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Issues: This paper identifies and synthesises explanations proposed in the literature for the (in)effectiveness of institutional anti-smoking health-information interventions (HII) among low-socioeconomic status (SES) adults in high-income countries. Approach: We searched eight databases for relevant papers from various disciplines: Studies published in English since 2009, on the effectiveness among low-SES adults of anti-smoking HIIs, aimed at changing knowledge/behaviour, and conducted by official institutions, were included. Through a scoping review, we synthesised: study design, SES indicator, intervention type, intervention source, study population, outcomes, low-SES effects, equity effects, proposed explanations and whether these were studied empirically. Key Findings: Thirty-eight studies were included in this scoping review. Seventeen suggested explanations for the (in)effectiveness of the HIIs in low-SES adults, but only nine assessed them empirically. Thematic analysis yielded six themes: message engagement, material conditions, cognition, risk perception, social environment and self-efficacy. Implications: Explanations for intervention results are not always present, and empirical evidence for explanations is often not provided. Including such explanations and testing their empirical merits in future research can provide the crucial information needed for developing more effective anti-smoking HIIs for low-SES adults. Conclusions: To our knowledge, this is the first review to explore the explanations proposed for why anti-smoking HIIs are (in)effective among low-SES adults. It contains insights for future studies aiming to provide empirical evidence on the causes of this (in)effectiveness, and concludes that such research is yet largely missing, but crucial to the quest for more effective and equitable anti-smoking interventions.

Background To understand determinants of oral health inequalities, multilevel modelling is a useful manner to study contextual factors in relation to individual oral health. Several studies outside Europe have been performed so far, however, contextual variables used are diverse and results conflicting. Therefore, this study investigated whether neighbourhood level differences in oral health exist, and whether any of the neighbourhood characteristics used were associated with oral health. Methods This study is embedded in The Generation R Study, a prospective cohort study conducted in The Netherlands. In total, 5 960 6-year-old children, representing 158 neighbourhoods in the area of Rotterdam, were included. Data on individual and neighbourhood characteristics were derived from questionnaires, and via open data resources. Caries was assessed via intraoral photographs, and defined as decayed, missing and filled teeth (dmft). Results Differences between neighbourhoods explained 13.3% of the risk of getting severe caries, and 2% of the chance of visiting the dentist yearly. After adjustments for neighbourhood and individual characteristics, neighbourhood deprivation was significantly associated with severe dental caries (OR: 1.48, 95% CI: 1.02–2.15), and suggestive of a low odds of visiting the dentist yearly (OR: 0.81, 95% CI: 0.56–1.18). Conclusions Childhood caries and use of dental services differs between neighbourhoods and living in a deprived neighbourhood is associated with increased dental caries and decreased yearly use of dental services. This highlights the importance of neighbourhoods for understanding differences in children’s oral health, and for targeted policies and interventions to improve the oral health of children living in deprived neighbourhoods.

Background Children of lower-educated parents and children in schools with a relatively high percentage of peers with lower-educated parents (lower parental education schools) are more likely to develop emotional and behavioural problems compared to children in higher-educated households and schools. Universal school-based preventive interventions, such as the Good Behaviour Game (GBG), are generally effective in preventing the development of emotional and behavioural problems, but information about potential moderators is limited. This study examined whether the effectiveness of the GBG in preventing emotional and behavioural problems differs between children in lower- and higher-educated households and schools. Methods Using a longitudinal multi-level randomized controlled trial design, 731 children (Mage=6.02 towards the end of kindergarten) from 31 mainstream schools (intervention arm: 21 schools, 484 children; control arm: 10 schools, 247 children) were followed annually from kindergarten to second grade (2004–2006). The GBG was implemented in first and second grades. Results Overall, the GBG prevented the development of emotional and behavioural problems. However, for emotional problems, the GBG-effect was slightly more pronounced in higher parental education schools than in lower parental education schools (Bhigher parental education schools =−0.281, P Conclusions Studies into universal school-based preventive interventions, and in particular the GBG, should consider and incorporate school-level factors when studying the effectiveness of such interventions. More attention should be directed towards factors that may influence universal prevention effectiveness, particularly in lower parental education schools.

