Socioeconomic inequalities in diets need to be tackled to improve population diets and prevent obesity and diet-related non-communicable diseases. The potential of food environment policies to reduce ...such inequalities has to date however not been appraised. The objective of this umbrella review was to assess the impact of food environment policies on socioeconomic inequalities in diets and to identify knowledge gaps in the existing literature, using the Healthy Food Environment Policy Index as a conceptual framework. The policies considered in the umbrella review are within six domains: 1) food composition 2) food labelling 3) food promotion 4) food provision 5) food retail 6) food pricing. A systematic search for systematic literature reviews on the effect of food environment policies on dietary-related outcomes across socioeconomic groups and published in English between 2004 and 2019 was conducted. Sixteen systematic literature reviews encompassing 159 primary studies were included, covering food composition (n = 2), food labelling (n = 3), food provision (n = 2), food prices (n = 13) and food in retail (n = 4). Quality assessment using the "Assessing the Methodological Quality of Systematic Reviews" quality rating scale showed that review quality was mainly low or critically low. Results suggest that food taxation may reduce socioeconomic inequalities in diets. For all other policy areas, the evidence base was poor. Current research largely fails to provide good quality evidence on impacts of food environment policies on socioeconomic inequalities in diets. Research to fill this knowledge gap is urgently needed.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Greenness exposure has been associated with many health benefits, for example through the pathway of providing opportunities for physical activity (PA). Beside the limited body of longitudinal ...research, most studies overlook to what extent different types of greenness exposures may be associated with varying levels of PA and sedentary behavior (SB). In this study, we investigated associations of greenness characterized by density, diversity and vegetation type with self-reported PA and SB over a 9-year period, using data from the ORISCAV-LUX study (2007-2017, n = 628).
The International Physical Activity Questionnaire (IPAQ) short form was used to collect PA and SB outcomes. PA was expressed as MET-minutes/week and log-transformed, and SB was expressed as sitting time in minutes/day. Geographic Information Systems (ArcGIS Pro, ArcMap) were used to collect the following exposure variables: Tree Cover Density (TCD), Soil-adjusted Vegetation Index (SAVI), and Green Land Use Mix (GLUM). The exposure variables were derived from publicly available sources using remote sensing and cartographic resources. Greenness exposure was calculated within 1000m street network buffers around participants' exact residential address.
Using Random Effects Within-Between (REWB) models, we found evidence of negative within-individual associations of TCD with PA (β = - 2.60, 95% CI - 4.75; - 0.44), and negative between-individual associations of GLUM and PA (β = - 2.02, 95% CI - 3.73; - 0.32). There was no evidence for significant associations between greenness exposure and SB. Significant interaction effects by sex were present for the associations between TCD and both PA and SB. Neighborhood socioeconomic status (NSES) did not modify the effect of greenness exposure on PA and SB in the 1000 m buffer.
Our results showed that the relationship between greenness exposure and PA depended on the type of greenness measure used, which stresses the need for the use of more diverse and complementary greenness measures in future research. Tree vegetation and greenness diversity, and changes therein, appeared to relate to PA, with distinct effects among men and women. Replication studies are needed to confirm the relevance of using different greenness measures to understand its' different associations with PA and SB.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Urbanization and ageing have important implications for public mental health and well-being. Cities pose major challenges for older citizens, but also offer opportunities to develop, test, and ...implement policies, services, infrastructure, and interventions that promote mental well-being. The MINDMAP project aims to identify the opportunities and challenges posed by urban environmental characteristics for the promotion and management of mental well-being and cognitive function of older individuals.
MINDMAP aims to achieve its research objectives by bringing together longitudinal studies from 11 countries covering over 35 cities linked to databases of area-level environmental exposures and social and urban policy indicators. The infrastructure supporting integration of this data will allow multiple MINDMAP investigators to safely and remotely co-analyse individual-level and area-level data. Individual-level data is derived from baseline and follow-up measurements of ten participating cohort studies and provides information on mental well-being outcomes, sociodemographic variables, health behaviour characteristics, social factors, measures of frailty, physical function indicators, and chronic conditions, as well as blood derived clinical biochemistry-based biomarkers and genetic biomarkers. Area-level information on physical environment characteristics (e.g. green spaces, transportation), socioeconomic and sociodemographic characteristics (e.g. neighbourhood income, residential segregation, residential density), and social environment characteristics (e.g. social cohesion, criminality) and national and urban social policies is derived from publically available sources such as geoportals and administrative databases. The linkage, harmonization, and analysis of data from different sources are being carried out using piloted tools to optimize the validity of the research results and transparency of the methodology.
MINDMAP is a novel research collaboration that is combining population-based cohort data with publicly available datasets not typically used for ageing and mental well-being research. Integration of various data sources and observational units into a single platform will help to explain the differences in ageing-related mental and cognitive disorders both within as well as between cities in Europe, the US, Canada, and Russia and to assess the causal pathways and interactions between the urban environment and the individual determinants of mental well-being and cognitive ageing in older adults.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
Experiencing financial scarcity taxes cognitive bandwidth. This leaves less capacity to withhold temptations and makes relying on easiest default options more likely. Whether this ...default option is (un)healthy may depend on the amount of cultural capital acquired during life course. This study examined whether the association between financial scarcity and health behaviours is moderated by cultural capital.
