cognitive ability measured in childhood and long term sickness
absence in adult life across three British birth cohorts. In all three cohorts the effects after adjustment
for sex and social class at birth were similar, and all three demonstrated a clear dose-response effect
whereby lower childhood cognitive ability was more strongly associated with long-term sick leave. In
each cohort there was little attenuation when previous history of depression was included. There was
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some attenuation of the effect when adult social class and, particularly, educational attainment was
included, and this attenuation was greater for those of lower cognitive ability. This suggests that some
of the effect of lower cognitive ability is mediated by educational attainment. For example low
educational attainment might lead to more insecure jobs or more manual jobs that could be more
difficult to sustain in the context of disability. However educational attainment does not fully explain
the association.
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Strengths and weaknesses
Strengths of this study include the use of data from three British cohorts across half a century, with
outcome data from both early (age 34) and late career (age 53), thus these results seem to transcend
period effects. These cohorts are broadly representative of the population born in UK in the years of
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their inception. Those relatively disadvantaged were more likely to be under-represented, but we
have no reason to believe that this would have altered the pattern of results reported here. Exposures
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were measured long before the outcomes occurred, and cognitive ability was assessed using well
recognised tools. Exposures in adult life were assessed independently of the research question,
limiting the impact of reporting bias.
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Weaknesses include the different assessment tools used to measure childhood cognitive ability in each
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cohort which raises questions of comparability of results between cohorts. Paternal social class at
birth was assessed by asking the participant’s mother. There is likely to be a degree of
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misclassification here, most notable in the 1946 cohort as many fathers were just returning from the
war. We believe any such misclassification is likely to be random. Although the associations between
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lower cognitive ability and long term sick leave remain after adjustment for parental social class we
are mindful of the possibility of residual confounding from unmeasured variables acting in early life
which might influence both childhood cognitive ability and adult ill-health. We used three birth
cohorts each of which has included a number of sweeps over at least 30 years. Non-participation in
the more recent sweeps of the 1946 cohort is associated with socio-economic disadvantage, and in the
1958 and 1970 cohorts with male sex and lower educational attainment. Although the remaining
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participants are still broadly representative of their generations and we have used multiple imputation
to minimise the impact of loss to follow-up it is possible that our cohort data is to some degree biased.
Any resulting error would, however, tend to underestimate the association between childhood
cognitive function and later occupational function.
Depression or psychological distress was measured using different self-report tools in all three
cohorts. Only recent difficulties were asked for and as with all cohort studies the data are silent as to
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what happens between ‘sweeps’. A more robust measure of depression which identified episodes of
illness between sweeps would have been preferable. We included depression in this analysis as it is
the leading cause of long term sick leave. Given the two-way relationship between physical and
mental ill health our results would have been illuminated had we included measures of physical illness
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in childhood and in adult life.
There is no accepted definition of long term sick leave. Although available in the 1958 and 1970
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cohorts, receipt of Incapacity Benefit was not available in the 1946 cohort and this is a limitation.
Nonetheless we believe the population captured under the heading “permanently sick or disabled” at
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age 53 to be very similar to those indentified as being in receipt of IB. Most IB recipients have been
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away from work for over 6 months. There are other routes in to incapacity benefit but the median time
spent on IB is 5 years and the advantages of using this outweigh any limitations. The population we
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have studied represents the persistent and severe long term absentees. IB receipt is a binary question,
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asked relatively context free and this will minimise any recall, reporting or observer bias, and any
misclassification is likely to be random. Furthermore we believe our findings have greater salience for
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policy makers as notwithstanding the introduction of Employment and Support Allowance they can be
mapped straight onto the existing UK benefits framework.
The effect sizes we have demonstrated are noticeably similar between the cohorts despite the
differences in the cohorts and the methods used to assess cognitive ability. The impact of cognitive
ability on later long term sickness absence attained conventional statistical significance in all three
cohorts though most strongly for the 1958 cohort. The higher P value in the 1946 cohorts reflects the
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smaller size of the cohort (less than half that of the other two). In the 1970 cohort the outcome was
rare (1%) and hence statistical power was greatest in the 1958 cohort. Our results cannot be accounted
for by the people with very low cognitive ability never entering the labour force as we restricted our
analyses to only those were either working or fulfilling other social roles (caring for a family or
studying) at the previous sweep.
