Social cohesion and associations with sedentary time, physical activity and dietary quality in The Maastricht Study.

INTRO: We aim to investigate the relationship between social cohesion and sedentary behavior (SB), total physical activity (PA), moderate-to-vigorous PA (MVPA), and dietary quality. Additionally, we assess whether these associations are independent of neighborhood walkability and the food environment. METHODS: A total of 7641 participants from The Maastricht Study in the Netherlands between the ages of 40 and 75 years were analyzed. Neighborhood social cohesion was obtained by participant questionnaire completed at baseline and measured by the Dutch Livability meter. Home addresses were linked to geographic information system (GIS) data from the Geoscience and Health Cohort Consortium (GECCO) to create neighborhood exposures of walkability and food environment. A thigh worn accelerometer collected data to measure sedentary time, total daily PA, and MVPA. Dietary quality was measured with a food frequency questionnaire. Multivariate linear regression analyses were adjusted for age, sex, socioeconomic position, neighborhood walkability, and food environment. RESULTS: Those living in the highest quartile area of perceived social cohesion had statistically significant lower levels of SB (Q4 B: -13.04; 95% CI = -20.23, -5.85), higher total PA (Q4 B: 4.39; 95% CI = 1.69, 7.10), and higher MVPA (Q4 B: 2.57; 95% CI = 0.83, 4.31) and better diet quality (Q4 B: 1.12; 95% CI = 0.24, 2.01) compared to the lowest quartile independent of walkability and food environment. Similar results were found using the Livability meter. CONCLUSION: We discovered neighborhood social cohesion as an important obesogenic determinant that should be considered in policymaking to encourage higher levels of PA and higher diet quality.

Associations of 24 h time-use compositions of sitting, standing, physical activity and sleeping with optimal cardiometabolic risk and glycaemic control: The Maastricht Study.

AIMS/HYPOTHESIS: The associations of sitting, standing, physical activity and sleep with cardiometabolic health and glycaemic control markers are interrelated. We aimed to identify 24 h time-use compositions associated with optimal metabolic and glycaemic control and determine whether these varied by diabetes status. METHODS: Thigh-worn activPAL data from 2388 participants aged 40-75 years (48.7% female; mean age 60.1 [SD = 8.1] years; n=684 with type 2 diabetes) in The Maastricht Study were examined. Compositional isometric log ratios were generated from mean 24 h time use (sitting, standing, light-intensity physical activity [LPA], moderate-to-vigorous physical activity [MVPA] and sleeping) and regressed with outcomes of waist circumference, fasting plasma glucose (FPG), 2 h plasma glucose, HbA1c, the Matsuda index expressed as z scores, and with a clustered cardiometabolic risk score. Overall analyses were adjusted for demographics, smoking, dietary intake and diabetes status, and interaction by diabetes status was examined separately. The estimated difference when substituting 30 min of one behaviour with another was determined with isotemporal substitution. To identify optimal time use, all combinations of 24 h compositions possible within the study footprint (1st-99th percentile of each behaviour) were investigated to determine those cross-sectionally associated with the most-optimal outcome (top 5%) for each outcome measure. RESULTS: Compositions lower in sitting time and with greater standing time, physical activity and sleeping had the most beneficial associations with outcomes. Associations were stronger in participants with type 2 diabetes (p<0.05 for interactions), with larger estimated benefits for waist circumference, FPG and HbA1c when sitting was replaced by LPA or MVPA in those with type 2 diabetes vs the overall sample. The mean (range) optimal compositions of 24 h time use, considering all outcomes, were 6 h (range 5 h 40 min-7 h 10 min) for sitting, 5 h 10 min (4 h 10 min-6 h 10 min) for standing, 2 h 10 min (2 h-2 h 20 min) for LPA, 2 h 10 min (1 h 40 min-2 h 20 min) for MVPA and 8 h 20 min (7 h 30 min-9 h) for sleeping. CONCLUSIONS/INTERPRETATION: Shorter sitting time and more time spent standing, undergoing physical activity and sleeping are associated with preferable cardiometabolic health. The substitutions of behavioural time use were significantly stronger in their associations with glycaemic control in those with type 2 diabetes compared with those with normoglycaemic metabolism, especially when sitting time was balanced with greater physical activity.

Both short and long sleep durations are associated with type 2 diabetes, independent from traditional lifestyle risk factors-The Maastricht Study.

