Complex causal process diagrams for analyzing the health impacts of policy interventions

A community-based systems dynamics approach for understanding determinants of children's social and emotional well-being

We report on our application of a community-based systems dynamics modelling approach to identify key factors affecting children's social and emotional well-being (SEW). Using a group model building process with 31 stakeholders in 2 communities in British Columbia, Canada, we constructed two causal loop diagrams composed of 250 variables, 534 connections and 63 feedback loops. Feedback loops, systems complexity, and prominent systems level variables illustrate the interconnectedness of multilevel determinants influencing children's SEW. The community-based models highlighted areas for place-based intervention planning that require collective community action and intersectoral commitment toward common objectives for practice and policy on SEW.

Understanding the effectiveness and underlying mechanisms of lifestyle modification interventions in adults with learning disabilities: protocol for a mixed-methods systematic review

BACKGROUND

Adults with learning disabilities have an increased disposition to unhealthy lifestyle behaviours which often occur simultaneously. Existing studies focus on complex interventions targeting unhealthy diet, physical inactivity, sedentary behaviour, smoking, and alcohol use to reduce health risks experienced. It is essential to understand how well these interventions work, what works, for whom, in what context and why. This study aims to investigate the effectiveness and underlying mechanisms of lifestyle modification interventions for adults with learning disabilities.

METHODS

This is a mixed-methods systematic review consisting of a network meta-analysis (NMA) and realist synthesis. Electronic databases (ASSIA, CINAHL, EMBASE, MEDLINE, and PsycINFO) will be searched from inception to 14 January 2021 with no language restriction. Additionally, trial registries, grey literature databases and references lists will be searched. Studies related to lifestyle modification interventions on the adult population (>18 years) with learning disabilities will be eligible for inclusion. Two independent researchers will screen studies, extract data and assess its quality and risk of bias using the Cochrane Collaboration's Risk of Bias Assessment Tool (RoB Version 2) and ROBINS-I. The strength of the body of evidence will be assessed based on the GRADE approach. The NMA will incorporate results from RCTs and quasi-experimental studies to estimate the effectiveness of various lifestyle interventions. Where appropriate, a component NMA (CNMA) will be used to estimate effectiveness. The realist synthesis will complement and explain the findings of NMA and CNMA by including additional qualitative and mixed-methods studies. Studies will be included based on their relevance to the programme theory and the rigour of their methods, as determined by quality appraisal tools appropriate to the study design. Results from both syntheses will be incorporated into a logic model.

DISCUSSION

The paucity of population-specific lifestyle interventions contributes to the challenges of behaviour change in adults with learning disabilities. This study will provide an evidence-base from which various stakeholders can develop effective interventions for adults with learning disabilities. The evidence will also help prioritise and inform research recommendations for future primary research so that people with learning disabilities live happier, healthier and longer lives.

TRIAL REGISTRATION

PROSPERO CRD 42020223290.

The Application of Systems Science in Nutrition-Related Behaviors and Outcomes Implementation Research: A Scoping Review

Use of systems science can improve the dissemination and implementation (D&I) process. However, little is known about use of systems science in nutrition D&I research. The purpose of this article is to synthesize the ways in which systems science methodology is applied in nutrition D&I research. Scoping review methodology involved searching 6 academic databases for full-text, peer-reviewed, English articles published between 1970 and 2020 that employed systems science within nutrition D&I research. Data extraction included intervention type, population, study aim, methods, theoretical approach, outcomes, and results. Descriptive statistics and qualitative thematic analysis followed. Thirty-four retained articles qualitatively identified benefits (successful planning and organization of complex interventions) and challenges (limited resources, trainings, and lack of knowledge) to utilizing systems science in nutrition D&I research. Future research should work toward building knowledge capacity among nutrition practitioners by increasing available trainings and resources to enhance the utilization of systems science in nutrition D&I research.

Statewide Evaluation of Washington's State Innovation Model Initiative: A Mixed-Methods Approach

The Washington State Innovation Model (SIM) $65 million Test Award from the Center for Medicare and Medicaid Innovation is a statewide intervention expected to improve population health, quality of care, and cost growth through 4 initiatives in 2016-2018: (1) regional accountable communities of health linking health and social services to address local needs; (2) a practice transformation support hub; (3) four value-based payment reform pilot projects mainly in state employee and Medicaid populations; and (4) data and analytic infrastructure development to support system transformation with common measures. A mixed-methods study design and data from the 2013-2018 Behavioral Risk Factor Surveillance System Surveys are used to estimate whether SIM resulted in changes in access to care, health behaviors, and health status in Washington's adult population. Semi-structured qualitative interviews also were conducted to assess stakeholder perceptions of SIM performance. SIM may have reduced binge drinking, but no effects were detected for heavy drinking, physical activity, smoking, having a regular doctor checkup, unmet health care needs, and fair or poor health status. Complex interventions, such as SIM, may have unintended consequences. SIM was associated unexpectedly with increased unhealthy days, but whether the association was related to the Initiative or other factors is unclear. Over 3 years, stakeholders generally agreed that SIM was implemented successfully and increased Washington's readiness for system transformation but had not yet produced expected outcomes, partly because SIM had not spread statewide. Stakeholders perceived that scaling up SIM statewide takes time to achieve and remains challenging.

The Shortage of Benzathine Penicillin and Its Impact on Congenital Syphilis Incidence: An Ecologic Study in the City of Rio de Janeiro

BACKGROUND

The Pan American Health Organization indicates that increased incidence of congenital syphilis (CS) can be attributed to the lack of penicillin. This study aimed to analyze the relationship between the benzathine penicillin shortage and the significant increase in the incidence of congenital syphilis in the city of Rio de Janeiro from 2013 to 2017.

METHODS

We used a mixed ecologic study design (temporal and multiple groups). Analysis units were the neighborhoods (spatial) and quarters (temporal) during those years. The study population consisted of CS patients who were living in the city of Rio de Janeiro. The benzathine penicillin supply measure for use in gestational syphilis considered the ratio between (1) the number of bottles dispensed to health facilities in each neighborhood and (2) the number of bottles necessary to treat pregnant women diagnosed with syphilis and their respective partners residing in each neighborhood. To evaluate the association between shortages and a significant increase in CS incidence, the negative-inflated zero-binomial regression model (longitudinal model) was used.

RESULTS

During the study period, the incidence rate of CS in Rio de Janeiro neighborhoods was on average 19.6 per 1000 live births. In the simple analysis, shortage was associated with a 2.17-fold increase in the risk of a significant increase in CS incidence. After adjustment for the sufficient minimum set, the strength of association increased to 2.23 (95% confidence interval, 1.15-4.30).

CONCLUSIONS

We conclude that the benzathine penicillin shortage had an impact on the increase in the incidence of CS in Rio de Janeiro.

