Subjective health and well-being: Toward robust cross-cultural comparisons

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Subjective health and well-being are of considerable interest in population health research. Subjective assessments offer unique scope to capture latent health concerns that cannot be directly (or cost-effectively) captured through objective assessments (Jylha, 2009). These assessments are sometimes more reliable predictors of old-age mortality than standard clinical biomarkers (Idler & Benyamini, 1997). At the same time, greater caution is warranted while studying subjective health and well-being in a cross-cultural setting (Jurges, 2007, Jylha et al., 1998, McDowell, 2006, Schwarz et al., 2010). Glei (2017) succinctly elicit these concerns while examining self-reported physical limitation in United States and three other countries having similar life-expectancy (England, Taiwan and Costa Rica). It is noted that the absolute population-level prevalence of self-reported physical limitations varies across the four US-based surveys (HRS, MIDUS, NHIS and NHANES) and thus disallows a robust cross-country comparison. Such variability can have non-trivial implications for comparisons as one can arrive at contradictory conclusions regarding the nature of associations. For instance, MIDUS suggests that American men report walking limitations much earlier than Costa Ricans whereas HRS based assessment indicates that the American men are more advantaged. Glei (2017) set up an interesting hypothesis regarding the association of subjective health indicators with macro- or country-level indicators such as life expectancy or per capita incomes. Although, data limitations in terms of country units for analysis can prohibit robust country-level inferences but it outlines an important agenda for further research. For example, Fig. 1 presents the country-level association of percentage bad and very-bad self-rated health with per capita gross national income and life expectancy at birth. There is an inverse association of per capita incomes and life-expectancies with percentage of population (age 25 and over) reporting bad or very bad health. The association appears consistent because high-income countries are also likely to have higher life expectancy at birth. Also, the fact that self-rated health and mortality share a significant relationship lends credence to this association (Idler & Benyamini, 1997). But the scatter also depicts considerable heterogeneity and reporting of bad or very-bad health has large variations at lower per capita incomes and at higher life expectancies. Open in a separate window Fig. 1 Association of percentage self-rated bad/very bad health (among aged 25 and over) with per capita GNI and life-expectancy at birth across 69 countries in 2002. Note: Data for the self-rated health status is based on World Health Survey (2002) and is sourced from Subramanian, Huijts, and Avendano (2010) whereas data for GNI per capita and life expectancy at birth are from World Development Indicators database. Linear trendline is also presented for GNI per capita (p < 0.01) and life expectancy at birth (p < 0.10).