Repeatedly measured material and behavioral factors changed the explanation of socioeconomic inequalities in all-cause mortality

A Dose of Reality About Dose-Response Relationships

Observational research can be strengthened by examining potential dose-response relationships that correlate a clinical intervention with a patient outcome. Despite being a classic criterion for establishing causality, dose-response testing can be difficult to interpret in clinical medicine due to multiple diverse pitfalls. This review introduces a cautionary framework for investigators considering dose-response relationships in observational research to support evidence-based medicine. Each pitfall is illustrated with a specific example relevant when analyzing a dose-response relationship. Several pitfalls stem from faulty interpretation including confounding by indication and fallible range selection. Additional pitfalls relate to improper analysis including fitting a nonlinear model and misclassification error. Further pitfalls arise in special situations including subjective self-report and artifacts from survival bias. These caveats are common sources of misunderstanding in analyses that examine the link between varying exposures and the intensity of clinical outcomes. Awareness of specific pitfalls, we suggest, might help advance the conduct, application, and translation of dose-response relationships in observational research to inform evidence-based medical care.

Using repeated measures to study the contribution of alcohol consumption and smoking to the social gradient in all-cause mortality: Results from the Stockholm Public Health Cohort

INTRODUCTION

The social gradient in consumption behaviours has been suggested to partly explain health inequalities. The majority of previous studies have only included baseline measurements and not considered potential changes in behaviours over time. The study aimed to investigate the contribution of alcohol consumption and smoking to the social gradient in mortality and to assess whether the use of repeated measurements results in larger attenuations of the main association compared to using single baseline assessments.

METHODS

Longitudinal survey data from the population-based Stockholm Public Health Cohort from 2006 to 2014 was linked to register data on mortality until 2018 for 13,688 individuals and analysed through Cox regression.

RESULTS

Low socioeconomic position (SEP) was associated with increased mortality compared with high SEP; hazard ratios 1.56 (95% CI 1.30-1.88) for occupational status and 1.77 (95% CI 1.49-2.11) for education, after adjustment for demographic characteristics. Using repeated measurements, alcohol consumption and smoking explained 44% of the association between occupational status and all-cause mortality. Comparing repeated and baseline measures, the percentage attenuation due to alcohol consumption increased from 11% to 18%, whereas it remained similar for smoking (25-23%).

DISCUSSION AND CONCLUSIONS

Smoking and alcohol consumption explained a large part of the association between SEP and mortality. Comparing results from time-fixed and time-varying models, there was an increase in overall percentage attenuation that was mainly due to the increased proportion explained by alcohol consumption. Repeated measurements provide a better estimation of the contribution of alcohol consumption, but not smoking, for the association between SEP and mortality.

Leisure-time physical activity, desire to increase physical activity, and mortality: A population-based prospective cohort study

The aim was to investigate associations between leisure-time physical activity (LTPA) and mortality, and associations between desire to increase LTPA and mortality within the low LTPA group. A public health survey questionnaire was sent in 2008 to a stratified random sample of the population aged 18-80 in southernmost Sweden, yielding a 54.1% response rate. Baseline 2008 survey data with 25,464 respondents was linked to cause of death register data to create a prospective cohort with 8.3-year follow-up. Associations between LTPA, desire to increase LTPA and mortality were analyzed in logistic regression models. An 18.4% proportion performed regular exercise (at least 90 min/week, leading to sweating), 23.2% moderate regular exercise (once or twice a week at least 30 min/occasion, leading to sweating), 44.3% moderate exercise (more than two hours walking or equivalent activity/week) and 14.1% reported low LTPA (less than two hours walking or equivalent activity/week). These four LTPA groups were significantly associated with covariates included in the multiple analyses. The results showed significantly higher all-cause, cardiovascular (CVD), cancer and other cause mortality for the low LTPA group but not for the moderate regular exercise and moderate exercise groups compared to the regular exercise group. Both the "Yes, but I need support" and the "No" fractions within the low LTPA group had significantly increased ORs of all-cause mortality compared to the "Yes, and I can do it myself" reference, while no significant associations were observed for CVD mortality. Physical activity promotion is particularly warranted in the low LTPA group.