OBJECTIVES: This study examined the cross-sectional association between sleep duration, prediabetes, and type 2 diabetes, and its independence from the traditional lifestyle risk factors diet, physical activity, smoking behavior, and alcohol consumption. METHODS: Cross-sectional data from 5561 people aged 40-75 years recruited into The Maastricht Study between 2010 and 2018 were used (1:1 female:male and mean age: 60.1 years [standard deviation: 8.6]). Sleep duration was operationalized as in-bed time, algorithmically derived from activPAL3 accelerometer data (median 7 nights, IQR 1). Glucose metabolism status was determined with an oral glucose tolerance test. Multinomial logistic regression was used to assess the association of sleep duration as restricted cubic spline with prediabetes and type 2 diabetes. We adjusted for sex, age, educational level, the use of sleep medication or antidepressants, and the following lifestyle risk factors: diet quality, physical activity, smoking behavior, and alcohol consumption. RESULTS: A U-shaped association between sleep duration and type 2 diabetes was found. Compared to those with a sleep duration of 8 hours, participants with a sleep duration of 5 and 12 hours had higher odds of type 2 diabetes (OR: 2.9 [95% CI 1.9 to 4.4] and OR 3.2 [2.0 to 5.2], respectively). This association remained after further adjustment for the lifestyle risk factors (OR: 2.6 [1.7 to 4.1] and OR 1.8 [1.1 to 3.1]). No such association was observed between sleep duration and prediabetes. CONCLUSIONS: Both short and long sleep durations are associated positively and independently of lifestyle and cardiovascular risk factors with type 2 diabetes, but not with prediabetes.

Regional differences in healthcare costs further explained: The contribution of health, lifestyle, loneliness and mastery.

Healthcare costs in the Netherlands are rising and vary considerably among regions. Explaining regional differences in healthcare costs can help policymakers in targeting appropriate interventions in order to restrain costs. Factors usually taken into account when analyzing regional differences in healthcare costs are demographic structure and socioeconomic status (SES). However, health, lifestyle, loneliness and mastery have also been linked to healthcare costs. Therefore, this study analyzes the contribution of health, lifestyle factors (BMI, alcohol consumption, smoking and physical activity), loneliness, and mastery to regional differences in healthcare costs. Analyses are performed in a linked dataset (n = 334,721) from the Dutch Public Health Services, Statistics Netherlands, the National Institute for Public Health and the Environment (year 2016), and the healthcare claims database Vektis (year 2017) with Poisson and zero-inflated binomial regressions. Regional differences in general practitioner consult costs remain significant even after taking into account health, lifestyle, loneliness, and mastery. Regional differences in costs for mental, pharmaceutical, and specialized care are less pronounced and can be explained to a large extent. For total healthcare costs, regional differences are mostly explained through the factors included in this study. Hence, addressing lifestyle factors, loneliness and mastery can help policymakers in restraining healthcare costs. In this study, the region of Zuid-Limburg represents the reference region. Use compare regions for health and healthcare costs (Regiovergelijker gezondheid en zorgkosten) in order to select all other Dutch regions as reference region. Supplementary Information: The online version of this article (10.1007/s12508-022-00369-4) contains supplementary material, which is available to authorized users.

Is Loneliness an Undervalued Pathway between Socio-Economic Disadvantage and Health?

Loneliness is a growing public health issue. It is more common in disadvantaged groups and has been associated with a range of poor health outcomes. Loneliness may also form an independent pathway between socio-economic disadvantage and poor health. Therefore, the aim of this study was to explore the contribution of loneliness to socio-economic health inequalities. These contributions were studied in a Dutch national sample (n = 445,748 adults (≥19 y.o.)) in Poisson and logistic regression models, controlling for age, gender, marital status, migration background, BMI, alcohol consumption, smoking, and physical activity. Loneliness explained 21% of socioeconomic health inequalities between the lowest and highest socio-economic groups in self-reported chronic disease prevalence, 27% in poorer self-rated health, and 51% in psychological distress. Subgroup analyses revealed that for young adults, loneliness had a larger contribution to socioeconomic gaps in self-rated health (37%) than in 80+-year-olds (16%). Our findings suggest that loneliness may be a social determinant of health, contributing to the socioeconomic health gap independently of well-documented factors such as lifestyles and demographics, in particular for young adults. Public health policies targeting socioeconomic health inequalities could benefit from integrating loneliness into their policies, especially for young adults.

