Leaving the labour market later in life. How does it impact on mechanisms for health?

Objectives: Negative associations between non-employment and health among older people are well established and are potentially important for successful ageing. However, opportunities to improve health through re-employment or extending working lives are limited as later-life exits from employment are often unwanted and permanent. We aim to establish a greater understanding of the psychosocial mechanisms underlying non-employment and health associations in older people to identify modifiable pathways through which the negative impact of non-employment can be ameliorated. Methods: Using multilevel analysis of four waves of repeated panel data from a representative sample of 1551 older men and women reaching state retirement age in the West of Scotland from 1987/1988 to 2000/2004, we explored respondents' strength of agreement with 20 statements relating to their self-defined employment status, covering themes of functioning, social engagement, self-esteem, mental engagement, stress, and control and autonomy. Results: Compared with those in employment, respondents who were retired, unemployed, sick/disabled and home makers were more likely to agree that this resulted in poor social engagement, low self-esteem and, with the possible exception of retirees, reduced mental engagement. Associations were particularly marked among unemployed and sick/disabled respondents who also agreed that their status was a source of worry and prevented them from feeling in control. Conclusion: Older people who are not in employment are at higher risk of poor physical and mental health. Interventions targeting psychosocial mechanisms such as social and mental engagement and self-esteem offer potentially valuable opportunities to improve health outcomes and promote successful ageing

Timing of poverty in childhood and adolescent health: Evidence from the US and UK

Childhood poverty is associated with poorer adolescent health and health behaviours, but the importance of the timing of poverty remains unclear. There may be critical or sensitive periods in early life or early adolescence, or poverty may have cumulative effects throughout childhood. Understanding when poverty is most important can support efficient timing of interventions to raise family income or buffer against the effects of low income, but answers may vary across social contexts. The US and the UK are a useful comparison with similar liberal approaches to cash transfers, but very different approaches to healthcare provision. Utilising data from large population studies in the US (n = 9408; born 1979–1996) and UK (n = 1204; born 1991–1997), this study employs a structured life course approach to compare competing hypotheses about the importance of the timing or pattern of childhood exposure to poverty in predicting adolescent health limitations, symptoms of psychiatric distress, and smoking at age 16 (age 15/16 in US). Household income histories identified experience of poverty (measured as <60% of the national median equivalised income for a given year) in early life (ages 0–5), mid-childhood (ages 6–10) and early adolescence (ages 11–15). The Bayesian Information Criterion (BIC) compared fit across models with variables representing different life course patterns of exposure to poverty. Adolescent distress was not associated with poverty in either country. In both countries, however, variables representing cumulative or persistent experiences of poverty exhibited optimal fit of all poverty exposure variables in predicting adolescent smoking and health limitations. There was also evidence of an early life sensitive period for smoking in the US. Poverty was more persistent in the US, but associations between poverty and outcomes were consistent across countries. Although poverty can have cumulative effects on health and behaviour, early interventions may offer the best long-term protection

Trends in population mental health before and after the 2008 recession: a repeat cross-sectional analysis of the 1991-2010 health surveys of England

<p>Objective: To assess short-term differences in population mental health before and after the 2008 recession and explore how and why these changes differ by gender, age and socio-economic position.</p> <p>Design: Repeat cross-sectional analysis of survey data.</p> <p>Setting: England.</p> <p>Participants: Representative samples of the working age (25–64 years) general population participating in the Health Survey for England between 1991 and 2010 inclusive.</p> <p>Main outcome measures: Prevalence of poor mental health (caseness) as measured by the general health questionnaire-12 (GHQ).</p> <p>Results: Age–sex standardised prevalence of GHQ caseness increased from 13.7% (95% CI 12.9% to 14.5%) in 2008 to 16.4% (95% CI 14.9% to 17.9%) in 2009 and 15.5% (95% CI 14.4% to 16.7%) in 2010. Women had a consistently greater prevalence since 1991 until the current recession. However, compared to 2008, men experienced an increase in age-adjusted caseness of 5.1% (95% CI 2.6% to 7.6%, p<0.001) in 2009 and 3% (95% CI 1.2% to 4.9%, p=0.001) in 2010, while no statistically significant changes were seen in women. Adjustment for differences in employment status and education level did not account for the observed increase in men nor did they explain the differential gender patterning. Over the last decade, socio-economic inequalities showed a tendency to increase but no clear evidence for an increase in inequalities associated with the recession was found. Similarly, no evidence was found for a differential effect between age groups.</p> <p>Conclusions: Population mental health in men has deteriorated within 2 years of the onset of the current recession. These changes, and their patterning by gender, could not be accounted for by differences in employment status. Further work is needed to monitor recessionary impacts on health inequalities in response to ongoing labour market and social policy changes.</p&gt

Employment status and income as potential mediators of educational inequalities in population mental health

We assessed whether educational inequalities in mental health may be mediated by employment status and household income. Poor mental health was assessed using General Health Questionnaire ‘caseness’ in working age adult participants (N = 48 654) of the Health Survey for England (2001–10). Relative indices of inequality by education level were calculated. Substantial inequalities were apparent, with adjustment for employment status and household income markedly reducing their magnitude. Educational inequalities in mental health were attenuated by employment status. Policy responses to economic recession (such as active labour market interventions) might reduce mental health inequalities but longitudinal research is needed to exclude reverse causation

