Complex systems thinking and current impasses in health disparities research

Integrating Systems Science and Community-Based Participatory Research to Achieve Health Equity

Unanswered questions about racial and socioeconomic health disparities may be addressed using community-based participatory research and systems science. Community-based participatory research is an orientation to research that prioritizes developing capacity, improving trust, and translating knowledge to action. Systems science provides research methods to study dynamic and interrelated forces that shape health disparities. Community-based participatory research and systems science are complementary, but their integration requires more research. We discuss paradigmatic, socioecological, capacity-building, colearning, and translational synergies that help advance progress toward health equity.

Social-Biological Interactions in Oral Disease: A 'Cells to Society' View

Oral diseases constitute a major worldwide public health problem, with their burden concentrating in socially disadvantaged and less affluent groups of the population, resulting in significant oral health inequalities. Biomedical and behavioural approaches have proven relatively ineffective in reducing these inequalities, and have potentially increased the health gap between social groups. Some suggest this stems from a lack of understanding of how the social and psychosocial contexts in which behavioural and biological changes occur influence oral disease. To unravel the pathways through which social factors affect oral health outcomes, a better understanding is thus needed of how the social 'gets under the skin,' or becomes embodied, to alter the biological. In this paper, we present the current knowledge on the interplay between social and biological factors in oral disease. We first provide an overview of the process of embodiment in chronic disease and then evaluate the evidence on embodiment in oral disease by reviewing published studies in this area. Results show that, in periodontal disease, income, education and perceived stress are correlated with elevated levels of stress hormones, disrupted immune biomarkers and increased allostatic load. Similarly, socioeconomic position and increased financial stress are related to increased stress hormones and cariogenic bacterial counts in dental caries. Based on these results, we propose a dynamic model depicting social-biological interactions that illustrates potential interdependencies between social and biological factors that lead to poor oral health. This work and the proposed model may aid in developing a better understanding of the causes of oral health inequalities and implicate the importance of addressing the social determinants of oral health in innovating public health interventions.

Extreme Weather-driven Disasters and Children’s Health

Extreme weather events such as heat waves, extreme precipitation, and storm surges are likely to become more frequent and intense with climate change. Extreme weather-driven disasters (EWDDs) cause a substantial burden of childhood mortality and morbidity worldwide. We reviewed the published literature on EWDDs and their health impacts on children, and developed a conceptual model based on complex systems thinking to identify the health risks, vulnerabilities, and capacities of children in the context of EWDDs as a means of informing areas for adaptive intervention. We found that direct and indirect physical and mental impacts of EWDDs on child health are abundant and interrelate in complex ways. The literature review and modeling demonstrated the centrality of resilience at the level of the child and his or her direct environment, suggesting that mental health status may play a key role in a child’s experience of numerous other health outcomes of EWDDs. EWDDs interact with environmental and social systems and with individual children and their contexts in complex ways, the impacts of which are nonlinear and difficult to predict. Traditional perspectives on climate change-driven health impacts often overlook complex bio-psychosocial interactions, suggesting a need to work on preventive strategies to reduce vulnerability and build individual child resilience.

Health disparities of Latino immigrant workers in the United States

Purpose

– The purpose of this paper is to provide an overview of the literature pertaining to occupational health disparities experienced by Latino immigrant workers in the USA and to advance a general framework based on systems science to inform epidemiological and intervention research.

Design/methodology/approach

– Using papers and other sources from 2000 to the present, the authors examined the employment conditions and health outcomes of Latino immigrant workers and critically analyzed the pervasive evidence of health disparities, including causal mechanisms and associated intervention programs.

Findings

– The occupations, including the work environment and resultant living conditions, frequently performed by Latino immigrants in the USA represent a distinct trigger of increased injury risk and poor health outcomes. Extant intervention programs have had modest results at best and are in need of more comprehensive approaches to address the complex nature of health disparities.

Practical implications

– An integrated, systems-based framework concerning occupational health disparities among Latino immigrant workers allows for a holistic approach encompassing innovative methods and can inform high-leverage interventions including public policy.

Originality/value

– Reductionist approaches to health disparities have had significant limitations and miss the complete picture of the many influences. The framework the authors have provided elucidates a valuable method for reducing occupational health disparities among Latino immigrant workers as well as other populations.

Switching to less expensive blindness drug could save medicare part B $18 billion over a ten-year period

The biologic drugs bevacizumab and ranibizumab have revolutionized treatment of diabetic macular edema and neovascular age-related macular degeneration, leading causes of blindness. Ophthalmologic use of these drugs has increased and now accounts for roughly one-sixth of the Medicare Part B drug budget. The two drugs have similar efficacy and potentially minor differences in adverse-event rates; however, at $2,023 per dose, ranibizumab costs forty times more than bevacizumab. Using modeling methods, we predict ten-year (2010-20) population-level costs and health benefits of using bevacizumab and ranibizumab. Our results show that if all patients were treated with the less expensive bevacizumab instead of current usage patterns, savings would amount to $18 billion for Medicare Part B and nearly $5 billion for patients. With an additional $6 billion savings in other health care expenses, the total savings would be almost $29 billion. Altering patterns of use with these therapies by encouraging bevacizumab use and hastening approval of biosimilar therapies would dramatically reduce spending without substantially affecting patient outcomes.

Reducing Income Inequalities in Food Consumption: Explorations With an Agent-Based Model

INTRODUCTION

Individual and environmental factors dynamically interact in shaping income inequalities in healthy food consumption. The agent-based model, Health Behaviors Simulation (HEBSIM), was developed to describe income inequalities in healthy food consumption. It simulates interactions between households and their environment. HEBSIM was used to explore the impact of interventions aimed at reducing food consumption inequalities.

