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.

Socioeconomic differences in metabolic syndrome development among males and females, and the mediating role of health literacy and self-management skills.

BACKGROUND: Our aim was to investigate sex differences in the associations between socioeconomic position (SEP) and metabolic syndrome (MetS) development, and to what extent these associations are mediated by health literacy and self-management skills. METHODS: A subsample (n = 88,384, 59.5% female) of the adult Lifelines Cohort Study was used. MetS development according to NCEP-ATPIII criteria was assessed on average 3.8 years after baseline. SEP-MetS associations were assessed for moderation by sex, and sex-stratified accordingly. Associations between SEP measures (education, income and occupational prestige), health literacy and self-management skills, and MetS development were investigated using logistic regression analyses. The mediating effects of health literacy and self-management skills on the SEP-MetS associations were investigated using the Karlson-Holm-Breen method. RESULTS: Among males and females, respectively 9.4% and 7.1% developed MetS. For males, education was inversely associated with MetS development; health literacy (7.1%) and self-management skills (1.9%) mediated a proportion of these educational differences. For females, education, income and occupational prestige were inversely associated with MetS development; health literacy (respectively 5.9% and 6.4%) and self-management skills (respectively 4.1% and 3.7%) mediated a proportion of the educational and occupational differences in MetS development. Neither health literacy nor self-management skills mediated female income differences in MetS development. CONCLUSIONS: Socioeconomic differences in MetS development differ between males and females. Both for males and females, health literacy and self-management skills mediated a small proportion of socioeconomic differences in MetS development.

Socioeconomic differences in metabolic syndrome development: examining the mediating role of chronic stress using the Lifelines Cohort Study.

BACKGROUND: Metabolic syndrome (MetS) development strongly varies based on individuals' socioeconomic position (SEP), but to date, no studies have assessed the mediating role of perceived stress from long-term difficulties (chronic stress) in this association. The aim of this study is to examine the mediating role of chronic stress in the associations of the SEP measures education, occupational prestige and income, with MetS development, and whether associations between chronic stress and MetS are moderated by sex. METHODS: We used an adult subsample (n = 53,216) from the Lifelines Cohort Study without MetS at baseline. MetS development was measured 3.9 years after baseline (follow-up), and defined according to National Cholesterol Education Program's Adult Treatment Panel III (NCEP-ATPIII) criteria. Direct associations between SEP, chronic stress and MetS development were estimated using multivariable logistic and linear regression analyses, and were adjusted for age, sex, the other SEP measures, and time between baseline and follow-up. The mediating percentages of chronic stress explaining the associations between SEP and MetS development were estimated using the Karlson-Holm-Breen method. RESULTS: Upon follow-up, 7.4% of the participants had developed MetS. Years of education and occupational prestige were inversely associated with MetS development. Chronic stress suppressed the association between education and MetS development (5.6%), as well as the association between occupational prestige and MetS development (6.2%). No effect modification of sex on the chronic stress-MetS pathway was observed. CONCLUSIONS: Chronic stress does not explain educational and occupational differences in developing MetS. In fact, individuals with more years of education or higher occupational prestige perceive more chronic stress than their lower SEP counterparts. Further, no difference between males and females was observed regarding the relationship between chronic stress and MetS development.

Understanding socioeconomic differences in metabolic syndrome remission among adults: what is the mediating role of health behaviors?

BACKGROUND: Although the incidence of metabolic syndrome (MetS) strongly varies based on individuals' socioeconomic position (SEP), as yet no studies have examined the SEP-MetS remission relationship. Our aim is to longitudinally assess the associations between SEP measures education, income and occupational prestige, and MetS remission, and whether these associations are mediated by health behaviors, including physical activity, smoking, alcohol intake and diet quality. METHODS: A subsample (n = 16,818) of the adult Lifelines Cohort Study with MetS at baseline was used. MetS remission was measured upon second assessment (median follow-up time 3.8 years), defined according to NCEP-ATPIII criteria. To estimate direct associations between SEP, health behaviors and MetS remission multivariable logistic regression analyses were used. To estimate the mediating percentages of health behaviors that explain the SEP-MetS remission relationship the Karlson-Holm-Breen method was used. Analyses were adjusted for age, sex, the other SEP measures and follow-up time. RESULTS: At the second assessment, 42.7% of the participants experienced MetS remission. Education and income were positively associated with MetS remission, but occupational prestige was not. The association between education and MetS remission could partly (11.9%) be explained by health behaviors, but not the association between income and MetS remission. CONCLUSIONS: Individuals with higher education more often experienced remission from MetS, mainly because individuals with higher education were more likely to have healthier behaviors. However, individuals with higher income more often experienced MetS remissions, regardless of their health behaviors. The occupational prestige of individuals was not associated with MetS remission.