The Role of Epigenetic Clocks in Explaining Educational Inequalities in Mortality: A Multicohort Study and Meta-analysis

Educational inequalities in all-cause mortality have been observed for decades. However, the underlying biological mechanisms are not well known. We aimed to assess the role of DNA methylation changes in blood captured by epigenetic clocks in explaining these inequalities. Data were from 8 prospective population-based cohort studies, representing 13 021 participants. First, educational inequalities and their portion explained by Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, and DNAmGrimAge epigenetic clocks were assessed in each cohort via counterfactual-based mediation models, on both absolute (hazard difference) and relative (hazard ratio) scales, and by sex. Second, estimates from each cohort were pooled through a random effect meta-analysis model. Men with low education had excess mortality from all causes of 57 deaths per 10 000 person-years (95% confidence interval [CI]: 38, 76) compared with their more advantaged counterparts. For women, the excess mortality was 4 deaths per 10 000 person-years (95% CI: -11, 19). On the relative scale, educational inequalities corresponded to hazard ratios of 1.33 (95% CI: 1.12, 1.57) for men and 1.15 (95% CI: 0.96, 1.37) for women. DNAmGrimAge accounted for the largest proportion, approximately 50%, of the educational inequalities for men, while the proportion was negligible for women. Most of this mediation was explained by differential effects of unhealthy lifestyles and morbidities of the World Health Organization (WHO) risk factors for premature mortality. These results support DNA methylation-based epigenetic aging as a signature of educational inequalities in life expectancy emphasizing the need for policies to address the unequal social distribution of these WHO risk factors.

What’s important to you? Socioeconomic inequalities in the perceived importance of health compared to other life domains

Background

Pressing issues, like financial concerns, may outweigh the importance people attach to health. This study tested whether health, compared to other life domains, was considered more important by people in high versus low socioeconomic positions, with future focus and financial strain as potential explanatory factors.

Methods

A cross-sectional survey was conducted in 2019 among N=1,330 Dutch adults. Participants rated the importance of two health-related domains (not being ill, living a long life) and seven other life domains (e.g., work, family) on a five-point scale. A latent class analysis grouped participants in classes with similar patterns of importance ratings. Differences in class membership according to socioeconomic position (indicated by income and education) were examined using structural equation modelling, with future focus and financial strain as mediators.

Results

Three classes were identified, which were defined as: neutralists, who found all domains neutral or unimportant (3.5% of the sample); hedonists, who found most domains important except living a long life, work, and religion (36.2%); and maximalists, who found nearly all domains important, including both health domains (60.3%). Of the neutralists, 38% considered not being ill important, and 30% considered living a long life important. For hedonists, this was 92% and 39%, respectively, and for maximalists this was 99% and 87%, respectively. Compared to belonging to the maximalists class, a low income predicted belonging to the neutralists, and a higher educational level and unemployment predicted belonging to the hedonists. No mediation pathways via future focus or financial strain were found.

Conclusions

Lower income groups were less likely to consider not being ill important. Those without paid employment and those with a higher educational level were less likely to consider living a long life important. Neither future focus nor financial strain explained these inequalities. Future research should investigate socioeconomic differences in conceptualisations of health, and if inequalities in the perceived importance of health are associated with inequalities in health. To support individuals dealing with challenging circumstances in daily life, health-promoting interventions could align to the life domains perceived important to reach their target group and to prevent widening socioeconomic health inequalities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-12508-2.

Socioeconomic inequalities in health behaviors: exploring mediation pathways through material conditions and time orientation

BACKGROUND

Socioeconomic inequalities in health behaviors have been attributed to both structural and individual factors, but untangling the complex, dynamic pathways through which these factors influence inequalities requires more empirical research. This study examined whether and how two factors, material conditions and time orientation, sequentially impact socioeconomic inequalities in health behaviors.