METHODS

HEBSIM includes households and food outlets. Households are characterized by location, composition, income, and preference for food. Decisions about where to shop for food (fruit/vegetable stores, supermarkets, or discount supermarkets) and whether to visit fast food outlets are based on distance, price, and food preference. Food outlets can close and new food outlets can enter the system. Three interventions to reduce healthy food consumption inequalities were tested: (1) eliminating residential segregation; (2) lowering the prices of healthy food; and (3) providing health education. HEBSIM was quantified using data from Statistics Netherlands, Statistics Eindhoven, and the GLOBE study (2011).

RESULTS

The model mimicked food consumption in Eindhoven. High-income households visited healthy food shops more often than low-income households. Eliminating residential segregation had the largest impact in reducing income inequalities in food consumption, but resulted partly from a worsening in healthy food consumption in high-income households. Lowering prices and health education could also substantially reduce inequalities. Most interventions took 5-10 years to reach their (almost) full effects.

CONCLUSIONS

HEBSIM is a promising tool for studying dynamic interactions between households and their environment and for assessing the impact of interventions on income inequalities in food consumption.

Historical Perspective and Risk of Multiple Neglected Tropical Diseases in Coastal Tanzania: Compositional and Contextual Determinants of Disease Risk

Background

In the past decade, research on neglected tropical diseases (NTDs) has intensified in response to the need to enhance community participation in health delivery, establish monitoring and surveillance systems, and integrate existing disease-specific treatment programs to control overlapping NTD burdens and detrimental effects. In this paper, we evaluated the geographical distribution of NTDs in coastal Tanzania.

Methods and Findings

We also assessed the collective (compositional and contextual) factors that currently determine risks to multiple NTDs using a cross sectional survey of 1253 individuals in coastal Tanzania. The results show that the effect size in decreasing order of magnitude for non-binary predictors of NTD risks is as follows: NTD comorbidities > poverty > educational attainment > self-reported household quality of life > ethnicity. The multivariate analysis explained 95% of the variance in the relationship between NTD risks and the theoretically-relevant covariates. Compositional (biosocial and sociocultural) factors explained more variance at the neighbourhood level than at the regional level, whereas contextual factors, such as access to health services and household quality, in districts explained a large proportion of variance at the regional level but individually had modest statistical significance, demonstrating the complex interactions between compositional and contextual factors in generating NTD risks.

Conclusions

NTD risks were inequitably distributed over geographic space, which has several important policy implications. First, it suggests that localities of high burden of NTDs are likely to diminish within statistical averages at higher (regional or national) levels. Second, it indicates that curative or preventive interventions will become more efficient provided they can be focused on the localities, particularly as populations in these localities are likely to be burdened by several NTDs simultaneously, further increasing the imperative of multi-disease interventions.

Neglected Tropical Diseases (NTDs) are characterized by their high incidence in low-income countries, thus maintaining the disastrous poverty-disease-poverty cycle. Apart from poverty, however, little is known of the magnitude of importance of both compositional and contextual factors in creating disease risk at the local level, although this knowledge is critical to disease control and policy action. In this study, we show that the order of importance of both sets of factors is as follows: NTD comorbidities > poverty > educational attainment > self-reported household quality of life > ethnicity.

The Challenge of Cardiovascular Diseases and Diabetes to Public Health: A Study Based on Qualitative Systemic Approach

The most common modeling approaches to understanding incidence, prevalence and control of chronic diseases in populations, such as statistical regression models, are limited when it comes to dealing with the complexity of those problems. Those complex adaptive systems have characteristics such as emerging properties, self-organization and feedbacks, which structure the system stability and resistance to changes. Recently, system science approaches have been proposed to deal with the range, complexity, and multifactor nature of those public health problems. In this paper we applied a multilevel systemic approach to create an integrated, coherent, and increasingly precise conceptual framework, capable of aggregating different partial or specialized studies, based on the challenges of the Longitudinal Study of Adult Health - ELSA-Brasil. The failure to control blood pressure found in several of the study's subjects was discussed, based on the proposed model, analyzing different loops, time lags, and feedback that influence this outcome in a population with high educational level, with reasonably good health services access. We were able to identify the internal circularities and cycles that generate the system's resistance to change. We believe that this study can contribute to propose some new possibilities of the research agenda and to the discussion of integrated actions in the field of public health.

Using the principles of complex systems thinking and implementation science to enhance maternal and child health program planning and delivery

Traditionally, epidemiologic methodologies have focused on measurement of exposures, outcomes, and program impact through reductionistic, yet complex statistical modeling. Although not new to the field of epidemiology, two frameworks that provide epidemiologists with a foundation for understanding the complex contexts in which programs and policies are implemented were presented to maternal and child health (MCH) professionals at the 2012 co-hosted 18th Annual MCH Epidemiology Conference and 22nd CityMatCH Urban Leadership Conference. The complex systems approach offers researchers in MCH the opportunity to understand the functioning of social, medical, environmental, and behavioral factors within the context of implemented public health programs. Implementation science provides researchers with a framework to translate the evidence-based program interventions into practices and policies that impact health outcomes. Both approaches offer MCH epidemiologists conceptual frameworks with which to re-envision how programs are implemented, monitored, evaluated, and reported to the larger public health audience. By using these approaches, researchers can begin to understand and measure the broader public health context, account for the dynamic interplay of the social environment, and ultimately, develop more effective MCH programs and policies.

Is uncertainty in complex disease epidemiology resolvable?

The imposed limitations on what we can know about nature have been long recognized. Yet in the field of epidemiology a futile search for lifestyle-related risk factors for common chronic diseases continues unabated. This has led to the production of a growing body of evidence about potential lifestyle risk factors that tend to be marginal, contradictory, irreproducible, or hard to interpret. While epidemiologists are calling for a more refined methodology, I argue that our limitation in studying complex diseases is insurmountable. This is because the study of lifestyle-related small risks requires accurate measurement of multiple behaviors-exposures over a long period of time. It is also because in complex systems such as population's health, the effect of rich interactions between its parts cannot be predicted based on traditional causal models of epidemiology. Within complex systems, understanding the interactions between system components can be more important than the contribution of each to disease risk.

