Sick countries and sick individuals: reassessing the inferential targets in global health research
Authors: S V Subramanian, Rockli Kim
Journal: The Lancet Global Health (2018)

In 2008, 5 years before the launch of The Lancet Global Health, the number of publications with the keyword “global health” in PubMed was approximately 4950. This number increased to over 8800 per year in 2012. Since 2013, the annual count of publications has increased to 22 800 in 2017. At face value, this trend suggests that The Lancet Global Health with its open access model might have served as a catalyst for research productivity and visibility in the field of global health. Most public health research focuses on drawing inference about a target population. Although the scope of global health includes “both prevention in populations and clinical care of individuals”,1Koplan JP Bond TC Merson MH et al.Towards a common definition of global health.Lancet. 2009; 373: 1993-1995Summary Full Text Full Text PDF PubMed Scopus (841) Google Scholar most empirical research implicitly or explicitly defines the target population of interest as a country or countries. However, it is crucial to remember that all aspects of illness, disease, and wellbeing are ultimately personal. For most health outcomes, an average at the country-level serves as a marker of general wellbeing in a population, with little intrinsic meaning at the country-level. Even as a marker, relying only on averages is misleading, given the large variation that exist between individuals within a country (hereafter referred to as between-individuals).2Subramanian S Kim R Christakis NA The “average” treatment effect: a construct ripe for retirement. A commentary on Deaton and Cartwright.Soc Sci Med. 2018; (published online Apr 19.)DOI:10.1016/j.socscimed.2018.04.027Crossref Scopus (32) Google Scholar In this Comment, we argue for reassessment of the idea of countries (or more generally, populations, including subnational aggregations or social groupings) as the sole target of scientific inference in global health research. Empirical investigation of BMI distribution across countries, for example, shows that an increase in mean BMI in a country seems to be accompanied by substantial increases in between-individual variation over time.3Razak F Corsi DJ Subramanian S Change in the body mass index distribution for women: analysis of surveys from 37 low-and middle-income countries.PLoS Med. 2013; 10: e1001367Crossref PubMed Scopus (58) Google Scholar At any point in time, between-individual variation also seems to differ systematically across socioeconomic and demographic groupings within countries.4Kim R, Kawachi I, Coull BA, Subramanian SV. Contribution of socioeconomic factors to explaining variation in body mass index: an analysis of 1 212 758 women from 58 low- and middle-income countries. Lancet Glob Health In press.Google Scholar, 5Kim R Kawachi I Coull BA Subramanian SV Patterning of individual heterogeneity in body mass index: evidence from 57 low-and middle-income countries.Eur J Epidemiol. 2018; (published online Jan 22.)DOI:10.1007/s10654-018-0355-2Crossref Scopus (15) Google Scholar Although subnational geographic heterogeneity in health is beginning to be recognised,6Ram U Jha P Gerland P et al.Age-specific and sex-specific adult mortality risk in India in 2014: analysis of 0·27 million nationally surveyed deaths and demographic estimates from 597 districts.Lancet Glob Health. 2015; 3: e767-e775Summary Full Text Full Text PDF PubMed Scopus (37) Google Scholar and is a welcome shift from the country focus, the fact that most of the variation is between-individual continues to be overlooked.2Subramanian S Kim R Christakis NA The “average” treatment effect: a construct ripe for retirement. A commentary on Deaton and Cartwright.Soc Sci Med. 2018; (published online Apr 19.)DOI:10.1016/j.socscimed.2018.04.027Crossref Scopus (32) Google Scholar To ignore the between-individual variation also pays a disservice to one of the core missions of global health, that is to assess and reduce health inequalities. For example, increases in global income inequality are largely driven by increasing inequality between-individuals, rather than between countries.7Anand S Segal P What do we know about global income inequality?.J Econ Lit. 2008; 46: 57-94Crossref Scopus (161) Google Scholar Given the strong connections between income and health, it is not unreasonable to expect that any increase in global inequality in disease burden will follow a similar pattern. In a 2018 study8Mejía-Guevara I Corsi DJ Perkins JM Kim R Subramanian S Variation in anthropometric status and growth failure in low-and middle-income countries.Pediatrics. 2018; (published online Feb 22.)DOI:10.1542/peds.2017-2183Crossref PubMed Scopus (12) Google Scholar that investigated the variation in child anthropometric status and growth failure in low-income and middle-income countries, 60–75% of the total variation (depending on the anthropometric measure) was attributable to variation between children.8Mejía-Guevara I Corsi DJ Perkins JM Kim R Subramanian S Variation in anthropometric status and growth failure in low-and middle-income countries.Pediatrics. 