We aim to investigate to what extent gender inequality at the labor market explains higher depression risk for older US women compared to men. We analyze data from 35,699 US adults aged 50–80 years ...that participated in the Health and Retirement Study. The gender gap is calculated as the difference in prevalence in elevated depressive symptoms (score ≥ 3 on the 8-item Center for Epidemiological Studies Depression Scale) between women and men. We employ a dynamic causal decomposition and simulate the life course of a synthetic cohort from ages 50–80 with the longitudinal g-formula and introduce four nested interventions by assigning women the same probabilities of A) being in an employment category, B) occupation class, C) current income and D) prior income group as men, conditional on women's health and family status until age 70. The gender gap in depression risk is 2.9%-points at ages 50–51 which increases to 7.6%-points at ages 70–71. Intervention A decreases the gender gap over ages 50–71 by 1.2%-points (95%CI for change: 2.81 to 0.4), intervention D by 1.64%-points (95%CI for change: 3.28 to −0.15) or 32% (95%CI: 1.39 to 62.83), and the effects of interventions B and C are in between those of A and D. The impact is particularly large for Hispanics and low educated groups. Gender inequalities at the labor market substantially explain the gender gap in depression risk in older US adults. Reducing these inequalities has the potential to narrow the gender gap in depression.
•We perform a dynamic causal decomposition analysis with the longitudinal g-formula.•The sample consists of US adults above the age of 50.•We study the gender depression gap and the role of labor market inequalities.•Unequal opportunities at the labor market explain 32% of the gender depression gap.
Whether income inequality is related to population health is still open to debate. We aimed to critically assess the relationship between income inequality and mortality in 43 European countries ...using comparable data between 1987 and 2008, controlling for time-invariant and time-variant country-level confounding factors. Annual data on income inequality, expressed as Gini index based on net household income, were extracted from the Standardizing the World Income Inequality Database. Data on life expectancy at birth and age-standardized mortality by cause of death were obtained from the Human Lifetable Database and the World Health Organization European Health for All Database. Data on infant mortality were obtained from the United Nations World Population Prospects Database. The relationships between income inequality and mortality indicators were studied using country fixed effects models, adjusted for time trends and country characteristics. Significant associations between income inequality and many mortality indicators were found in pooled cross-sectional regressions, indicating higher mortality in countries with larger income inequalities. Once the country fixed effects were added, all associations between income inequality and mortality indicators became insignificant, except for mortality from external causes and homicide among men, and cancers among women. The significant results for homicide and cancers disappeared after further adjustment for indicators of democracy, education, transition to national independence, armed conflicts, and economic freedom. Crosssectional associations between income inequality and mortality seem to reflect the confounding effects of other country characteristics. In a European context, national levels of income inequality do not have an independent effect on mortality.
There is limited evidence regarding socioeconomic inequalities of exposure to the food environment and its contribution to childhood obesity.
We used data from 4235 children from the Generation R ...Study, a large birth-cohort conducted in the city of Rotterdam, The Netherlands. We included 11,277 person-observations of body mass index (BMI) and 6240 person-observations of DXA-derived fat mass index (FMI) and fat-free mass index (FFMI) when children were between 4 and 14 years. We applied linear regression models to evaluate changes in the relative and absolute exposure of fast-food outlets, and the healthiness of the food environment within 400 m from home by maternal education. Furthermore, we used individual-level fixed-effects models to study changes in the food environment to changes in BMI, FMI and FFMI.
Children from lower educated mothers were exposed to more fast-food outlets at any time-point between the age of 4 and 14 years. Over a median period of 7.1 years, the absolute (0.6 fast-food outlet (95% CI: 0.4-0.8)) and relative (2.0%-point (95% CI: 0.7-3.4)) amount of fast-food outlets increased more for children from lower as compared to higher educated mothers. The food environment became more unhealthy over time, but no differences in trends were seen by maternal education level. Changes in the food environment were not associated with subsequent changes in BMI, FMI and FFMI. For children from lower educated mothers not exposed to fast-food at first, we found some evidence that the introduction of fast-food was associated with small increases in BMI.
Our findings provide evidence of widening inequalities in exposure to fast-food in an already poor food environment. Access to more fast-food outlets does not seem to have an additional impact on BMI in contemporary contexts with ubiquitous fast-food outlets.
Background The rapid increase of frail older people worldwide will have a substantial impact on healthcare systems. The frailty process may be delayed or even reversed, which makes it attractive for ...early interventions. However, little is known about the determinants of frailty state changes. The aim of this study is to compare socio-demographic determinants of worsening in frailty state in 11 European countries. Methods Data of 14 424 community-dwelling persons aged ≥55 years, enrolled in 2004 in the Survey of Health, Ageing and Retirement in Europe, were analysed. Three frailty states were identified (non-frail, pre-frail and frail) using Fried's criteria, and frailty state changes over a 2-year period were determined. Multinomial regression analyses adjusted for baseline frailty state were conducted to investigate whether sex, age, marital status and level of education determined a worsening in frailty state in the total and country-specific European population. Results Of all individuals, 22.1% worsened, 61.8% showed no change and 16.1% improved in frailty state. Women, those aged ≥65 years, and lower educated persons showed an increased risk of worsening in frailty state. In Southern European countries, there was an earlier and larger increase in risk of worsening in frailty state in life, which was more pronounced in women compared with men. Conclusions In Europe, persons aged ≥65 years, women and lower educated persons are at increased risk of worsening in frailty state. Differences between countries indicate that interventions aimed at delaying the frailty process in Southern European countries should start earlier with more attention towards women.