What matters most: quantifying an epidemiology of consequence

Risk factor epidemiology has contributed to substantial public health success. In this essay, we argue, however, that the focus on risk factor epidemiology has led epidemiology to ever increasing focus on the estimation of precise causal effects of exposures on an outcome at the expense of engagement with the broader causal architecture that produces population health. To conduct an epidemiology of consequence, a systematic effort is needed to engage our science in a critical reflection both about how well and under what conditions or assumptions we can assess causal effects and also on what will truly matter most for changing population health. Such an approach changes the priorities and values of the discipline and requires reorientation of how we structure the questions we ask and the methods we use, as well as how we teach epidemiology to our emerging scholars.

The effect of geography and citizen behavior on motor vehicle deaths in the United States

Death due to motor vehicle collisions (MVCs) remains a leading cause of death in the US and alcohol plays a prominent role in a large proportion of these fatalities nationwide. Rates for these incidents vary widely among states and over time. Here, we explore the extent to which driving volume, alcohol consumption, legislation, political ideology, and geographical factors influence MVC deaths across states and time. We specify structural equation models for extracting associations between the factors and outcomes for MVC deaths and compute correlation functions of states’ relative geographic and political positions to elucidate the relative contribution of these factors. We find evidence that state-level variation in MVC deaths is associated with time-varying driving volume, alcohol consumption, and legislation. These relationships are modulated by state spatial proximity, whereby neighboring states are found to share similar MVC death rates over the thirty-year observation period. These results support the hypothesis that neighboring states exhibit similar risk and protective characteristics, despite differences in political ideology.

Community-Engaged Public Health Research to Inform Hospital Campus Planning in a Low Socioeconomic Status Urban Neighborhood

Objective:

To compare sociodemographic and motivational factors for healthcare use and identify desirable health-promoting resources among groups in a low socioeconomic status (SES) community in Chicago, IL.

Background:

Disparities in health services and outcomes are well established in low SES urban neighborhoods in the United States and many factors beyond service availability and quality impact community health. Yet there is no clear process for engaging communities in building resources to improve population-level health in such locales.

Methods:

A hospital building project led to a partnership of public health researchers, architects, and planners who conducted community-engaged research. We collected resident data and compared factors for healthcare use and choice and likelihood of engaging new health-promoting services.

Results:

Neighborhood areas were strongly associated with ethnic groupings, and there were differences between groups in healthcare choice and service needs, such as, proximity to home was more important to Latinos than African Americans in choice of healthcare facility (  padj = .001). Latinos expressed higher likelihood to use a fitness facility (  padj = .001). Despite differences in vehicle ownership, >75% of all respondents indicated that nearby public transportation was important in choosing healthcare.

Conclusion:

Knowledge of community needs and heterogeneity is essential to decision makers of facility and community development plans. Partnerships between public health, urban planning, architecture, and local constituents should be cultivated toward focus on reducing health disparities. Further work to integrate community perspectives through the planning and design process and to evaluate the long-term impact of such efforts is needed.

Translating evidence into population health improvement: strategies and barriers

Among the challenges facing research translation-the effort to move evidence into policy and practice-is that key questions chosen by investigators and funders may not always align with the information priorities of decision makers, nor are the findings always presented in a form that is useful for or relevant to the decisions at hand. This disconnect is a problem particularly for population health, where the change agents who can make the biggest difference in improving health behaviors and social and environmental conditions are generally nonscientists outside of the health professions. To persuade an audience that does not read scientific journals, strong science may not be enough to elicit change. Achieving influence in population health often requires four ingredients for success: research that is responsive to user needs, an understanding of the decision-making environment, effective stakeholder engagement, and strategic communication. This article reviews the principles and provides examples from a national and local initiative.

Invited commentary: The virtual epidemiologist—promise and peril

The simulation of complex systems has received increasing attention as a useful approach in epidemiology. As discussed by Marshall and Galea in this issue of the Journal (Am J Epidemiol. 2015;181(2):92-99), systems approaches are appealing because they allow explicit recognition of feedback, interference, adaptation over time, and nonlinearities. However, they differ fundamentally from the traditional approaches to causal inference used in epidemiology in that they involve creation of a virtual world. Systems modeling can help us understand the plausible implications of the knowledge that we have and how pieces can act together in ways that we might not have predicted. It can help us integrate quantitative and qualitative information and explore basic dynamics. It can generate new questions that can be investigated through new observations or experiments. The process of building a systems model forces us to think about dynamic relationships and the ways in which they may play a role in the process we are studying. However, the validity of any causal conclusions derived from systems models hinges on the extent to which the models represent the fundamental dynamics relevant to the process in the real world. For this reason, systems modeling will never replace causal inference based on empirical observation. Causal inference based on empirical observation and simulation modeling serve interrelated but different purposes.

Is ethnic density associated with risk of child pedestrian injury? A comparison of inter-census changes in ethnic populations and injury rates

OBJECTIVES

Research on inequalities in child pedestrian injury risk has identified some puzzling trends: although, in general, living in more affluent areas protects children from injury, this is not true for those in some minority ethnic groups. This study aimed to identify whether 'group density' effects are associated with injury risk, and whether taking these into account alters the relationship between area deprivation and injury risk. 'Group density' effects exist when ethnic minorities living in an area with a higher proportion of people from a similar ethnic group enjoy better health than those who live in areas with a lower proportion, even though areas with dense minority ethnic populations can be relatively more materially disadvantaged.