A systematic review on economic evaluations of school-based lifestyle interventions targeting weight-related behaviours among 4-12 year olds: Issues and ways forward.

Current guidelines for economic evaluations do not provide specific recommendations for the evaluation of school-based lifestyle interventions. This study examined and discussed the key aspects in the design of economic evaluations on school-based interventions targeting weight-related behaviours among 4-12 year olds. The PubMed and CRD databases (NHS EED) were searched. Grey literature was identified from reference lists and websites of relevant organizations. Full economic evaluations on school-based interventions targeting physical activity, sedentariness, or diet were selected. Key aspects included the objective, audience, intervention, comparator, population, type of analysis, perspective, costs, outcomes, and time horizon. Information was also extracted on measuring and valuing costs and outcomes, linking and extrapolating outcomes, and the maintenance of intervention effects. The 23 included studies reported on cost-effectiveness (CEAs) (N = 12), cost-utility (CUAs) (N = 9), social cost benefit (SCBA) (N = 2), and social return on investment (SROI) (N = 1) analysis. The usual practice comparator was generally not clearly defined. The SROI analysis was the single study that included outcomes in other persons than the child. Healthcare costs (N = 14), productivity costs (N = 4), and costs to the household (N = 3), or education (N = 2) sector were examined. The outcome in trial-based CEAs consisted of a variety of weight-related measures. Seven distinctive models were used to extrapolate health and/or productivity costs. To enhance the usefulness of economic evaluations on school-based lifestyle interventions in allocating public health budgets, transparent reporting on key aspects, broadening the scope of economic evaluations, and standardizing the measurement, valuation, and extrapolation of costs and outcomes should be improved. This study was conducted in Maastricht, the Netherlands.

Socioeconomic multi-domain health inequalities in Dutch primary school children.

Background: This study assesses socio-economic health inequalities (SEHI) over primary school-age (4- to 12-years old) across 13 outcomes (i.e. body-mass index [BMI], handgrip strength, cardiovascular fitness, current physical conditions, moderate to vigorous physical activity, sleep duration, daily fruit and vegetable consumption, daily breakfast, exposure to smoking, mental strengths and difficulties, self-efficacy, school absenteeism and learning disabilities), covering four health domains (i.e. physical health, health behaviour, mental health and academic health). Methods: Multilevel mixed effect (linear and logistic) regression analyses were applied to cross-sectional data of a Dutch quasi-experimental study that included 1403 pupils from nine primary schools. Socioeconomic background (high-middle-low) was indicated by maternal education (n = 976) and parental material deprivation (n = 784). Results: Pupils with higher educated mothers had lower BMIs, higher handgrip strength and higher cardiovascular fitness; their parents reported more daily fruit and vegetable consumption, daily breakfast and less exposure to smoking. Furthermore these pupils showed less mental difficulties and less school absenteeism compared with pupils whose mothers had a lower education level. When using parental material deprivation as socio-economic indicator, similar results were found for BMI, cardiovascular fitness, sleep duration, exposure to smoking and mental strengths and difficulties. Socio-economic differences in handgrip strength, cardiovascular fitness and sleep duration were larger in older than in younger pupils. Conclusions: Childhood SEHI are clearly found across multiple domains, and some are larger in older than in younger pupils. Interventions aiming to tackle SEHI may therefore need a comprehensive and perhaps more fundamental approach.

A mixed methods study on evaluating the performance of a multi-strategy national health program to reduce maternal and child health disparities in Haryana, India.

