Do health behaviour and psychosocial risk factors explain the European east-west gap in health status?

BACKGROUND: Mortality rates are much more favourable in Western European countries than in those of Eastern Europe. Health behaviour and psychosocial factors have been suggested to be important contributors to East-West differences in mortality and health status. METHODS: To compare reported health status as well as health behaviours and psychosocial factors which may be related to unequal health status in different parts of Europe, standardised postal surveys of representative populations samples were conducted in six Eastern and Western European areas. RESULTS: Higher mortality in the eastern populations was associated with more reported morbidity and generally more negative health ratings. Health behaviours and psychosocial factors were also more negative in the East. Multivariate analyses suggested that the East-West difference in health status may be partly explained by differences in health behaviours and psychosocial factors. CONCLUSION: Efforts to promote health in Eastern Europe should concentrate both on the promotion of healthier lifestyles and on improvement of social and economic conditions.     

Do risk factors and health behaviours contribute to self-ratings of health?

This study examined the relative importance of five risk factors and health behaviours (namely dietary habits, leisure time exercise, smoking, alcohol consumption and body mass index) on self-ratings of health among the Swedish adult population. The data come from the 1991 Swedish Level of Living Survey, a face-to-face survey interview based on a sample representative of the Swedish population aged between 18 and 75 years (n = 5306). The analyses were carried out using logistic regression analysis. With the exception of the consumption of dietary fat, all the risk factors and health behaviours studied were associated with self-rated health. When they were adjusted for health problems and functional limitations most of the associations weakened or disappeared altogether, but smoking and use of vegetables in the diet were still associated with self-rated health. Self-ratings of young adults (18-34 years) were found to be related to body mass index even when health problems were adjusted for, with both obesity and underweight contributing to less than good self-rated health. The results indicate that risk factors and health behaviours do not, in general, directly contribute to self-ratings of health. Instead, their effect is mediated by more specific health problems and their functional consequences. However, smoking and not consuming vegetables, as well as obesity and underweight among young respondents, were found to have an independent association with self-rated health. This may reflect the effects of health problems not captured by our indicators of ill health, but may also indicate that risk factors and risky behaviours are considered to have an effect on one's perceived health even in the absence of health consequences.     

Widening of a social gradient in obesity risk? German national health surveys 1990 and 1998

Objective Whether differences in obesity prevalences across social status levels have widened remains controversial. Methods We used German national health surveys (1990–1992 and 1998, n = 7,466 and 5,583, age 25–69 years) to estimate obesity prevalences and its associations with calendar year, age (25–39, 40–60, and 61–69), and educational level (low, middle, and high), as well as an interaction term (year × educational level) in men and women. We used multiple regression models, considering the sample design. Results Obesity prevalence in 1990 and 1998 was 18.1 (95% CI 16.5–19.7) and 19.9 (18.2–21.6) in men and 20.9 (19.2–22.6) and 21.6 (19.3–23.7) in women, with statistically significantly higher prevalences in higher age and lower education. A statistically significant increase of obesity prevalence was present only in men after adjustment for age and education. The increase seems to be highest in high-educated subjects. However, interaction was not statistically significant, except in middle compared to high-educated men (OR 0.67; 0.47–0.96). Conclusions Obesity prevalence increased only moderately in Germany between 1990–1992 and 1998. There was a tendency of reduction of the social gradient in obesity instead of a widening.     

Do social policies and political context matter for health in the United Kingdom?

This U.K. case study combines lessons from historical assessments with new empirical analyses of trends over the last decade to inform an appraisal of the impact of social actions on health. The empirical analyses examine life expectancy in the 354 local government councils in England by first identifying those that have better or worse health than expected fromtheir socioeconomic profile, and then selecting paired sets of "overachievers" and "underachievers" for more in-depth analysis. The findings taken as a whole provide evidence that social policies and political context do indeed matter for health. The historical material from the first industrial revolution, in particular, provides some of the most compelling evidence for this proposition. The empirical analyses over the last decade found a very powerful inverse association: the more deprived the local council, the lower the life expectancy of the population within that locality. However, even for the same level of deprivation and socioeconomic characteristics, some councils were doing much better than others in terms of health: for example, more than three years difference in life expectancy for carefully matched "urban fringe" councils. The article then examines the councils' political makeup and hence their likely policy perspective.     

Do income effects mask social and behavioural factors when looking at universal health care provision?