2018; (published online Feb 22.)DOI:10.1542/peds.2017-2183Crossref PubMed Scopus (12) Google Scholar In the presence of such large and possibly increasing between-individual heterogeneity, research and policies confined to a one-size-fits-all approach based on averages may probably not work optimally, and therefore fail to improve overall population health and reduce health disparity.2Subramanian S Kim R Christakis NA The “average” treatment effect: a construct ripe for retirement. A commentary on Deaton and Cartwright.Soc Sci Med. 2018; (published online Apr 19.)DOI:10.1016/j.socscimed.2018.04.027Crossref Scopus (32) Google Scholar Global health research would serve its mission well by explicitly and simultaneously considering and routinely reporting “inequalities in health between populations” (eg, differences in the mean values of BMI between countries) and “inequalities in health between individuals” (eg, inter-individual inequalities in BMI within countries).9Gakidou EE Murray CJ Frenk J Defining and measuring health inequality: an approach based on the distribution of health expectancy.Bull World Health Organ. 2000; 78: 42-54PubMed Google Scholar Accurate description of risk factor distribution in a population needs two parameters: mean and dispersion. Two countries may not only have different mean BMI but also have different variation within country, thereby making the mean-only assessment less meaningful. Conversely, two countries with the same mean BMI might also have very different within-country variation (appendix). Building a foundation for a population-based perspective to health, and for most part using a country as a population, Geoffrey Rose10Rose G Ancel Keys lecture.Circulation. 1991; 84: 1405-1409Crossref PubMed Scopus (30) Google Scholar proposed a distinction between two types of inferential questions: “why do some populations have much hypertension, whilst in others it is rare?” or “why do some individuals have hypertension?”, and argued that the former is of greater significance.10Rose G Ancel Keys lecture.Circulation. 1991; 84: 1405-1409Crossref PubMed Scopus (30) Google Scholar However, improvements in the health of populations cannot be achieved without real improvements in the health and wellbeing of individuals.2Subramanian S Kim R Christakis NA The “average” treatment effect: a construct ripe for retirement. A commentary on Deaton and Cartwright.Soc Sci Med. 2018; (published online Apr 19.)DOI:10.1016/j.socscimed.2018.04.027Crossref Scopus (32) Google Scholar, 4Kim R, Kawachi I, Coull BA, Subramanian SV. Contribution of socioeconomic factors to explaining variation in body mass index: an analysis of 1 212 758 women from 58 low- and middle-income countries. Lancet Glob Health In press.Google Scholar The inferential targets between individuals and between countries are inextricably related.2Subramanian S Kim R Christakis NA The “average” treatment effect: a construct ripe for retirement. A commentary on Deaton and Cartwright.Soc Sci Med. 2018; (published online Apr 19.)DOI:10.1016/j.socscimed.2018.04.027Crossref Scopus (32) Google Scholar, 4Kim R, Kawachi I, Coull BA, Subramanian SV. Contribution of socioeconomic factors to explaining variation in body mass index: an analysis of 1 212 758 women from 58 low- and middle-income countries. Lancet Glob Health In press.Google Scholar Globally, within-country income inequality is increasing, advances are being made in personalised and targeted medicine, incredible opportunities for individual expressions are facilitated through the internet and social media, and sociopolitical narratives increasingly take a within-country perspective. Routine incorporation of between-individual, within-country variability into the narratives of between-country (or country level) assessment will go a long way in making global health research useful and relevant for the population and people it is intended to benefit. In fact, this is an important course correction that much of population health and epidemiological research, as well as journals such as The Lancet Global Health, would do well to consider. We declare no competing interests. Download .pdf (.56 MB) Help with pdf files Supplementary appendix 5 years laterA lot can happen in 5 years. In many parts of the world, so much can happen that a child's reaching that milestone age is a cause for celebration. In 5 years, a medical student can receive her basic training and start treating patients. 5-year action plans are common components of global health programmes, this timeframe being considered adequate to optimise the use of available funds and implement strategies. 5 years is also the amount of time granted a newly-elected WHO Director-General to reform the institution, set priorities, and orient the global health agenda to make a difference. Full-Text PDF Open Access