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Area-based measures of socioeconomic position (SEP) suitable for epidemiological research are lacking in Switzerland. The authors developed the Swiss neighbourhood index of SEP (Swiss-SEP).

Background: Recent large-scale studies suggest that obesity and overweight may confer protection against future dementia. This observation could, however, be generated by reverse causality. That is, weight loss in the incipient phase of dementia ascribed to diminished self-care, including sub-optimal nutrition, would have the effect of generating such an inverse association. One approach to circumventing this problem would be to measure weight in a population which is young enough to be free of the symptoms of dementia which is then followed up for dementia occurrence over many decades. Methods: In a prospective cohort study, body mass index, and other potential risk factors, were measured in 9547 male university undergraduates (mean age 20.5 years) in 1948-68 who were then linked to national mortality registers. Results: Of 2537 deaths over a mean of 50.6 years follow up, 140 were ascribed to dementia. There was no association between overweight and future dementia deaths at conventional levels of statistical significance (age-adjusted hazard ratio; 95% confidence interval: 0.93; 0.49, 1.79). Conclusion: In this cohort study of former university students, being overweight in youth did not confer protection against later dementia death.

Living in high-rise buildings could influence the health of residents. Previous studies focused on structural features of high-rise buildings or characteristics of their neighbourhoods, ignoring differences within buildings in socio-economic position or health outcomes. We examined mortality by floor of residence in the Swiss National Cohort, a longitudinal study based on the linkage of December 2000 census with mortality and emigration records 2001-2008. Analyses were based on 1.5 million people living in buildings with four or more floors and 142,390 deaths recorded during 11.4 million person-years of follow-up. Cox models were adjusted for age, sex, civil status, nationality, language, religion, education, professional status, type of household and crowding. The rent per m² increased with higher floors and the number of persons per room decreased. Mortality rates decreased with increasing floors: hazard ratios comparing the ground floor with the eighth floor and above were 1.22 [95% confidence interval (CI) 1.15-1.28] for all causes, 1.40 (95% CI 1.11-1.77) for respiratory diseases, 1.35 (95% CI 1.22-1.49) for cardiovascular diseases and 1.22 (95% CI 0.99-1.50) for lung cancer, but 0.41 (95% CI 0.17-0.98) for suicide by jumping from a high place. There was no association with suicide by any means (hazard ratio 0.81; 95% CI 0.57-1.15). We conclude that in Switzerland all-cause and cause-specific mortality varies across floors of residence among people living in high-rise buildings. Gradients in mortality suggest that floor of residence captures residual socioeconomic stratification and is likely to be mediated by behavioural (e.g. physical activity), and environmental exposures, and access to a method of suicide.

Objective: To update a systematic review on the association between childhood socioeconomic circumstances and cause-specific mortality. Studies published since 2003 include a far greater number of deaths than was previously available justifying an update of the previous systematic review. Methods: Individual-level studies examining childhood socioeconomic circumstances and adult overall and cause-specific mortality published between 2003 and April 2007. Results and conclusions: The new studies confirmed that mortality risk for all causes was higher among those who experienced poorer socioeconomic circumstances during childhood. As already suggested in the original systematic review, not all causes of death were equally related to childhood socioeconomic circumstances. A greater proportion of new studies included women and showed that a similar pattern is valid for both genders. In addition, the new studies show that this association persists among younger birth cohorts, despite temporal general improvements in childhood conditions across successive birth cohorts. The difficulties of establishing a particular life-course model were highlighted.

This is the second part of a glossary on indicators of socioeconomic position used in health research (the first part was published in the January issue of the journal).

There is convincing evidence that exposures acting across the life course influence adult health outcomes (1–3). Lifecourse epidemiology examines a range of potential processes through which exposures acting at different stages of life can, singly or in combination, influence disease risk (table 1) (4). In the critical period model, an exposure acting at a specific time has long-lasting effects on the structure or function of the body. The fetal origins hypothesis, in its original formulation, took this approach (5). Other examples of processes where outcomes appear to depend upon the time window during which an exposure acts are limb development (in relation to maternal thalidomide use); infection with hepatitis B and risk of adulthood liver cancer (with very early postnatal infection being most implicated); and environmental lead exposure, which results in serious neurodevelopmental deficits only if occurring in infancy and childhood (3). However, the influence of exposures acting during critical periods of susceptibility may be modified by later life exposures. This is the case for the associations of birth weight with coronary heart disease, high blood pressure, and insulin resistance, where associations are stronger (or only evident) among those who become obese during adolescence or adulthood (6–8).

Objective: In this article we review different measures of socioeconomic position (SEP) and their uses in health-related research. Areas of agreement: Socioeconomic circumstances influence health. Areas of controversy: Generally, poorer socioeconomic circumstances lead to poorer health. This has generated a search for generic mechanisms that could explain such a general association. However, we propose that there is a greater variation in the association between SEP and health than is generally acknowledged when specific health outcomes are investigated. We propose that studying these variations provide a better understanding of the aetiological mechanisms relating specific diseases with specific exposures. Areas to develop research: Using different indicators of SEP in health research can better capture these variations and is important when evaluating the full contribution of confounding by socioeconomic conditions. We propose that using an array of SEP indicators within a life course framework also offers considerable opportunity to explore causal pathways in disease aetiology.

This glossary presents a comprehensive list of indicators of socioeconomic position used in health research. A description of what they intend to measure is given together with how data are elicited and the advantages and limitation of the indicators. The glossary is divided into two parts for journal publication but the intention is that it should be used as one piece. The second part highlights a life course approach and will be published in the next issue of the journal.