Summary Objectives: To investigate whether permanent and transitory income effects mask the impact of unobservable factors on the uptake of health check-ups in Britain. Methods: We used a secondary data representative of the British population, the British Household Panel Survey. Outcome variables included uptake of dental health check-ups, eyesight tests, blood pressure checks, cholesterol tests, mammograms and cervical smear tests. Transitory income was measured as monthly household income and permanent income as average income over 13 years. Estimation method applied dynamic random effect probit model. Results: Results showed the absence of permanent and transitory effects on the uptake of eyesight tests, cholesterol tests, mammograms and cervical smear tests. Permanent income was associated with dental check-ups and transitory income with uptake of blood pressure tests. Conclusions: The presence of income effects on the uptake of blood pressure checks may be due to factors associated with income, such as stress or lifestyles, rather than income per se. A permanent income effect on dental health care in Britain, which is not free of charge, could indicate the possibility of economic constraints to service uptake, but it does not guarantee that income is the only factor that matters as there may important cultural and behavioural barriers. Submitted: 8 August 2006; Revised: 18 April 2007; Accepted 18 July 2007     

Do measures of self-reported morbidity bias the estimation of the determinants of health care utilisation?

Most national surveys of health care utilisation capture only self-reported measures of morbidity. If self-reported morbidity is measured with error, then the results of applied work may be misleading. In this paper we propose a model of the relationship between morbidity and health service utilisation which allows for reporting errors and simultaneity. Errors in self-reported morbidity are expressed as a function of person-specific reporting thresholds and recent contact with health services, arising because of better self-evaluation of current health status or a desire to justify consumption of a publicly-provided good. We demonstrate the bias in ignoring the potential problems of reporting errors and simultaneity for a variety of special cases, but in the general case the biases are of ambiguous sign. The empirical nature of these biases is investigated using limiting long-standing illness (LLI) and recent contact with a General Practitioner (GP) in two waves of The UK Health and Lifestyle Survey. Biomedical measures of functioning are used as objective indicators of health status. We find evidence of substantial and significant differences between individuals in reporting thresholds and some evidence that the reporting of LLI may depend on recent visits to a GP. Adjustments for these biases significantly increase the estimated effect of morbidity on utilisation.     

Does the primary school attended influence self-reported health or its risk factors in later life? Aberdeen Children of the 1950s Study

BACKGROUND: Adult health and its determinants are influenced by the environment in childhood. The school attended is known to affect the health behaviours of pupils while still at school. Little is known about the long-term influence of school attended on health. METHODS: A total of 7,095 respondents (mean age 47 years) to a follow-up questionnaire who attended primary school in Aberdeen, UK, provided information on self-reported health; self-reported high blood pressure; GHQ-4; smoking status; alcohol intake; and obesity. Variance partition coefficients (VPCs) summarized the variation in adult health outcomes and behaviours across schools. Multilevel logistic regression was used to estimate the contribution of school to variation in the outcomes taking into account individual-level and school-level factors. RESULTS: There was some variation across schools in the proportion of adults reporting poor self-rated health (VPC = 0.020) and smoking (0.019). Higher VPCs were found for factors potentially confounded with school: paternal social classes (I&II) (0.45) and gender (0.44). Age at leaving secondary education (0.28) and income (0.10) varied across schools. The effects of primary school diminished after adjusting for individual-level childhood risk factors. The further addition of adult risk factors attenuated these childhood effects. After full adjustment there was no effect of the primary school attended for high blood pressure, current smoking, alcohol intake, and obesity, and negligible effects for the other outcomes. CONCLUSIONS: Contrary to our expectations, we found little evidence of any relationship between primary school and adult self-reported health or behaviour. This is surprising given the extent to which characteristics known to be associated with adult health were clustered within schools.     

Do the wealthy have a health advantage? Cardiovascular disease risk factors and wealth

The use of wealth as a measure of socioeconomic status (SES) remains uncommon in epidemiological studies. When used, wealth is often measured crudely and at a single point in time. Our study explores the relationship between wealth and three cardiovascular disease (CVD) risk factors (smoking, obesity and hypertension) in a US population. We improve upon existing literature by using a detailed and validated measure of wealth in a longitudinal setting. We used four waves of data from the Panel Study of Income Dynamics (PSID) collected between 1999 and 2005. Inverse probability weights were employed to control for time-varying confounding and to estimate both relative (risk ratio) and absolute (risk difference) measures of effect. Wealth was defined as inflation-adjusted net worth and specified as a six category variable: one category for those with less than or equal to zero wealth and quintiles of positive wealth. After adjusting for income and other time-varying confounders, as well as baseline covariates, the risk of becoming obese was inversely related to wealth. There was a 40%-89% higher risk of becoming obese among the less wealthy relative to the wealthiest quintile and 11 to 25 excess cases (per 1000 persons) among the less wealthy groups over six years of follow up. Smoking initiation had similar but more moderate effects; risk ratios and differences both revealed a smaller magnitude of effect compared to obesity. Of the three CVD risk factors examined here, hypertension incidence had the weakest association with wealth, showing a smaller increased risk and fewer excess cases among the less wealthy groups. In conclusion, this study found a strong inverse association between wealth and obesity incidence, a moderate inverse association between wealth and smoking initiation and a weak inverse association between wealth and hypertension incidence after controlling for income and other time-varying confounders.     