There are no data on the cognitive abilities of people claiming Incapacity Benefit. Our study shows
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that the bottom two quartiles of cognitive ability are responsible for a considerable proportion of the
IB recipient population. We present regression models showing the impact of controlling for a
number of variables on these associations. It is worth noting that we do not consider these factors
predominantly as confounders – in other words, although the association between cognition is
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attenuated and becomes non-significant in two of the three cohorts when educational attainment, adult
social class, and depression are controlled, this does not indicate that the univariate association
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between cognition and long term sickness absence is merely a result of confounding. Rather, we
consider it probable that these variables are mediators of the association. Thus the association
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between lower cognitive status and long term sickness absence is in part explained by a pathway via
educational attainment and adult social class. It should be noted however that the relationships
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between risk factors identified in early life, education, health and employment factors in leading to the
receipt of HRBs is not clear and is likely to be complex.
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There is an extensive literature on the health implications of low cognitive ability35-37. However we
think it unlikely that the association we gave described between low cognitive ability in childhood and
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adult occupational outcomes is simply because these individuals are more likely to become unwell.
First, we have deliberately not attempted to ascertain the clinical labels as to why an individual is in
receipt of IB – the effect of cognitive ability is substantial enough to be observed at cohort level.
Second, the very limited attenuating effect of depression in all three cohorts suggests that the
mechanism behind this association is largely independent of mental health, the most common reason
for long term sick leave. This is also suggested by the consistency of results across the three cohorts
as the health difficulties suffered by those in their thirties are likely to be different to those suffered by
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people in their fifties. Last, whilst previous work on the 1946 cohort38, replicating work on the 1958
and 1970 cohorts26 39-41, has shown an association between cognitive ability and adult chronic physical
diseases, these associations were mediated by education and to a lesser degree socioeconomic status,
both of which are included in our analyses.
In trying to understand how childhood cognitive function affects adult occupational function it is
important to recognise that long term sick leave is the result of a process rather than an event10. These
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data are unable to tell us if lower cognitive ability makes it more likely that an individual with a
particular disorder or set of symptoms is more likely to go off work sick, or less able to get
appropriate support when they are ill, or find it more difficult to negotiate a successful return to work
after a period of ill health. Cognitive ability might impact on any or all of these, possibly in “soft”
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ways such as by directing responses to illness or by facilitating the recruitment of support from health
professionals, line managers, colleagues and friends. Such a model has previously been proposed for
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the association between IQ and mortality42. The important role of education, identified in all three
cohorts, is consistent with this idea. Low cognitive ability and/or low educational attainment are likely
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to be associated with a limited ability to transfer skills. So, for example, if an individual with few
skills goes off sick from a labouring job, the options with regard to alternative employment are few.
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The change in last 40 years from a manufacturing economy to a service-based economy makes such a
lack of flexibility all the more problematic.
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Our findings suggest that health is only one factor in understanding long term sickness absence. We
suggest that education should form part of the policy response to long term sickness absence: for
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future generations equipping children with skills necessary for labour market flexibility may inoculate
them from the risk of long term sickness absence. For the present cohorts of individuals on incapacity
benefits it is important to recognise that their cognitive abilities may be below average and that the
most fruitful approach to rehabilitation may be to improve skills. More broadly the devastating
outcome of long term worklessness for those with health problems needs to be seen as having its roots
as much in a combination of individual risk factors as in the health and workplace factors which have
been the basis for much of the policy response to date.