METHODS

Dutch adults 25 and older self-reported highest attained educational level, a measure of socioeconomic position (SEP); material conditions (financial strain, housing tenure, income); time orientation; health behaviors including smoking and sports participation; and health behavior-related outcomes including body mass index (BMI) and self-assessed health in three surveys (2004, 2011, 2014) of the longitudinal GLOBE (Dutch acronym for "Health and Living Conditions of the Population of Eindhoven and surroundings") study. Two hypothesized pathways were investigated during a ten-year time period using sequential mediation analysis, an approach that enabled correct temporal ordering and control for confounders such as baseline health behavior.

RESULTS

Educational level was negatively associated with BMI, positively associated with sports participation and self-assessed health, and not associated with smoking in the mediation models. For smoking, sports participation, and self-assessed health, a pathway from educational level to the outcome mediated by time orientation followed by material conditions was observed.

CONCLUSIONS

Time orientation followed by material conditions may play a role in determining socioeconomic inequalities in certain health behavior-related outcomes, providing empirical support for the interplay between structural and individual factors in socioeconomic inequalities in health behavior. Smoking may be determined by prior smoking behavior regardless of SEP, potentially due to its addictive nature. While intervening on time orientation in adulthood may be challenging, the results from this study suggest that policy interventions targeted at material conditions may be more effective in reducing socioeconomic inequalities in certain health behaviors when they account for time orientation.

Understanding the influence of socioeconomic status on the association between combinations of lifestyle factors and adverse health outcomes: a systematic review protocol

INTRODUCTION

Combinations of unhealthy lifestyle factors are strongly associated with mortality, cardiovascular disease (CVD) and cancer. It is unclear how socioeconomic status (SES) affects those associations. Lower SES groups may be disproportionately vulnerable to the effects of unhealthy lifestyle factors compared with higher SES groups via interactions with other factors associated with low SES (eg, stress) or via accelerated biological ageing. This systematic review aims to synthesise studies that examine how SES moderates the association between lifestyle factor combinations and adverse health outcomes. Greater understanding of how lifestyle risk varies across socioeconomic spectra could reduce adverse health by (1) identifying novel high-risk groups or targets for future interventions and (2) informing research, policy and interventions that aim to support healthy lifestyles in socioeconomically deprived communities.

METHODS AND ANALYSIS

Three databases will be searched (PubMed, EMBASE, CINAHL) from inception to March 2020. Reference lists, citations and grey literature will also be searched. Inclusion criteria are: (1) prospective cohort studies; (2) investigations of two key exposures: (a) lifestyle factor combinations of at least three lifestyle factors (eg, smoking, physical activity and diet) and (b) SES (eg, income, education or poverty index); (3) an assessment of the impact of SES on the association between combinations of unhealthy lifestyle factors and health outcomes; (4) at least one outcome from-mortality (all cause, CVD and cancer), CVD or cancer incidence. Two independent reviewers will screen titles, abstracts and full texts of included studies. Data extraction will focus on cohort characteristics, exposures, direction and magnitude of SES effects, methods and quality (via Newcastle-Ottawa Scale). If appropriate, a meta-analysis, pooling the effects of SES, will be performed. Alternatively, a synthesis without meta-analysis will be conducted.

ETHICS AND DISSEMINATION

Ethical approval is not required. Results will be disseminated via peer-reviewed publication, professional networks, social media and conference presentations.

PROSPERO REGISTRATION NUMBER

CRD42020172588.

Working conditions and health behavior as causes of educational inequalities in self-rated health: an inverse odds weighting approach

Objective:

Using a novel mediation method that presents unbiased results even in the presence of exposure–mediator interactions, this study estimated the extent to which working conditions and health behaviors contribute to educational inequalities in self-rated health in the workforce.

Methods:

Respondents of the longitudinal Survey of Health, Ageing, and Retirement in Europe (SHARE) in 16 countries were selected, aged 50–64 years, in paid employment at baseline and with information on education and self-rated health (N=15 028). Education, health behaviors [including body mass index (BMI)] and working conditions were measured at baseline and self-rated health at baseline and two-year follow-up. Causal mediation analysis with inverse odds weighting was used to estimate the total effect of education on self-rated health, decomposed into a natural direct effect (NDE) and natural indirect effect (NIE).