Purpose: Neighborhood conditions may affect health, but health may also determine a preference for where to live. This study estimates the effect of neighborhood characteristics on mental health while aiming to adjust for this residential self-selection. Methods: A two-step method was implemented using register data from Statistics Netherlands from all residents of the city of Rotterdam relocating within the city in 2013 (N = 12,456). First, using a conditional logit model, we estimated for each individual the probability of relocating to a neighborhood over all other neighborhoods in Rotterdam, based on personal and neighborhood characteristics in 2013. Second, we corrected this selection process in a model investigating the effects of neighborhood characteristics in 2014 on reimbursed anti-depressant or anti-psychotic medication in 2016. Results: Personal and neighborhood characteristics predicted neighborhood choice, indicating strong patterns of selection into neighborhoods. Unadjusted for selection log neighborhood income was associated with reimbursed medication (β = −0.040, 95% CI = −0.060, −0.020), but the association strongly attenuated after controlling for self-selection into neighborhoods (β = −0.010, 95% CI = −0.030, 0.011). The opposite was observed for contact with neighbors; unadjusted for self-selection there was no association (β = −0.020, 95% CI = −0.073, 0.033), but after adjustment increased neighborhood contact was associated with an 8.5% relative reduction in reimbursed medication (β = −0.075, 95% CI = −0.126, −0.025). Conclusions: The method illustrated in this study offers new opportunities to disentangle selection from causation in neighborhood health research.

Recent electoral shifts toward populist parties may have been partly driven by deteriorating health, although empirical evidence on this link is primarily confined to ecological designs. We performed both ecological- and individual-level analyses to investigate whether changes in health are associated with changes in the support for populist parties. Data were used on the strategic Dutch case, the only liberal democracy featuring leftist and rightist populist politicians in parliament for over a decade. We used: (a) fixed effects models to examine whether changes in the standardized mortality ratios and self-assessed health (SAH) in municipalities were associated with changes in the populist vote share in four parliamentary elections (2006/2010/2012/2017); and (b) 10 waves of panel data collected in 2008 to 2018 to investigate if changes in individual-level SAH were linked to movement in the sympathy, intention to vote, and actual voting for populist parties. The ecological analyses showed that: changes in municipality mortality ratios were positively linked to changes in the vote share of right-wing populist parties, while changes in the prevalence of less-than-good SAH were negatively associated with changes in the vote share for left-wing populist parties. The individual-level analyses identified no such associations. Our findings imply that support for populist parties may be driven by health concerns at the ecological, but not the individual, level. This suggests that sociotropic (e.g. perceiving population health issues as a social problem), but not egotropic (e.g. relating to personal health issues like experienced stigma), concerns may underlie rising support for populist parties.

A widely used indicator for cultural class is strongly related to a lower body mass index (BMI): cultural capital measured as ‘highbrow' taste. This study’s objective was to theorise and measure aspects of cultural class that are more plausibly linked to low BMI, and subsequently explore their relevance. Building on Bourdieusian theory we derive four of those aspects: ‘refinement’ (valuing form and appearance over function and substance), ‘asceticism’ (self‐imposed constraints), ‘diversity’ (appreciation of variety in and of itself) and ‘reflexivity’ (reflexive deliberation and internal dialogue). Using standardised interviews with 597 participants in the Dutch GLOBE study in 2016, we subsequently demonstrate: (i) newly developed survey items can reliably measure four aspects of cultural class: ‘asceticism’, ‘general refinement’, ‘food refinement’ and ‘reflexivity’ (Cronbach’s alphas between 0.67–0.77); (ii) embodied/objectified cultural capital (i.e. ‘highbrow’ taste) was positively associated with general refinement, food refinement and reflexivity, whereas institutionalised cultural capital (i.e. education) was positively associated with asceticism and reflexivity; (iii) asceticism, general refinement, reflexivity, but not food refinement, were associated with a lower BMI; (iv) asceticism, general refinement and reflexivity together accounted for 52% of the association between embodied/objectified cultural capital and BMI, and 38% of the association between institutionalised cultural capital and BMI.

Despite many efforts, nutritional health interventions have been largely unable to reduce health inequalities between less- and more-educated individuals, since their effectiveness among the former is often limited. Conventionally, adverse financial circumstances and poorer health literacy are argued to explain this. Drawing on recent sociological insights, we propose a complementing and novel sociocultural explanation based on how contemporary power relations in society breed anti-institutionalism among less-educated individuals. Using a survey of a representative sample of the Dutch population (n = 2398), we focus on the strategic case of the lower uptake of nutrition information among less-educated individuals. We find that two aspects of anti-institutionalism, i.e. institutional distrust and antipaternalism, substantially account for the educational gap in the uptake of nutrition information. This indicates that current nutrition information inspires opposition among less-educated individuals. More generally, it suggests that the development of nutritional health interventions should avoid invoking institutional connotations, to increase their acceptance by those who commonly need these most.