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Table 1 Distribution of covariables in 3 British birth cohorts
1946 cohort
Social class
at birth
Educational
attainment
Long term
sick leave
(n=159)
Whole
cohort
(n=15 053)
Long term
sick leave
(n=431)
Whole
cohort
(n=14 713)
Long term
sick leave
(n=153)
Male
1561 (54%)
72 (45%)
7483 (50%)
190 (44%)
7373 (50%)
62 (41%)
Female
1333 (46%)
89 (55%)
7570 (50%)
241 (55%)
7340 (50%)
91 (59%)
I/II
656 (23%)
18 (11%)
2611 (17%)
37 (8%)
2431 (17%)
20 (13%)
III
1505 (52%)
76 (47%)
8849 (59%)
274 (64%)
10359 (70%)
80 (52%)
IV/V
733 (25%)
67 (42%)
3593 (24%)
120 (28%)
1923 (13%)
53 (35%)
Degree
30 (1%)
1 (0.5%)
1867 (12%)
21 (5%)
2708 (18%)
16 (10%)
A levels
270 (9%)
3 (2%)
1962 (13%)
86 (20%)
2054 (14%)
14 (9%)
O Levels
740 (26%)
17 (10.5%)
5200 (35%)
143 (33%)
6178 (42%)
77 (50%)
575 (20%)
25 (16%)
4204 (28%)
79 (18%)
2904 (20%)
34 (22%)
No qualifications
1279 (44%)
115 (71%)
1820 (12%)
103 (24%)
869 (6%)
12 (8%)
I/II
1284 (45%)
40 (25%)
2675 (18%)
55 (13%)
6037 (41%)
47 (31%)
III
1138 (39%)
60 (37%)
7779 (52%)
220 (51%)
6159 (42%)
64 (42%)
IV/V
472 (16%)
61 (38%)
4599 (30%)
156 (36%)
2517 (17%)
42 (27%)
Yes
502 (17%)
37 (23%)
946 (6%)
73 (17%)
3387 (23%)
36 (24%)
No
2392 (83%)
124 (77%)
14107 (94%)
358 (83%)
11326 (77%)
117 (76%
Quartile 1
(least able)
Quartile 2
657 (23%)
76 (47%)
3768 (25%)
175 (41%)
3663 (25%)
49 (32%)
707 (24%)
37 (23%)
3776 (25%)
125 (29%)
3758 (26%)
47 (31%)
Quartile 3
757 (26%)
28 (17%)
3907 (26%)
77 (18%)
3722 (25%)
35 (23%)
Quartile 4
(most able)
773 (27%)
20 (13%)
3602 (24%)
CSEs
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Cognitive ability
in childhood
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Previous
depression
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Social class at
last sweep
1970 cohort
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Sex
1958 cohort
Whole
cohort
(n=2894)
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54 (12%)
3570 (24%)
22 (14%)
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Table 2. The association between childhood cognitive ability and long term sickness absence in 3 British birth cohorts
1946
cohort
1958
cohort
1970
cohort
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Adjusted for all covariables
Model 1: Unadjusted
Model 2: Adjusted for sex,
paternal social class
Model 2 + adult social class
Model 2 + educational
attainment
Model 2 + depression
OR (95% CI)
p
OR (95% CI)
p
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
p
P<0.001
0.70 (0.56,0.86)
P=0.001
0.78 (0.63,0.98)
P=0.04
0.80 (0.63,1.02)
P=0.07
0.69 (0.56,0.86)
P=0.001
0.84 (0.66, 1.07)
P=0.15
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Cognition
0.66 (0.53,0.82)
Quartile 1
(least able)
1
Quartile 2
0.77 (0.46,1.29)
P=0.32
0.84 (0.50,1.42)
Quartile 3
0.49 (0.27,0.88)
P=0.02
0.54 (0.30,0.96)
Quartile 4
(most able)
0.26 (0.11,0.58)
P=0.001
Cognition
0.68 (0.60,0.76)
P<0.001
Quartile 1
(least able)
1
Quartile 2
0.67 (0.51,0.88)
P=0.004
0.68 (0.52,0.89)
P=0.005
0.68 (0.52,0.90)
P=0.006
Quartile 3
0.43 (0.31,0.59)
P<0.001
0.44 (0.32, 0.61)
P<0.001
0.45 (0.33,0.62)
P<0.001
Quartile 4
(most able)
0.32 (0.22,0.48)
P<0.001
0.35 (0.24,0.52)
P<0.001
0.36 (0.24,0.54)
Cognition
0.78 (0.64,0.94)
P=0.01
0.80 (0.66,0.97)
P=0.03
0.84 (0.69,1.03)
Quartile 1
(least able
1
Quartile 2
0.94 (0.48,1.82)
P=0.85
0.97 (0.50,1.88)
P=0.93
1.03 (0.52,2.03)
P=0.93
1.0 (0.51,1.94)
P=0.99
0.97 (0.50,1.87)
P=0.92
1.03 (0.52,2.02)
P=0.93
Quartile 3
0.71 (0.44,1.15)
P=0.17
0.74 (0.46,1.21)
P=0.24
0.82 (0.50,1.34)
P=0.43
0.80 (0.50,1.29)
P=0.37
0.75 (0.46,1.22)
P=0.24
0.82 (0.50,1.34)
P=0.43
Quartile 4
(most able)
0.44 (0.21,0.90)
P=0.03
0.48 (0.24,0.98)
P=0.04
0.56 (0.26,1.19)
0.13
0.57 (0.28,1.12)
P=0.10
0.48 (0.24,0.98)
P=0.04
0.56 (0.26,1.19)