BACKGROUND: A multi pronged community based strategy, known as National Rural Health Mission (NRHM), was implemented from 2005-06 to 2012-13 in India to curtail maternal and child health (MCH) disparities between poor and rich, rural and urban areas, and boys and girls,. This study aimed to determine the degree to which MCH plans of NRHM implemented, and resulted in improving the MCH outcomes and reducing the inequalities. METHODS: An explanatory sequential mixed methods study was conducted, first to assess the degree of implementation of MCH plans by estimating the budget utilization rates of each MCH plan, and the effectiveness of these plans by comparing demographic health surveys data conducted post (2012-13), during (2007-08) and pre- (2002-04) NRHM implementation period, in the quantitative study. Then, perceptions and beliefs of stakeholders regarding extent and effectiveness of NRHM in Haryana were explored in the qualitative study during 2013. A logistic regression analysis was done for quantitative data, and inductive applied thematic analysis for qualitative data. The findings of the quantitative and qualitative parts of study were mixed at the interpretation level. RESULTS: The MCH plans, like free ambulance service, availability of free drugs and logistics, accredited social health activists were fully implemented according to the budget spent on implementing these activities in Haryana. This was also validated by qualitative study. Availability of free medicines and treatment in the public health facilities had benefitted the poor patients the most. Accredited Social Health Activists scheme was also the most appreciated scheme that had increased the institutional delivery rates. There was acute shortage of human resources in-spite of full utilization of funds allocated for this plan. The results of the qualitative study validated the findings of quantitative study of significant (p < 0.05) improvement in MCH indicators and reduction in MCH disparities between higher and lower socioeconomic groups, and rural and urban areas. CONCLUSIONS: MCH plans of NRHM might have succeeded in improving the MCH outcomes and reducing the geographical and socioeconomic MCH inequalities by successfully implementing the schemes like accredited social health activists, free ambulance services, free treatment and medicines in hospitals for the poor and in rural areas.

Unhealthy lifestyles do not mediate the relationship between socioeconomic status and incident depressive symptoms: the Health ABC study.

BACKGROUND: The relationship between low socioeconomic status (SES) and depressive symptoms is well described, also in older persons. Although studies have found associations between low SES and unhealthy lifestyle factors, and between unhealthy lifestyle factors and depressive symptoms, not much is known about unhealthy lifestyles as a potential explanation of socioeconomic differences in depressive symptoms in older persons. METHODS: To study the independent pathways between SES (education, income, perceived income, and financial assets), lifestyle factors (smoking, alcohol use, body mass index, and physical activity), and incident depressive symptoms (Center for Epidemiologic Studies-Depression [CES-D 10] and reported use of antidepressant medication), we used 9 years of follow-up data (1997-2007) from 2,694 American black and white participants aged 70-79 years from the Health, Aging, and Body Composition (Health ABC) study. At baseline, 12.1% of the study population showed prevalent depressive symptoms, use of antidepressant medication, or treatment of depression in the 5 years prior to baseline. These persons were excluded from the analyses. RESULTS: Over a period of 9 years time, 860 participants (31.9%) developed depressive symptoms. Adjusted hazard ratios for incident depressive symptoms were higher in participants from lower SES groups compared with the highest SES group. The strongest relationships were found for black men. Although unhealthy lifestyle factors were consistently associated with low SES, they were weakly related to incident depressive symptoms. Lifestyle factors did not significantly reduce hazard ratios for depressive symptoms by SES. CONCLUSION: In generally healthy persons aged 70-79 years, lifestyle factors do not explain the relationship between SES and depressive symptoms.

Perceived unfairness and socioeconomic inequalities in functional decline: the Dutch SMILE prospective cohort study.

BACKGROUND: People in lower socioeconomic positions report worse health-related functioning. Only few examined whether perceptions of unfairness are particularly common in these people and whether this perceived unfairness relates to their subsequent poor health outcomes. We thus set out to examine the contribution of perceived unfairness to the higher risks of physical and mental dysfunction in men and women with a lower socioeconomic position. METHODS: Seven-year prospective cohort data from the Dutch SMILE study among 1,282 persons, 55 years old and older, were used. Physical and mental health-related functioning was measured with the SF-36, socioeconomic status with income and education, and the perception of unfairness with an extended new measure asking for such perceptions in both work and non-work domains. RESULTS: Perceived unfairness was more common in lower socioeconomic positions. Such perpection was related to both physical (odds ratio = 1.57 (95% confidence interval: 1.17-2.11)) and mental (1.47 (1.07-2.03)) decline, while low socioeconomic position was only related to mental decline (1.33 (1.06-1.67)). When socioeconomic position and perceived unfairness were simultaneously controlled, odds ratios for both determinants decreased only very little. Socioeconomic position and perceived unfairness were for the largest part independently related to longitudinal health-related decline. CONCLUSIONS: The general perception of unfairness, at work and beyond work, might have implications for functional decline in middle and older age. We recommend that - rather than addressing and changing individual perceptions of unfairness--more research is needed to find out whether specific environments can be defined as unfair and whether such environments can be effectively tackled in an attempt to truly improve public health.