Developing and Using Multiple Models to Promote Scientific Literacy in the Context of Socio-Scientific Issues

Learning science in the context of socio-scientific issues (SSI) can promote scientific literacy that links science to everyday life and society. In this position paper, we argue that developing and using multiple models equip students with the appropriate knowledge and skills needed to deal with complex issues. We draw upon literature from science education and philosophy of science and advance our theoretical argument about why it is critical for students to develop and use multiple models as part of their science learning experiences in general, and how the practice benefits students in the context of SSI in particular. We posit that students should engage in both scientific and socio-scientific models as they explore a complex societal issue because (1) engagement in multiple scientific models promotes students' understanding about the phenomena relevant to the focal issue, and (2) engagement in socio-scientific models helps students to use that scientific knowledge in the larger social contexts and reason about how interacting science and social factors may impact students' positions on the complex issue. We take COVID-19 as the learning context and present exemplar models students can develop and use as they learn about the pandemic. We conclude the paper by discussing the teaching aspects of the proposed modeling approach for SSI-based instruction as well as identifying possible areas for future research.

A novel method for predicting the progression rate of ALS disease based on automatic generation of probabilistic causal chains

Causal discovery is considered as a major concept in biomedical informatics contributing to diagnosis, therapy, and prognosis of diseases. Probabilistic causality approaches in epidemiology and medicine is a common method for finding relationships between pathogen and disease, environment and disease, and adverse events and drugs. Bayesian Network (BN) is one of the common approaches for probabilistic causality, which is widely used in health-care and biomedical science. Since in many biomedical applications we deal with temporal dataset, the temporal extension of BNs called Dynamic Bayesian network (DBN) is used for such applications. DBNs define probabilistic relationships between parameters in consecutive time points in the form of a graph and have been successfully used in many biomedical applications. In this paper, a novel method was introduced for finding probabilistic causal chains from a temporal dataset with the help of entropy and causal tendency measures. In this method, first, Causal Features Dependency (CFD) matrix is created on the basis of parameters changes in consecutive events of a phenomenon, and then the probabilistic causal graph is constructed from this matrix based on entropy criteria. At the next step, a set of probabilistic causal chains of the corresponding causal graph is constructed by a novel polynomial-time heuristic. Finally, the causal chains are used for predicting the future trend of the phenomenon. The proposed model was applied to the Pooled Resource Open-Access Clinical Trials (PRO-ACT) dataset related to Amyotrophic Lateral Sclerosis (ALS) disease, in order to predict the progression rate of this disease. The results of comparison with Bayesian tree, random forest, support vector regression, linear regression, and multivariate regression show that the proposed algorithm can compete with these methods and in some cases outperforms other algorithms. This study revealed that probabilistic causality is an appropriate approach for predicting the future states of chronic diseases with unknown cause.

Development of Conceptual Models to Guide Public Health Research, Practice, and Policy: Synthesizing Traditional and Contemporary Paradigms

This applied paper is intended to serve as a "how to" guide for public health researchers, practitioners, and policy makers who are interested in building conceptual models to convey their ideas to diverse audiences. Conceptual models can provide a visual representation of specific research questions. They also can show key components of programs, practices, and policies designed to promote health. Conceptual models may provide improved guidance for prevention and intervention efforts if they are based on frameworks that integrate social ecological and biological influences on health and incorporate health equity and social justice principles. To enhance understanding and utilization of this guide, we provide examples of conceptual models developed by the Prevention of Lower Urinary Tract Symptoms (PLUS) Research Consortium. PLUS is a transdisciplinary U.S. scientific network established by the National Institutes of Health in 2015 to promote bladder health and prevent lower urinary tract symptoms, an emerging public health and prevention priority. The PLUS Research Consortium is developing conceptual models to guide its prevention research agenda. Research findings may in turn influence future public health practices and policies. This guide can assist others in framing diverse public health and prevention science issues in innovative, potentially transformative ways.

Water, sanitation and hygiene risk factors for the transmission of cholera in a changing climate: using a systematic review to develop a causal process diagram

Cholera is a severe diarrhoeal disease affecting vulnerable communities. A long-term solution to cholera transmission is improved access to and uptake of water, sanitation and hygiene (WASH). Climate change threatens WASH. A systematic review and meta-analysis determined five overarching WASH factors incorporating 17 specific WASH factors associated with cholera transmission, focussing upon community cases. Eight WASH factors showed lower odds and six showed higher odds for cholera transmission. These results were combined with findings in the climate change and WASH literature, to propose a health impact pathway illustrating potential routes through which climate change dynamics (e.g. drought, flooding) impact on WASH and cholera transmission. A causal process diagram visualising links between climate change dynamics, WASH factors, and cholera transmission was developed. Climate change dynamics can potentially affect multiple WASH factors (e.g. drought-induced reductions in handwashing and rainwater use). Multiple climate change dynamics can influence WASH factors (e.g. flooding and sea-level rise affect piped water usage). The influence of climate change dynamics on WASH factors can be negative or positive for cholera transmission (e.g. drought could increase pathogen desiccation but reduce rainwater harvesting). Identifying risk pathways helps policymakers focus on cholera risk mitigation, now and in the future.

RE-AIM Evaluation Plan for Washington State Innovation Models Project

The State of Washington received a State Innovation Models (SIM) $65 million award from the federal Centers for Medicare & Medicaid Services to improve population health and quality of care and reduce the growth of health care costs in the entire state, which has over 7 million residents. SIM is a "complex intervention" that implements several interacting components in a complex, decentralized health system to achieve goals, which poses challenges for evaluation. Our purpose is to present the state-level evaluation methods for Washington's SIM, a 3-year intervention (2016-2018). We apply the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) evaluation framework to structure our evaluation. We create a conceptual model and a plan to use multiple and mixed methods to study SIM performance in the RE-AIM components from a statewide, population-based perspective.

Is the decline of active travel to school unavoidable by-products of economic growth and urbanization in developing countries?

BACKGROUND

Economic growth and urbanization may contribute to the decline of active travel to school (ATS). We aim to explain the change of ATS in China between 1997 and 2011 and to predict the prevalence of ATS in China within the next 30 years using various scenario.

METHODS

We developed a system dynamics model to study ATS and the model assumes the prevalence of ATS is determined by the dynamic interaction of four exogenous and eight endogenous variables.

RESULTS

The simulated prevalence of ATS is roughly consistent with empirical data. Economic development and urban sprawl are more influential than urban design and crime in terms of ATS. Under a relatively reasonable scenario, the prevalence of ATS is projected to decrease from 73% in 2011 to 65% in 2014, and the prevalence of childhood overweight & obesity is projected to increase from 24% in 2011 to 34% in 2041. With the maintaining of economic development grow, to control urban sprawl is the most effective measure to promote ATS and decrease childhood obesity.

CONCLUSIONS

Overall, the model enabled us to conduct experiments to test the possible effects of changing one or more factors taking into account their dynamic interrelationship, and our study may provide implications for policy intervention.

