Recent quantitative research on determinants of health in high income countries: A scoping review

• Published in: PloS one 2020-09, Vol.15 (9), p.e0239031-e0239031
• Main Authors: Varbanova, Vladimira, Beutels, Philippe, Kabir, Russell, Radfar, Amir
• Format: Article
• Language: English
• Subjects: Age; Analysis; Biology and Life Sciences; Cluster analysis; Demographics; Demography; Fertility; Gender; Health aspects; Health disparities; Health economics; High income; Income; Industrialized countries; Inequality; Infectious diseases; Life expectancy; Life span; Literature reviews; Medical research; Medicine and Health Sciences; Mortality; Multidimensional scaling; People and Places; Population; Population health; Psychology; Quantitative research; Regression analysis; Regression models; Research and Analysis Methods; Social medicine; Social Sciences; Statistical analysis; Statistical methods; Statistics; Vaccines
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0239031

Identifying determinants of health and understanding their role in health production constitutes an important research theme. We aimed to document the state of recent multi-country research on this theme in the literature. We followed the PRISMA-ScR guidelines to systematically identify, triage and review literature (January 2013-July 2019). We searched for studies that performed cross-national statistical analyses aiming to evaluate the impact of one or more aggregate level determinants on one or more general population health outcomes in high-income countries. To assess in which combinations and to what extent individual (or thematically linked) determinants had been studied together, we performed multidimensional scaling and cluster analysis. Sixty studies were selected, out of an original yield of 3686. Life-expectancy and overall mortality were the most widely used population health indicators, while determinants came from the areas of healthcare, culture, politics, socio-economics, environment, labor, fertility, demographics, life-style, and psychology. The family of regression models was the predominant statistical approach. Results from our multidimensional scaling showed that a relatively tight core of determinants have received much attention, as main covariates of interest or controls, whereas the majority of other determinants were studied in very limited contexts. We consider findings from these studies regarding the importance of any given health determinant inconclusive at present. Across a multitude of model specifications, different country samples, and varying time periods, effects fluctuated between statistically significant and not significant, and between beneficial and detrimental to health. We conclude that efforts to understand the underlying mechanisms of population health are far from settled, and the present state of research on the topic leaves much to be desired. It is essential that future research considers multiple factors simultaneously and takes advantage of more sophisticated methodology with regards to quantifying health as well as analyzing determinants' influence.