Background Differences in health care utilization by educational level can contribute to inequalities in health. Understanding health care utilization and health-related quality of life (HRQoL) of educational groups may provide important insights into the presence of these inequalities. Therefore, we assessed characteristics, health care utilization and HRQoL of injury patients by educational level. Method Data for this registry based cohort study were extracted from the Dutch Injury Surveillance System. At 6-month follow-up, a stratified sample of patients (≥25 years) with an unintentional injury reported their health care utilization since discharge and completed the EQ-5-Dimension, 5-Level (EQ-5D-5L) and visual analogue scale (EQ VAS). Logistic regression analyses, adjusting for patient and injury characteristics, were performed to investigate the association between educational level and health care utilization. Descriptive statistics were used to analyse HRQoL scores by educational level, for hospitalized and non-hospitalized patients. Results This study included 2606 patients; 47.9% had a low, 24.4% a middle level, and 27.7% a high level of education. Patients with low education were more often female, were older, had more comorbidities, and lived more often alone compared to patients with high education (p Conclusion Post-discharge, level of education was associated with visiting the general practitioner and nursing care at home, but not significantly with use of other health care services in the 6 months post-injury. Additionally, patients with a low educational level had a poorer HRQoL. However, other factors including age and sex may also explain a part of these differences between educational groups. It is important that patients are aware of potential consequences of their trauma and when and why they should consult a specific health care service after ED or hospital discharge.

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.

Evaluating whether social policies reduce health inequalities is complicated by the fact that these upstream determinants may also change the socioeconomic distribution. Failure to account for these compositional changes may severely bias the effect estimation procedure. In this article, we illustrate how a health inequality impact assessment of a policy that (also) changes the socioeconomic distribution may produce biased results. First, we show why analyses that do not account for compositional changes fail to estimate the correct counterfactual outcome. This problem most notably occurs when using repeated cross-sectional data, often the only available option to evaluate the health effect of large-scale policies. Second, we conducted a microsimulation study to estimate the magnitude of the bias under various conditions. The results showed that the actual impact of the policy on health inequalities is often underestimated and may even produce results that are in the opposite direction of the actual causal effect of the policy. Future studies should explore new strategies, such as simulation methods, to assess the impact of policies that (also) cause changes in the socioeconomic composition of the population, to enable researchers to accurately estimate their effect on health inequalities.

Background Loneliness is associated with several adverse mental and physical health outcomes in older adults. Previous studies have shown that a variety of individual-level and perceived area-level characteristics are associated with loneliness. This study examined the associations of objectively measured social and physical neighbourhood characteristics with loneliness. Methods We used cross-sectional data from 1959 older adults (63–98 years) who participated in the Longitudinal Ageing Study Amsterdam (LASA; wave 2011/12) and the Health and Living Conditions of the Population of Eindhoven and Surroundings study (GLOBE; wave 2014) in the Netherlands. Study-specific loneliness scores were harmonised across both cohort studies and divided into tertiles denoting low, medium and high levels of loneliness. Objectively measured neighbourhood characteristics, including area-level percentages of low educated residents, social security beneficiaries and unoccupied dwellings, average income, crime levels and land use mix, were linked to individual-level data. Multinomial logistic regression analyses were conducted to examine the associations of interest. Results There was no statistical evidence for an association of the included neighbourhood characteristics with loneliness. Although not statistically significant, the observed associations suggested that participants living in neighbourhoods with more heterogeneous land use mix were less likely to have a medium and high level of loneliness than those living in more homogeneous neighbourhoods in terms of land use mix (ORmedium=0.54, 95% CI=0.18–1.67; ORhigh=0.67, 95% CI=0.21–2.11). Conclusion The results indicate that the included objectively measured social and physical neighbourhood characteristics are not associated with loneliness in old age.

Background Studies on associations between urban green space and mental health have yielded mixed results. This study examines associations of green space exposures with subjective health and depressed affect of middle-aged and older adults in four European cohorts. Methods Data came from four Western-European and Central-European ageing cohorts harmonised as part of the Mindmap project, comprising 16 189 adults with an average age of 50–71 years. Green space exposure was based on the distance to the nearest green space and the amount of green space within 800 m buffers around residential addresses. Cohort-specific and one-step individual participant data (IPD) meta-analyses were used to examine associations of green space exposures with subjective health and depressed affect. Results The amount of green spaces within 800 m buffers was lowest for Residential Environment and CORonary heart Disease (Paris, 15.0 hectares) and highest for Health, Alcohol and Psychosocial factors In Eastern Europe (Czech Republic, 35.9 hectares). IPD analyses indicated no evidence of an association between the distance to the nearest green space and depressed affect (OR 0.98, 95% CI 0.96 to 1.00) or good self-rated health (OR 1.01, 95% CI 0.99 to 1.02). Likewise, the amount of green space within 800 m buffers did not predict depressed affect (OR 0.98, 95% CI 0.96 to 1.00) or good self-rated health (OR 1.01, 95% CI 0.99 to 1.02). Findings were consistent across all cohorts. Conclusions Data from four European ageing cohorts provide no support for the hypothesis that green space exposure is associated with subjective health or depressed affect. While longitudinal evidence is required, these findings suggest that green space may be less important for older urban residents.