P=0.13
1
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1
1
P=0.52
0.98 (0.57,1.67)
P=0.93
0.95 (0.56,1.61)
P=0.84
0.84 (0.50,1.41)
P=0.51
1.02 (0.60,1,74)
P=0.94
P=0.04
0.65 (0.36,1.19)
P=0.17
0.67 (0.36,1.24)
P=0.21
0.52 (0.29,0.95)
P=0.03
0.71 (0.38,1.33)
P=0.29
0.31 (0.13,0.70)
0.45 (0.18,1.11)
P=0.09
0.30 (0.13,0.69)
P=0.005
0.53 (0.21,1.33)
P=0.17
0.69 (0.61,0.77)
P=0.001
0.72 (0.64,0.81)
P<0.001
0.79 (0.68,0.92)
P=0.002
P=0.005
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0.44 (0.18,1.05)
P=0.06
P<0.001
0.69 (0.61,0.78)
P<0.001
1
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0.77 (0.67,0.90)
1
1
0.78 (0.59,1.03)
P=0.09
0.56 (0.40,0.79)
P=0.001
P<0.001
0.49 (0.30,0.81)
P=0.1
0.85 (0.70,1.02)
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P=0.02
0.81 (0.61,1.07)
P=0.13
0.49 (0.35,0.68)
P<0.001
0.60 (0.42,0.84)
P=0.003
P=0.005
0.72 (0.54,0.94)
0.39 (0.26,0.59)
P<0.001
0.53 (0.32,0.86)
P=0.01
P=0.08
0.80 (0.66,0.98)
P=0.03
0.87 (0.72,1.05)
P=0.15
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WHAT IS ALREADY KNOWN ON THIS SUBJECT
•
Mental ill health and musculoskeletal disorders are the most common diagnoses in people on
long term sick leave.
•
However, the associations between objective measures of health and long term sick leave are
weak
•
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Most research has focussed on occupational risk factors for sickness absence, such as the
psychosocial work environment.
•
Relatively little research has examined the role of individual risk factors
WHAT THIS STUDY ADDS
There is a clear dose-response relationship between lower cognitive function in childhood and
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•
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increased odds of being on long term sick leave in adulthood.
•
This association applies to younger as well as older workers, and holds true irrespective of the
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decade of birth.
This association is mediated in part by education attainment suggesting improved education,
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•
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especially for those with lower cognitive abilities, may help inoculate them from the risk of
long term sickness absence.
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CONTRIBUTORS
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Henderson, Hotopf and Stansfeld conceived the study. Henderson Hotopf and Richards analysed the
data. Henderson Hotopf Stansfeld and Richards interpreted the results. Henderson drafted the
manuscript. Hotopf Stansfeld and Richards critically revised the manuscript for important intellectual
content.
All authors approved the final version.
Henderson is the guarantor.
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Page 25 of 28
ETHICAL APPROVAL
Not required for this study.
ACKNOWLEDGEMENTS
We are grateful to all the participants of each cohort study. We acknowledge the support of Imran
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Shah at the National Survey of Health and Development in providing us with data.
FUNDING
ee
Dr Henderson received support from a Medical Research Council Research Training Fellowship in
Health Services and Health of the Public Research. He is now supported by the NIHR Biomedical
rr
Research Centre BRC Nucleus jointly funded by the Guys and St Thomas’ Charity and the South
London and Maudsley Trustees. Professor Hotopf is supported by the NIHR Biomedical Research
ev
Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and Institute of
Psychiatry, Kings College London.
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All authors confirm that this research was carried out independent of the funders.
