Journal of Epidemiology and Community Health最新文献

Background: The background of educational disparities in coronary heart disease (CHD) risk is still not well understood. We used a polygenic score for education (PGS_EDU), socioeconomic indicators and indicators of CHD risk to investigate whether these disparities result from causality or are influenced by shared factors.

Methods: Population-based health surveys including baseline measures on cardiometabolic risk factors at 25-70 years of age (N=32 610) and PGS_EDU were conducted in Finland between 1992 and 2011. Longitudinal information on education, social class, income and CHD incidence (1716 CHD cases up to 2019) was based on national registers. Linear regression, Poisson regression, Cox regression and linear structural equation models were used.

Results: Education and PGS_EDU were inversely associated with body mass index, systolic and diastolic blood pressure, total cholesterol and CHD incidence and positively associated with high-density lipoprotein cholesterol in men and women. Part of the associations of PGS_EDU with CHD incidence (57% in men and 28% in women) and cardiometabolic factors (30%-55% and 31%-92%, respectively) were mediated by education, social class and income, but a substantial part of them was independent of socioeconomic factors. These associations were consistent across different levels of education.

Conclusions: PGS_EDU captures CHD risk that is not solely attributable to education and other socioeconomic indicators. This suggests that not only causality affects the educational disparities of CHD risk but also factors reflected by PGS_EDU can contribute to them. Identifying these factors can help to understand and reduce socioeconomic health disparities.

Objectives: To quantify developmental vulnerability at age 5 by child protection contacts before school in two Australian states.

Methods: All children with birth, child protection and/or 2009, 2012, 2015 and 2018 Australian Early Development Census (AEDC) data in New South Wales (NSW) and South Australia (SA) were grouped according to child protection contact before school: no contact, child protection reports, screened-in reports, investigations, substantiations and out-of-home care (OOHC). The outcome was developmental vulnerability on ≥1 AEDC domains or medically diagnosed conditions with support needs at school entry.

Results: 56 650 (14.2%) NSW children and 12 617 (15.6%) SA children had ≥1 child protection contact before school. Developmental vulnerability on ≥1 domains or medically diagnosed conditions was lowest in the no child protection group (NSW, 21-22%; SA, 24-25%), with progressively higher risk in the child protection report (NSW, 35%; SA, 41-46%) through to the OOHC (NSW, 50-54%; SA, 59-66%) groups in all AEDC years. Developmental risk was higher among children aged <2 years at first contact and those with more reports. Children with only one child protection report before school had approximately 65% higher developmental risk than the no child protection group in both states.

Conclusions: A single child protection report before school was an early indicator of higher developmental risk at age 5, with higher developmental risks among children with earlier, more serious and frequent child protection contacts. Beyond child safety screening, child protection reports represent an opportunity to mobilise early health and social support for children with developmental support needs.

Background: Poor adherence to antidiabetic medication in individuals with type 2 diabetes (T2D) may lead to increased risk of morbidity and mortality. Socioeconomic and demographic factors associated with non-adherence have been mainly identified via cross-sectional studies. To investigate the association between antidiabetic medication adherence and income, cohabitation and area of residence.

Methods: Register-based cohort study of individuals with T2D living in Sweden and initiating antidiabetic treatment between 2006 and 2022. Confounding adjustment and competing events were accounted for via inverse probability of treatment and censoring weighting. Exposures were disposable income, social income support, cohabitation status and area of residence. Outcomes were antidiabetic medication adherence during the first year from treatment initiation and treatment interruption at 12 and 60 months.

Results: This study included 594 918 individuals with T2D. Low disposable income (adjusted OR: 1.18, 95% CI: (1.14 to 1.21)), social income support (1.09, (1.05 to 1.14)), living in large cities (1.28, (1.24 to 1.31)) and cohabitation (1.09, (1.06 to 1.11)) were associated with non-adherence (proportion of days covered ≤0.2), as compared with high adherence (proportion of days covered >0.8). Consistently, treatment interruption was associated with social income support (relative risk ratio at 12 months: 1.10, (1.06 to 1.14) and at 60 months 1.02 (1.00 to 1.05)), living in large cities (1.13, (1.12 to 1.14); 1.08, (1.07 to 1.08)) and low income (1.05, (1.03 to 1.07); 1.01, (1.00 to 1.02)).

Conclusions: Low income levels, cohabitation and living in large cities were associated with non-adherence to antidiabetic medication and risk of treatment interruption. The results highlight the need for targeted interventions aiming at improving adherence to treatments both at patient and healthcare system levels.

Background: Previous study revealed that social isolation and loneliness are associated with incident type 2 diabetes mellitus (T2DM). However, the long-term effects of social isolation and loneliness on the population with T2DM have not been known. This study aims to evaluate the potential associations of social isolation and loneliness with all-cause and cause-specific mortality in individuals with T2DM.