Salmonella and the changing environment: systematic review using New York State as a model

Salmonella is a public health concern, for which a complex interplay between host, agent, and environment exists. An improved understanding of causal processes can be used to better gauge the causes and trajectory of Salmonella in a changing environment. This would be useful in determining the impact of climate change on the New York State (NYS) environment, the effect of climate change on Salmonella in NYS, factors contributing to Salmonella vulnerability in humans, and aspects of climate change and Salmonella which necessitate further research. A systematic review was conducted to study associations between Salmonella and the environment. Using the search criteria, a total of 91 relevant articles were identified from four electronic databases. Key information was abstracted, organized, and synthesized to identify causal processes and linkages between climate change, the environment of NYS, and Salmonella-related outcomes, as well as risk factors to characterize Salmonella vulnerabilities. Three inter-related domains were identified for consideration and application to epidemiological research to confirm and extrapolate disease patterns using climate change scenarios: improved quantification of causal relationships, inclusion of factors linked to sectors not immediately associated with the exposure and outcome, and increased capacity to validate models in diverse settings.

Synthesising quantitative evidence in systematic reviews of complex health interventions

Public health and health service interventions are typically complex: they are multifaceted, with impacts at multiple levels and on multiple stakeholders. Systematic reviews evaluating the effects of complex health interventions can be challenging to conduct. This paper is part of a special series of papers considering these challenges particularly in the context of WHO guideline development. We outline established and innovative methods for synthesising quantitative evidence within a systematic review of a complex intervention, including considerations of the complexity of the system into which the intervention is introduced. We describe methods in three broad areas: non-quantitative approaches, including tabulation, narrative and graphical approaches; standard meta-analysis methods, including meta-regression to investigate study-level moderators of effect; and advanced synthesis methods, in which models allow exploration of intervention components, investigation of both moderators and mediators, examination of mechanisms, and exploration of complexities of the system. We offer guidance on the choice of approach that might be taken by people collating evidence in support of guideline development, and emphasise that the appropriate methods will depend on the purpose of the synthesis, the similarity of the studies included in the review, the level of detail available from the studies, the nature of the results reported in the studies, the expertise of the synthesis team and the resources available.

Professional learning and development of postdoctoral scholars: a scoping review protocol

BACKGROUND

A growing number of postdoctoral scholars are following diverse career paths that require broad skill sets to ensure success. Yet, most postdoctoral professional learning and development initiatives are intended for academic careers and seldom include professional skills needed to succeed in non-academic settings. Given that fewer than 20% of postdoctoral scholars will obtain tenure-track academic positions, there is a great need for postdoctoral scholars to prepare for a range of future careers. Creating professional learning and development strategies to address these concerns requires an understanding of current approaches, yet there is a distinct lack of literature exploring and synthesizing sources of evidence on the professional learning and development of postdoctoral scholars. The purpose of this scoping review is to examine, synthesize, and map the sources of evidence on professional learning and development pertaining to postdoctoral scholars.

METHODS

We will perform a scoping review to identify sources of evidence around professional learning and development of postdoctoral scholars. Our search strategy, limited to English language, will include searching relevant disciplinary and interdisciplinary databases with no limitation on date of publication. We will conduct forward and backward citation chasing of included articles. Gray literature will be searched in electronic databases and websites of national postdoctoral associations. Search strategies will be developed using controlled vocabulary and keyword terms related to postdoctoral scholars and professional development. Two reviewers will independently screen titles and abstracts for inclusion, and two reviewers will independently screen full text to determine final inclusion. These data will be summarized quantitatively (using a simple numerical count) and qualitatively using thematic analysis methods. Through this process, we will summarize the current state of evidence around professional development and learning of postdoctoral scholars and identify current gaps in the literature, as well as the research areas requiring systematic reviews and/or primary research.

DISCUSSION

Despite the growing numbers of postdoctoral scholars, there has been no synthesis of the sources of evidence of postdoctoral scholars' professional learning and development. In reviewing a wide range of evidence and integrating it into a manageable and meaningful whole, this scoping review will be a critical first step in understanding the professional learning and development of postdoctoral scholars. Our results will help inform future research and the development of a framework for postdoctoral scholar's professional learning and development.

Using systems science to understand the determinants of inequities in healthy eating

INTRODUCTION

Systems thinking has emerged in recent years as a promising approach to understanding and acting on the prevention and amelioration of non-communicable disease. However, the evidence on inequities in non-communicable diseases and their risks factors, particularly diet, has not been examined from a systems perspective. We report on an approach to developing a system oriented policy actor perspective on the multiple causes of inequities in healthy eating.

METHODS

Collaborative conceptual modelling workshops were held in 2015 with an expert group of representatives from government, non-government health organisations and academia in Australia. The expert group built a systems model using a system dynamics theoretical perspective. The model developed from individual mind maps to pair blended maps, before being finalised as a causal loop diagram.

RESULTS

The work of the expert stakeholders generated a comprehensive causal loop diagram of the determinants of inequity in healthy eating (the HE2 Diagram). This complex dynamic system has seven sub-systems: (1) food supply and environment; (2) transport; (3) housing and the built environment; (4) employment; (5) social protection; (6) health literacy; and (7) food preferences.

DISCUSSION

The HE2 causal loop diagram illustrates the complexity of determinants of inequities in healthy eating. This approach, both the process of construction and the final visualisation, can provide the basis for planning the prevention and amelioration of inequities in healthy eating that engages with multiple levels of causes and existing policies and programs.

Nature Contact and Human Health: A Research Agenda

BACKGROUND

At a time of increasing disconnectedness from nature, scientific interest in the potential health benefits of nature contact has grown. Research in recent decades has yielded substantial evidence, but large gaps remain in our understanding.

OBJECTIVES

We propose a research agenda on nature contact and health, identifying principal domains of research and key questions that, if answered, would provide the basis for evidence-based public health interventions.

DISCUSSION

We identify research questions in seven domains: a) mechanistic biomedical studies; b) exposure science; c) epidemiology of health benefits; d) diversity and equity considerations; e) technological nature; f) economic and policy studies; and g) implementation science.

CONCLUSIONS

Nature contact may offer a range of human health benefits. Although much evidence is already available, much remains unknown. A robust research effort, guided by a focus on key unanswered questions, has the potential to yield high-impact, consequential public health insights. https://doi.org/10.1289/EHP1663.

A Patient and Provider Research Agenda on Diabetes and Hypertension Management

INTRODUCTION

A demonstration project in Richmond, Virginia involved patients and other stakeholders in the creation of a research agenda on dietary and behavioral management of diabetes and hypertension. Given the impact of these diseases on morbidity and mortality, considerable research has been directed at the challenges patients face in chronic disease management. The continuing need to understand disparities and find evidence-based interventions to improve outcomes has been fruitful, but disparities and unmet needs persist.

METHODS

The Stakeholder Engagement in Question Development (SEED) method is a stakeholder engagement methodology that combines engagement with a review of available evidence to generate research questions that address current research gaps and are important to patients and other stakeholders. Using the SEED method, patients and other stakeholders participated in research question development through a combination of collaborative, participatory, and consultative engagement. Steps in the process included: (1) identifying the topic and recruiting participants; (2) conducting focus groups and interviews; (3) developing conceptual models; (4) developing research questions; and (5) prioritizing research questions.