Understanding socioeconomic differences in incident metabolic syndrome among adults: What is the mediating role of health behaviours?

BACKGROUND: The incidence of metabolic syndrome (MetS) strongly varies by socioeconomic position (SEP), but little is known about the mediating role of health behaviours in this association. This study examines the associations between the SEP measures, education, income and occupational prestige, and incident MetS and whether the associations are mediated by health behaviours, including physical activity, smoking, alcohol intake and diet quality. METHODS: A subsample (n = 85,910) of the adult Lifelines Cohort Study without MetS at baseline was used. MetS was measured at the second assessment (median follow-up time 3.8 years) defined according to the NCEP-ATPIII criteria. Direct associations between SEP, health behaviours and incident MetS were estimated using multivariable logistic regression analyses. The mediating percentages of health behaviours explaining the associations between SEP and incident MetS were estimated using the Karlson-Holm-Breen method. Analyses were independent of age, sex, the other SEP measures and follow-up time. RESULTS: Education and occupational prestige were inversely associated with MetS. Income was not associated with MetS. Health behaviours explained only partly (13.8%) the association between education and MetS, with smoking as the strongest mediating factor (8.8%). Health behaviours played also a minor role (2.7%) in explaining occupational MetS differences, with physical activity as the strongest suppressing factor (-9.4%). CONCLUSION: Individuals with more years of education or a higher occupational prestige had a lower risk to develop MetS. This was mainly because of non-smoking, less excessive alcohol intake and a higher diet quality. However, individuals with a higher SEP were more often physically inactive.

Validation of the online prediction model CancerMath in the Dutch breast cancer population.

PURPOSE: CancerMath predicts the expected benefit of adjuvant systemic therapy on overall (OS) and breast cancer-specific survival (BCSS). Here, CancerMath was validated in Dutch breast cancer patients. METHODS: All operated women diagnosed with stage I-III primary invasive breast cancer in 2005 were identified from the Netherlands Cancer Registry. Calibration was assessed by comparing 5- and 10-year predicted and observed OS/BCSS using χ2 tests. A difference > 3% was considered as clinically relevant. Discrimination was assessed by area under the receiver operating characteristic (AUC) curves. RESULTS: Altogether, 8032 women were included. CancerMath underestimated 5- and 10-year OS by 2.2% and 1.9%, respectively. AUCs of 5- and 10-year OS were both 0.77. Divergence between predicted and observed OS was most pronounced in grade II, patients without positive nodes, tumours 1.01-2.00 cm, hormonal receptor positive disease and patients 60-69 years. CancerMath underestimated 5- and 10-year BCSS by 0.5% and 0.6%, respectively. AUCs were 0.78 and 0.73, respectively. No significant difference was found in any subgroup. CONCLUSION: CancerMath predicts OS accurately for most patients with early breast cancer although outcomes should be interpreted with care in some subgroups. BCSS is predicted accurately in all subgroups. Therefore, CancerMath can reliably be used in (Dutch) clinical practice.

Socioeconomic differences in major depressive disorder onset among adults are partially explained by lifestyle factors: A longitudinal analysis of the Lifelines Cohort Study.

BACKGROUND: Major depressive disorder (MDD) onset varies by socioeconomic position (SEP), this could be explained by lifestyle factors, but little is known about this pathway. Our study aims to disentangle the interplay between SEP measures (i.e., education, income and occupational prestige) and MDD onset and to examine to what extent these associations are mediated by lifestyle (i.e., occupational- and leisure time physical activity, smoking, alcohol intake, diet quality, sleep and central adiposity). METHODS: A subsample (n = 76,045) of the Lifelines Cohort Study without MDD at baseline was included. MDD onset was measured after a median follow-up time of 3.8 years with the Mini International Neuropsychiatric Interview (MINI). Direct associations between SEP, lifestyle and MDD onset were estimated using logistic regression analyses. Mediating percentages were estimated using the Karlson-Holm-Breen method. RESULTS: 1864 participants (2.5 %) showed MDD at follow-up. SEP was inversely associated with MDD onset, with education showing the strongest association. Educational, income and occupational differences in MDD onset were for 18.7 %, 5.9 % and 21.7 % explained by lifestyle factors (mainly smoking, alcohol intake and central adiposity). LIMITATIONS: SEP and lifestyle factors were measured simultaneously at baseline. MDD status (only based on a screening tool) was only measured at baseline and 3.8 years later. CONCLUSIONS: Compared to their lower SEP counterparts, higher SEP individuals had a lower risk of MDD onset. This was partially explained by a healthier lifestyle (mainly less smoking, alcohol intake and central adiposity) of the higher SEP individuals.