Social networks and social support are supposed to contribute to the development of unequal health within populations. However, little is known about their socio-economic distribution. In this study, we explore this distribution. This study analyses the association of two indicators of socio-economic position, education and income, with different measures of social networks and support. Cross-sectional data have been derived from the baseline examination of an epidemiological cohort study of 4.814 middle aged urban inhabitants in Germany (Heinz Nixdorf Recall Study). Bivariate and multivariate logistic regression analysis were carried out to estimate the risk of having poor social networks and support across socio-economic groups. Socially disadvantaged persons more often report poor social networks and social support. In multivariate analyses, based on education, odds ratios range from 1.0 (highest education) to 4.9 (lowest education) in a graded way. Findings based on income show similar effects, ranging from 1.0 to 2.5. There is one exception: no association of SEP with close ties living nearby and regularly seen was observed. Poor social networks and low social support are more frequent among socio-economically disadvantaged people. To some extent, this finding varies according to the indicator chosen to measure these social constructs.

Previous studies have shown that deprived neighbourhoods have higher cardiovascular mortality and morbidity rates. Inequalities in the distribution of behaviour related risk factors are one possible explanation for this trend. In our study, we examined the association between cardiovascular risk factors and neighbourhood characteristics. To assess the consistency of associations the design is cross-national with data from nine industrial towns from the Czech Republic and Germany. We combined datasets from two population based studies, one in Germany ('Heinz Nixdorf Recall (HNR) Study'), and one in the Czech Republic ('Health, Alcohol and Psychosocial Factors in Eastern Europe (HAPIEE) Study'). Participation rates were 56% in the HNR and 55% in the HAPIEE study. The subsample for this particular analysis consists of 11,554 men and women from nine German and Czech towns. Census based information on social characteristics of 326 neighbourhoods were collected from local administrative authorities. We used unemployment rate and overcrowding as area-level markers of socioeconomic status (SES). The cardiovascular risk factors obesity, hypertension, smoking and physical inactivity were used as response variables. Regression models were complemented by individual-level social status (education) and relevant covariates. Smoking, obesity and low physical activity were more common in deprived neighbourhoods in Germany, even when personal characteristics including individual education were controlled for. For hypertension associations were weak. In the Czech Republic associations were observed for smoking and physical inactivity, but not for obesity and hypertension when individual-level covariates were adjusted for. The strongest association was found for smoking in both countries: in the fully adjusted model the odds ratio for 'high unemployment rate' was 1.30 [95% CI 1.02–1.66] in the Czech Republic and 1.60 [95% CI 1.29–1.98] in Germany. In this comparative study, the effects of neighbourhood deprivation varied by country and risk factor; the strongest and most consistent effects were found for smoking. Results indicate that area level SES is associated with health related lifestyles, which might be a possible pathway linking social status and cardiovascular disease. Individual-level education had a considerable influence on the association between neighbourhood characteristics and risk factors.

Social relations have repeatedly been found to be an important determinant of health. However, it is unclear whether the association between social relations and health is consistent throughout different status groups. It is likely that health effects of social relations vary in different status groups, as stated in the hypothesis of differential vulnerability. In this analysis we explore whether socioeconomic status (SES) moderates the association between social relations and health. In the baseline examination of the Heinz Nixdorf Recall study, conducted in a dense populated Western German region (N = 4,814, response rate 56%), SES was measured by income and education. Social relations were classified by using both structural as well as functional measures. The Social Integration Index was used as a structural measure, whilst functional aspects were assessed by emotional and instrumental support. Health was indicated by self-rated health (1 item) and a short version of the CES-D scale measuring the frequency of depressive symptoms. Based on logistic regression models we calculated the relative excess risk due to interaction (RERI) which indicates existing moderator effects. Our findings show highest odds ratios (ORs) for both poor self-rated health and more frequent depressive symptoms when respondents have a low SES as well as inappropriate social relations. For example, respondents with low income and a low level of social integration have an OR for a high depression score of 2.85 (95% CI 2.32-4.49), compared to an OR of 1.44 (95% CI 1.12-1.86) amongst those with a low income but a high level of social integration and an OR of 1.72 (95% CI 1.45-2.03) amongst respondents with high income but a low level of social integration. As reference group those reporting high income and a high level of social integration were used. The analyses indicate that the association of social relations and subjective health differs across SES groups as we find moderating effects of SES. However, results are inconsistent as nearly all RERI scores are positive but do not reach a significant level. Also moderating effects vary between women and men and depending on the indicators of SES and social relations used. Thus, the hypothesis of differential vulnerability can only partially be supported. In terms of practical implications, psychosocial and health interventions aiming towards the enhancement of social relations should especially consider the situation of the socially deprived.

Socio economic inequalities in adult health behaviour are consistently observed. Despite a well-documented pattern, social determinants of variations in health behaviour have not been sufficiently clarified. This article therefore presents sociological pathways to explain the existing inequalities in health behaviour. At a micro level, control beliefs have been part of several behavioural theories. We suggest that these beliefs might bridge the gap between sociology and psychology by emphasising their roots in fundamental socio-economic environments. At a meso level, social networks and support have not been explicitly considered as behavioural determinants. This contribution states that these social factors influence health behaviour while being unequally distributed across society. At a macro level, characteristics of the neighbourhood environment influence health behaviour of its residents above and beyond their individual background. Providing further opportunity for policy makers, it is shown that peer and school context equalise inequalities in risky behaviour in adolescence. As a conclusion, factors such as control expectations, social networks, neighbourhood characteristics, and school context should be included as strategies to improve health behaviour in socially disadvantaged people.