The association of earnings with health in middle age: Do self-reported earnings for the previous year tell the whole story?

Research on earnings and health frequently relies on self-reported earnings (SRE) for a single year, despite repeated criticism of this measure. We use 31 years (1961–1991) of earnings recorded by the United States Social Security Administration (SSA) to predict the 1992 prevalence of disability, diabetes, stroke, heart disease, cancer, depression and death by 2002 in a subset of Health and Retirement Study participants (n = 5951). We compare odds ratios (ORs) for each health outcome associated with self-reported or administratively recorded earnings. Individuals with no 1991 SSA earnings had worse health in multiple domains than those with positive earnings. However, this association diminished as the time lag between earnings and health increased, so that the absence of earnings before approximately 1975 did not predict health in 1992. Among those with positive earnings, lengthening the lag between SSA earnings and health did not significantly diminish the magnitude of the association with diabetes, heart disease, stroke, or death. Longer lags did reduce but did not eliminate the association between earnings and both disability and depression. Despite theoretical limitations of single year SRE, there were no statistically significant differences between the ORs estimated with single-year SRE and those estimated with a 31-year average of SSA earnings. For example, a one unit increase in logged SRE for 1991 predicted a 19% reduction in the odds of dying by 2002 (OR = 0.81; 95% confidence interval: 0.72,0.90), while a similar increase in average SSA earnings for 1961–1991 had an OR of 0.72 (0.63, 0.82). The point estimates for the OR associated with 31 year average SSA earnings were further from the null than the ORs associated with single year SRE for heart disease, depression, and death, and closer to the null for disability, diabetes, and stroke, but none of these differences was statistically significant.     

Do changes in effort-reward imbalance at work contribute to an explanation of the social gradient in angina?

Aims: To determine whether an increase in effort-reward imbalance over time increases the risk of angina, and whether such increases are associated with lower occupational position.

Methods: Effort-reward imbalance (ERI) at work was measured in the Whitehall II occupational cohort of London based civil servants at baseline (1985–88) and in 1997. Coronary heart disease was measured in a self-reported health questionnaire by combining the Rose Angina Questionnaire with doctor diagnosed angina in 2001.

Results: Among men, increase in ERI over time was associated with an increased risk of incident angina. Moreover, as increases in ERI were more common among lower grade civil servants, change in imbalance, to some extent, contributed to explaining the social gradient in angina. Among women, increases in imbalance were not associated with risk of angina, and therefore did not contribute to the explanation of the social gradient.

Conclusions: Reductions in effort-reward imbalance at work may reduce the risk of coronary heart disease among men.

     

Do health behaviors mediate the association between social capital and health?

INTRODUCTION: There is increasing evidence that social capital is important for people's health. However, there is still considerable disagreement about the specific pathways that links social capital to health. This study investigates the hypothesis that the association between social capital and health is mediated by people's health behaviors. METHOD: Data from the 2002 Health Survey for England (n = 7394) were used and analyzed from a multilevel perspective. The association between social capital and self-rated health were examined before and after controlling for smoking, alcohol intake, and fruit/vegetable consumption. RESULTS: Social capital was found to be associated with self-rated health, as well as with the different health behaviors. In addition, the health behaviors were significantly related to self-rated health. However, controlling for smoking, alcohol intake, and fruit/vegetable consumption did not substantially affect the association between social capital and self-rated health. CONCLUSIONS: The results demonstrate that social capital and support are important determinants of self-rated health and health behaviors. But only limited support was found for the hypothesis that health behaviors mediate the association between social capital and health.     

Can patient self-management explain the health gradient? Goldman and Smith's “Can patient self-management help explain the SES health gradient?” (2002) revisited

In their much-cited paper, “Can patient self-management help explain the SES health gradient?” Goldman and Smith (2002) use samples of diabetic and HIV+ patients in the United States to conclude that disease self-management is an important explanation for the much-documented positive gradient in education and health outcomes. In this paper, I revisit their analysis and point to some fundamental difficulties in interpreting their results as conclusive evidence in favor of self-management. I also argue that for individuals for whom self-management might be expected to matter –i.e. populations of patients managing complex conditions – economic factors such as resource availability and insurance access might be a more important mechanism behind the gradient than medical compliance. The impact of self-management, though it might matter, is likely to be small.     

The dynamics of income and neighborhood context for population health: Do long-term measures of socioeconomic status explain more of the black/white health disparity than single-point-in-time measures?