DESIGN

This study utilised variation in minority ethnic densities in London between two census periods to identify any associations between group density and injury risk. Using police data on road traffic injury and population census data from 2001 to 2011, the numbers of 'White,' 'Asian' and 'Black' child pedestrian injuries in an area were modelled as a function of the percentage of the population in that area that are 'White,' 'Asian' and 'Black,' controlling for socio-economic disadvantage and characteristics of the road environment.

RESULTS

There was strong evidence (p < 0.001) of a negative association between 'Black' population density and 'Black' child pedestrian injury risk [incidence (of injury) rate ratios (IRR) 0.575, 95% CI 0.515-0.642]. There was weak evidence (p = 0.083) of a negative association between 'Asian' density and 'Asian' child pedestrian injury risk (IRR 0.901, 95% CI 0.801-1.014) and no evidence (p = 0.412) of an association between 'White' density and 'White' child pedestrian injury risk (IRR 1.075, 95% CI 0.904-1.279). When group density effects are taken into account, area deprivation is associated with injury risk of all ethnic groups.

CONCLUSIONS

Group density appears to protect 'Black' children living in London against pedestrian injury risk. These findings suggest that future research should focus on structural properties of societies to explain the relationships between minority ethnicity and risk.

New walking and cycling routes and increased physical activity: one- and 2-year findings from the UK iConnect Study

OBJECTIVES

We evaluated the effects of providing new high-quality, traffic-free routes for walking and cycling on overall levels of walking, cycling, and physical activity.

METHODS

1796 adult residents in 3 UK municipalities completed postal questionnaires at baseline (2010) and 1-year follow-up (2011), after the construction of the new infrastructure. 1465 adults completed questionnaires at baseline and 2-year follow-up (2012). Transport network distance from home to infrastructure defined intervention exposure and provided a basis for controlled comparisons.

RESULTS

Living nearer the infrastructure did not predict changes in activity levels at 1-year follow-up but did predict increases in activity at 2 years relative to those living farther away (15.3 additional minutes/week walking and cycling per km nearer; 12.5 additional minutes/week of total physical activity). The effects were larger among participants with no car.

CONCLUSIONS

These new local routes may mainly have displaced walking or cycling trips in the short term but generated new trips in the longer term, particularly among those unable to access more distant destinations by car. These findings support the potential for walking and cycling infrastructure to promote physical activity.

Evaluation and the NIH clinical and translational science awards: a "top ten" list

Since 2006, a total of 61 Clinical and Translational Science Institutes (CTSAs) have been funded by the National Institutes of Health (NIH), with the aim of reducing translation time from a bench discovery to when it impacts patients. This special issue of Evaluation & the Health Professions focuses on evaluation within and across the large, complex system of the CTSA Program of NIH. Through insights gained by reading the articles in this special edition and the experience of the authors, a "top ten" list of lessons learned and insights gained is presented. The list outlines issues that face those who evaluate the influence of the CTSA Program, as they work to anticipate what will be needed for continuing success. Themes include (1) considering the needs of stakeholders, (2) the perspective of the evaluators, (3) the importance of service improvement, (4) the importance of teams and people, (5) costs and return on investments, (6) methodology considerations to evaluate the CTSA enterprise, (7) innovation in evaluation, (8) defining the transformation of research, (9) evaluating the long-term impact of the CTSAs on public health, and (10) contributing to science policy formulation and implementation. The establishment of the CTSA Program, with its mandated evaluation component, has not only influenced the infrastructure and nature of translational research but will continue to impact policy and management in science.

Urban design and health: progress to date and future challenges

Over the last 15 years, a growing body of Australian and international evidence has demonstrated that urban design attributes are associated with a range of health outcomes. For example, the location of employment, shops and services, provision of public and active transport infrastructure and access to open space and recreational opportunities are associated with chronic disease risk factors such as physical activity levels, access to healthy food, social connectedness, and air quality. Despite the growing knowledge base, this evidence is not being consistently translated into urban planning policy and practice in Australia. Low-density neighbourhoods with poor access to public transport, shops and services continue to be developed at a rapid rate in the sprawling outer suburbs of Australian cities. This paper provides an overview of the evidence of the association between the built environment and chronic diseases, highlighting progress and future challenges for health promotion. It argues that health promotion practitioners and researchers need to more closely engage with urban planning practitioners, policymakers and researchers to encourage the creation of healthy urban environments through integrated transport, land use and infrastructure planning. There is also a need for innovative research to evaluate the effectiveness of policy options. This would help evidence to be more effectively translated into policy and practice, making Australia a leader in planning healthy communities.

Genetic associations with micronutrient levels identified in immune and gastrointestinal networks

The discovery of vitamins and clarification of their role in preventing frank essential nutrient deficiencies occurred in the early 1900s. Much vitamin research has understandably focused on public health and the effects of single nutrients to alleviate acute conditions. The physiological processes for maintaining health, however, are complex systems that depend upon interactions between multiple nutrients, environmental factors, and genetic makeup. To analyze the relationship between these factors and nutritional health, data were obtained from an observational, community-based participatory research program of children and teens (age 6–14) enrolled in a summer day camp in the Delta region of Arkansas. Assessments of erythrocyte S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), plasma homocysteine (Hcy) and 6 organic micronutrients (retinol, 25-hydroxy vitamin D3, pyridoxal, thiamin, riboflavin, and vitamin E), and 1,129 plasma proteins were performed at 3 time points in each of 2 years. Genetic makeup was analyzed with 1 M SNP genotyping arrays, and nutrient status was assessed with 24-h dietary intake questionnaires. A pattern of metabolites (met_PC1) that included the ratio of erythrocyte SAM/SAH, Hcy, and 5 vitamins were identified by principal component analysis. Met_PC1 levels were significantly associated with (1) single-nucleotide polymorphisms, (2) levels of plasma proteins, and (3) multilocus genotypes coding for gastrointestinal and immune functions, as identified in a global network of metabolic/protein–protein interactions. Subsequent mining of data from curated pathway, network, and genome-wide association studies identified genetic and functional relationships that may be explained by gene–nutrient interactions. The systems nutrition strategy described here has thus associated a multivariate metabolite pattern in blood with genes involved in immune and gastrointestinal functions.