Many governments have implemented strict lockdown measures to prevent the transmission of the new coronavirus (SARS-CoV-2). Compliance with these restrictions is vital and depends greatly on the level of trust in the institutions central to their development and implementation. The objectives of this study were to assess: (1) the effects of the Dutch lockdown measures imposed in March 2020 on trust in government and trust in science; and (2) whether these differ across social groups. We draw on unique data from the high-quality Longitudinal Internet Studies for the Social Sciences panel, which comprises a true probability sample of Dutch households (average participation rate: 80.4%). Our data were collected on an ongoing basis from December 2017 to March 2020 (n = 2219). Using the implementation of lockdown measures in mid-March as a natural experiment, we employed difference-in-differences analyses to assess the causal effect of the Dutch lockdown measures on trust in government and trust in science. We estimated that the imposition of the measures caused an 18% increase (95% confidence interval (CI):15%–21%)) in trust in government and a 6% increase (95% CI: 4%–8%) in trust in science. The impact on trust in government was greater among the participants aged 65 and older and those with poor self-assessed health, although the relevant CIs were wide and, in the case of self-assessed health, included the null. No differential effects were observed for trust in science. Our study indicates that the strict public-health measures imposed in the Netherlands during an acute phase of the COVID-19 pandemic generated trust in the institutions involved in drafting and implementing them, especially among those with a higher risk of serious health outcomes. This suggests that, to prevent a major public-health crisis, people appreciate firm government intervention during the acute phase of an infectious disease pandemic.

How long does the average person sleep? Here, Kocevska et al. conducted a meta-analysis including over 1.1 million people to produce age- and sex-specific population reference charts for sleep duration and efficiency.We aimed to obtain reliable reference charts for sleep duration, estimate the prevalence of sleep complaints across the lifespan and identify risk indicators of poor sleep. Studies were identified through systematic literature search in Embase, Medline and Web of Science (9 August 2019) and through personal contacts. Eligible studies had to be published between 2000 and 2017 with data on sleep assessed with questionnaires including >= 100 participants from the general population. We assembled individual participant data from 200,358 people (aged 1-100 years, 55% female) from 36 studies from the Netherlands, 471,759 people (40-69 years, 55.5% female) from the United Kingdom and 409,617 people (>= 18 years, 55.8% female) from the United States. One in four people slept less than age-specific recommendations, but only 5.8% slept outside of the 'acceptable' sleep duration. Among teenagers, 51.5% reported total sleep times (TST) of less than the recommended 8-10 h and 18% report daytime sleepiness. In adults (>= 18 years), poor sleep quality (13.3%) and insomnia symptoms (9.6-19.4%) were more prevalent than short sleep duration (6.5% with TST < 6 h). Insomnia symptoms were most frequent in people spending >= 9 h in bed, whereas poor sleep quality was more frequent in those spending = 41 years) reported sleeping shorter times or slightly less efficiently than men, whereas with actigraphy they were estimated to sleep longer and more efficiently than man. This study provides age- and sex-specific population reference charts for sleep duration and efficiency which can help guide personalized advice on sleep length and preventive practices.

Purpose Quality of life (QoL) is an important yet complex outcome of care in patients with advanced cancer. QoL is associated with physical and psychosocial symptoms and with patients’ illness perceptions (IPs). IPs are modifiable cognitive constructs developed to make sense of one’s illness. It is unclear how IPs influence patients’ QoL. A better understanding of this relationship can inform and direct high quality care aimed at improving patients’ QoL. We therefore investigated the mediating role of anxiety and depression in the association of IPs with QoL. Methods Data from 377 patients with advanced cancer were used from the PROFILES registry. Patients completed measures on IPs (BIPQ), QoL (EORTC QLQ-C30), and symptoms of anxiety and depression (HADS). Mediation analyses were conducted to decompose the total effect of IPs on QoL into a direct effect and indirect effect. Results All IPs but one (“Comprehensibility”) were negatively associated with QoL (p Conclusion Negative IPs are associated with worse QoL. Anxiety and depression mediate this association. Targeting symptoms of anxiety and depression, through the modification of IPs, has the potential to improve QoL of patients with advanced cancer.