Socioeconomic status, though a robust and strong predictor of health, has generally been unable to fully explain the health gap between blacks and whites in the United States. However, at both the individual and neighborhood levels, socioeconomic status is often treated as a static factor with only single-point-in-time measurements. These cross-sectional measures fail to account for possible heterogeneous histories within groups who may share similar characteristics at a given point in time. As such, ignoring the dynamic nature of socioeconomic status may lead to the underestimation of its importance in explaining health and racial health disparities.     

Alkylphenols in the environment: a risk for human health?

Endocrine Disrupting Chemicals (ECD) are a class of chemical compounds widely utilized for many industrial and civil applications and, consequently, widely diffused in the environment. Due to their chemical-physical characteristics, ECD may interfere with several endocrine functions in humans. Alkylphenols (APs), mainly produced by biodegradation of alkylphenols polyethoxylates surfactants, are a relevant group of ECD, both for their environmental diffusion and demonstrated estrogenic activity. Aim of this paper is to assess the potential risk of exposure to APs for humans, on the basis of the available data in literature concerning APs: environmental levels, accumulation in sediments and biota, toxicological effects on experimental animals.     

Does area-based social capital matter for the health of Australians? A multilevel analysis of self-rated health in Tasmania

BACKGROUND: Material circumstances and collective psychosocial processes have been invoked as potential explanations for socioeconomic inequalities in health; and, linking social capital has been proposed as a way of reconciling these apparently opposing explanations. METHODS: We conducted multilevel logistic regression of self-rated health (fair or poor vs excellent, very good, or good) on 14 495 individuals living within 41 statistical local areas who were respondents to the 1998 Tasmanian Healthy Communities Study. We modelled the effects of area-level socioeconomic disadvantage and social capital (neighbourhood integration, neighbourhood alienation, neighbourhood safety, social trust, trust in public/private institutions, and political participation), and adjusted for the effects of individual characteristics. RESULTS: Area-level socioeconomic disadvantage was associated with poor self-rated health (beta = 0.0937, P < 0.001) an effect that was attenuated, but remained significant, after adjusting for individual characteristics (beta = 0.0419, P < 0.001). Social trust was associated with a reduction in poor self-rated health (beta = -0.0501, p = 0.008) and remained significant when individual characteristics (beta = -0.0398, P = 0.005) were included. Political participation was non-significant in the unadjusted model but became significant when adjusted for individual characteristics (beta = -0.2557, P = 0.045). The effects of social trust and political participation were attenuated and became non-significant when area-level socioeconomic disadvantage was included. CONCLUSION: Area-based socioeconomic disadvantage is a determinant of self-rated health in Tasmania, but we did not find an independent effect of area-level social capital. These findings suggest that in Tasmania investments in improving the material circumstances in which people live are likely to lead to greater improvements in population health than attempts to increase area-level social capital.     

Self-assessed health and mortality: could psychosocial factors explain the association?

BACKGROUND: The single-item question of self-assessed health has consistently been reported to be associated with mortality, even after controlling for a wide range of health measurements and known risk factors for mortality. It has been suggested that this association is due to psychosocial factors which are both related to self-assessed health and to mortality. We tested this hypothesis. METHODS: The study was carried out in a subsample (n = 5667) of the GLOBE-population, a prospective cohort study conducted in the southeastern part of the Netherlands. Data on self-assessed health, sociodemographic variables, various aspects of health status, behavioural risk factors, and a number of psychosocial factors (social support, psychosocial stressors, personality traits, and coping styles) were collected by postal survey and structured interview in 1991, and mortality data were collected between 1991 and 1998. Cox proportional hazards analyses were used to calculate the association between self-assessed health and mortality, before and after controlling for the psychosocial variables. RESULTS: After controlling for sociodemographic variables, various aspects of health status, and behavioural risk factors, self-assessed health is still strongly associated with mortality in our dataset (Relative Risk [RR] of dying for 'poor' versus 'very good' self-assessed health = 3.98; 95% CI: 1.65-9.61). After controlling for the same set of confounders, many of the psychosocial variables are statistically significantly associated with a 'less-than-good' self-assessed health, particularly instrumental social support, long-lasting difficulties, neuroticism, and locus of control. However, only 'disclosure of emotions'-coping style has a statistically significant relationship with mortality. Adding the psychosocial variables to a model already containing self-assessed health does not attenuate the association between self-assessed health and mortality. CONCLUSIONS: We did not find indications that the association between self-assessed health and mortality is due to the psychosocial factors included in this analysis. It seems likely that the unexplained mortality effects of self-assessed health are due to the fact that self-assessed health is a very inclusive measure of health reflecting health aspects relevant to survival which are not covered by other health indicators.