Examining the impact of the walking school bus with an agent-based model

We used an agent-based model to examine the impact of the walking school bus (WSB) on children's active travel to school. We identified a synergistic effect of the WSB with other intervention components such as an educational campaign designed to improve attitudes toward active travel to school. Results suggest that to maximize active travel to school, children should arrive on time at "bus stops" to allow faster WSB walking speeds. We also illustrate how an agent-based model can be used to identify the location of routes maximizing the effects of the WSB on active travel. Agent-based models can be used to examine plausible effects of the WSB on active travel to school under various conditions and to identify ways of implementing the WSB that maximize its effectiveness.

Are researcher development interventions, alone or in any combination, effective in improving researcher behavior? A systematic review

Academic institutions funded by the Clinical and Translational Science Awards (CTSA) Program of the National Institutes of Health were challenged recently by the Institute of Medicine to expand traditional mentoring of graduate and postdoctoral scholars to include training and continuing education for faculty, professional staff, and community partners. A systematic review was conducted to determine whether researcher development interventions, alone or in any combination, are effective in improving researcher behavior. PubMed, CINAHL, and Education Research Complete databases and select journals were searched for relevant articles published from January 2000 through October 2012. A total of 3,459 papers were identified, and 114 papers were retrieved for in-depth analysis. None included randomization. Twenty-two papers reported subjects with professional degrees, interventions, and outcomes. Interventions were meetings, outreach visits, colleague mediation, audit and feedback, and multifaceted interventions. Most studies reported multifaceted interventions (68.2%), often involving mentored learning experiences, and meetings. All studies reported a change in performance, including numbers of publications or grant applications. Nine studies reported changes in competence, including writing, presentation, or analytic skills, and performance in research practice (40.9%). Even as, the quality of evidence was weak to establish causal linkages between researcher development and improved researcher behavior, nearly all the projects (81.8%) received funding from governmental agencies, professional societies, or other organizations. Those who design researcher development activities and those who evaluate the programs are challenged to develop tools and conduct studies that measure the effectiveness, costs, and sustainability of researcher development in the CTSA Program.

Lifecourse health development: past, present and future

During the latter half of the twentieth century, an explosion of research elucidated a growing number of causes of disease and contributors to health. Biopsychosocial models that accounted for the wide range of factors influencing health began to replace outmoded and overly simplified biomedical models of disease causation. More recently, models of lifecourse health development (LCHD) have synthesized research from biological, behavioral and social science disciplines, defined health development as a dynamic process that begins before conception and continues throughout the lifespan, and paved the way for the creation of novel strategies aimed at optimization of individual and population health trajectories. As rapid advances in epigenetics and biological systems research continue to inform and refine LCHD models, our healthcare delivery system has struggled to keep pace, and the gulf between knowledge and practice has widened. This paper attempts to chart the evolution of the LCHD framework, and illustrate its potential to transform how the MCH system addresses social, psychological, biological, and genetic influences on health, eliminates health disparities, reduces chronic illness, and contains healthcare costs. The LCHD approach can serve to highlight the foundational importance of MCH, moving it from the margins of national debate to the forefront of healthcare reform efforts. The paper concludes with suggestions for innovations that could accelerate the translation of health development principles into MCH practice.

Lifecourse health development: past, present and future

During the latter half of the twentieth century, an explosion of research elucidated a growing number of causes of disease and contributors to health. Biopsychosocial models that accounted for the wide range of factors influencing health began to replace outmoded and overly simplified biomedical models of disease causation. More recently, models of lifecourse health development (LCHD) have synthesized research from biological, behavioral and social science disciplines, defined health development as a dynamic process that begins before conception and continues throughout the lifespan, and paved the way for the creation of novel strategies aimed at optimization of individual and population health trajectories. As rapid advances in epigenetics and biological systems research continue to inform and refine LCHD models, our healthcare delivery system has struggled to keep pace, and the gulf between knowledge and practice has widened. This paper attempts to chart the evolution of the LCHD framework, and illustrate its potential to transform how the MCH system addresses social, psychological, biological, and genetic influences on health, eliminates health disparities, reduces chronic illness, and contains healthcare costs. The LCHD approach can serve to highlight the foundational importance of MCH, moving it from the margins of national debate to the forefront of healthcare reform efforts. The paper concludes with suggestions for innovations that could accelerate the translation of health development principles into MCH practice.

Understanding the rural-urban differences in nonmedical prescription opioid use and abuse in the United States

Nonmedical prescription opioid misuse remains a growing public problem in need of action and is concentrated in areas of US states with large rural populations such as Kentucky, West Virginia, Alaska, and Oklahoma. We developed hypotheses regarding the influence of 4 factors: (1) greater opioid prescription in rural areas, creating availability from which illegal markets can arise; (2) an out-migration of young adults; (3) greater rural social and kinship network connections, which may facilitate drug diversion and distribution; and (4) economic stressors that may create vulnerability to drug use more generally. A systematic consideration of the contexts that create differences in availability, access, and preferences is critical to understanding how drug use context varies across geography.

