Reducing social inequalities in health: the role of simulation modelling in chronic disease epidemiology to evaluate the impact of population health interventions

The Joint Effect of Education and Alcohol Use on 100% Alcohol-attributable Hospitalization or Death in Canada

BACKGROUND

Individuals with low socioeconomic position (SEP) experience disproportionately greater alcohol-attributable harm than individuals with high SEP despite similar or less alcohol use (i.e., the alcohol harm paradox). We examined the sex/gender- specific independent and joint effects of education and heavy drinking or volume of alcohol use on 100% alcohol-attributable hospitalization or death.

METHODS

We conducted a cohort study among 199,125 current and former alcohol users aged 15-64 years from population-representative Canadian Community Health Surveys (2000-2008) linked to hospitalization and mortality records through 2017. We estimated the sex/gender-specific associations between education and heavy drinking or volume of alcohol use and incident 100% alcohol-attributable hospitalization or death using multivariable Fine and Gray subdistribution hazard models with competing risk (non-100% alcohol-attributable deaths), assessing additive interactions using the Synergy Index (S).

RESULTS

Overall, heavy drinking prevalence and volume of alcohol use were similar or lower in individuals with lower education compared with higher education. Lower education levels compared with a bachelor's degree or above were associated with increased 100% alcohol-attributable hospitalization or death [e.g., less than high school, men: hazard ratio (HR) = 2.78; 95% CI = 2.17, 3.56; women: HR = 2.98; 95% CI = 2.00, 4.44]. We found superadditive joint effects between low education and heavy drinking (men: S = 1.22; 95% CI = 1.14, 1.30; women: S = 1.34; 95% CI = 0.88, 2.04) and low education and higher volume of alcohol use (e.g., excess volume, men: S = 1.30; 95% CI = 1.05, 1.62; women: S = 1.41; 95% CI = 0.77, 2.58), with larger inequities in women than men with similar alcohol use.

CONCLUSIONS

Our study is consistent with the hypothesis that increased vulnerability to alcohol use among individuals with lower education partially explains the alcohol harm paradox in Canada.

Bridging ethics and epidemiology: Modelling ethical standards of health equity

Health inequities are differences in health that are 'unjust'. Yet, despite competing ethical views about what counts as an 'unjust difference in health', theoretical insights from ethics have not been systematically integrated into epidemiological research. Using diabetes as an example, we explore the impact of adopting different ethical standards of health equity on population health outcomes. Specifically, we explore how the implementation of population-level weight-loss interventions using different ethical standards of equity impacts the intervention's implementation and resultant population health outcomes. We conducted a risk prediction modelling study using the nationally representative 2015-16 Canadian Community Health Survey (n = 75,044, 54% women). We used the Diabetes Population Risk Tool (DPoRT) to calculate individual-level 10-year diabetes risk. Hypothetical weight-loss interventions were modelled in individuals with overweight or obesity based on each ethical standard: 1) health sufficiency (reduce DPoRT risk below a high-risk threshold (16.5%); 2) health equality (equalize DPoRT risk to the low risk group (5%)); 3) social-health sufficiency (reduce DPoRT risk <16.5 in individuals with lower education); 4) social-health equality (equalize DPoRT risk to the level of individuals with high education). For each scenario, we calculated intervention impacts, diabetes cases prevented or delayed, and relative and absolute educational inequities in diabetes. Overall, we estimated that achieving health sufficiency (i.e., all individuals below the diabetes risk threshold) was more feasible than achieving health equality (i.e., diabetes risk equalized for all individuals), requiring smaller initial investments and fewer interventions; however, fewer diabetes cases were prevented or delayed. Further, targeting only diabetes inequalities related to education reduced the target population size and number of interventions required, but consequently resulted in even fewer diabetes cases prevented or delayed. Using diabetes as an example, we found that an explicit, ethically-informed definition of health equity is essential to guide population-level interventions that aim to reduce health inequities.