RESULTS

Stakeholders were involved in the SEED process from February to August 2015. Eighteen questions were prioritized for inclusion in the research agenda, covering diverse domains, from healthcare provision to social and environmental factors. Data analysis took place September to May 2016. During this time, researchers conducted a literature review to target research gaps.

CONCLUSIONS

The stakeholder-prioritized, novel research questions developed through the SEED process can directly inform future research and guide the development of evidence that translates more directly to clinical practice.

Causal inference in cumulative risk assessment: The roles of directed acyclic graphs

Cumulative risk assessments (CRAs) address exposures to multiple chemical and nonchemical stressors and often focus on characterization of health risks in vulnerable populations. Evaluating complex exposure-response relationships in CRAs requires the use of formal and rigorous methods for causal inference. Directed acyclic graphs (DAGs) are graphical causal models used to organize and communicate knowledge about the underlying causal structure that generates observable data. Using existing graphical theories for causal inference with DAGs, risk analysts can identify confounders and effect measure modifiers to determine if the available data are both internally valid to obtain unbiased risk estimates and are generalizable to populations of interest. Conditional independencies implied by the structure of a DAG can be used to test assumptions used in a CRA against empirical data in a selected study and can contribute to the evidence evaluations related to specific causal pathways. This can facilitate quantitative use of these data, as well as help identify key research gaps, prioritize data collection activities, and evaluate risk management alternatives. DAGs also enable risk analysts to be explicit about sources of uncertainty and to determine whether a causal effect can be estimated from available data. Using a conceptual model and DAG for a hypothetical community located near a concentrated animal feeding operation (CAFO), we illustrate the advantages of using DAGs for evaluating causality in CRAs. DAGs also can be used in conjunction with weight of evidence (WOE) methodology to improve causal analysis for CRA, which could lead to more effective interventions to reduce population health risks.

Describing complex clinical scenarios at the bed-side: Is a systems science approach useful? Exploring a novel diagrammatic approach to facilitate clinical reasoning

Clinicians often encounter patients having complex clinical scenarios (CCS) where diverse and dynamic diagnostic and therapeutic issues interact. A limited range of bedside methods are available to describe such patients and most often it is a diagnostic summary, a problem list, or a list of differential diagnoses. These methods fail to portray the interconnected nature of CCCs. They prevent visualization of a system of networks or a web of causation operative in CCSs.A more holistic conceptualization is required and the author argues for an approach based on systems science. The latter views the human body to consist of several closely linked organ systems, constantly interacting with each other and embedded in, and 'open' to the external environment. In order to capture the systems nature at bedside, a tool based on network diagrams, termed a Clinical Reasoning Map (CRM) is proposed which depicts diseases or conditions as nodes linked to each other by lines or arrows. The latter linkages follow simple rules: possible causes or associations as mere lines; probable cause using a single dotted arrow with directionality (from 'cause' to 'effect'); definite causal pathways by directional arrows; and bi-directional arrows to indicate organs-systems influencing each other.CRM's utility was investigated in several groups of undergraduate medical students. The results varied: 289, 5th year and 4th year medical students showed that 245 (85.5 %) perceived CRM improve their understanding of the case. However, there was no clear advantage in the CRM over a list of diagnoses in recall of key information. A majority (83.9 %) were keen to learn the technique of drawing a CRM. Postgraduates too found the tool to be useful to understand the interconnected nature of real-life complex case scenarios and pathogenesis of their multifaceted condition to generate differential diagnosis and to select appropriate investigations. Effectiveness of CRM is supported by adult learning theories such as meaningful learning and experiential learning.The author proposes that systems science and tools based in this approach such as CRM has utility in understanding and managing complex case scenarios. They differ significantly from other diagrammatic methods available in the medical literature.

A systematic literature review of the key challenges for developing the structure of public health economic models

OBJECTIVES

To identify the key methodological challenges for public health economic modelling and set an agenda for future research.

METHODS

An iterative literature search identified papers describing methodological challenges for developing the structure of public health economic models. Additional multidisciplinary literature searches helped expand upon important ideas raised within the review.

RESULTS

Fifteen articles were identified within the formal literature search, highlighting three key challenges: inclusion of non-healthcare costs and outcomes; inclusion of equity; and modelling complex systems and multi-component interventions. Based upon these and multidisciplinary searches about dynamic complexity, the social determinants of health, and models of human behaviour, six areas for future research were specified.

CONCLUSIONS

Future research should focus on: the use of systems approaches within health economic modelling; approaches to assist the systematic consideration of the social determinants of health; methods for incorporating models of behaviour and social interactions; consideration of equity; and methodology to help modellers develop valid, credible and transparent public health economic model structures.

The Mental Health Outcomes of Drought: A Systematic Review and Causal Process Diagram

Little is understood about the long term, indirect health consequences of drought (a period of abnormally dry weather). In particular, the implications of drought for mental health via pathways such as loss of livelihood, diminished social support, and rupture of place bonds have not been extensively studied, leaving a knowledge gap for practitioners and researchers alike. A systematic review of literature was performed to examine the mental health effects of drought. The systematic review results were synthesized to create a causal process diagram that illustrates the pathways linking drought effects to mental health outcomes. Eighty-two articles using a variety of methods in different contexts were gathered from the systematic review. The pathways in the causal process diagram with greatest support in the literature are those focusing on the economic and migratory effects of drought. The diagram highlights the complexity of the relationships between drought and mental health, including the multiple ways that factors can interact and lead to various outcomes. The systematic review and resulting causal process diagram can be used in both practice and theory, including prevention planning, public health programming, vulnerability and risk assessment, and research question guidance. The use of a causal process diagram provides a much needed avenue for integrating the findings of diverse research to further the understanding of the mental health implications of drought.

Adherence to medication is associated with non-planning impulsivity in euthymic bipolar disorder patients

BACKGROUND

Adherence to medication is a major issue in bipolar disorder. Non-planning impulsivity, defined as a lack of future orientation, has been demonstrated to be the main impulsivity domain altered during euthymia in bipolar disorder patients. It was associated with comorbidities.

METHODS

To investigate relationship between adherence to medication and non-planning impulsivity, we included 260 euthymic bipolar patients. Adherence to medication was evaluated by Medication Adherence Rating Scale and non-planning impulsivity by Barrat Impulsiveness Scale. Univariate analyses and linear regression were used. We conducted also a path analysis to examine whether non-planning impulsivity had direct or indirect effect on adherence, mediated by comorbidities.

RESULTS

Adherence to medication was correlated with non-planning impulsivity, even after controlling for potential confounding factors in linear regression analysis (Beta standardized coefficient = 0.156; p = 0.015). Path analysis demonstrated only a direct effect of non-planning impulsivity on adherence to medication, and none indirect effect via substance use disorders and anxiety disorders.

LIMITATIONS

Our study is limited by its cross-sectional design and adherence to medication was assessed only by self-questionnaire.