A Recommendation to Use the Diffusion of Innovations Theory to Understand School Nurses' Role in HPV Vaccine Uptake

Vaccinations represent one of the greatest public health achievements of the past century, but their success largely depends on populations' uptake. Seven years after its approval in 2006 for females, the HPV vaccination rates remain relatively low. Previous literature provides information about research examining U.S. physicians, pediatricians, and other healthcare providers' knowledge, attitudes, and professional practice toward the HPV vaccine. No research has yet investigated U.S. school nurses' role in educating the school community about the vaccine's benefits. Diffusion of Innovations theory is an appropriate perspective for examining school nurses as opinion leaders who can influence the uptake of the HPV vaccine for youth. This theory explains how innovations diffuse throughout a social system, and highlights the construct of opinion leadership. School nurses exhibit the characteristics of opinion leaders; therefore, Diffusion of Innovations can be a useful lens for assessing their role in efforts to promote HPV vaccination for youth.

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

Reducing health inequalities has become a major public health priority internationally. However, how best to achieve this goal is not well understood. Population health intervention research has the potential to address some of this knowledge gap. This review argues that simulation studies can produce unique evidence to build the population health intervention research evidence base on reducing social inequalities in health. To this effect, the advantages of using simulation models over other population health intervention research methods are discussed. Key questions regarding the potential challenges of developing simulation models to investigate population health intervention research on reducing social inequalities in health and the types of population health intervention research questions that can be answered using this methodology are reviewed. We use the example of social inequalities in coronary heart disease to illustrate how simulation models can elucidate the effectiveness of a number of ‘what-if’ counterfactual population health interventions on reducing social inequalities in coronary heart disease. Simulation models are a flexible, cost-effective, evidence-based research method with the capacity to inform public health policy-makers regarding the implementation of population health interventions to reduce social inequalities in health.

Insights in public health: systems thinking: basic constructs, application challenges, misuse in health, and how public health leaders can pave the way forward

The strengthening of health systems is fundamental to improving health outcomes, crisis preparedness, and our capacity to meet global challenges, such as accelerating progress towards the Millennium Development Goals, reducing maternal and child mortality, combating HIV, malaria and other diseases, limiting the effects of a new influenza pandemic, and responding appropriately to climate change. To meet these complex needs, the Association of Schools and Programs in Public Health, the World Health Organization, and the Institute of Medicine promote systems thinking as the only sensible means to respond to issues that greatly exceed the normal capacity of health and medical services. This paper agrees with the application of systems thinking but argues that health organizations have misunderstood and misapplied systems thinking to the extent that the term has become meaningless. This paper presents the basic constructs of systems thinking, explains why systems thinking has been misapplied, examines some misapplications of systems thinking in health, and suggests how the concept can be applied correctly to medicine and public health to achieve the reason it was adopted in the first place.

Understanding social forces involved in diabetes outcomes: a systems science approach to quality-of-life research

PURPOSE

The field of quality-of-life (QOL) research would benefit from learning about and integrating systems science approaches that model how social forces interact dynamically with health and affect the course of chronic illnesses. Our purpose is to describe the systems science mindset and to illustrate the utility of a system dynamics approach to promoting QOL research in chronic disease, using diabetes as an example.

METHODS

We build a series of causal loop diagrams incrementally, introducing new variables and their dynamic relationships at each stage.

RESULTS

These causal loop diagrams demonstrate how a common set of relationships among these variables can generate different disease and QOL trajectories for people with diabetes and also lead to a consideration of non-clinical (psychosocial and behavioral) factors that can have implications for program design and policy formulation.

CONCLUSIONS

The policy implications of the causal loop diagrams are discussed, and empirical next steps to validate the diagrams and quantify the relationships are described.

[A Latin-American perspective regarding the past, present and future of epidemiology]

This article addresses three questions. Concerning the past, why was there no pre-Columbian epidemiology? What are the origins of modern epidemiology (including its South American roots)? A surrealistic title has been chosen regarding the future to emphasise the fact that making predictions is not easy. Why are complex phenomena the dark object of epidemiological desire?

Clashing paradigms: an empirical examination of cultural proxies and socioeconomic condition shaping Latino health

OBJECTIVE

Much debate exists regarding the role of culture versus socioeconomic position in shaping the health of Latino populations. We propose that both may matter for health and explicitly test their independent and joint effects on smoking and physical activity.

METHODS

We used the 2010 National Health Interview Survey, a population-based survey of the U.S. population, to estimate the prevalence of smoking and physical activity by language use (cultural proxy) and education among Latino adults (n = 4929). We fit log binomial regression models to estimate prevalence ratios and test for interaction.

RESULTS

English-language use and educational attainment were each independently associated with smoking and physical activity. Joint effect models showed that individuals with both greater use of the English language and low levels of education were nearly three times more likely to smoke (prevalence ratio, 2.59; 95% confidence interval, 1.83-3.65) than those with low English language use and high education (referent group); high acculturation and high education were jointly associated with increased activity (prevalence ratio 2.24, 95% confidence interval, 1.79-2.81).

CONCLUSIONS

Cultural proxies such as language use and educational attainment are both important determinants of health among Latinos. Their joint effect suggests the need to simultaneously consider Latinos' socioeconomic position and their increased risk of adopting health-damaging behaviors while addressing culturally-specific factors that may mitigate risk.

Social, behavioral, and genetic linkages from adolescence into adulthood

The influence of genetic factors on health and behavior is conditioned by social, cultural, institutional, and physical environments in which individuals live, work, and play. We encourage studies supporting multilevel integrative approaches to understanding these contributions to health, and describe the Add Health study as an exemplar. Add Health is a large sample of US adolescents in grades 7 to 12 in 1994-1995 followed into adulthood with 4 in-home interviews and biomarker collections, including DNA. In addition to sampling multiple environments and measuring diverse social and health behavior, Add Health features a fully articulated behavioral genetic sample (3000 pairs) and ongoing genotyping of 12,000 archived samples. We illustrate approaches to understanding health through investigation of the interplay among biological, psychosocial, and physical, contextual, or cultural experiences.