Modeling cigarette smoking disparities between people with and without serious psychological distress in the US, 1997-2100

Cigarette smoking rates are significantly higher among people with serious psychological distress (SPD) compared to the general population. US simulation models that project future smoking disparities by SPD status could inform policy interventions, but have not been developed. We calibrated two compartmental models to the National Health Interview Survey 1997-2018 for populations with and without SPD, calculating smoking prevalence, mortality, and life-years lost by SPD status under different scenarios from 2023 to 2100. Under the Status Quo, smoking prevalence among women with SPD falls from 27.0% in 2023 to 10.7% in 2100 (men: 30.1% to 12.2%). For women without SPD, it declines from 9.4% to 3.1% (men: 11.5% to 4.0%). The absolute difference in smoking prevalence between those with and without SPD decreases over time, whereas the relative smoking prevalence ratio increases. From 2023 to 2100, 609,000 premature smoking-attributable deaths would occur in the SPD population, with 8 million life-years lost. Under an ideal tobacco control scenario for people with SPD, in which all smokers quit in 2023 and no new smoking initiation occurs thereafter, up to 386,000 of these premature deaths could be averted with 4.9 million life-years gained. Preventing smoking initiation could avert up to 18% of these deaths, while improving smoking cessation could avert up to 82%. Smoking-related disparities for people with SPD will persist unless a shift in tobacco control substantially improves cessation and prevents initiation in this subpopulation. Smoking disparities by SPD may widen in relative but narrow in absolute terms, so both perspectives should be evaluated.

Cost optimisation analysis of the expanded programme for immunisation: balancing equity and coverage in Pakistan

Introduction

With limited resources, attaining maximal average health service coverage can be at odds with maximising equity which attempts to promote greater reach among underserved populations. In this study, we examined the trade-offs in immunisation coverage levels and equity for children under 5 years of age in Pakistan across various subpopulations who can be targeted with different combinations of immunisation service modalities.

Methods

We conducted a detailed costing exercise across 16 geographically and demographically diverse districts in Pakistan. These data were the basis for (a) technical efficiency benchmarking via Data Envelopment Analysis to identify potential efficiency gains by location, delivery model and cost ingredient; (b) allocative efficiency optimisation modelling to understand how resource allocations could be optimised and to devise recommended budget allocations and operational metrics. Finally, the hypothetical overall efficiency gains attainable were estimated if available resources were allocated with the optimal emphases, and if service delivery models operated at productivity levels at the benchmarked frontier of efficiency.

Results

Benchmarking suggests that ~44% of delivery models are running efficiently and 37% are highly inefficient. While coverage and equity are usually at odds, surprisingly, the optimisation modelling revealed that substantial improvements in equity between subpopulations does not necessarily cost very much in overall immunisation coverage: theoretically, equity can be achieved while still attaining close to maximal immunisation coverage. Overall, analyses suggest greater emphases should be placed on outreach delivery models which particularly target rural areas and slum populations.

Conclusion

The unit cost differentials within districts are not sufficiently large for there to be a large reduction in potential Fully Immunised Children coverage if one focuses on maximising equity. However, reallocations of programme budgets can have a significant impact on equity outcomes, particularly at current low spending amounts. Therefore, it is recommended to address equity as the key objective in national immunisation programming.

Interventions on Socioeconomic and Racial Inequities in Respiratory Pandemics: a Rapid Systematic Review

Purpose of Review

Racial and socioeconomic inequities in respiratory pandemics have been consistently documented, but little official guidance exists on effective action to prevent these. We systematically reviewed quantitative evaluations of (real or simulated) interventions targeting racial and socioeconomic inequities in respiratory pandemic outcomes.

Recent Findings

Our systematic search returned 10,208 records, of which 5 met inclusion criteria, including observational (n = 1), randomized trial (n = 1), and simulation (n = 3) studies. Interventions studied included vaccination parity, antiviral distribution, school closure, disinfection, personal protective equipment, and paid sick leave, with a focus on Black (n = 3) and/or Latinx (n = 4) or low-SES (n = 2) communities. Results are suggestive that these interventions might be effective at reducing racial and/or SES disparities in pandemics.

Summary

There is a dearth of research on strategies to reduce pandemic disparities. We provide theory-driven, concrete suggestions for incorporating equity into intervention research for pandemic preparedness, including a focus on social and economic policies.