Supplemental Digital Content is available in the text., Background: We investigated to what extent social inequalities in childhood obesity could be reduced by eliminating differences in screen media exposure. Methods: We used longitudinal data from the UK-wide Millennium Cohort Study (n = 11,413). The study measured mother’s educational level at child’s age 5. We calculated screen media exposure as a combination of television viewing and computer use at ages 7 and 11. We derived obesity at age 14 from anthropometric measures. We estimated a counterfactual disparity measure of the unmediated association between mother’s education and obesity by fitting an inverse probability-weighted marginal structural model, adjusting for mediator–outcome confounders. Results: Compared with children of mothers with a university degree, children of mothers with education to age 16 were 1.9 (95% confidence interval [CI] = 1.5, 2.3) times as likely to be obese. Those whose mothers had no qualifications were 2.0 (95% CI = 1.5, 2.5) times as likely to be obese. Compared with mothers with university qualifications, the estimated counterfactual disparity in obesity at age 14, if educational differences in screen media exposure at age 7 and 11 were eliminated, was 1.8 (95% CI = 1.4, 2.2) for mothers with education to age 16 and 1.8 (95% CI = 1.4, 2.4) for mothers with no qualifications on the risk ratio scale. Hence, relative inequalities in childhood obesity would reduce by 13% (95% CI = 1%, 26%) and 17% (95% CI = 1%, 33%). Estimated reductions on the risk difference scale (absolute inequalities) were of similar magnitude. Conclusions: Our findings are consistent with the hypothesis that social inequalities in screen media exposure contribute substantially to social inequalities in childhood obesity.

ObjectivesThis study aims to investigate the association of neighbourhood socioeconomic status (SES) and social cohesion (SC) within the neighbourhood with mental health service use in children, independent of individual-level characteristics and mental health problems.Design, setting and participantsA longitudinal analysis was done using data from the Generation R Study, a prospective, population-based cohort of children born in Rotterdam, the Netherlands. These data were linked to the Neighbourhood Profile, containing registry and survey data on residents of Rotterdam. Data of 3403 children (mean age: 13.6 years, SD: 0.4) were used to study the associations between neighbourhood SES, SC (SC belonging and SC relations) and mental health service use, adjusted for mental health problems and sociodemographic characteristics.Outcome measuresMental health service use was reported by the accompanying parent at the research centre using the question: ‘Did your child visit a psychologist or psychiatrist between 9 and 13 years old?’.ResultsMental health services were used by 524 (15.4%) children between ages 9 and 13 years. No significant differences in mental health service use between neighbourhoods were identified (median OR: 1.07 (p=0.50)). The neighbourhood social characteristics were associated with mental health service use, but only when adjusted for each other. Children living in neighbourhoods with a low SES (OR 0.57 (95% CI 0.32 to 1.00)) or high SC belonging (OR 0.79 (95% CI 0.64 to 0.96)) were less likely to use services compared with children in a high SES or low SC belonging neighbourhood. SC relations was not associated with mental health service use.ConclusionsOur findings indicate that children living in high SES neighbourhoods or in neighbourhoods where people feel less sense of belonging are more likely to use mental health services. As these associations were only present when studied jointly, more research is warranted on the complex associations of neighbourhood factors with children’s mental health service use.

OBJECTIVES: We examined whether using repeatedly measured material and behavioral factors contributed differently to socioeconomic inequalities in all-cause mortality compared to one baseline measurement.STUDY DESIGN AND SETTING: Data from the Dutch prospective GLOBE cohort were linked to mortality register data (1991-2013; N = 4,851). Socioeconomic position was measured at baseline by educational level and occupation. Material factors (financial difficulties, housing tenure, health insurance) and behavioral factors (smoking, leisure time physical activity, sports participation, and body mass index) were self-reported in 1991, 1997, and 2004. Cox proportional hazards regression and bootstrap methods were used to examine the contribution of baseline-only and time-varying risk factors to socioeconomic inequalities in mortality.RESULTS: Men and women in the lowest educational and occupational groups were at an increased risk of dying compared to the highest groups. The contribution of material factors to socioeconomic inequalities in mortality was smaller when multiple instead of baseline-only measurements were used (25%-65% vs. 49%-93%). The contribution of behavioral factors was larger when multiple measurements were used (39%-51% vs. 19%-40%).CONCLUSION: Inclusion of time-dependent risk factors contributes to understanding socioeconomic inequalities in mortality, but careful examination of the underlying mechanisms and suitability of the model is required.