Methods
Self-reported data were used from Dutch adults of the 2014-survey of the GLOBE study (N = 2466). Using linear regression analysis, financial strain (no, some, great) and cultural capital (institutionalized, objectivized, incorporated) were related to body mass index (BMI), alcohol intake, sports participation, cycling and walking, fruit intake and vegetable consumption. The interaction between financial strain and cultural capital was used to assess moderation.
Results
Experiencing some financial strain was associated with a higher BMI (0.7 kg/m2) and less sport participation (−31.8 min/week). Great financial strain was associated with less sport participation (−41.4 min/week). Being in the lowest tertile of cultural capital was associated with a higher BMI (1.3 kg/m2), drinking less alcohol (−10.0 units/week), less sport participation (−31.5 min/week) and consuming less fruit (−2.9 pieces/week). Cultural capital had no significant moderating effect on the relationship between financial strain and these health behaviours.
Conclusion
Financial strain and cultural capital seem associated with different health behaviours. Cultural capital had no moderating effect on the relationship between financial strain and different health behaviours. While financial strain and cultural capital could both be entry points for interventions to improve health behaviour, underlying mechanisms require further attention.
Material and behavioural factors play an important role in explaining educational inequalities in mortality, but gender differences in these contributions have received little attention thus far. We ...examined the contribution of a range of possible mediators to relative educational inequalities in mortality for men and women separately.
Baseline data (1991) of men and women aged 25 to 74 years participating in the prospective Dutch GLOBE study were linked to almost 23 years of mortality follow-up from Dutch registry data (6099 men and 6935 women). Cox proportional hazard models were used to calculate hazard ratios with 95% confidence intervals, and to investigate the contribution of material (financial difficulties, housing tenure, health insurance), employment-related (type of employment, occupational class of the breadwinner), behavioural (alcohol consumption, smoking, leisure and sports physical activity, body mass index) and family-related factors (marital status, living arrangement, number of children) to educational inequalities in all-cause and cause-specific mortality, i.e. mortality from cancer, cardiovascular disease, other diseases and external causes.
Educational gradients in mortality were found for both men and women. All factors together explained 62% of educational inequalities in mortality for lowest educated men, and 71% for lowest educated women. Yet, type of employment contributed substantially more to the explanation of educational inequalities in all-cause mortality for men (29%) than for women (- 7%), whereas the breadwinner's occupational class contributed more for women (41%) than for men (7%). Material factors and employment-related factors contributed more to inequalities in mortality from cardiovascular disease for men than for women, but they explained more of the inequalities in cancer mortality for women than for men.
Gender differences in the contribution of employment-related factors to the explanation of educational inequalities in all-cause mortality were found, but not of material, behavioural or family-related factors. A full understanding of educational inequalities in mortality benefits from a gender perspective, particularly when considering employment-related factors.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cash transfer interventions broadly improve the lives of the vulnerable, making them exceedingly popular. However, evidence of impacts on mental health is limited, particularly for conditional cash ...transfer (CCT) programs. We examined the impacts of Tanzania’s government-run CCT program on depressive symptoms of youth aged 14–28.
We utilized cluster randomized controlled trial data of 84 communities (48 intervention; 36 control). The intervention administered bimonthly CCTs to eligible households, while control communities were assigned to delayed intervention. The analysis included youth with measurements of depression (10-item Centre for Epidemiological Studies Depression Scale) at baseline and 18 months later. We determined impacts using analysis of covariance models, adjusting for youth characteristics (including baseline depression), district-level fixed effects, and community-level random effects. Differential effects by sex and baseline social support were also estimated.
Although no evidence was found to suggest that the intervention impacted depressive symptoms among the full sample (n = 880) (effect −.20, 95% confidence interval CI −.88 to .48, p = .562), subsample results indicated that depressive symptoms were reduced 1.5 points among males (95% CI −2.56 to −.04, p = .007) and increased 1.1 points among females (95% CI .11–2.09, p = .029). Females 18+ years old (effect 1.55, 95% CI .27–2.83, p = .018) and females with children (effect 1.32, 95% CI −.13 to 2.78, p = .074) drove this negative impact. Social support did not moderate impacts.
Despite no overall intervention effects, results suggest that receiving a CCT has differential effects on mental health by sex. Although males benefited from the intervention, conditions which rely on stereotypically female roles may result in negative consequences among women.
Abstract
Background
In the light of urbanization and aging, a crucially relevant policy question is how to shape neighborhoods to foster healthy aging. An important debate is whether older adults ...should group in neighborhoods, or whether a more mixed neighborhood age composition is more beneficial to health and well-being. We therefore assessed the association between neighborhood age structure and mental health and the mediating role of individual perceptions of neighborhood social factors.
