Previous studies on health and socio-economic determinants of later-life labour force participation have mainly come from high-income European countries and the United States of America (USA). Findings vary between studies due to different measures of socio-economic status and labour force outcomes. This study investigated longitudinal associations of physical incapacity and wealth with remaining in paid employment after age 60 in middle- and high-income countries. Using harmonised cohort data in the USA, England, Japan, Mexico and China (N = 32,132), multilevel logistic regression was applied for main associations. The age-related probabilities of remaining in paid employment by physical incapacity and wealth were estimated using marginal effects. This study found that physical incapacity predicted lower odds of remaining in paid employment in each country. Wealth was associated with higher odds of remaining in paid employment in the USA, England and Japan, but not in Mexico. Probabilities of remaining in paid employment were high in Mexico but low in China. The absolute difference in the probability of remaining in paid employment between the richest and the poorest groups was greater in the USA than that in any other country. In the USA, England and Japan, the inverse association between physical incapacity and remaining in paid employment could be partially compensated by wealth only when physical incapacity was not severe. National policies, including considering older adults’ changing capacities for job placement and prioritising the provision of supportive services for socio-economically disadvantaged older adults, developing pathways for informal workers to access social security and pension coverage, and encouraging employers to hire socio-economically disadvantaged older workers and enhancing their employability, could be facilitated. Future studies, such as exploring health and socio-economic determinants of remaining in part-time and full-time paid employment separately in more countries, and the moderating effects of relevant policies on these associations, are needed.

The evidence, which is summarised in this editorial, shows that the circumstances in which people are born, grow, live, work and age are powerful determinants of health and of the unfair distribution of health – health inequity. Discrimination against people with mental illness shows how the relation can go the other way: for example, when people with mental ill health cannot get back into work.

On August 28, 2008, Michael Marmot, Chair of the Commission on Social Determinants of Health, formally handed over the Commission’s Final Report to Margaret Chan, the Director-General of the World Health Organization, at the Palais des Nations in Geneva. It was a significant moment. Dr. Chan addressed a hall packed with representatives of the world’s communications media in a speech that was remarkably direct. Dr. Chan reiterated the Commission’s position that to improve health and health equity action needs to be taken not just across the health sector but across all social and economic policy areas, and stated, “Social deprivation is not a matter of fate. It is a marker of policy failure.” This was a bold statement from one of the world’s leading diplomats. Policy failure! The phrase echoes the Commission’s assertion that “a toxic combination of poor social policies, unfair economic arrangements and bad politics is killing people on a grand scale.” The Commission’s messages are far reaching.

From the start, the WHO Commission on Social Determinants of Health built its case for taking action on the social determinants of health, unashamedly, on principles of social justice. Quite simply, the Commission stated that health inequities in the sense of avoidable and preventable differences in health between countries, and between groups within countries according to income, occupation, education, ethnicity or between men and women, are unjust. Taking this position has brought praise and blame: praise for the Commission’s boldness in putting fairness on the global health agenda1 in the face of the dominant global model of economic growth as an end in itself, and blame for the Commission’s unworldliness in apparently not recognising that economic arguments push the political agenda.

At least fourteen cohort studies have documented an inverse association between coffee consumption and risk of type 2 diabetes. We examined the prospective association between coffee and tea consumption and the risk of type 2 diabetes mellitus among British men (n 4055) and women (n 1768) from the Whitehall II cohort. During 11·7 years follow-up there were a total of 387 incident cases of diabetes confirmed by self-report of doctor's diagnosis or glucose tolerance tests. Despite an inverse association between coffee intake and 2 h post-load glucose concentration at the baseline assessment, combined caffeinated and decaffeinated coffee (hazard ratio (HR) 0·80; 95 % CI 0·54, 1·18) or only decaffeinated coffee intake (HR 0·65; 95 % CI 0·36, 1·16) was not significantly associated with diabetes risk at follow-up after adjustment for possible confounders. There was an association between tea intake and diabetes (HR 0·66; 95 % CI 0·61, 1·22; P < 0·05) after adjustment for age, gender, ethnicity and social status, which was not robust to further adjustments. There was, however, an association between combined intake of tea and coffee (two or more cups per day of both beverage) and diabetes (HR 0·68; 95 % CI 0·46, 0·99; P < 0·05) after full adjustment. In conclusion, relatively moderate intake (more than three cups per day) of coffee and tea were not prospectively associated with incidence of type 2 diabetes although there was evidence of a combined effect. The limited range of exposure and beverage consumption according to socio-economic class may explain these conflicting findings.