CONCLUSIONS

Higher non-planning impulsivity is associated with low medication adherence, without an indirect effect via comorbidities.

The current deconstruction of paradoxes: one sign of the ongoing methodological "revolution"

The current deconstruction of paradoxes is one among several signs that a profound renewal of methods for clinical and epidemiological research is taking place; perhaps for some basic life sciences as well. The new methodological approaches have already deconstructed and explained long puzzling apparent paradoxes, including the (non-existent) benefits of obesity in diabetics, or of smoking in low birth weight. Achievements of the new methods also comprise the elucidation of the causal structure of long-disputed and highly complex questions, as Berkson's bias and Simpson's paradox, and clarifying reasons for deep controversies, as those on estrogens and endometrial cancer, or on adverse effects of hormone replacement therapy. These are signs that the new methods can go deeper and beyond the methods in current use. A major example of a highly relevant idea is: when we condition on a common effect of a pair of variables, then a spurious association between such pair is likely. The implications of these ideas are potentially vast. A substantial number of apparent paradoxes may simply be the result of collider biases, a source of selection bias that is common not just in epidemiologic research, but in many types of research in the health, life, and social sciences. The new approaches develop a new framework of concepts and methods, as collider, instrumental variables, d-separation, backdoor path and, notably, Directed Acyclic Graphs (DAGs). The current theoretical and methodological renewal-or, perhaps, "revolution"-may be changing deeply how clinical and epidemiological research is conceived and performed, how we assess the validity and relevance of findings, and how causal inferences are made. Clinical and basic researchers, among others, should get acquainted with DAGs and related concepts.

[Psychiatric comorbidities and quality of life in adult individuals with high potential: Relationships with self-esteem]

OBJECTIVE

The objectives of this study were: 1) to describe the psychiatric comorbidities in adult individuals with high potential; 2) to assess self-esteem and quality of life in comparison with general population; 3) to study the relationships between intelligent quotient (IQ), self-esteem, psychiatric comorbidities and quality of life.

METHODS

This cross-sectional study was conducted in the psychiatric department of a public university hospital (Marseille, France). An outpatient hospital service has been specifically opened to test intelligence since 2012. During a period of six months, it was proposed to all the major individuals with high intellectual potential to receive a psychiatric evaluation using the Mini International Neuropsychiatric Interview (MINI) and to complete self-report questionnaires assessing depression (Beck scale), anxiety (STAI), self-esteem (Rosenberg scale) and quality of life (SF-36). Relationships between IQ, self-esteem, psychiatric comorbidities and quality of life were analyzed using a Bayesian path analysis.

RESULTS

Twenty-eight subjects were included, 8 had an IQ between 115 and 130, and 20 had an IQ>130. Fifty-seven percent of individuals had generalized anxiety, 21.4% a current major depressive episode, and 75% a past major depressive episode. Subjects had a low self-esteem and quality of life levels significantly lower than those in the French general population. Subjects with higher self-esteem levels had more depressive (β=0.726, P<0.001) and anxiety (β=0.335, P<0.001) disorders, associated with lower quality of life levels (β=-0.447, P<0.001 and β=-0.276, P=0.012), suggesting that self-esteem was defensive and inadequate.

CONCLUSION

Our study found a high frequency of psychiatric disorders associated with low levels of self-esteem and quality of life. A psychological treatment focusing on self-esteem may have a beneficial effect on anxiety, depression and quality of life.

Towards a framework for evaluating and grading evidence in public health

The Project on a Framework for Rating Evidence in Public Health (PRECEPT) is an international collaboration of public health institutes and universities which has been funded by the European Centre for Disease Prevention and Control (ECDC) since 2012. Main objective is to define a framework for evaluating and grading evidence in the field of public health, with particular focus on infectious disease prevention and control. As part of the peer review process, an international expert meeting was held on 13-14 June 2013 in Berlin. Participants were members of the PRECEPT team and selected experts from national public health institutes, World Health Organization (WHO), and academic institutions. The aim of the meeting was to discuss the draft framework and its application to two examples from infectious disease prevention and control. This article introduces the draft PRECEPT framework and reports on the meeting, its structure, most relevant discussions and major conclusions.

Applications of systems science in biomedical research regarding obesity and noncommunicable chronic diseases: opportunities, promise, and challenges

Interest in the application of systems science (SS) in biomedical research, particularly regarding obesity and noncommunicable chronic disease (NCD) research, has been growing rapidly over the past decade. SS is a broad term referring to a family of research approaches that include modeling. As an emerging approach being adopted in public health, SS focuses on the complex dynamic interaction between agents (e.g., people) and subsystems defined at different levels. SS provides a conceptual framework for interdisciplinary and transdisciplinary approaches that address complex problems. SS has unique advantages for studying obesity and NCD problems in comparison to the traditional analytic approaches. The application of SS in biomedical research dates back to the 1960s with the development of computing capacity and simulation software. In recent decades, SS has been applied to addressing the growing global obesity epidemic. There is growing appreciation and support for using SS in the public health field, with many promising opportunities. There are also many challenges and uncertainties, including methodologic, funding, and institutional barriers. Integrated efforts by stakeholders that address these challenges are critical for the successful application of SS in the future.

A social-ecological analysis of community perceptions of dengue fever and Aedes aegypti in Machala, Ecuador

Background

The growing burden of dengue fever and the lack of a vaccine or specific medical treatment have increased the urgency of the public health sector to identify alternative management strategies. A prevailing trend in Latin America has been a shift towards decentralized vector control programs with integrated management strategies, requiring significant intersectoral coordination, community engagement, and knowledge of the local social-ecological system (SES). Community perceptions and responses are a critical component of this system, since perceptions shape actions, and thus govern behavioral responses and acceptance of shifts in policy and management.

Methods

We investigated perceptions, misconceptions, and local SES risk factors for dengue in high risk communities located at the urban periphery and center in Machala, Ecuador. We facilitated twelve focus group discussions with community members using semi-structured question guides and causal diagrams. Focus groups were recorded, transcribed, and coded to identify emergent themes using qualitative methods for theme analysis. To estimate the relative importance of the themes in each study area, we tabulated the number of focus groups in which each theme was present. Household surveys (n = 79) were conducted to further explore these themes, and we compared survey responses from the two areas using descriptive statistics.

Results

We identified thirty biophysical, political-institutional, and community-household risk factors for dengue. People at the periphery identified a greater number of risk factors. Dengue control required considerable investment of time and resources, which presented a greater challenge for women and people at the periphery. Common misperceptions included confusion with other febrile diseases, lack of knowledge of transmission mechanisms, and misconceptions about mosquito behavior. People perceived that dengue control programs had been limited by the lack of inter-institutional coordination and lack of social cohesion.

Conclusions

There is a need for local, policy-relevant research that can be translated to strengthen the design, implementation, and evaluation of new dengue management strategies. This study contributes to a growing body of research in this area. Based on these findings, we identify key policy and management recommendations that will inform the ongoing transition to a decentralized dengue control program in Ecuador and other dengue endemic countries.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2458-14-1135) contains supplementary material, which is available to authorized users.