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BMJ Open
RESEARCH CHECKLIST: The association between childhood cognitive ability and long term sickness absence in 3
British birth cohorts
Title and abstract
Introduction
Background/rationale
Objectives
Methods
Study design
Setting
Item
No
1
2
Recommendation
(a) Indicate the study’s design with a commonly used term in the title or the
abstract
2
Explain the scientific background and rationale for the investigation being
reported
3-4
3
State specific objectives, including any prespecified hypotheses
4
4
Present key elements of study design early in the paper
4
5
Describe the setting, locations, and relevant dates, including periods of
recruitment, exposure, follow-up, and data collection
6
(a) Give the eligibility criteria, and the sources and methods of selection of
participants. Describe methods of follow-up
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Participants
Page no.
in paper
1
(b) Provide in the abstract an informative and balanced summary of what
was done and what was found
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4-7
4-5
Author note: Our study used data from 3 British birth cohorts, all of which
have been extensively investigated and reported on
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(b) For matched studies, give matching criteria and number of exposed and
unexposed
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NA
Variables
7
Clearly define all outcomes, exposures, predictors, potential confounders,
and effect modifiers. Give diagnostic criteria, if applicable
Data sources/
measurement
8*
For each variable of interest, give sources of data and details of methods of
assessment (measurement). Describe comparability of assessment methods
if there is more than one group
5-7
Bias
9
Describe any efforts to address potential sources of bias
9-10
Study size
10
Explain how the study size was arrived at
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Author note: we used data from 3 well established birth cohorts and have
Quantitative
variables
11
Statistical methods
12
cited detailed descriptions of each
Explain how quantitative variables were handled in the analyses. If
applicable, describe which groupings were chosen and why
6-7
(a) Describe all statistical methods, including those used to control for
confounding
7
(b) Describe any methods used to examine subgroups and interactions
n/a
(c) Explain how missing data were addressed
7
(d) If applicable, explain how loss to follow-up was addressed
7
(e) Describe any sensitivity analyses
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None
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Results
Participants
13*
(a) Report numbers of individuals at each stage of study—eg numbers
potentially eligible, examined for eligibility, confirmed eligible, included in
the study, completing follow-up, and analysed
8
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Author note: we cite “About the cohort” papers for all 3 cohorts in addition
to Professor Wadsworth’s book which provides further information. We
would happily include further information in the paper if required but with 3
birth cohorts we felt this was too much
Descriptive data
14*
(a) Give characteristics of study participants (eg demographic, clinical,
social) and information on exposures and potential confounders
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Fo
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(b) Indicate number of participants with missing data for each variable of
interest
(c) Summarise follow-up time (eg, average and total amount)
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n/a
Outcome data
15*
Report numbers of outcome events or summary measures over time
8
Main results
16
(a) Give unadjusted estimates and, if applicable, confounder-adjusted
estimates and their precision (eg, 95% confidence interval). Make clear
which confounders were adjusted for and why they were included
13
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(b) Report category boundaries when continuous variables were categorized
NA
(c) If relevant, consider translating estimates of relative risk into absolute
risk for a meaningful time period
NA
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Other analyses
17
Report other analyses done—eg analyses of subgroups and interactions, and
sensitivity analyses
None
Discussion
Key results
18
Summarise key results with reference to study objectives
8-9
Limitations
19
Discuss limitations of the study, taking into account sources of potential bias
or imprecision. Discuss both direction and magnitude of any potential bias
9-10
Interpretation
20
Give a cautious overall interpretation of results considering objectives,
limitations, multiplicity of analyses, results from similar studies, and other
relevant evidence
11-12
Generalisability
21
Discuss the generalisability (external validity) of the study results
11-12
Other information
Funding
22
Give the source of funding and the role of the funders for the present study
and, if applicable, for the original study on which the present article is based
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*Give information separately for exposed and unexposed groups.
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BMJ Open
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and
published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely
available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is
available at http://www.strobe-statement.org.
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Page 28 of 28
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The association between childhood cognitive
ability and adult long-term sickness absence in
three British birth cohorts: a cohort study
Max Henderson, Marcus Richards, Stephen Stansfeld and Matthew Hotopf
BMJ Open 2012 2:
doi: 10.1136/bmjopen-2011-000777
Updated information and services can be found at:
http://bmjopen.bmj.com/content/2/2/e000777
These include:
Supplementary Supplementary material can be found at:
Material http://bmjopen.bmj.com/content/suppl/2012/04/10/bmjopen-2011-000777.
DC1.html
References
This article cites 27 articles, 18 of which you can access for free at:
http://bmjopen.bmj.com/content/2/2/e000777#BIBL
Open Access
This is an open-access article distributed under the terms of the Creative
Commons Attribution Non-commercial License, which permits use,
distribution, and reproduction in any medium, provided the original work is
properly cited, the use is non commercial and is otherwise in compliance with
the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and
http://creativecommons.org/licenses/by-nc/2.0/legalcode.
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