The health status of populations of the countries of Central and Eastern Europe and the former Soviet Union underwent major changes after the fall of communism. While mortality started declining in Central Europe, mortality in Russia and most other countries of the former Soviet Union rose dramatically and has yet to improve. In terms of the socioeconomic changes, some countries (mainly Central Europe) were able to contain the fall in income and rise in income inequalities, but across the former Soviet Union gross domestic product plummeted and income inequality grew rapidly. This led to two types of inequality: first, the widening gap in mortality between countries, and second, the increasing social gradient in health and disease within countries. The thrust of our argument is that the disadvantages in health in Eastern Europe, and the growing social inequalities in health in the region, are direct results of the social changes, and that psychosocial factors played a pivotal role in the health pattern seen in Central and Eastern Europe.

In the 20th century, European countries had marked declines in mortality rates, initially at younger ages, and subsequently at older ages. This resulted in ‘rectangularization’ of the survival curve: large proportions of the population surviving to older ages, at which point mortality rates increase sharply. The extent to which this will be accompanied by increases in the proportions of older people suffering morbidity has been debated. There are marked differences in life expectancy at older ages among European countries. France, Italy, Spain, and Sweden have better than average life expectancy at age 65. Denmark, Germany, the UK and the Netherlands have lower. Within countries, there are marked socio-economic differences in morbidity and mortality at older ages. The impact of illness is also likely to differ according to an individual's social circumstances. It is essential to have longitudinal studies examining the determinants and impact of health and well-being in ageing populations. Ideally, these should be carried out in a way that facilitates international comparisons

The aim of the present cross-sectional study was to examine the agreement and disagreement between a 7 d diet diary (7DD) and a self-administered machine-readable food-frequency questionnaire (FFQ) asking about diet in the previous year, and to validate both methods with biomarkers of nutrient intake. The subjects were an age- and employment-grade-stratified random subsample of London-based civil servants (457 men and 403 women), aged 39–61 years, who completed both a 7DD and a FFQ at phase 3 follow-up (1991–1993) of the Whitehall II study. Mean daily intakes of dietary energy, total fat, saturated, monounsaturated and polyunsaturated fatty acids, linoleic acid, total carbohydrate excluding fibre, sugars, starch, dietary fibre, protein, vitamin C, vitamin E (as α-tocopherol equivalents), folate, carotenes (as total β-carotene activity), Fe, Ca, Mg, K and alcohol were measured. Serum cholesteryl ester fatty acids (CEFA), plasma α-tocopherol and β-carotene were also measured as biomarkers. Estimates of mean energy intake from the two methods were similar in men, and some 10 % higher according to the FFQ in women. Compared with the 7DD, the FFQ tended to overestimate plant-derived micronutrient intakes (carotenes from FFQ v. 7DD men 2713 (SD 1455) V. 2180 (sd 1188) μg/d, women 3100 (sd 1656) v. 2221 (sd 1180) μg/d, both differences P<0·0001) and to underestimate fat intake. Against plasma β-carotene/cholesterol, carotene intake was as well estimated by the FFQ as the 7DD (Spearman rank correlations, men 0·32 v. 0·30, women 0·27 v. 0·22, all P≤0·0001, energy-adjusted data). Ranking of participants by other nutrient intakes tended to be of the same order according to the two dietary methods, e.g. rank correlations for CEFA linoleic acid against FFQ and 7DD estimates respectively, men 0·38 v. 0·41, women 0·53 v. 0·62, all P≤0·0001, energy-adjusted % fat). For α-tocopherol there were no correlations between plasma level and estimated intakes by either dietary method. Quartile agreement for energy-adjusted nutrient intakes between the two self-report methods was in the range 37–50 % for men and 32–44 % for women, and for alcohol, 57 % in both sexes. Disagreement (misclassification into extreme quartiles of intake) was in the range 0–6 % for both sexes. The dietary methods yielded similar prevalences (about 34 %) of low energy reporters. The two methods show satisfactory agreement, together with an expected level of systematic differences, in their estimates of nutrient intake. Against the available biomarkers, the machine-readable FFQ performed well in comparison with the manually coded 7DD in this study population. For both methods, regression-based adjustment of nutrient intake to mean dietary energy intake by gender appears on balance to be the optimal approach to data presentation and analysis, in view of the complex problem of low energy reporting.