2. Current challenges in modeling the social determinants of health and aging call for comparative approaches
Socially and economically disadvantaged persons experience a higher accumulation of risk factors (low income: Bor et al., 2017; Hirai et al., 2012; migrants: Riosmena et al., 2014; racial minorities: Shah et al., 2020; Wallace, 2015; Williams and Chiquita, 1995) and increased mortality (Chetty et al., 2016; National Center for Health Statistics, 2016). Yet, common approaches to modeling health trajectories (e.g., growth curve models, latent class models) often report similar health profiles between socially disadvantaged and advantaged groups (Brown et al., 2012; Gueorguieva et al., 2009; Markides and Coreil, 1986) or favorable health trajectories in traditionally marginalized groups (i.e., Migrant Effect and the Hispanic Paradox; Franzini et al., 2001; Markides and Rote, 2019; Quiñones et al., 2011). This divergence between evidence of cumulative risk and increased mortality on the one hand, and methodological approaches that model average health trajectories of disadvantaged groups on the other, suggests that current forecasting methods for predicting the progression of individual health may fail to capture critical aspects of human sociality and thus not accurately capture human health trajectories (Engelman and Jackson, 2019). Another issue when modeling the social determinants of human health and aging concerns limitations in handling missing data when this missing data is not random. As individuals age and their health deteriorates, longitudinal studies suffer non-random reductions in the number of participants due to mortality and other sources of attrition (Vaupel, 2010). Thus, many studies of human health and aging may have biases in that robust individuals will remain in the study into very old age, whereas those who die earlier or have unknown fates will not be included (Jackson et al., 2019). Finally, survey responses – a common method in human studies – are influenced by many other factors such as the personal perceptions of respondent and interviewers (Courtenay, 2000; Davis et al., 2010; Dowd and Zajacova, 2010; Gunasekara et al., 2012; Salazar, 1990; Sorlie et al., 1992; Williams and Chiquita, 1995) that can limit our understanding of the causal mechanisms of individual health and consequent aging. We argue that animal models for the social dimensions of health and aging can therefore provide a new and valuable opportunity to test novel biodemographic perspectives on analyzing individual health and improve methods to forecast health over the life course that can be applied to humans.