Natural experiments: An overview of methods, approaches, and contributions to public health intervention research

Population health interventions are essential to reduce health inequalities and tackle other public health priorities, but they are not always amenable to experimental manipulation. Natural experiment (NE) approaches are attracting growing interest as a way of providing evidence in such circumstances. One key challenge in evaluating NEs is selective exposure to the intervention. Studies should be based on a clear theoretical understanding of the processes that determine exposure. Even if the observed effects are large and rapidly follow implementation, confidence in attributing these effects to the intervention can be improved by carefully considering alternative explanations. Causal inference can be strengthened by including additional design features alongside the principal method of effect estimation.NEstudies often rely on existing (including routinely collected) data. Investment in such data sources and the infrastructure for linking exposure and outcome data is essential if the potential for such studies to inform decision making is to be realized

How does money influence health?

This study looks at hundreds of theories to consider how income influences health. There is a graded association between money and health – increased income equates to better health. But the reasons are debated.<p></p> Researchers have reviewed theories from 272 wide-ranging papers, most of which examined the complex interactions between people’s income and their health throughout their lives.<p></p> Key points<p></p> This research identifies four main ways money affects people’s wellbeing:<p></p> Material: Money buys goods and services that improve health. The more money families have, the better the goods they can buy.<p></p> Psychosocial: Managing on a low income is stressful. Comparing oneself to others and feeling at the bottom of the social ladder can be distressing, which can lead to biochemical changes in the body, eventually causing ill health.<p></p> Behavioural: For various reasons, people on low incomes are more likely to adopt unhealthy behaviours – smoking and drinking, for example – while those on higher incomes are more able to afford healthier lifestyles.<p></p> Reverse causation (poor health leads to low income): Health may affect income by preventing people from taking paid employment. Childhood health may also affect educational outcomes, limiting job opportunities and potential earnings

Comparison of the Rowe?Kahn Model of Successful Aging With Self-rated Health and Life Satisfaction: The West of Scotland Twenty-07 Prospective Cohort Study

Purpose of the Study: With increasing longevity in industrialized populations, there is growing interest in what defines ?successful aging? (SA). Various SA measures have been proposed but no consensus has been reached and many have been criticized for not representing the views and priorities of older people. We consider whether the Rowe?Kahn SA model captures older individual?s perceptions of their own health and aging. Methods: Using two cohorts of 886 and 483 men and women from the West of Scotland Twenty-07 Study, aged around 57 and 76, respectively, we explored associations between Rowe?Kahn SA dimensions (absence of disease/disability; good physical/cognitive functioning; good interpersonal/productive social engagement) and four aspects of self-rated health and satisfaction (current general health; health for age; satisfaction with health; satisfaction with life). Results: Respondents? self-rated health and satisfaction was generally good but few had all six Rowe?Kahn dimensions positive, the conventional definition of SA. All individual positive SA dimensions were associated with better self-rated health and satisfaction. This was consistent across age, gender, manual/nonmanual occupations, and personality. The prevalence of good self-rated health and satisfaction increased with increasing numbers of positive SA dimensions. Implications: The Rowe?Kahn model provides a functional definition of SA. Future work on ageing should include all Rowe?Kahn dimensions and consider SA as a continuum

Insomnia symptoms as a cause of type 2 diabetes incidence: a 20 year cohort study

Background: Insomnia symptoms are associated with type 2 diabetes incidence but are also associated with a range of potential time-varying covariates which may confound and/or mediate associations. We aimed to assess whether cumulative exposure to insomnia symptoms has a causal effect on type 2 diabetes incidence. Methods: A prospective cohort study in the West of Scotland, following respondents for 20 years from age 36. 996 respondents were free of diabetes at baseline and had valid data from up to four follow-up visits. Type 2 diabetes was assessed at the final visit by self-report, taking diabetic medication, or blood-test (HbA1c ≥ 6.5% or 48 mmol/mol). Effects of cumulative insomnia exposure on type 2 diabetes incidence were estimated with traditional regression and marginal structural models, adjusting for time-dependent confounding (smoking, diet, physical inactivity, obesity, heavy drinking, psychiatric distress) as well as for gender and baseline occupational class. Results: Traditional regression yielded an odds ratio (OR) of 1.34 (95% CI: 1.06-1.70) for type 2 diabetes incidence for each additional survey wave in which insomnia was reported. Marginal structural models adjusted for prior covariates (assuming concurrently measured covariates were potential mediators), reduced this OR to 1.20 (95% CI: 0.98-1.46), and when concurrent covariates were also included (viewing them as potential confounders) this dropped further to 1.08 (95% CI: 0.85-1.37). Conclusions: The association between cumulative experience of insomnia and type 2 diabetes incidence appeared confounded. Evidence for a residual causal effect depended on assumptions as to whether concurrently measured covariates were confounders or mediators