Methods
We conducted multivariable linear regression models and causal mediation analyses in 1255 older adults of the Dutch Globe study. The neighborhood age structure was measured in 2011 as the homogeneity of the age composition (using the Herfindahl-Hirschman index, range from 0 to 100, a higher score indicating more homogeneity) and the percentage of specific age groups in a neighborhood. Mental health was measured in 2014 by the Mental Health Inventory-5 score (range 0 to 100, a higher score indicating better mental health). Potential mediators were assessed in 2011 and included perceptions of neighborhood social cohesion, feeling at home in a neighborhood, and social participation.
Results
A more homogeneous age composition (not specified for age) and a higher percentage of children living in a neighborhood were associated with better mental health, the other age categories were not. Social cohesion, feeling at home and social participation did not mediate the associations.
Conclusions
The neighborhood age composition may be an interesting but currently insufficiently understood entry point for policies to improve older adult’s mental health status.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
BackgroundUrban green spaces have been linked to different health benefits, but longitudinal studies on the effect of green spaces on mental health are sparse and evidence often inconclusive. Our ...objective was to study the effect of changes in green spaces in the residential environment on changes in mental health using data with 10 years of follow-up (2004–2014).MethodsData from 3175 Dutch adults were linked to accessibility and availability measures of green spaces at three time points (2004/2011/2014). Mental health was measured with the Mental Health Inventory-5. Fixed effects analyses were performed to assess the effect of changes in green spaces on mental health.ResultsCross-sectional analysis of baseline data showed significant associations between Euclidean distances to the nearest green space and mental health, with an increase of 100 m correlating with a lower mental health score of approximately 0.5 (95% CI −0.87 to −0.12) on a 0–100 scale. Fixed effects models showed no evidence for associations between changes in green spaces and changes in mental health both for the entire sample as well as for those that did not relocate during follow-up.ConclusionsDespite observed cross-sectional correlations between the accessibility of green space in the residential environment and mental health, no evidence was found for an association between changes in green spaces and changes in mental health. If mental health and green spaces are indeed causally linked, then changes in green spaces in the Eindhoven area between 2004 and 2014 are not enough to produce a significant effect.
Research suggests that genetic predisposition for common mental disorders may be moderated by the environment. This study examines whether a polygenic risk score (PRS) for depression is moderated by ...the level of residential area urbanicity using five symptoms of poor mental health as outcomes.
The study sample consisted of 41 198 participants from the 2006-2008 wave of the Norwegian HUNT study. We created a weighted PRS for depression based on 99 variants identified in a recent genome -wide association study. Participants were classified into urban or rural place of residence based on wards that correspond to neighbourhoods. Mixed effects logistic regression models with participants nested in 477 neighbourhoods were specified.
A SD increase in PRS for depression was associated with a small but statistically significant increase in the odds of anxiety, comorbid anxiety and depression and mental distress. Associations for depression were weaker and not statistically significant. Compared with urban residents, rural resident had higher odds for reporting poor mental health. Genetic propensity for depression was higher for residents of urban than rural areas, suggesting gene-environment correlation. There was no sign of effect modification between genetic propensity and urbanicity for depression, anxiety, comorbid anxiety and depression, or mental distress.
The PRS predicted small but significant odds of anxiety, comorbid anxiety and depression and mental distress, but we found no support for a differential effect of genetic propensity in urban and rural neighbourhoods for any of the outcomes.
Metrics based on self-reports of health status have been proposed for tracking population health and making comparisons among different populations. While these metrics have been used in the US to ...explore disparities by sex, race/ethnicity, and socioeconomic position, less is known about how self-reported health varies geographically. This study aimed to describe county-level trends in the prevalence of poor self-reported health and to assess the face validity of these estimates.
We applied validated small area estimation methods to Behavioral Risk Factor Surveillance System data to estimate annual county-level prevalence of four measures of poor self-reported health (low general health, frequent physical distress, frequent mental distress, and frequent activity limitation) from 1995 and 2012. We compared these measures of poor self-reported health to other population health indicators, including risk factor prevalence (smoking, physical inactivity, and obesity), chronic condition prevalence (hypertension and diabetes), and life expectancy.
We found substantial geographic disparities in poor self-reported health. Counties in parts of South Dakota, eastern Kentucky and western West Virginia, along the Texas-Mexico border, along the southern half of the Mississippi river, and in southern Alabama generally experienced the highest levels of poor self-reported health. At the county level, there was a strong positive correlation among the four measures of poor self-reported health and between the prevalence of poor self-reported health and the prevalence of risk factors and chronic conditions. There was a strong negative correlation between prevalence of poor self-reported health and life expectancy. Nonetheless, counties with similar levels of poor self-reported health experienced life expectancies that varied by several years. Changes over time in life expectancy were only weakly correlated with changes in the prevalence of poor self-reported health.
This analysis adds to the growing body of literature documenting large geographic disparities in health outcomes in the United States. Health metrics based on self-reports of health status can and should be used to complement other measures of population health, such as life expectancy, to identify high need areas, efficiently allocate resources, and monitor geographic disparities.
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