Spatial Polygamy and Contextual Exposures (SPACEs): Promoting Activity Space Approaches in Research on Place and Health

Exposure science has developed rapidly and there is an increasing call for greater precision in the measurement of individual exposures across space and time. Social science interest in an individual's environmental exposure, broadly conceived, has arguably been quite limited conceptually and methodologically. Indeed, we appear to lag behind our exposure science colleagues in our theories, data, and methods. In this paper we discuss a framework based on the concept of spatial polygamy to demonstrate the need to collect new forms of data on human spatial behavior and contextual exposures across time and space. Adopting new data and methods will be essential if we want to better understand social inequality in terms of exposure to health risks and access to health resources. We discuss the opportunities and challenges focusing on the potential seemingly offered by focusing on human mobility, and specifically the utilization of activity space concepts and data. A goal of the paper is to spatialize social and health science concepts and research practice vis-a-vis the complexity of exposure. The paper concludes with some recommendations for future research focusing on theoretical and conceptual development, promoting research on new types of places and human movement, the dynamic nature of contexts, and on training. "When we elect wittingly or unwittingly, to work within a level … we tend to discern or construct - whichever emphasis you prefer - only those kinds of systems whose elements are confined to that level."Otis Dudley Duncan (1961, p. 141)."…despite the new ranges created by improved transportation, local government units have tended to remain medieval in size."Torsten Hägerstrand (1970, p.18)"A detective investigating a crime needs both tools and understanding. If he has no fingerprint powder, he will fail to find fingerprints on most surfaces. If he does not understand where the criminal is likely to have put his fingers, he will not look in the right places. Equally, the analyst of data needs both tools and understanding."John Tukey (1977, p.1)"When we observe the environment, we necessarily do so on only a limited number of scales."Simon Levin (1992, p. 1945)There is a desperate need to develop methods with the same precision for an individual's environmental exposure as we have for an individual's genome … even a partial, targeted understanding of exposure can provide substantial advantages."Christopher Wild (2005, p.1848).

Why some walk and others don't: exploring interactions of perceived safety and social neighborhood factors with psychosocial cognitions

Although physical activity is often believed to be influenced by both environmental and individual factors, little is known about their interaction. This study explores interactions of perceived safety and social neighborhood factors with psychosocial cognitions for leisure-time walking. Cross-sectional data were obtained from residents (age 25-75 years) of 212 neighborhoods in the South-East of the Netherlands, who participated in the Dutch GLOBE study in 2004 (N = 4395, survey response 64.4%). Direct associations of, and interactions between perceived neighborhood safety, social neighborhood factors (social cohesion, social network and feeling at home) and psychosocial cognitions (attitude, self-efficacy, social influence and intention) on two outcomes of leisure-time walking [yes versus no (binary), and among walkers: minutes per week (continuous)] were analyzed in multilevel regression models. The association between attitude and participating in leisure-time walking was stronger in those who felt less at home in their neighborhood. Social influence and attitude were stronger associated with participation in leisure-time walking in those who sometimes felt unsafe in their neighborhood. A positive intention was associated with more minutes walked in those who perceived their neighborhood as unsafe among those who walked. Only limited support was found for interactions between neighborhood perceptions and psychosocial cognitions for leisure-time walking.

Causal inference in public health

Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.

Clarifying the use of aggregated exposures in multilevel models: self-included vs. self-excluded measures

BACKGROUND

Multilevel analyses are ideally suited to assess the effects of ecological (higher level) and individual (lower level) exposure variables simultaneously. In applying such analyses to measures of ecologies in epidemiological studies, individual variables are usually aggregated into the higher level unit. Typically, the aggregated measure includes responses of every individual belonging to that group (i.e. it constitutes a self-included measure). More recently, researchers have developed an aggregate measure which excludes the response of the individual to whom the aggregate measure is linked (i.e. a self-excluded measure). In this study, we clarify the substantive and technical properties of these two measures when they are used as exposures in multilevel models.

METHODS

Although the differences between the two aggregated measures are mathematically subtle, distinguishing between them is important in terms of the specific scientific questions to be addressed. We then show how these measures can be used in two distinct types of multilevel models-self-included model and self-excluded model-and interpret the parameters in each model by imposing hypothetical interventions. The concept is tested on empirical data of workplace social capital and employees' systolic blood pressure.

RESULTS

Researchers assume group-level interventions when using a self-included model, and individual-level interventions when using a self-excluded model. Analytical re-parameterizations of these two models highlight their differences in parameter interpretation. Cluster-mean centered self-included models enable researchers to decompose the collective effect into its within- and between-group components. The benefit of cluster-mean centering procedure is further discussed in terms of hypothetical interventions.

CONCLUSIONS

When investigating the potential roles of aggregated variables, researchers should carefully explore which type of model-self-included or self-excluded-is suitable for a given situation, particularly when group sizes are relatively small.

The contribution of stress to the social patterning of clinical and subclinical CVD risk factors in African Americans: the Jackson Heart Study

It is often hypothesized that psychosocial stress may contribute to associations of socioeconomic position (SEP) with risk factors for cardiovascular disease (CVD). However, few studies have investigated this hypothesis among African Americans, who may be more frequently exposed to stressors due to social and economic circumstances. Cross-sectional data from the Jackson Heart Study (JHS), a large population-based cohort of African Americans, were used to examine the contributions of stressors to the association of SEP with selected cardiovascular (CVD) risk factors and subclinical atherosclerotic disease. Among women, higher income was associated with lower prevalence of hypertension, obesity, diabetes and carotid plaque and lower levels of stress. Higher stress levels were also weakly, albeit positively, associated with hypertension, diabetes, and obesity, but not with plaque. Adjustment for the stress measures reduced the associations of income with hypertension, diabetes and obesity by a small amount that was comparable to, or larger, than the reduction observed after adjustment for behavioral risk factors. In men, high income was associated with lower prevalence of diabetes and stressors were not consistently associated with any of the outcomes examined. Overall, modest mediation effects of stressors were observed for diabetes (15.9%), hypertension (9.7%), and obesity (5.1%) among women but only results for diabetes were statistically significant. No mediation effects of stressors were observed in men. Our results suggest that stressors may partially contribute to associations of SEP with diabetes and possibly hypertension and obesity in African American women. Further research with appropriate study designs and data is needed to understand the dynamic and interacting effects of stressors and behaviors on CVD outcomes as well as sex differences in these effects.