Background Social capital is an important determinant of health, but how specific sub-dimensions of social capital affect health and health-related behaviors is still unknown. To better understand its role for health inequalities, it is important to distinguish between bonding social capital (connections between homogenous network members; e.g. similar educational level) and bridging social capital (connections between heterogeneous network members). In this study, we test the hypotheses that, 1) among low educational groups, bridging social capital is positively associated with health-behavior, and negatively associated with overweight and obesity, and 2) among high educational groups, bridging social capital is negatively associated with health-behavior, and positively with overweight and obesity. Methods Cross-sectional data on educational level, health-behavior, overweight and obesity from participants (25–75 years; Eindhoven, the Netherlands) of the 2014-survey of the GLOBE study were used (N = 2702). Social capital (“How many of your close friends have the same educational level as you have?”) was dichotomized as: bridging (‘about half’, ‘some’, or ‘none of my friends’), or bonding (‘all’ or ‘most of my friends’). Logistic regression models were used to study whether bridging social capital was related to health-related behaviors (e.g. smoking, food intake, physical activity), overweight and obesity, and whether these associations differed between low and high educational groups. Results Among low educated, having bridging social capital (i.e. friends with a higher educational level) reduced the likelihood to report overweight (OR 0.73, 95% CI 0.52–1.03) and obesity (OR 0.58, 95% CI 0.38–0.88), compared to low educated with bonding social capital. In contrast, among high educated, having bridging social capital (i.e. friends with a lower educational level) increased the likelihood to report daily smoking (OR 2.11, 95% CI 1.37–3.27), no leisure time cycling (OR 1.55, 95% CI 1.17–2.04), not meeting recommendations for vegetable intake (OR 2.09, 95% CI 1.50–2.91), and high meat intake (OR 1.39, 95% CI 1.05–1.83), compared to high educated with bonding social capital. Conclusions Bridging social capital had differential relations with health-behavior among low and high educational groups. Policies aimed at reducing segregation between educational groups may reduce inequalities in overweight, obesity and unhealthy behaviors.

Low self-control and financial strain may limit individuals&rsquo, capacity to resist temptations in the local food environment. We investigated the moderating role of self-control and financial strain in the relation between the food environment and higher body weight. We used data from 2812 Dutch adults who participated in the population-based GLOBE study in 2014. Participants&rsquo, home addresses and the location of food retailers in 2013 were mapped using GIS. The density of fast food retailers and the totality of food retailers in Euclidean buffers of 250, 400 and 800 m around the home were linked to body mass index and overweight status. A higher density of fast food outlets (B (95% confidence interval (CI)) = &minus, 0.04 (&minus, 0.07, &minus, 0.01)) and the totality of food outlets (B (95% CI) = &minus, 0.01 (&minus, 0.01, 0.00)) were associated with a lower body mass index. Stratification showed that associations were strongest for those experiencing low self-control or great financial strain. For example, every additional fast food outlet was associated with a 0.17 point lower BMI in those with great financial strain, while not significantly associated with BMI in those with no financial strain. In conclusion, we did find support for a moderating role of self-control and financial strain, but associations between the food environment and weight status were not in the expected direction.

Background The importance of culture for food consumption is widely acknowledged, as well as the fact that culture-based resources (“cultural capital”) differ between educational groups. Since current explanations for educational inequalities in healthy and unhealthy food consumption (e.g. economic capital, social capital) are unable to fully explain this gradient, we aim to investigate a new explanation for educational inequalities in healthy food consumption, i.e. the role of cultural capital. Methods Data were obtained cross-sectionally by a postal survey among participants of the GLOBE study in the Netherlands in 2011 (N = 2953; response 67.1%). The survey measured respondents’ highest attained educational level, food-related cultural capital (institutionalised, objectivised and incorporated cultural capital), economic capital (e.g. home ownership, financial strain), social capital (e.g. social support, health-related social leverage, interpersonal relationships), and frequency of consumption of healthy and unhealthy food products. Two general outcomes (overall healthy food consumption, and overall unhealthy food consumption), and seven specific food consumption outcomes were constructed, and prevalence ratios (PR) were estimated in Poisson regression models with robust variance. Results Cultural capital was significantly associated with all food outcomes, also when social and economic capital were taken into account. Those with low levels of cultural capital were more likely to have a lower overall healthy food consumption (PR 1.35, 95% CI 1.22–1.49), a lower consumption of whole wheat bread (PR 1.21, 95% CI 1.05–1.38), vegetables (PR 1.55, 95% CI 1.40–1.71), and meat-substitutes and fish (PR 1.74, 95% CI 1.53–1.97), and a higher consumption of fried food (PR 1.59, 95% CI 1.31–1.93). Social capital was positively associated with overall healthy food consumption, whole wheat bread consumption, and the consumption of fish and meat-substitutes, and economic capital with none of the outcomes. The PR of the lowest educational group to have a low overall healthy food consumption decreased from 1.48 (95% CI 1.28–1.73) to 1.22 (95% CI 1.04–1.43) when cultural, social and economic capital were taken into account. Conclusions Cultural capital contributed to the explanation of educational inequalities in food consumption in The Netherlands, over and above economic and social capital. The socialisation processes through which cultural capital is acquired could offer new entry-points for the promotion of healthy food consumption among low educational groups. Electronic supplementary material The online version of this article (10.1186/s12939-018-0884-z) contains supplementary material, which is available to authorized users.