Methods: The prospective cohort study included 26 549 UK adults diagnosed with T2DM at baseline. Social isolation and loneliness were evaluated through a self-reported questionnaire. Mortality data was obtained from the National Death Registration Centre.

Results: During a median follow-up of 13.3 years (IQR: 12.5-14.2 years), 5467 (20.6%) participants died from all-cause, 1953 (7.4%) from cardiovascular disease (CVD) and 1569 (5.9%) from cancer. Social isolation could increase the risks of all-cause, CVD and cancer mortality (most vs least; adjusted HR (95% CI): 1.32 (1.22-1.42), 1.44 (1.26-1.65) and 1.19 (1.05-1.34), respectively). Similarly, loneliness significantly increased the risks of all-cause, and CVD mortality (yes vs no; adjusted HR (95% CI): 1.17 (1.07-1.28) and 1.26 (1.07-1.48)). In joint analyses, as the degree of social isolation intensified, there were concomitant rises in the risks of all-cause, and CVD mortality in the no-loneliness or loneliness subgroup (adjusted HR (95% CI): 1.4 (1.21-1.61) and 1.65 (1.29-2.11)).

Conclusions: This study found that social isolation was significantly associated with the increased risks of all-cause, CVD and cancer mortality among individuals with T2DM. Loneliness was also associated with all-cause mortality and CVD mortality, but not cancer mortality. These findings highlight the importance of social isolation and loneliness management in patients with T2DM.

Introduction: Observational studies have shown that more educated people are at lower risk of developing type 2 diabetes (T2D). However, robust study designs are needed to investigate the likelihood that such a relationship is causal. This study used genetic instruments for education to estimate the effect of education on T2D using the Mendelian randomisation (MR) approach.

Methods: Analyses have been conducted in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct study (more than 20 000 individuals), a case-cohort study of T2D nested in the EPIC cohort. Education was measured as Years of Education and Relative Index of Inequality. Prentice-weighted Cox models were performed to estimate the association between education and T2D. One-sample MR analyses investigated whether genetic predisposition towards longer education was associated with risk of T2D and investigated potential mediators of the association.

Results: MR estimates indicated a risk reduction of about 15% for each year of longer education on the risk of developing T2D, confirming the protective role estimated by observational models (HR 0.96, 95% CI 0.95 to 0.96). MR analyses on putative mediators showed a significant role of education on body mass index, alcohol consumption, adherence to the Mediterranean diet and smoking habits.

Conclusion: The results supported the hypothesis that higher education is a protective factor for the risk of developing T2D. Based on its position in the causal chain, education may be antecedent of other known risk factors for T2D including unhealthy behaviours. These findings reinforce evidence obtained through observational study designs and bridge the gap between correlation and causation.

Background: There is a paucity of literature regarding income inequality and adolescent movement behaviours (physical activity, sedentary behaviours, sleep). This study examined whether income inequality was associated with meeting Canadian 24-Hour Movement Guidelines (24HMG) recommendations among adolescents over time.

Methods: Longitudinal data from adolescents (n=9299) in the Cannabis, Obesity, Mental health, Physical activity, Sedentary behaviour and Smoking study (2016-2017 to 2018-2019) were linked with income data at the census division (CD) level from the 2016 Canadian Census. Adolescents (aged 13-19 years) reported on their physical activity, sleep duration and screen time via questionnaire. Gini coefficients were calculated at the CD level using after-tax household income from the 2016 Canadian Census. Multilevel logistic regression analyses were performed to test the association between income inequality and meeting several 24HMG recommendations.

Results: The joint effect (income inequality*time) was significant for meeting the sleep duration recommendation (2017-2018 OR=0.83, 95% CI 0.74, 0.92; 2018-2019 OR=0.77, 95% CI 0.70, 0.86; p<0.0001), meeting any two recommendations over time (2017-2018 OR=0.97, 95% CI 0.86, 1.09; 2018-2019 OR=0.85, 95% CI 0.75, 0.97; p=0.0402) and meeting combined sleep and physical activity recommendations (2017-2018 OR=0.93, 95% CI 0.82, 1.06; 2018-2019 OR=0.82, 95% CI 0.71, 0.94; p=0.0200). Joint effects (income inequality*time) were not significant (p>0.05) for screen time or physical activity independently of sleep.

Conclusion: Adolescents attending schools in areas with greater income inequality may be at higher risk for inadequate sleep and combined short sleep and physical inactivity.

Background: It is necessary to explore the health problems of vulnerable workers who experience repeated unemployment spells. The number of unemployment spells should be considered in the relationship between unemployment and cardiovascular disease (CVD) mortality. Using nationwide data, we aimed to investigate the relationship between unemployment and CVD mortality and examine whether this effect varies depending on the number of unemployment spells.