Geographic inequalities in all-cause mortality in Japan: compositional or contextual?

Background

A recent study from Japan suggested that geographic inequalities in all-cause premature adult mortality have increased since 1995 in both sexes even after adjusting for individual age and occupation in 47 prefectures. Such variations can arise from compositional effects as well as contextual effects. In this study, we sought to further examine the emerging geographic inequalities in all-cause mortality, by exploring the relative contribution of composition and context in each prefecture.

Methods

We used the 2005 vital statistics and census data among those aged 25 or older. The total number of decedents was 524,785 men and 455,863 women. We estimated gender-specific two-level logistic regression to model mortality risk as a function of age, occupation, and residence in 47 prefectures. Prefecture-level variance was used as an estimate of geographic inequalities in mortality, and prefectures were ranked by odds ratios (ORs), with the reference being the grand mean of all prefectures (value  = 1).

Results

Overall, the degree of geographic inequalities was more pronounced when we did not account for the composition (i.e., age and occupation) in each prefecture. Even after adjusting for the composition, however, substantial differences remained in mortality risk across prefectures with ORs ranging from 0.870 (Okinawa) to 1.190 (Aomori) for men and from 0.864 (Shimane) to 1.132 (Aichi) for women. In some prefectures (e.g., Aomori), adjustment for composition showed little change in ORs, while we observed substantial attenuation in ORs in other prefectures (e.g., Akita). We also observed qualitative changes in some prefectures (e.g., Tokyo). No clear associations were observed between prefecture-level socioeconomic status variables and the risk of mortality in either sex.

Conclusions

Geographic disparities in mortality across prefectures are quite substantial and cannot be fully explained by differences in population composition. The relative contribution of composition and context to health inequalities considerably vary across prefectures.

Integrating climate change adaptation into public health practice: using adaptive management to increase adaptive capacity and build resilience

BACKGROUND

Climate change is expected to have a range of health impacts, some of which are already apparent. Public health adaptation is imperative, but there has been little discussion of how to increase adaptive capacity and resilience in public health systems.

OBJECTIVES

We explored possible explanations for the lack of work on adaptive capacity, outline climate-health challenges that may lie outside public health's coping range, and consider changes in practice that could increase public health's adaptive capacity.

METHODS

We conducted a substantive, interdisciplinary literature review focused on climate change adaptation in public health, social learning, and management of socioeconomic systems exhibiting dynamic complexity.

DISCUSSION

There are two competing views of how public health should engage climate change adaptation. Perspectives differ on whether climate change will primarily amplify existing hazards, requiring enhancement of existing public health functions, or present categorically distinct threats requiring innovative management strategies. In some contexts, distinctly climate-sensitive health threats may overwhelm public health's adaptive capacity. Addressing these threats will require increased emphasis on institutional learning, innovative management strategies, and new and improved tools. Adaptive management, an iterative framework that embraces uncertainty, uses modeling, and integrates learning, may be a useful approach. We illustrate its application to extreme heat in an urban setting.

CONCLUSIONS

Increasing public health capacity will be necessary for certain climate-health threats. Focusing efforts to increase adaptive capacity in specific areas, promoting institutional learning, embracing adaptive management, and developing tools to facilitate these processes are important priorities and can improve the resilience of local public health systems to climate change.

Promoting health at the community level: thinking globally, acting locally

Prevention of childhood obesity is a societal priority. Despite our knowledge about the scope of the problem and the determinants that lead to it, we have yet to produce meaningful declines in obesity rates. Recent attention has been given to interventions that employ multiple strategies across multiple settings involving whole communities given their promising results. The next era of science calls for interdisciplinary teams who will envision a whole system approach to advance the community-based obesity prevention model. This perspective describes some of the more recent discussions of community-based methodologies such as the ANGELO (Analysis Grid for Environments Linked to Obesity) framework, best-practice principles, and a whole system intervention approach to obesity prevention. The proposed required elements to advance community-based research to address childhood obesity are: A systems perspective and approach, training of future leaders in community research methodology and social change, applying transdisciplinary strategies, funding to conduct rigorous trials to determine efficacy and effectiveness, enhanced design and analysis approaches, new and improved tools and methodologies to collect quantitative and qualitative data, enhanced community engagement models and sustainability frameworks, advancement of a bold public policy agenda, economic modeling, and acknowledgment of the approach as viable. To reverse childhood obesity, we need to embrace and integrate complex strategies at multiple levels within communities across the globe.

Conceptual approaches to the study of health disparities

Scientific and policy interest in health disparities, defined as systematic, plausibly avoidable health differences adversely affecting socially disadvantaged groups, has increased markedly over the past few decades. Like other research, research in health disparities is strongly influenced by the underlying conceptual model of the hypothetical causes of disparities. Conceptual models are important and a major source of debate because multiple types of factors and processes may be involved in generating disparities, because different disciplines emphasize different types of factors, and because the conceptual model often drives what is studied, how results are interpreted, and which interventions are identified as most promising. This article reviews common conceptual approaches to health disparities including the genetic model, the fundamental cause model, the pathways model, and the interaction model. Strengths and limitations of the approaches are highlighted. The article concludes by outlining key elements and implications of an integrative systems-based conceptual model.