Background 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. Methods 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. Results 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. Conclusions 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. Electronic supplementary material The online version of this article (10.1186/s12889-018-5940-5) contains supplementary material, which is available to authorized users.

Background: This study aimed to assess the contribution of material, behavioural, cultural and psychosocial factors in the explanation of socioeconomic inequalities (education and income) in oral health of Dutch adults.Methods: Cross-sectional data from participants (25-75 years of age) of the fifth wave of the GLOBE cohort were used (n = 2812). Questionnaires were used to obtain data on material factors (e.g. financial difficulties), behavioural factors (e.g. smoking), cultural factors (e.g. cultural activities) and psychosocial factors (e.g. psychological distress). Oral health outcomes were self-reported number of teeth and self-rated oral health (SROH). Mediation analysis, using multivariable negative binomial regression and logistic regression, was performed.Results: Education level and income showed a graded positive relationship with both oral health outcomes. Adding material, behavioural, cultural and psychosocial factors substantially reduced the rate ratio for the number of teeth of the lowest education group from 0.79 (95% confidence interval (CI): 0.75-0.83) to 0.92 (95% CI: 0.87-0.97) and of the lowest income group from 0.80 (95% CI: 0.73-0.88) to 1.04 (95% CI: 0.96-1.14). Inclusion of all factors also substantially reduced the odds ratio for poor SROH of the lowest education group from 1.61 (95% CI: 1.28-2.03) to 1.12 (95% CI: 0.85-1.48) and of the lowest income groups from 3.18 (95% CI: 2.13-4.74) to 1.48 (95% CI: 0.90-2.45).Conclusion: In general, behavioural factors contributed most to the explanation of socioeconomic inequalities in adult oral health, followed by material factors. The contribution of cultural and psychosocial factors was relatively moderate.

Background: Why lower socioeconomic groups behave less healthily can only partly be explained by direct costs of behaving healthily. We hypothesize that low income increases the risk of facing financial strain. Experiencing financial strain takes up cognitive 'bandwidth' and leads to less self-control, and subsequently results in more unhealthy behaviour. We therefore aim to investigate (i) whether a low income increases the likelihood of experiencing financial strain and of unhealthy behaviours, (ii) to what extent more financial strain is associated with less self-control and, subsequently, (iii) whether less self-control is related to more unhealthy behaviour.Methods: Cross-sectional survey data were obtained from participants (25-75 years) in the fifth wave of the Dutch GLOBE study (N = 2812) in 2014. The associations between income, financial strain, self-control and health-behaviour-related outcomes (physical inactivity in leisure-time, obesity, smoking, excessive alcohol intake, and weekly fruit and vegetable intake) were analysed with linear regression and generalized linear regression models (log link).Results: Experiencing great compared with no financial strain increased the risk of all health-behaviour-related outcomes, independent of income. Low self-control, as compared with high self-control, also increased the risk of an unhealthy lifestyle. Taking self-control into account slightly attenuated the associations between financial strain and the outcomes.Conclusion: Great financial strain and low self-control are consistently associated with unhealthy behaviours. Self-control may partly mediate between financial strain and unhealthy behaviour. Interventions that relieve financial strain may free up cognitive bandwidth and improve health behaviour.