Evolution and Reproducibility of Simulation Modeling in Epidemiology and Health Policy Over Half a Century

Simulation models are increasingly being used to inform epidemiologic studies and health policy, yet there is great variation in their transparency and reproducibility. In this review, we provide an overview of applications of simulation models in health policy and epidemiology, analyze the use of best reporting practices, and assess the reproducibility of the models using predefined, categorical criteria. We identified and analyzed 1,613 applicable articles and found exponential growth in the number of studies over the past half century, with the highest growth in dynamic modeling approaches. The largest subset of studies focused on disease policy models (70%), within which pathological conditions, viral diseases, neoplasms, and cardiovascular diseases account for one-third of the articles. Model details were not reported in almost half of the studies. We also provide in-depth analysis of modeling best practices, reporting quality and reproducibility of models for a subset of 100 articles (50 highly cited and 50 randomly selected from the remaining articles). Only 7 of 26 in-depth evaluation criteria were satisfied by more than 80% of samples. We identify areas for increased application of simulation modeling and opportunities to enhance the rigor and documentation in the conduct and reporting of simulation modeling in epidemiology and health policy.

Equity impacts of interventions to increase physical activity among older adults: a quantitative health impact assessment

BACKGROUND

Behavioural interventions may increase social inequalities in health. This study aimed to project the equity impact of physical activity interventions that have differential effectiveness across education groups on the long-term health inequalities by education and gender among older adults in Germany.

METHODS

We created six intervention scenarios targeting the elderly population: Scenarios #1-#4 applied realistic intervention effects that varied by education (low, medium high). Under scenario #5, all older adults adapted the physical activity pattern of those with a high education. Under scenario #6, all increased their physical activity level to the recommended 300 min weekly. The number of incident ischemic heart disease, stroke and diabetes cases as well as deaths from all causes under each of these six intervention scenarios was simulated for males and females over a 10-year projection period using the DYNAMO-HIA tool. Results were compared against a reference-scenario with unchanged physical activity.

RESULTS

Under scenarios #1-#4, approximately 3589-5829 incident disease cases and 6248-10,320 deaths could be avoided among males over a 10-year projection period, as well as 4381-7163 disease cases and 6914-12,605 deaths among females. The highest reduction for males would be achieved under scenario #4, under which the intervention is most effective for those with a high education level. Scenario #4 realizes 2.7 and 2.4% of the prevented disease cases and deaths observed under scenario #6, while increasing inequalities between education groups. In females, the highest reduction would be achieved under scenario #3, under which the intervention is most effective amongst those with low levels of education. This scenario realizes 2.7 and 2.9% of the prevented disease cases and deaths under scenario #6, while decreasing inequalities between education groups. Under scenario #5, approximately 31,687 incident disease cases and 59,068 deaths could be prevented among males over a 10-year projection period, as well as 59,173 incident disease cases and 121,689 deaths among females. This translates to 14.4 and 22.2% of the prevented diseases cases among males and females under scenario #6, and 13.7 and 27.7% of the prevented deaths under scenario #6.

CONCLUSIONS

This study shows how the overall population health impact varies depending on how the intervention-induced physical activity change differs across education groups. For decision-makers, both the assessment of health impacts overall as well as within a population is relevant as interventions with the greatest population health gain might be accompanied by an unintended increase in health inequalities.

Impact of Self-Monitoring of Blood Pressure on Processes of Hypertension Care and Long-Term Blood Pressure Control

Background Self-monitoring of blood pressure (SMBP) improves blood pressure (BP) outcomes at 12-months, but information is lacking on how SMBP affects hypertension care processes and longer-term BP outcomes. Methods and Results We pooled individual participant data from 4 randomized clinical trials of SMBP in the United Kingdom (combined n=2590) with varying intensities of support. Multivariable random effects regression was used to estimate the probability of antihypertensive intensification at 12 months for usual care versus SMBP. Using these data, we simulated 5-year BP control rates using a validated mathematical model. Trial participants were mostly older adults (mean age 66.6 years, SD 9.5), male (53.9%), and predominantly white (95.6%); mean baseline BP was 151.8/85.0 mm Hg. Compared with usual care, the likelihood of antihypertensive intensification increased with both SMBP with feedback to patient or provider alone (odds ratio 1.8, 95% CI 1.2-2.6) and with telemonitoring or self-management (3.3, 2.5-4.2). Over 5 years, we estimated 33.4% BP control (<140/90 mm Hg) with usual care (95% uncertainty interval 27.7%-39.4%). One year of SMBP with feedback to patient or provider alone achieved 33.9% (28.3%-40.3%) BP control and SMBP with telemonitoring or self-management 39.0% (33.1%-45.2%) over 5 years. If SMBP interventions and associated BP control processes were extended to 5 years, BP control increased to 52.4% (45.4%-59.8 %) and 72.1% (66.5%-77.6%), respectively. Conclusions One year of SMBP plus telemonitoring or self-management increases the likelihood of antihypertensive intensification and could improve BP control rates at 5 years; continuing SMBP for 5 years could further improve BP control.