BackgroundEfforts to explain social inequalities in health have mainly focused on adults. Few studies have systematically analysed different explanatory pathways in adolescence. This study is among ...the first to examine the contribution of material, psychosocial and behavioural factors in the explanation of inequalities in adolescent health.MethodsData were obtained from the German part of the cross-sectional ‘Health Behaviour in School-aged Children’ Survey in 2006, with a total of 6997 respondents aged 11–15 years (response rate 86%). Socioeconomic position was measured using the Family Affluence Scale. Multistage logistic regression models were used to assess the relative importance of explanatory factors.ResultsCompared with adolescents from high affluent backgrounds, the ORs of fair/poor self-rated health increased to 1.53 (95% CI 1.11 to 2.12) in low affluent boys and to 2.08 (95% CI 1.62 to 2.67) in low affluent girls. In the separate analyses, material, psychosocial and behavioural factors attenuated the OR by 30–50%. Together, the three explanatory factors reduced the OR by about 80% in low affluent boys and girls. The combined analyses illustrated that material factors contributed most to the differences in self-rated health because of their direct and indirect effect (through psychosocial and behavioural factors).ConclusionsThe findings show that the main explanatory approaches for adults also apply to adolescents. The direct and indirect contribution of material factors for inequalities in self-rated health was stronger than that of behavioural and psychosocial factors. Strategies for reducing health inequalities should primarily focus on improving material circumstances in lower affluent groups.
IMPORTANCE: County-level patterns in mortality rates by cause have not been systematically described but are potentially useful for public health officials, clinicians, and researchers seeking to ...improve health and reduce geographic disparities. OBJECTIVES: To demonstrate the use of a novel method for county-level estimation and to estimate annual mortality rates by US county for 21 mutually exclusive causes of death from 1980 through 2014. DESIGN, SETTING, AND PARTICIPANTS: Redistribution methods for garbage codes (implausible or insufficiently specific cause of death codes) and small area estimation methods (statistical methods for estimating rates in small subpopulations) were applied to death registration data from the National Vital Statistics System to estimate annual county-level mortality rates for 21 causes of death. These estimates were raked (scaled along multiple dimensions) to ensure consistency between causes and with existing national-level estimates. Geographic patterns in the age-standardized mortality rates in 2014 and in the change in the age-standardized mortality rates between 1980 and 2014 for the 10 highest-burden causes were determined. EXPOSURE: County of residence. MAIN OUTCOMES AND MEASURES: Cause-specific age-standardized mortality rates. RESULTS: A total of 80 412 524 deaths were recorded from January 1, 1980, through December 31, 2014, in the United States. Of these, 19.4 million deaths were assigned garbage codes. Mortality rates were analyzed for 3110 counties or groups of counties. Large between-county disparities were evident for every cause, with the gap in age-standardized mortality rates between counties in the 90th and 10th percentiles varying from 14.0 deaths per 100 000 population (cirrhosis and chronic liver diseases) to 147.0 deaths per 100 000 population (cardiovascular diseases). Geographic regions with elevated mortality rates differed among causes: for example, cardiovascular disease mortality tended to be highest along the southern half of the Mississippi River, while mortality rates from self-harm and interpersonal violence were elevated in southwestern counties, and mortality rates from chronic respiratory disease were highest in counties in eastern Kentucky and western West Virginia. Counties also varied widely in terms of the change in cause-specific mortality rates between 1980 and 2014. For most causes (eg, neoplasms, neurological disorders, and self-harm and interpersonal violence), both increases and decreases in county-level mortality rates were observed. CONCLUSIONS AND RELEVANCE: In this analysis of US cause-specific county-level mortality rates from 1980 through 2014, there were large between-county differences for every cause of death, although geographic patterns varied substantially by cause of death. The approach to county-level analyses with small area models used in this study has the potential to provide novel insights into US disease-specific mortality time trends and their differences across geographic regions.
The worksite is a promising setting for health promotion. This review summarizes the evidence of effect of intervention studies in European countries promoting a healthy diet solely and in ...combination with increasing physical activity at the workplace.
A systematic review of published literature was carried out. Inclusion criteria were: studies conducted in European countries; papers published from 1 January 1990 to 1 October 2010; worksite-based interventions promoting a healthy diet solely or in combination with physical activity; primary prevention; measurement of anthropometrical or behavioural change and adults (≥18 years old). Levels of evidence for intervention effectiveness on behavioural determinants, nutrition and physical activity behaviours and body composition and the quality of the included interventions were assessed.
