We compared socioeconomic life course models to decompose the direct and mediated effects of socioeconomic status (SES) in different periods of life on late-life oral health. We used data from 2 longitudinal Swedish studies: the Level of Living Survey and the Swedish Panel Study of Living Conditions of the Oldest Old. Two birth cohorts (older, 1925 to 1934; younger, 1944 to 1953) were followed between 1968 and 2011 with 6 waves. SES was measured with 4 indicators of SES and modeled as a latent variable. Self-reported oral health was based on a tooth conditions question. Variables in the younger and older cohorts were grouped into 4 periods: childhood, young/mid-adulthood, mid /late adulthood, late adulthood/life. We used structural equation modeling to fit the following into lagged-effects life course models: 1) chain of risk, 2) sensitive period with late-life effect, 3) sensitive period with early- and late-life effects, 4) accumulation of risks with cross-sectional effects, and 5) accumulation of risks. Chain of risk was incorporated into all models and combined with accumulation, with cross-sectional effects yielding the best fit (older cohort: comparative fit index = 0.98, Tucker-Lewis index = 0.98, root mean square error of approximation = 0.04, weighted root mean square residual = 1.51). For the older cohort, the chain of SES from childhood → mid-adulthood → late adulthood → late life showed the following respective standardized coefficients: 053, 0.92, and 0.97. The total effect of childhood SES on late-life tooth loss (standardized coefficient: -0.23 for older cohort, -0.17 for younger cohort) was mediated by previous tooth loss and SES. Cross-sectional effects of SES on tooth loss were observed throughout the life course, but the strongest coefficients were at young/mid-adulthood (standardized coefficient: -0.41 for older cohort, -0.45 for younger cohort). SES affects oral health cumulatively over the life course and through a chain of risks. Actions to improve socioeconomic conditions in early life might have long-lasting effects on health if they help prevent people from becoming trapped in a chain of risks.
Keywords: birth cohort; gerontology; life cycle stages; socioeconomic status; structural equation modeling; tooth loss.