Racial differences in mortality in older adults: factors beyond socioeconomic status.

BACKGROUND: Little is known about the simultaneous effect of socioeconomic status (SES), psychosocial, and health-related factors on race differences in mortality in older adults. PURPOSE: This study examined the association between race and mortality and the role of SES, health insurance, psychosocial factors, behavioral factors, and health-related factors in explaining these differences. METHODS: Data consisted of 2,938 adults participating in the Health, Aging and Body Composition study. Mortality was assessed over 8 years. RESULTS: SES differences accounted for 60% of the racial differences in all-cause mortality; behavioral factors and self-rated health further reduced the disparity. The racial differences in coronary heart disease mortality were completely explained by SES. Health insurance and behavioral factors accounted for some, but not all, of the race differences in cancer mortality. CONCLUSIONS: Race-related risk factors for mortality may differ by the underlying cause of mortality.

Health-related behaviors of Sudanese adolescents.

CONTEXT: Adolescence is the age period from 10-19 years when lifestyle patterns of behavior are being formed. These behaviors set the stage for future health problems. Behaviors and lifestyles are determinants of future health, illness, disability, and premature mortality. OBJECTIVES: To gain new insight into health behaviors, lifestyles and their context in adolescents in order to assess the determinants and barriers to the improvement of health. METHODS: A cross-sectional descriptive study. A random sample of 1200 adolescents within the age group of 10-19 years (53.2% girls and 46.8% boys) were interviewed individually. A self-reported questionnaire was developed for data collection by trained interviewers. Bivariate and logistic regression analyses were conducted. OUTCOMES: The overall prevalence of smoking among adolescents was 4.9%. More boys (9.1%) than girls (1.3%) reported smoking. Older participants and those with higher levels of education reported higher rates of tobacco use (10.4 % and 7.9%). Consumption of alcohol was significantly more common for boys (2.3%). More boys than girls reported they were actively engaged in sports. Inactivity was significantly higher among older age groups and was associated with lack of education. 58% of girls and 8.7% of boys were physically inactive. More than half of the boys go hungry due to lack of availability of food in the house and this was somewhat less common for girls (43%). Adolescents 16 years and older reported significantly less consumption of both nutritious and non-nutritious foods than other age groups. CONCLUSION: Our research contributed to greater understanding of current health-related behaviors of Sudanese adolescents. There are a number of implications for potential interventions (e.g. physical inactivity of girls and hunger experiences).

Associations between lifestyle and depressed mood: longitudinal results from the Maastricht Aging Study.

OBJECTIVES: We examined whether healthy lifestyles are associated with absence of depressed mood. METHODS: A sample of 1169 adult participants in the Maastricht Aging Study provided baseline and 6-year follow-up data on smoking, alcohol use, physical exercise, body mass index, and mood. We examined associations between lifestyles and depressed mood using longitudinal analyses controlling for baseline depressive symptoms and covariates. RESULTS: Reports of excessive alcohol use at baseline predicted depressed mood at follow-up (relative risk [RR] = 2.48; 95% confidence interval [CI] = 1.08, 5.69), and reports of more than 30 minutes of physical exercise per day at baseline were associated with an absence of depressed mood at follow-up (RR=0.52; 95% CI=0.29, 0.92). Reports of being engaged in physical exercise throughout the 6-year follow-up period were also associated with absence of depressed mood (RR=0.56; 95% CI=0.34, 0.93). CONCLUSIONS: In this relatively healthy population sample, certain lifestyles either predicted or protected against depressed mood. Adopting or maintaining healthy lifestyles might be a starting point in preventing or treating depressed mood over time.

Socioeconomic differences in incident depression in older adults: the role of psychosocial factors, physical health status, and behavioral factors.

OBJECTIVE: The objective of this study was to examine the association between socioeconomic status (SES) and the onset of depression in older adults and to determine the relative contribution of psychosocial factors, physical health status, and behavioral factors in explaining this link. METHODS: Data were from 2593 men and women, aged 55-85 years, participating in the Longitudinal Aging Study Amsterdam. Two indicators of SES were used: education and income. The onset of depression was measured over 9 years of follow-up. RESULTS: Adjusted hazard ratios of incident depression were significantly higher in those with low education and low income. Psychosocial factors explained on average 16% of the SES differences in incident depression, physical health status on average 7%, and behavioral factors less than 5%. CONCLUSION: In older adults, low SES predicted the incidence of depression. Part of this association was explained by psychosocial factors and physical health status.