Seventeen studies solely focusing on promotion of a healthy diet were identified. Eight were educational, one used worksite environmental change strategies, and eight used a combination of both (multi-component). None of the interventions were rated as 'strong'; seven met the criteria for 'moderate' quality. The reviewed studies show moderately evidence for effects on diet. Thirteen studies focusing both on nutrition and physical activity (nine educational and four multi-component studies) were identified. Ten were rated as having 'weak' and three as having 'moderate' methodological quality, providing inconclusive evidence for effects.
Limited to moderate evidence was found for positive effects of nutrition interventions implemented at the workplace. Effects of workplace health promotion interventions may be improved if stronger adherence to established quality criteria for such interventions is realized.
Regular meal consumption is considered an important aspect of a healthy diet. While ample evidence shows social inequalities in breakfast skipping among adolescents, little is known about social ...inequalities in breakfast skipping and skipping of other meals among young school-aged children. Such information is crucial in targeting interventions aimed to promote a healthy diet in children.
We examined data from 4704 ethnically diverse children participating in the Generation R Study, a population-based prospective cohort study in Rotterdam, the Netherlands. Information on family socioeconomic position (SEP), ethnic background, and meal skipping behaviors was assessed by parent-reported questionnaire when the child was 6 years old. Multiple logistic regression analyses were performed to assess the associations of family SEP (educational level, household income, employment status, family composition) and ethnic background with meal skipping behaviors, using high SEP children and native Dutch children as reference groups.
Meal skipping prevalence ranged from 3% (dinner) to 11% (lunch). The prevalence of meal skipping was higher among low SEP children and ethnic minority children. Maternal educational level was independently associated with breakfast skipping (low maternal educational level OR: 2.21; 95% CI: 1.24,3.94). Paternal educational level was independently associated with lunch skipping (low paternal educational level OR: 1.53; 95% CI: 1.06,2.20) and dinner skipping (mid-high paternal educational level OR: 0.39; 95% CI: 0.20,0.76). Household income was independently associated with breakfast skipping (low income OR: 2.43, 95% CI: 1.40,4.22) and dinner skipping (low income OR: 2.44; 95% CI: 1.22,4.91). In general, ethnic minority children were more likely to skip breakfast, lunch, and dinner compared with native Dutch children. Adjustment for family SEP attenuated the associations of ethnic minority background with meal skipping behaviors considerably.
Low SEP children and ethnic minority children are at an increased risk of breakfast, lunch, and dinner skipping compared with high SEP children and native Dutch children, respectively. Given these inequalities, interventions aimed to promote regular meal consumption, breakfast consumption in particular, should target children from low socioeconomic groups and ethnic minority children. More qualitative research to investigate the pathways underlying social inequalities in children's meal skipping behaviors is warranted.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Lower educated older persons are at increased risk of becoming frail as compared with higher educated older persons. To reduce educational inequalities in the development of frailty, we investigated ...whether lifestyle, health and social participation mediate this relationship.
Longitudinal data of 14 082 European community-dwelling persons aged 55 years and older participating in the Survey on Health, Ageing, and Retirement in Europe (SHARE) in 2004 and 2006, were used. Associations of lifestyle (smoking behaviour and alcohol consumption), health (depression, memory function, chronic diseases) and social participation, with educational level and frailty worsening were investigated using regression models. In multinomial logistic regression analysis, mediators were added to models in which educational level was associated with worsening in frailty over 2 years follow-up.
In all countries, frailty worsening was more prevalent among lower as compared with higher educated persons, although odds ratios were only statistically significant in five of the 11 countries included ORs varying from 1.40 (95% CI: 1.06-1.84) to 1.61 (95% CI: 1.21-2.14). Except for smoking behaviour and memory function, the factors under study all showed associations with educational level and frailty worsening that met the conditions for mediation. After inclusion of the four relevant mediators, attenuation of odds ratios varied between 4.9 and 31.5%.
While lifestyle, health and social participation were associated with frailty worsening over 2 years among European community-dwelling older persons, only small to moderate parts of educational inequalities in frailty worsening were explained by these factors.
Summary
Despite evidence for the effectiveness of policies that target obesogenic environments, their adoption remains deficient. Using methods and concepts from complexity and political science ...(Stock‐and‐Flow analysis and Punctuated Equilibrium Theory) and a qualitative literature review, we developed system maps to identify feedback loops that hinder policymaking on mitigating obesogenic environments and feedback loops that could trigger and sustain policy change. We found numerous self‐reinforcing feedback loops that buttress the assumption that obesity is an individual problem, strengthening the biomedical and commercial weight‐loss sectors' claim to “ownership” over solutions. That is, improvements in therapies for individuals with obesity reinforces policymakers' reluctance to target obesogenic environments. Random events that focus attention on obesity (e.g., celebrities dismissing soda) could disrupt this cycle, when actors from outside the medical and weight‐loss sector (e.g., anti‐weight stigma activists) successfully reframe obesity as a societal problem, which requires robust and politically relevant engagement with affected communities prior to such events taking place. Sustained prioritization of policies targeting obesogenic environments requires shared problem ownership of affected communities and nonhealth government sectors, by emphasizing cobenefits of policies that target obesogenic environments (e.g., ultraprocessed food taxation for raising revenue) and solutions that are meaningful for affected communities.
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