Simulations of future cardiometabolic disease and life expectancy under counterfactual obesity reduction scenarios

•

HIAs provide simulations of future disease levels related to an array of obesity scenarios.

•

In a relatively lean population, obesity still contribute to a substantial reduction in life expectancy.

•

Large reductions in diabetes and multi-morbidity is estimated as an effect of reducing obesity.

•

Incremental increase in future stroke and IHD cases is expected.

The aim of this study was to provide decision makers with an assessment of potential future health effects of interventions against overweight and obesity (OWOB). By means of the DYNAMO-HIA tool we conducted a health impact assessment simulating future prevented disease (ischemic heart disease (IHD), diabetes, stroke, and multi morbidity) incidence, prevalence and life expectancy (LE) related to a scenario where OWOB is reduced by 25% and a scenario where obesity is eliminated. The study covered projected number of persons living in Copenhagen, Denmark during year 2014–2040 (n 2040 = 742,129). Reducing the proportion of men/women with OWOB with 25% will increase population LE by 2.4/1.2 months and at the same time decrease LE with diabetes by 3.1/2.2 months. As a result of eliminating obesity, total LE will increase by 6.0/3.6 months and LE with diabetes will decrease with 9.8/10.3 months for men/women. We found no important effects on LE with IHD and stroke. This illustrates that the positive effects of lowering OWOB levels on IHD and stroke incidence is offset due to increasing total LE. Although the population of Copenhagen is relatively lean, reducing obesity levels will result in significant benefits for population cardiometabolic health status and LE. Future public health prevention programs may use the results as reference data for potential impact of reductions in OWOB.

An exploration using system dynamics modelling of population-level mindfulness, mindful eating and healthy weight following intervention

BACKGROUND

Mindful eating has been introduced as a strategy to help prevent overweight and obesity.

AIM

The purpose of this research was to develop a simple system dynamics model to investigate the impact of different interventions on population level mindfulness, mindful eating and healthy weight over a 10-year period.

METHODS

A model was constructed and outcomes analysed following the addition of four mindful eating interventions, including decreasing busyness (formal and informal work), promotion of mindful eating (e.g. classes and media), promotion of mindfulness, reduction of external eating cues (decreased portion sizes and variety) or a combination of all interventions.

RESULTS

The model projected that if the current situation was to continue over the next 10-year period, there would be a small decrease of 0.6% in the healthy-weight population despite a 42% increase in people practising mindfulness and 40% increase in people eating mindfully. Of the four interventions introduced, decreasing busyness had the greatest impact on the number of people practising mindfulness, eating mindfully and of a healthy weight. However, when all four interventions were introduced together this resulted in the greatest (19%) increase in the proportion of healthy-weight people.

CONCLUSIONS

The study suggests that mindful eating can be improved through intervention, however, the interventions will not greatly contribute to improving the healthy-weight population unless implemented in combination.

The effect of income-based policies on mortality inequalities in Scotland: a modelling study

BACKGROUND

The unequal distribution of income is a fundamental determinant of health inequalities. Decision making around economic policies could be enhanced by showing their potential health effects. We used scenario modelling to assess the effects of 12 income-based policies on years of life lost (YLL) and inequalities in YLL in Scotland for the 2017-21 period.