Methods: Using data from Statistics Korea and employment insurance databases from 2018 to 2019, we identified an average of 1387 CVD deaths per year among 7.76 million workers who had at least one employment record prior to their death. The number of unemployment spells was calculated based on the employment history over the past 5 years. Crude mortality rates per 100 000 individuals and age-standardised mortality rates (SMRs) and sex-SMRs were calculated.

Results: The crude mortality rate due to CVD was 17.9 per 100 000 individuals among workers. Workers with one unemployment spell in the past 5 years had a significantly higher SMR than those without (2.01; 95% CI 1.87 to 2.16). Additionally, as unemployment spells increased, the SMR increased. The impact was more substantial among older workers than among younger workers. These findings remained consistent when CVD was divided into ischaemic heart disease and cerebrovascular disease.

Conclusion: Repeated unemployment spells may be a risk factor for increased CVD mortality. These findings underscore the vulnerability of individuals facing repeated unemployment spells, highlighting the necessity for economic as well as health and psychological support.

Background: Low family socioeconomic position is a well-established determinant of poor health in youth. Much less is known about the social patterning of youth medication use, and the current evidence is mixed. Furthermore, previous studies have not assessed important confounders of the associations. We analyse differences in youth medication use by childhood family income and medication type.

Methods: Administrative register data on full Finnish cohorts born in 1979-2003 (n=1 490 666) and survival analysis were used to assess the risk of using common prescription medications between ages 16 and 20 according to mean household income in ages 11-15, accounting for several observed familial characteristics including parental health. We also compared siblings with discordant childhood income exposures to assess whether any differences are explained by unobserved familial confounding.

Results: For each 10% increase in childhood family income, there was a 0.6%-1.7% increase in the probability of using the most common prescription medications: antibiotics, painkillers, and allergy and asthma medications. In contrast, a 10% increase in childhood income was related to a 2.5% decrease in the probability of psychotropic medication use. In sibling comparisons, childhood income was not associated with any type of medication use.

Conclusion: Apart from psychotropics, the results may indicate medication underuse among youth from low-income families. The sibling comparisons suggest that moderate differences in childhood income are unlikely to cause differences in youth medication use and thus, in contexts of relative income equality, income differences in medication use are likely to reflect other, unobserved, family factors shared by siblings.

Background: Income is one of the most widely used indicators of socioeconomic position in studies of health inequalities. Despite its frequent use, no empirical-driven guidelines exist on how to operationalise and analytically handle income. In this study, we develop straightforward step-by-step graphical guidelines based on a comprehensive comparative examination.

Methods: We followed the entire population aged 30-65 residing in Denmark in 2010 (n=2 699 296) until death, diagnosis of either severe mental disorder or neurotic, stress-related somatoform or depressive disorders, respectively, or censoring. Adjusted HRs were estimated for four tax-reported income measures, examining variations due to the handling of extreme values, income categorisation and reference categories, both overall and stratified by sex.

Results: Across all income measures and handling strategies, lower baseline incomes were consistently associated with an elevated risk of experiencing adverse health outcomes with reversed patterns at the lowest end of the income spectrum. At these low-income levels, lower income was associated with a steep increase in corresponding household assets, with very high asset values observed at both ends of the income spectrum. Associations varied mainly for the lowest income categories with some differences in these patterns between males and females depending on the handling of extreme values, income categorisation and choice of reference category.

Conclusion: The findings indicate a misclassification of financial capability for the lowest tax-reported incomes and emphasise the need for methodological clarity in income-based health research. The step-by-step graphical guidelines, informed by the findings, offer a methodological framework aiming to enhance the precision, comparability and relevance of future studies.

Background: Health effects of multiple role occupancy and their mechanism are not fully addressed. We examined (1) the association between the number of social roles and self-rated health (SRH) and (2) the mediation effects of ikigai (the sense of life worth living) and the size of close social networks to the association.

Methods: We analysed the cross-sectional baseline questionnaire data of the Japan Public Health Center-based Prospective Study for the Next Generation (JPHC-NEXT) of 22 180 men and 26 616 women in age 40-59 years. The independent variable was the number of social roles, counting five social roles as a spouse, parent, child, worker and a role in a community. The dependent variable was poor SRH. Logistic regression was used to estimate the ORs for poor SRH by the number of social roles and to test linear trends. Mediation analyses were conducted to estimate the proportion mediated by ikigai and the size of close social networks.

Results: Compared with people with 0-1 social role, those who had two or more roles had a lower OR of poor SRH in both men and women. There was a linear inverse trend in the association; people having the largest (5) versus lowest (0-1) number of social roles had the lowest ORs: 0.55 (95% CI 0.46 to 0.66) in men and 0.72 (95% CI 0.61 to 0.86) in women. The estimated proportion mediated by ikigai was over 50%, whereas the size of close social networks mediated the association by approximately 20%.

Conclusion: An inverse association between the number of social roles and poor SRH and mediation effects of ikigai and the size of close social networks were identified. Having even one more social role might benefit subjective health via increased ikigai and the size of close social networks.