Educational inequalities in major depressive disorder prevalence, timing and duration among adults over the life course: a microsimulation analysis based on the Lifelines Cohort Study.

BACKGROUND: Educational inequalities in major depressive disorder (MDD) pose a major challenge. Tackling this issue requires evidence on the long-term impact of intervening on modifiable factors, for example lifestyle and psychosocial factors. For this reason, we aimed to simulate the development of educational inequalities in MDD across the life course, and to estimate the potential impact of intervening on modifiable factors. METHODS: We used data from the prospective Dutch Lifelines Cohort Study to estimate the required input for a continuous-time microsimulation. The microsimulation allowed us to project the development of educational inequalities in MDD between ages 18 and 65, and to assess the potential benefit of intervening on quality of social contacts, health literacy and smoking. RESULTS: On average, an additional 19.1% of individuals with low education will ever experience MDD between ages 18 and 65 compared with those with high education. Additionally, individuals with low education generally will develop MDD 0.9 years earlier and spend 1.2 years more with MDD, than individuals with high education. Improving the quality of social contacts in individuals with low education produced the largest effect; it would reduce the inequalities in the prevalence, onset and duration of MDD by an average of 18.4%, 18.3% and 28.6%, respectively. CONCLUSIONS: Intervening on modifiable factors, particularly quality of social contacts, in individuals with low education could help reduce the estimated educational inequalities in MDD over the life course.

Educational inequalities in metabolic syndrome prevalence, timing, and duration amongst adults over the life course: a microsimulation analysis based on the lifelines cohort study.

BACKGROUND: Educational inequalities in metabolic syndrome (MetS) are a growing public health concern. Intervening on modifiable factors may help reduce these inequalities, but there is a need for evidence on the long-term impact of intervening on these factors. Thus, we simulate the development of educational inequalities in MetS across the life course and assess the impact of intervening on the modifiable factors that contribute to these inequalities. METHODS: We used data from the prospective multigenerational Dutch Lifelines Cohort Study to estimate the required input for a continuous-time microsimulation. The microsimulation projects the development of educational inequalities in MetS between ages 18 and 65, and assesses the potential benefit of intervening on smoking, alcohol use, diet quality, and health literacy. FINDINGS: The likelihood of ever experiencing MetS between ages 18 and 65 varies from 32.5% among high educated women to 71.5% among low educated men. On average, 27.6% more individuals with low education will ever experience MetS between ages 18 and 65 compared to those with high education. Additionally, individuals with low education generally will develop MetS 2.3 years earlier, and will spend an extra 2.6 years with MetS, compared to individuals with high education. Changes to smoking behaviours in individuals with low education produced the largest effect; it would reduce inequalities in prevalence, timing and duration by an average of 7.5%, 9.5%, and 6.9%, respectively. CONCLUSIONS: Interventions targeting the modifiable factors included in this study, especially smoking, could help reduce the estimated educational inequalities in MetS over the life course.

Disentangling rectangularization and life span extension with the moving rectangle method.

PURPOSE: The moving rectangle method is used to disentangle the contributions of rectangularization and life span extension to the increase in life expectancy. It requires the choice of an endpoint of the survival curve that approaches the maximum age at death. We examined the effect of choosing different end points on the outcomes of this method. METHODS: For five developed countries, survival curves from age 50 years were constructed per calendar year from 1922 onward. Survival values of 0.1, 0.01, and 0.001 were chosen as end points of the survival curve, and the contributions of rectangularization and life span extension to the increase in life expectancy were calculated using the moving rectangle method. RESULTS: The choice of different survival values as end points profoundly influenced the estimated contributions of rectangularization and life span extension to the increase in life expectancy. When choosing 0.001, rectangularization contributed most years, whereas when choosing 0.1, life span extension contributed most years. CONCLUSIONS: When the moving rectangle method is used to estimate the contributions of rectangularization and life span extension to the increase in life expectancy, its outcomes depend on the choice of the endpoint of the survival curve.