Epidemiologic Study on Social Determinants of Health: What’s Next?

In this issue, Kachi et al have reported novel evidence on health inequalities among young Japanese children and adolescents, showing that overweight is more prevalent among children who are socioeconomically disadvantaged in terms of parental income, expenditure, occupation, and education.1 The results are not surprising, as they are similar to data from other parts of the world, but the key message we should take from the results is that Japan—a country long considered an egalitarian society—is not an exception. In its final report, the World Health Organization’s (WHO) Commission on Social Determinants of Health provided three essential policy recommendations.2 The first one concerns “improving daily living conditions” by addressing “the wellbeing of girls and women and the circumstances in which their children are born, put[ting] major emphasis on early child development and education for girls and boys+”. Although we still do not know whether health inequalities among Japanese children have widened or narrowed in recent decades, nor the potential macro-socioeconomic determinants of such trends, epidemiology and public health should go beyond health policy, dealing with wider social environments and policies that determine health. It is time to start managing health inequalities among Japanese children at a higher level. The WHO report also recommends that we “measure and understand the problem and assess the impact of action”. The analysis by Kachi et al provides a good example of how such measurement or monitoring of health inequality is possible using data created from the individual linkage of multiple governmental surveys. Although the data were reported as an academic finding published in a peer-reviewed journal, this kind of health inequality monitoring should become a routine annual public endeavour, with which any governmental policy reforms can be evaluated from the perspective of health inequalities.3 For example, recent policy reforms that may directly and indirectly affect child health, including the establishment of the Child Poverty Act in 2013 and recent modifications of the child allowance policy, can be evaluated. Nevertheless, the current condition of available secondary data from governmental surveys presents some critical challenges. For example, Kachi et al linked two national surveys to use both health and socioeconomic variables. They linked two datasets using their original individual identification (ID) codes, which were created with information on respondents’ area of residence, sex, age, household identification number, and within-household ordered number of its members. Unfortunately, this approach could suffer from linkage errors due to the existence of multiple same-age household members within a household and incidental incorrect numbering of household members between the two surveys. Other potential limitations include the small sample size and large amounts of missing data, which may make the results less representative. The solution to these challenges is very simple and remarkably effective: use national personal ID numbers. For example, the forthcoming ‘My Number’ system, which is a new Japanese tax and social security ID system, can be used for epidemiologic research purposes. Nordic states are the global leaders in terms of the application of such identity systems in scientific research; there are many examples that demonstrate that the use of such individual ID-based data linkage is effective in monitoring health inequality over time.4 Use of large national datasets is also very important when evaluating health issues among minorities. In Japan, for example, evidence of the health statuses of immigrants, sexual minorities, and people who are extremely poor and socially isolated is scarce because of the difficulty in capturing data on those populations through regular sampling surveys. Reliable healthcare databases (eg, health insurance claims and clinical registries) should also be useful for monitoring health inequality across subpopulations if they are individually