METHODS

In this modelling study, we used EUROMOD version H1.0+, a tax-benefit microsimulation model, to estimate the effects of hypothetical fiscal policies on household income for Scottish households in the 2014/15 Family Resources Survey (n=2871). The effects were modelled excluding housing costs. Income change from baseline was estimated for each quintile of the 2016 Scottish Index of Multiple Deprivation (SIMD) after weighting to account for differential non-response to the Family Resources Survey, and incomes were equivalised according to the Organisation for Economic Co-operation and Development's modified equivalence scale. A regression analysis of cross-sectional data was used to estimate the relationship between income change and all-cause mortality, followed up by a sensitivity analysis to account for uncertainties around the assumptions on effect size. Informing Interventions to reduce health Inequalities (Triple I), a health inequalities scenario modelling tool, was used to estimate policy effects on YLL and government spending after five years of theoretical implementation. The Triple I model used population estimates for 2016 stratified by sex, 5-year age group, and SIMD quintile, which were obtained from the National Records of Scotland. Preliminary estimates of relative policy costs were calculated from the EUROMOD-derived combined effects of each policy on tax bills, National Insurance contributions, and benefits receipts for Scottish households.

FINDINGS

Taxation-based policies did not substantially affect household incomes, whereas benefits-based policies had large effects across the quintiles. The best policy for improving health and narrowing health inequalities was a 50% increase to means-tested benefits (approximately 105 177 [4·7%] YLL fewer than the baseline of 2·2 million, and a 7·9% reduction in relative index of inequality). Effects on YLL and health inequalities were inversely correlated in response to changes in taxation policy. Citizen's Basic Income (CBI) schemes also substantially narrowed inequalities (3·7% relative index of inequality for basic scheme, 5·9% for CBI with additional payments for individuals with disability), and modestly reduced YLL (0·7% for the basic scheme and 1·4% with additional payments). The estimated government spending associated with a policy was proportional to its effect on YLL, but less closely related to its effect on inequalities in YLL.

INTERPRETATION

Policies that affect incomes could potentially have marked effects on health and health inequalities in Scotland. Our projections suggest that the most effective policies for reducing health inequalities appeared to be those that disproportionately increased incomes in the most deprived areas. Although modelling was subject to various assumptions, the approach can be useful to inform decisions around addressing the upstream determinants of health inequalities.

FUNDING

None.

Socioeconomic inequalities in obesity: modelling future trends in Australia

OBJECTIVES

To develop a model to predict future socioeconomic inequalities in body mass index (BMI) and obesity.

DESIGN

Microsimulation modelling using BMI data from adult participants of Australian Health Surveys, and published data on the relative risk of mortality in relation to BMI and socioeconomic position (SEP), based on education.

SETTING

Australia.

PARTICIPANTS

74 329 adults, aged 20 and over from Australian Health Surveys, 1995-2015.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcomes were BMI trajectories and obesity prevalence by SEP for four birth cohorts, born 10 years apart, centred on 1940, 1950, 1960 and 1970.

RESULTS

Simulations projected persistent or widening socioeconomic inequality in BMI and obesity over the adult life course, for all birth cohorts. Recent birth cohorts were predicted to have greater socioeconomic inequality by middle age, compared with earlier cohorts. For example, among men, there was no inequality in obesity prevalence at age 60 for the 1940 birth cohort (low SEP 25% (95% CI 17% to 34%); high SEP 26% (95% CI 19% to 34%)), yet for the 1970 birth cohort, obesity prevalence was projected to be 51% (95% CI 43% to 58%) and 41% (95% CI 36% to 46%) for the low and high SEP groups, respectively. Notably, for more recent birth cohorts, the model predicted the greatest socioeconomic inequality in severe obesity (BMI >35 kg/m²) at age 60.

CONCLUSIONS

Lower SEP groups and more recent birth cohorts are at higher risk of obesity and severe obesity, and its consequences in middle age. Prevention efforts should focus on these vulnerable population groups in order to avoid future disparities in health outcomes. The model provides a framework for further research to investigate which interventions will be most effective in narrowing the gap in socioeconomic disparities in obesity in adulthood.

Quantifying the impact of reducing socioeconomic inequalities in modifiable risk factors on mortality and mortality inequalities in South Korea

OBJECTIVES

We quantified the impact of reducing socioeconomic inequalities in risk factors on mortality and mortality inequalities in South Korea.

METHODS

The mortality risk function from the 12-year mortality follow-up data of the National Health Insurance Service-National Health Screening Cohort, the prevalence of major risk factors from the Korea National Health and Nutrition Examination Survey 2013-2015, and the Health Plan 2020 (HP2020) goals for major risk factors were used to estimate the magnitude of reduction in mortality inequalities by changing the magnitude of income-based inequalities in risk factors in various scenarios under gender-specific models among participants aged 40-79 years.