Results:

Lower educated workers were more likely to perceive their health as poor than higher educated workers [relative risk (RR) 1.48, 95% confidence interval (CI) 1.37–1.60]. They were also more likely to have unfavorable working conditions and unhealthy behaviors, except for alcohol consumption. When all working conditions were included, the remaining NDE was RR 1.30 (95% CI 1.15–1.44). When BMI and health behaviors were included, the remaining NDE was RR 1.40 (95% CI 1.27–1.54). Working conditions explained 38% and health behaviors and BMI explained 16% of educational inequalities in health. Including all mediators explained 64% of educational inequalities in self-rated health.

Conclusions:

Working conditions and health behaviors explain over half of the educational inequalities in self-rated health. To reduce health inequalities, improving working conditions seems to be more important than introducing health promotion programs in the workforce.

Socioeconomic disparities in U.S. mortality: The role of smoking and alcohol/drug abuse

Prior studies have identified smoking as a key driver of socioeconomic disparities in U.S. mortality, but the growing drug epidemic leads us to question whether drug abuse is exacerbating those disparities, particularly for mortality from external causes. We use data from a national survey of midlife Americans to evaluate socioeconomic disparities in all-cause and cause-specific mortality over an 18-year period (1995-2013). Then, we use marginal structural modeling to quantify the indirect effects of smoking and alcohol/drug abuse in mediating those disparities. Our results demonstrate that alcohol/drug abuse makes little contribution to socioeconomic disparities in all-cause mortality, probably because the prevalence of substance abuse is low and socioeconomic differences in abuse are small, especially at older ages when most Americans die. Smoking prevalence is much higher than drug/alcohol abuse and socioeconomic differentials in smoking are large and have widened among younger cohorts. Not surprisingly, smoking accounts for the majority (62%) of the socioeconomic disparity in mortality from smoking-related diseases, but smoking also makes a substantial contribution to cardiovascular (38%) and all-cause mortality (34%). Based on the observed cohort patterns of smoking, we predict that smoking will further widen SES disparities in all-cause mortality until at least 2045 for men and even later for women. Although we cannot yet determine the mortality consequences of recent widening of the socioeconomic disparities in drug abuse, social inequalities in mortality are likely to grow even wider over the coming decades as the legacy of smoking and the recent drug epidemic take their toll.

Socioeconomic inequalities in effectiveness of and compliance to workplace health promotion programs: an individual participant data (IPD) meta-analysis

BACKGROUND

This individual patient data (IPD) meta-analysis aimed to investigate socioeconomic inequalities in effectiveness on healthy behavior of, and compliance to, workplace health promotion programs.

METHODS

Dutch (randomized) controlled trials were identified and original IPD were retrieved and harmonized. A two-stage meta-analysis was conducted where linear mixed models were performed per study (stage 1), after which individual study effects were pooled (stage 2). All models were adjusted for baseline values of the outcomes, age and gender. Intervention effects were assessed on physical activity, diet, alcohol use, and smoking. Also, we assessed whether effects differed between participants with low and high program compliance and. All analyses were stratified by socioeconomic position.

RESULTS

Data from 15 studies (n = 8709) were harmonized. Except for fruit intake (beta: 0·12 [95% CI 0·08 0·15]), no effects were found on health behaviors, nor did these effects differ across socioeconomic groups. Only participants with high compliance showed significant improvements in vigorous and moderate-to-vigorous physical activity, and in more fruit and less snack intake. There were no differences in compliance across socioeconomic groups.

CONCLUSIONS

Workplace health promotion programs were in general not effective. Neither effectiveness nor compliance differed across socioeconomic groups (operationalized by educational level). Even though stronger effects on health behavior were found for participations with high compliance, effects remained small. The results of the current study emphasize the need for new directions in health promotion programs to improve healthy behavior among workers, in particular for those in lower socioeconomic position.