BACKGROUND: The key mechanisms underlying socioeconomic inequalities in dietary intake are still poorly understood, hampering the development of interventions. An important, but sparsely mentioned mechanism is that of 'social distinction', whereby those in a higher socioeconomic position adopt dietary patterns by which they can distinguish themselves from lower socioeconomic groups. We investigated the importance of distinction as a mechanism, by testing the socioeconomic gradient in the consumption of so-called 'superfoods' and the contribution of a well-established indicator of distinction, cultural participation.METHODS: Data from participants (25-75 years) of the 2014 survey of the Dutch population-based GLOBE study were used (N = 2812). Multivariable regression models were used to analyse the association between education, income and cultural participation (e.g. visits to museums, opera, theatre, concerts) and the consumption of superfoods (spelt, quinoa and goji berries, chia seeds or wheatgrass).RESULTS: The consumption of superfoods is far more prevalent among higher socioeconomic groups. Adjusting for cultural participation strongly attenuated the educational and income gradient in superfoods consumption, whereas cultural participation remained strongly associated with superfoods consumption. Those in the highest quintile of cultural participation reported the highest consumption of spelt products (OR = 2.97, 95% CI = 2.10;4.18), quinoa (OR = 3.50, 95% CI = 2.12;5.79) and goji berries, chia seeds or wheatgrass (OR = 2.69, 95% CI = 1.73;4.17).CONCLUSIONS: The associations between socioeconomic position and the consumption of 'superfoods' seem to be partially driven by a process of social distinction. These findings suggest that distinction may be an important, but currently neglected mechanism in generating socioeconomic inequalities in dietary intake. It deserves a more prominent role in interventions to reduce these inequalities.

This study examined whether changes in green space within the living environment were associated with changes in walking and cycling frequencies in a cohort of 3,220 Dutch adults between 2004, 2011 and 2014. Data on self-reported weekly time spent walking and cycling for active commute and leisure were linked to geographic information system (GIS) measures of total green areas within 1000 m buffer zones around each participant's home address, and distance to the nearest green space. First, cross-sectional linear regression models showed no statistically significant associations between green space measures and walking and cycling. Second, fixed effects (FE) models were used to analyze whether changes in green space were associated with changes in walking and cycling, using longitudinal data from respondents who did not relocate over time. As distance to the nearest green area increased by 100 m, individuals spent 22.76 fewer (95% CI: −39.92, −5.60) minutes walking for leisure per week and 3.21 more (95% CI: 0.46, 5.96) minutes walking for active commute. Changes in distance to green space were not significantly related to changes in cycling measures. No clear associations between changes in green areas within 1000 m buffers and changes in walking and cycling were observed. Overall, there was weak evidence of an effect of changes in green space area on changes in walking, and no evidence for cycling.

BackgroundThis study aims to estimate to what extent working conditions and health behaviours mediate the increased risk of low educated workers to report a poor health.MethodsRespondents of the longitudinal Survey of Health, Ageing, and Retirement in Europe (SHARE) in 18 European countries were selected aged between 50 years and 64 years, in paid employment at baseline and with information on education and self-rated health (n=15,126). Health behaviours and physical and psychosocial work characteristics were measured at baseline, while self-rated health was measured at 2 year follow up. We used loglinear regression models and Inverse Odds Weighting causal mediation analysis to estimate the total effect of low education on self-rated health and to decompose the effect into natural direct (NDE) and natural indirect effects (NIE).ResultsLower educated workers were more likely to be in poor health compared to higher educated workers. The total effect of low education on self-rated health was RR=1.81 [95% CI 1.66–1.97]. For work conditions, having a physical demanding job was the strongest mediator, followed by lack of job control and lack of job rewards. NIE through working conditions was RR=1.16 [95% CI 1.06–1.25], explaining about 30% of educational inequalities in self-rated health. For health behaviour, body mass index and alcohol were the strongest mediators, followed by smoking. NIE though health behaviour was RR=1.14 [95% CI 1.07–1.20], explaining about 27% of educational inequalities in self-rated health.ConclusionsPreventive interventions focusing on reducing physical work demands as well as improving health behaviour may contribute to reducing educational inequalities in self-rated health among workers in Europe.

A higher prevalence of unhealthy behaviours in lower socioeconomic groups contributes to socioeconomic inequalities in mortality. Recent cohort studies suggest that the contribution of health behaviours to socioeconomic inequalities in mortality is larger when measured repeatedly over time ('time-varying') instead of once only ('time-fixed'). Explanations for a larger contribution of health behaviours, however, are hardly discussed in the current literature, and appear to be more complex than a widening of inequalities in health behaviours over time alone. We describe the use of time-varying health behaviours to examine socioeconomic inequalities in mortality, systematically listing underlying mechanisms that may cause differences between time-varying and time-fixed models, and show that these mechanisms may be specific for each health behaviour. The use of time-varying health behaviours advances our understanding of the explanation of socioeconomic inequalities in mortality, but underlying mechanisms must be carefully examined.