Is personality a driving force for socioeconomic differences in young adults’ health care use? A prospective cohort study

Abstract

ObjectivesTo relate personality characteristics at the age of 12 to socioeconomic differences in health care use in young adulthood. And thereby examining the extent to which socioeconomic differences in the use of health care in young adulthood are based on differences in personality characteristics, independent of the (parental) socioeconomic background.MethodsPersonality of more than 13,000 Dutch 12-year old participants was related to their health and socioeconomic position after a follow-up of 13 years (when the participants had become young adults).ResultsIn young adulthood, low socioeconomic status was related to high health care use (e.g. low education -hospital admission: OR = 2.21; low income -GP costs: OR = 1.25). Odds ratios (for the socioeconomic health differences) did not decrease when controlled for personality.ConclusionsIn this Dutch sample of younger people, personality appeared not to be a driving force for socioeconomic differences in health care use. Findings thus do not support the personality-related, indirect selection perspective on the explanation of socioeconomic differences in health.

Leadership position and physician visits – results of a nationally representative longitudinal study in Germany

“…This might be explained by a lack of statistical power. Moreover, a recent study showed that only high neuroticism was associated with HCU among Dutch young adults [ 66 ], whereas the other personality factors were not associated with high GP costs (dichotomized outcome measure with low and high GP costs). However, we expect that significant associations between personality factors and HCU (particularly with mental HCU [ 67 ]) might appear in a large sample representing the general population [ 41 ].…”

The contribution of intellectual abilities to young adult's educational differences in health care use – A prospective cohort study

“…After the exclusion of missing cases due to death (N = 58), incomplete intelligence tests (N = 6545), and missing covariates (N = 5093), 10,400 participants (53.6%) remained for the analyses. More in-depth information can be found in Kraft, Traag, Arts, Otten, and Bosma (2016).…”