On the road to a stronger public health workforce: visual tools to address complex challenges

The public health workforce is vital to protecting the health and safety of the public, yet for years, state and local governmental public health agencies have reported substantial workforce losses and other challenges to the workforce that threaten the public's health. These challenges are complex, often involve multiple influencing or related causal factors, and demand comprehensive solutions. However, proposed solutions often focus on selected factors and might be fragmented rather than comprehensive. This paper describes approaches to characterizing the situation more comprehensively and includes two visual tools: (1) a fishbone, or Ishikawa, diagram that depicts multiple factors affecting the public health workforce; and (2) a roadmap that displays key elements-goals and strategies-to strengthen the public health workforce, thus moving from the problems depicted in the fishbone toward solutions. The visual tools aid thinking about ways to strengthen the public health workforce through collective solutions and to help leverage resources and build on each other's work. The strategic roadmap is intended to serve as a dynamic tool for partnership, prioritization, and gap assessment. These tools reflect and support CDC's commitment to working with partners on the highest priorities for strengthening the workforce to improve the public's health.

The role of public health in the prevention of war: rationale and competencies

In 2009 the American Public Health Association approved the policy statement, "The Role of Public Health Practitioners, Academics, and Advocates in Relation to Armed Conflict and War." Despite the known health effects of war, the development of competencies to prevent war has received little attention. Public health's ethical principles of practice prioritize addressing the fundamental causes of disease and adverse health outcomes. A working group grew out of the American Public Health Association's Peace Caucus to build upon the 2009 policy by proposing competencies to understand and prevent the political, economic, social, and cultural determinants of war, particularly militarism. The working group recommends that schools of public health and public health organizations incorporate these competencies into professional preparation programs, research, and advocacy.

Crime, fear of crime and mental health: synthesis of theory and systematic reviews of interventions and qualitative evidence

Background

Crime and fear of crime may impact negatively on health and well-being. Interventions to reduce crime and fear of crime, particularly interventions in the physical environment, may be a promising way to improve population-level well-being.

Project components

(1) Mapping review of theories and pathways; (2) systematic review of effectiveness; (3) systematic review of UK qualitative data; and (4) focus groups and interviews with stakeholders.

Methods

(1) The mapping review was a pragmatic non-systematic review focusing on theoretical literature and observational quantitative studies and development of a theoretical model of pathways. (2 and 3) The systematic reviews followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance. In total, 18 databases including EMBASE, MEDLINE, PsycINFO and Science Citation Index were searched from inception to 2010. Studies presenting data on the built environment and the fear of crime were included. Quality assessment was conducted. Data synthesis was conducted narratively for the intervention review, with harvest plots to synthesise data on inequalities, and by thematic analysis for the review of qualitative evidence. (4) Semistructured interviews with nine stakeholders working in community safety and two focus groups with members of the public were conducted to inform the methods of the project and the dissemination of findings. Data were analysed thematically.

Results

(1) There are complex and often indirect links between crime, fear of crime, environment, and health and well-being at both individual and population levels. Fear of crime is associated with poorer health outcomes. There is considerable debate about the measurement of fear of crime. Both fear of crime and crime are associated with a range of environmental factors. (2) A total of 12,093 references were screened on abstract for the two systematic reviews. Of these, 47 effectiveness studies (22 controlled and 25 uncontrolled) were included in the systematic review of effectiveness, with 36 conducted in the UK, 10 in the USA and one in the Netherlands. There is some evidence that home security improvements and non-crime-related environmental improvements may improve some fear of crime outcomes. There is little evidence that the following reduce fear of crime: street lighting improvements, closed-circuit television, multicomponent environmental crime prevention programmes or regeneration programmes. The evidence on housing improvement is mixed. Very few data on the health and well-being outcomes of crime reduction interventions were located and the study quality overall is poor. (3) A total of 39 studies were included in the systematic review of qualitative data. Several factors in the physical environment are perceived to impact on fear of crime. However, factors in the local social environment appear to be more important as drivers of fear of crime. There is considerable evidence for limitations on physical activity as a result of fear of crime, but less for mental health impacts. (4) Stakeholders see fear of crime as harder to address than crime and as linked to health and well-being. Environmental interventions, such as Secured by Design, are widely used and positively regarded.

Limitations

The review is relatively restricted in its scope and a number of relevant interventions and themes are excluded. The underlying evidence base is of limited quality, particularly for the effectiveness review, and is heterogeneous.

Conclusions

Broader social interventions appear more promising than crime-focused environmental interventions as a means of improving fear of crime, health and well-being. The qualitative evidence suggests that fear of crime may impact on physical activity. More broadly, crime and fear of crime appear to be linked to health and well-being mainly as aspects of socioeconomic disadvantage. This review indicates the following gaps in the literature: evaluation research on the health impacts of crime reduction interventions; more robust research on interventions to reduce fear of crime; systematic reviews of non-environmental interventions to reduce fear of crime and systematic reviews of qualitative evidence on other crime-related topics.

Funding

The National Institute for Health Research Public Health Research programme.

Diagram-based Analysis of Causal Systems (DACS): elucidating inter-relationships between determinants of acute lower respiratory infections among children in sub-Saharan Africa

BACKGROUND

Effective interventions require evidence on how individual causal pathways jointly determine disease. Based on the concept of systems epidemiology, this paper develops Diagram-based Analysis of Causal Systems (DACS) as an approach to analyze complex systems, and applies it by examining the contributions of proximal and distal determinants of childhood acute lower respiratory infections (ALRI) in sub-Saharan Africa.

RESULTS

Diagram-based Analysis of Causal Systems combines the use of causal diagrams with multiple routinely available data sources, using a variety of statistical techniques. In a step-by-step process, the causal diagram evolves from conceptual based on a priori knowledge and assumptions, through operational informed by data availability which then undergoes empirical testing, to integrated which synthesizes information from multiple datasets. In our application, we apply different regression techniques to Demographic and Health Survey (DHS) datasets for Benin, Ethiopia, Kenya and Namibia and a pooled World Health Survey (WHS) dataset for sixteen African countries. Explicit strategies are employed to make decisions transparent about the inclusion/omission of arrows, the sign and strength of the relationships and homogeneity/heterogeneity across settings.Findings about the current state of evidence on the complex web of socio-economic, environmental, behavioral and healthcare factors influencing childhood ALRI, based on DHS and WHS data, are summarized in an integrated causal diagram. Notably, solid fuel use is structured by socio-economic factors and increases the risk of childhood ALRI mortality.

CONCLUSIONS

Diagram-based Analysis of Causal Systems is a means of organizing the current state of knowledge about a specific area of research, and a framework for integrating statistical analyses across a whole system. This partly a priori approach is explicit about causal assumptions guiding the analysis and about researcher judgment, and wrong assumptions can be reversed following empirical testing. This approach is well-suited to dealing with complex systems, in particular where data are scarce.