Influence of deprivation on initial severity and prognosis of patients admitted to the ICU: the prospective, multicentre, observational IVOIRE cohort study

Background

The influence of socioeconomic status on patient outcomes is unclear. We assessed the impact of socioeconomic deprivation on severity of illness at intensive care unit (ICU) admission, and on the risk of death at 3 months after ICU admission.

Methods

The IVOIRE study was a prospective, observational, multicentre cohort study in the ICU of 8 participating hospitals in France, including patients aged ≥ 18 years admitted to the ICU and receiving at least one life support therapy for organ failure. The primary outcomes were severity at admission (assessed by SAPSII score), and mortality at 3 months. Socioeconomic data were obtained from interviews with patients or family. Deprivation was assessed using the EPICES score.

Results

Among 1294 patents included between 2013 and 2016, 629 (48.6%) were classed as deprived and differed significantly from non-deprived subjects in terms of sociodemographic characteristics and pre-existing conditions. The mean SAPS II score at admission was 50.1 ± 19.4 in deprived patients and 52.3 ± 17.3 in non-deprived patients, with no significant difference by multivariable analysis (β = − 1.85 [95% CI − 3.86; + 0.16, p = 0.072]). The proportion of death was 31.1% at 3 months, without significant differences between deprived and non-deprived patients, even after adjustment for confounders.

Conclusions

Deprivation is frequent in patients admitted to the ICU and is not associated with disease severity at admission, or with mortality at 3 months between deprived and non-deprived patients.

Trial registration The IVOIRE cohort is registered with ClinicalTrials.gov under the identifier NCT01907581, registration date 17/7/2013

How does bridging social capital relate to health-behavior, overweight and obesity among low and high educated groups? A cross-sectional analysis of GLOBE-2014

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.

What's the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality

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.

Urban population density and mortality in a compact Dutch city: 23-year follow-up of the Dutch GLOBE study

We investigated the association and underlying pathways between urban population density and mortality in a compact mid-sized university city in the Netherlands. Baseline data from the GLOBE cohort study (N = 10,120 residents of Eindhoven) were linked to mortality after 23 years of follow up and analyzed in multilevel models. Higher population density was modestly related to increased mortality, independently of baseline socioeconomic position and health. Higher population density was related to more active transport, more perceived urban stress and smoking. Increased active transport suppressed the mortality-increasing impact of higher population density. Overall, in dense cities with good infrastructure for walking and cycling, high population density may negatively impact mortality.

Public rental housing and its association with mortality - a retrospective, cohort study

BACKGROUND

Socioeconomic status (SES) is a well-established determinant of health status and home ownership is a commonly used composite indicator of SES. Patients in low-income households often stay in public rental housing. The association between public rental housing and mortality has not been examined in Singapore.

METHODS

A retrospective, cohort study was conducted involving all patients who utilized the healthcare facilities under SingHealth Regional Health (SHRS) Services in Year 2012. Each patient was followed up for 5 years. Patients who were non-citizens or residing in a non-SHRS area were excluded from the study.

RESULTS

A total of 147,004 patients were included in the study, of which 7252 (4.9%) patients died during the study period. The mean age of patients was 50.2 ± 17.2 years old and 7.1% (n = 10,400) of patients stayed in public rental housing. Patients who passed away had higher utilization of healthcare resources in the past 1 year and a higher proportion stayed in public rental housing (p < 0.001). They also had higher rates of co-morbidities such as hypertension, hyperlipidaemia and diabetes. (p < 0.001) After adjustment for demographic and clinical covariates, residence in public rental housing was associated with increased risk of all-cause mortality (Adjusted hazard ratio: 1.568, 95% CI: 1.469-1.673).

CONCLUSION

Public rental housing was an independent risk factor for all-cause mortality. More studies should be conducted to understand health-seeking behavior and needs of public rental housing patients, to aid policymakers in formulating better plans for improving their health outcomes.