Association of inflammatory markers with socioeconomic status.

BACKGROUND: This study examines the association between socioeconomic status (SES) and inflammatory markers in well-functioning older adults and seeks to determine whether any association remains after adjusting for biomedical and behavioral factors typically related to elevated serum levels of inflammatory markers. METHODS: Data were obtained from 3044 men and women, aged 70-79 from Pittsburgh, Pennsylvania and Memphis, Tennessee participating in the Health, Aging and Body Composition study. Three indicators of SES were used: education, income, and ownership of financial assets. Serum levels of interleukin-6, C-reactive protein, and tumor necrosis factor-alpha were measured. RESULTS: Low SES was associated with significantly elevated levels of interleukin-6, C-reactive protein, and tumor necrosis factor-alpha compared to high SES. Behavioral factors (including smoking, drinking, obesity) explained a substantial part of the inverse association between SES and inflammatory markers. Adjustment for prevalent diseases (including heart diseases, lung disease, and diabetes) associated with inflammation explained less of the association. CONCLUSIONS: This study suggests that interventions to improve health behaviors, even in old age and especially in low SES groups, may be useful in reducing risks associated with inflammation.

Change in sensory functioning predicts change in cognitive functioning: results from a 6-year follow-up in the maastricht aging study.

OBJECTIVES: To examine the longitudinal relationship between sensory functioning and a broad range of cognitive functions after 6 years follow-up and whether cataract surgery or first-time hearing aid use affected cognition. DESIGN: Hierarchical regression procedures were employed to determine whether sensory functioning was predictive of cognitive performance. SETTING: Maastricht University and the University Hospital Maastricht, the Netherlands. PARTICIPANTS: Older Dutch adults (>/=55) enrolled in the Maastricht Aging Study (N=418). MEASUREMENTS: Visual and auditory acuity, the Visual Verbal Learning Test (VVLT), the Stroop Color Word Test (SCWT), the Concept Shifting Task (CST), the Verbal Fluency Test, and the Letter-Digit Substitution Test (LDST). RESULTS: A change in visual acuity was associated with change in most cognitive measures, including the total and recall scores of the VVLT, the mean score of the first two SCWT cards, the mean score of the first two CST cards and the LDST. In addition, a change in auditory acuity predicted change in memory performance (VVLT total and recall scores), and auditory acuity measured at baseline predicted change in the mean score of the first two SCWT cards and the LDST. CONCLUSION: The findings support the notion of a strong connection between sensory acuity in auditory and visual domains and cognitive performance measures, both from a cross-sectional and a longitudinal perspective. They also suggest that it is essential to screen older individuals in a clinical context for sensory functioning so that changes in visual or auditory acuity are not interpreted as changes in cognitive performance.

Material and behavioral factors in the explanation of educational differences in incidence of acute myocardial infarction: the Globe study.

PURPOSE: To quantify the contribution of material and behavioral factors to educational differences in the incidence of acute myocardial infarction (AMI), taking into account their interrelationship. METHODS: Self-reported information about educational level, behavioral factors (alcohol, smoking, physical inactivity, and obesity), and material factors (housing conditions, crowding, employment status, financial problems, and an income proxy) was obtained from 45 to 74 year old responders to the baseline measurement of the Dutch prospective GLOBE-study in 1991 (n = 9872). Incidence of AMI in study participants was determined by hospital admissions due to AMI between 1991 and 1998. RESULTS: The increased hazard ratio of AMI in the lowest compared to the highest educational group [hazard ratio (HR) = 1.85, 95% confidence interval (CI): 1.19; 2.88] decreased by 60% after adjustment for all four behavioral factors. Similarly, adjustment for housing conditions, employment status and the income proxy reduced the hazard ratio by 76%. Thirty-six percent of the contribution of behavioral factors to educational differences in AMI in the lowest compared to the highest educational group was the result of more often living in worse material circumstances in the first group. CONCLUSIONS: Material factors contribute more to educational differences in incidence of AMI than behavioral factors. Improving material circumstances in lower educational groups may form an important strategy in the reduction of inequalities in AMI, partly because of its influence on unhealthy behavior.