How do experts define relevance criteria when initiating Health Impact Assessments of national policies?

AIM

The aim of this article is to present how the Danish Disease Prevention Committee (DDPC) members and HIA-experts understand when HIA is "relevant", which in this context means when there is "presumed to be a direct and documented effect on the health and morbidity of citizens".

METHOD

DDPC members were interviewed face-to-face; HIA experts participated in an e-survey.

RESULTS

Six DDPC members were interviewed and 100 HIA-experts participated in a survey. The DDPC members consider direct as the link between determinants and the related risk factors. The HIA experts consider direct as the link between policy and the related risk factors. Both groups favour the use of scientific evidence according to the traditional biomedical evidence hierarchy but HIA-experts also judge that there is value in using evidence that can be considered weak such as local community knowledge.

CONCLUSIONS

It is clear that the DDPC recommendation gives rise to a discussion on differing perceptions of relevance. The same definition can be used for both direct and indirect effects depending on interpretation. Documented evidence for an effect is desirable in the form provided by the traditional biomedical evidence hierarchy but HIA-experts emphasises use of local knowledge. The primary criteria for initiating a HIA, is whether the outcome of the HIA is expected to be taken into account in the decision-making process. The second criteria, is how do decision-makers perceive or interpret a decision to be relevant for HIA. This has implications for how and whether HIA will be implemented in Denmark in the future.

Reducing health inequities: the contribution of core public health services in BC

BACKGROUND

Within Canada, many public health leaders have long identified the importance of improving the health of all Canadians especially those who face social and economic disadvantages. Future improvements in population health will be achieved by promoting health equity through action on the social determinants of health. Many Canadian documents, endorsed by government and public health leaders, describe commitments to improving overall health and promoting health equity. Public health has an important role to play in strengthening action on the social determinants and promoting health equity. Currently, public health services in British Columbia are being reorganized and there is a unique opportunity to study the application of an equity lens in public health and the contribution of public health to reducing health inequities. Where applicable, we have chosen mental health promotion, prevention of mental disorders and harms of substance use as exemplars within which to examine specific application of an equity lens.

METHODS/DESIGN

This research protocol is informed by three theoretical perspectives: complex adaptive systems, critical social justice, and intersectionality. In this program of research, there are four inter-related research projects with an emphasis on both integrated and end of grant knowledge translation. Within an overarching collaborative and participatory approach to research, we use a multiple comparative case study research design and are incorporating multiple methods such as discourse analysis, situational analysis, social network analysis, concept mapping and grounded theory.

DISCUSSION

An important aim of this work is to help ensure a strong public health system that supports public health providers to have the knowledge, skills, tools and resources to undertake the promotion of health equity. This research will contribute to increasing the effectiveness and contributions of public health in reducing unfair and inequitable differences in health among population groups. As a collaborative effort between public health practitioners/decision makers and university researchers, this research will provide important understanding and insights about the implementation of the changes in public health with a specific focus on health equity, the promotion of mental health and the prevention of harms of substance use.

Statistical methods for cost-effectiveness analyses that use observational data: a critical appraisal tool and review of current practice

Many cost-effectiveness analyses (CEAs) use data from observational studies. Statistical methods can only address selection bias if they make plausible assumptions. No quality assessment tool is available for appraising CEAs that use observational studies. We developed a new checklist to assess statistical methods for addressing selection bias in CEAs that use observational data. The checklist criteria were informed by a conceptual review and applied in a systematic review of economic evaluations. Criteria included whether the study assessed the 'no unobserved confounding' assumption, overlap of baseline covariates between the treatment groups and the specification of the regression models. The checklist also considered structural uncertainty from the choice of statistical approach. We found 81 studies that met the inclusion criteria: studies tended to use regression (51%), matching on individual covariates (25%) or matching on the propensity score (22%). Most studies (77%) did not assess the 'no observed confounding' assumption, and few studies (16%) fully considered structural uncertainty from the choice of statistical approach. We conclude that published CEAs do not assess the main assumptions behind statistical methods for addressing selection bias. This checklist can raise awareness about the assumptions behind statistical methods for addressing selection bias and can complement existing method guidelines for CEAs.

Integrating human health and environmental health into the DPSIR framework: a tool to identify research opportunities for sustainable and healthy communities

The U.S. Environmental Protection Agency has recently realigned its research enterprise around the concept of sustainability. Scientists from across multiple disciplines have a role to play in contributing the information, methods, and tools needed to more fully understand the long-term impacts of decisions on the social and economic sustainability of communities. Success will depend on a shift in thinking to integrate, organize, and prioritize research within a systems context. We used the Driving forces-Pressures-State-Impact-Response (DPSIR) framework as a basis for integrating social, cultural, and economic aspects of environmental and human health into a single framework. To make the framework broadly applicable to sustainability research planning, we provide a hierarchical system of DPSIR keywords and guidelines for use as a communication tool. The applicability of the integrated framework was first tested on a public health issue (asthma disparities) for purposes of discussion. We then applied the framework at a science planning meeting to identify opportunities for sustainable and healthy communities research. We conclude that an integrated systems framework has many potential roles in science planning, including identifying key issues, visualizing interactions within the system, identifying research gaps, organizing information, developing computational models, and identifying indicators.

Epidemiology, policy, and racial/ethnic minority health disparities

PURPOSE

Epidemiologists have long contributed to policy efforts to address health disparities. Three examples illustrate how epidemiologists have addressed health disparities in the United States and abroad through a "social determinants of health" lens.

METHODS

To identify examples of how epidemiologic research has been applied to reduce health disparities, we queried epidemiologists engaged in disparities research in the United States, Canada, and New Zealand, and drew upon the scientific literature.

RESULTS

Resulting examples covered a wide range of topic areas. Three areas selected for their contributions to policy were: (1) epidemiology's role in definition and measurement, (2) the study of housing and asthma, and (3) the study of food policy strategies to reduce health disparities. Although epidemiologic research has done much to define and quantify health inequalities, it has generally been less successful at producing evidence that would identify targets for health equity intervention. Epidemiologists have a role to play in measurement and basic surveillance, etiologic research, intervention research, and evaluation research. However, our training and funding sources generally place greatest emphasis on surveillance and etiologic research.

CONCLUSIONS

The complexity of health disparities requires better training for epidemiologists to effectively work in multidisciplinary teams. Together we can evaluate contextual and multilevel contributions to disease and study intervention programs to gain better insights into evidenced-based health equity strategies.

Causal diagrams in systems epidemiology

Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s). Transmitted causes ("causes of causes") tend not to be systematically analysed.

The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties.

The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets.

Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback.

A review of causal inference for biomedical informatics

Causality is an important concept throughout the health sciences and is particularly vital for informatics work such as finding adverse drug events or risk factors for disease using electronic health records. While philosophers and scientists working for centuries on formalizing what makes something a cause have not reached a consensus, new methods for inference show that we can make progress in this area in many practical cases. This article reviews core concepts in understanding and identifying causality and then reviews current computational methods for inference and explanation, focusing on inference from large-scale observational data. While the problem is not fully solved, we show that graphical models and Granger causality provide useful frameworks for inference and that a more recent approach based on temporal logic addresses some of the limitations of these methods.