RESULTS

The greatest reduction in absolute and relative inequalities in mortality would occur if the low-income group achieved the HP2020 goals earlier than the high-income group. A 10-20% reduction in all-cause mortality inequalities was expected if absolute gaps between income groups in risk factors were halved.

CONCLUSIONS

With the practical goal halving the socioeconomic gaps in modifiable risk factors, reducing inequalities in all-cause mortality by 10-20% would be possible. Further reduction in mortality inequalities would need more aggressive policies on social determinants of health.

Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century

Addressing minority health and health disparities has been a missing piece of the puzzle in Big Data science. This article focuses on three priority opportunities that Big Data science may offer to the reduction of health and health care disparities. One opportunity is to incorporate standardized information on demographic and social determinants in electronic health records in order to target ways to improve quality of care for the most disadvantaged populations over time. A second opportunity is to enhance public health surveillance by linking geographical variables and social determinants of health for geographically defined populations to clinical data and health outcomes. Third and most importantly, Big Data science may lead to a better understanding of the etiology of health disparities and understanding of minority health in order to guide intervention development. However, the promise of Big Data needs to be considered in light of significant challenges that threaten to widen health disparities. Care must be taken to incorporate diverse populations to realize the potential benefits. Specific recommendations include investing in data collection on small sample populations, building a diverse workforce pipeline for data science, actively seeking to reduce digital divides, developing novel ways to assure digital data privacy for small populations, and promoting widespread data sharing to benefit under-resourced minority-serving institutions and minority researchers. With deliberate efforts, Big Data presents a dramatic opportunity for reducing health disparities but without active engagement, it risks further widening them.

Informing Investment to Reduce Inequalities: A Modelling Approach

Background

Reducing health inequalities is an important policy objective but there is limited quantitative information about the impact of specific interventions.

Objectives

To provide estimates of the impact of a range of interventions on health and health inequalities.

Materials and Methods

Literature reviews were conducted to identify the best evidence linking interventions to mortality and hospital admissions. We examined interventions across the determinants of health: a ‘living wage’; changes to benefits, taxation and employment; active travel; tobacco taxation; smoking cessation, alcohol brief interventions, and weight management services. A model was developed to estimate mortality and years of life lost (YLL) in intervention and comparison populations over a 20-year time period following interventions delivered only in the first year. We estimated changes in inequalities using the relative index of inequality (RII).

Results

Introduction of a ‘living wage’ generated the largest beneficial health impact, with modest reductions in health inequalities. Benefits increases had modest positive impacts on health and health inequalities. Income tax increases had negative impacts on population health but reduced inequalities, while council tax increases worsened both health and health inequalities. Active travel increases had minimally positive effects on population health but widened health inequalities. Increases in employment reduced inequalities only when targeted to the most deprived groups. Tobacco taxation had modestly positive impacts on health but little impact on health inequalities. Alcohol brief interventions had modestly positive impacts on health and health inequalities only when strongly socially targeted, while smoking cessation and weight-reduction programmes had minimal impacts on health and health inequalities even when socially targeted.

Conclusions

Interventions have markedly different effects on mortality, hospitalisations and inequalities. The most effective (and likely cost-effective) interventions for reducing inequalities were regulatory and tax options. Interventions focused on individual agency were much less likely to impact on inequalities, even when targeted at the most deprived communities.

Social Determinants of Population Health: A Systems Sciences Approach

Population distributions of health emerge from the complex interplay of health-related factors at multiple levels, from the biological to the societal level. Individuals are aggregated within social networks, affected by their locations, and influenced differently across time. From aggregations of individuals, group properties can emerge, including some exposures that are ubiquitous within populations but variant across populations. By combining a focus on social determinants of health with a conceptual framework for understanding how genetics, biology, behavior, psychology, society, and environment interact, a systems science approach can inform our understanding of the underlying causes of the unequal distribution of health across generations and populations, and can help us identify promising approaches to reduce such inequalities. In this paper, we discuss how systems science approaches have already made several substantive and methodological contributions to the study of population health from a social epidemiology perspective.