State policies targeting junk food in schools: racial/ethnic differences in the effect of policy change on soda consumption

OBJECTIVES

We estimated the association between state policy changes and adolescent soda consumption and body mass index (BMI) percentile, overall and by race/ethnicity.

METHODS

We obtained data on whether states required or recommended that schools prohibit junk food in vending machines, snack bars, concession stands, and parties from the 2000 and 2006 School Health Policies and Programs Study. We used linear mixed models to estimate the association between 2000-2006 policy changes and 2007 soda consumption and BMI percentile, as reported by 90 730 students in 33 states and the District of Columbia in the Youth Risk Behavior Survey, and to test for racial/ethnic differences in the associations.

RESULTS

Policy changes targeting concession stands were associated with 0.09 fewer servings of soda per day among students (95% confidence interval [CI] = -0.17, -0.01); the association was more pronounced among non-Hispanic Blacks (0.19 fewer servings per day). Policy changes targeting parties were associated with 0.07 fewer servings per day (95% CI = -0.13, 0.00). Policy changes were not associated with BMI percentile in any group.

CONCLUSIONS

State policies targeting junk food in schools may reduce racial/ethnic disparities in adolescent soda consumption, but their impact appears to be too weak to reduce adolescent BMI percentile.

Using logic models to capture complexity in systematic reviews

Logic models have long been used to understand complex programs to improve social and health outcomes. They illustrate how a program is designed to achieve its intended outcomes. They also can be used to describe connections between determinants of outcomes, for example, low high-school graduation rates or spiraling obesity rates, thus aiding the development of interventions that target causal factors. However, these models have not often been used in systematic reviews. This paper argues that logic models can be valuable in the systematic review process. First, they can aid in the conceptualization of the review focus and illustrate hypothesized causal links, identify effect mediators or moderators, specify intermediate outcomes and potential harms, and justify a priori subgroup analyses when differential effects are anticipated. Second, logic models can be used to direct the review process more specifically. They can help justify narrowing the scope of a review, identify the most relevant inclusion criteria, guide the literature search, and clarify interpretation of results when drawing policy-relevant conclusions about review findings. We present examples that explain how logic models have been used and how they can be applied at different stages in a systematic review. Copyright © 2011 John Wiley & Sons, Ltd.

A Simple Method for Causal Analysis of Return on IT Investment

This paper proposes a method for examining the causal relationship among investment in information technology (IT) and the organization's productivity. In this method, first a strong relationship among (1) investment in IT, (2) use of IT and (3) organization's productivity is verified using correlations. Second, the assumption that IT investment preceded improved productivity is tested using partial correlation. Finally, the assumption of what may have happened in the absence of IT investment, the so called counterfactual, is tested through forecasting productivity at different levels of investment. The paper applies the proposed method to investment in the Veterans Health Information Systems and Technology Architecture (VISTA) system. Result show that the causal analysis can be done, even with limited data. Furthermore, because the procedure relies on overall organization's productivity, it might be more objective than when the analyst picks and chooses which costs and benefits should be included in the analysis.

An applied ecological framework for evaluating infrastructure to promote walking and cycling: the iConnect study

Improving infrastructure for walking and cycling is increasingly recommended as a means to promote physical activity, prevent obesity, and reduce traffic congestion and carbon emissions. However, limited evidence from intervention studies exists to support this approach. Drawing on classic epidemiological methods, psychological and ecological models of behavior change, and the principles of realistic evaluation, we have developed an applied ecological framework by which current theories about the behavioral effects of environmental change may be tested in heterogeneous and complex intervention settings. Our framework guides study design and analysis by specifying the most important data to be collected and relations to be tested to confirm or refute specific hypotheses and thereby refine the underlying theories.

Mexico's conditional cash transfer programme increases cesarean section rates among the rural poor

BACKGROUND

Caesarean section rates are increasing in Mexico and Latin America. This study evaluates the impact of a large-scale, conditional cash transfer programme in Mexico on caesarean section rates. The programme provides cash transfers to participating low income, rural households in Mexico conditional on accepting health care and nutrition supplements.

METHODS

The primary analyses uses retrospective reports from 979 women in poor rural communities participating in an effectiveness study and randomly assigned to incorporation into the programme in 1998 or 1999 across seven Mexican states. Using multivariate and instrumental variable analyses, we estimate the impact of the programme on caesarean sections and predict the adjusted mean rates by clinical setting. Programme participation is measured by beneficiary status, programme months and cash transfers.

RESULTS

More than two-thirds of poor rural women delivered in a health facility. Beneficiary status is associated with a 5.1 percentage point increase in caesarean rates; this impact increases to 7.5 percentage points for beneficiaries enrolled in the programme for >or=6 months before delivery. Beneficiaries had significantly higher caesarean delivery rates in social security facilities (24.0 compared with 5.6% among non-beneficiaries) and in other government facilities (19.3 compared with 9.5%).

CONCLUSION

The Oportunidades conditional cash transfer programme is associated with higher caesarean section rates in social security and government health facilities. This effect appears to be driven by the increases in disposable income from the cash transfer. These findings are relevant to other countries implementing conditional cash transfer programmes and health care requirements.

The tobacco use management system: analyzing tobacco control from a systems perspective

We use systems thinking to develop a strategic framework for analyzing the tobacco problem and we suggest solutions. Humans are vulnerable to nicotine addiction, and the most marketable form of nicotine delivery is the most harmful. A tobacco use management system has evolved out of governments' attempts to regulate tobacco marketing and use and to support services that provide information about tobacco's harms and discourage its use. Our analysis identified 5 systemic problems that constrain progress toward the elimination of tobacco-related harm. We argue that this goal would be more readily achieved if the regulatory subsystem had dynamic power to regulate tobacco products and the tobacco industry as well as a responsive process for resourcing tobacco use control activities.

Mathematical modeling and the epidemiological research process

The authors of this paper advocate for the expanded use of mathematical models in epidemiology and provide an overview of the principles of mathematical modeling. Mathematical models can be used throughout the epidemiological research process. Initially they may help to refine study questions by visually expressing complex systems, directing literature searches, and identifying sensitive variables. In the study design phase, models can be used to test sampling strategies, to estimate sample size and power, and to predict outcomes for studies impractical due to time or ethical considerations. Once data are collected, models can assist in the interpretation of results, the exploration of causal pathways, and the combined analysis of data from multiple sources. Finally, models are commonly used in the process of applying research findings to public health practice by estimating population risk, predicting the effects of interventions, and contributing to the evaluation of ongoing programs. Mathematical modeling has the potential to make significant contributions to the field of epidemiology by enhancing the research process, serving as a tool for communicating findings to policymakers, and fostering interdisciplinary collaboration.