Obesity prevention: the impact of local health departments

Effectively communicating with local policymakers: a randomized trial of policy brief dissemination to address obesity

Introduction

Evidence-based policies are a powerful tool for impacting health and addressing obesity. Effectively communicating evidence to policymakers is critical to ensure evidence is incorporated into policies. While all public health is local, limited knowledge exists regarding effective approaches for improving local policymakers' uptake of evidence-based policies.

Methods

Local policymakers were randomized to view one of four versions of a policy brief (usual care, narrative, risk-framing, and narrative/risk-framing combination). They then answered a brief survey including questions about their impressions of the brief, their likelihood of using it, and how they determine legislative priorities.

Results

Responses from 331 participants indicated that a majority rated local data (92%), constituent needs/opinions (92%), and cost-effectiveness data (89%) as important or very important in determining what issues they work on. The majority of respondents agreed or strongly agreed that briefs were understandable (87%), believable (77%), and held their attention (74%) with no brief version rated significantly higher than the others. Across the four types of briefs, 42% indicated they were likely to use the brief. Logistic regression models showed that those indicating that local data were important in determining what they work on were over seven times more likely to use the policy brief than those indicating that local data were less important in determining what they work on (aOR = 7.39, 95% CI = 1.86,52.57).

Discussion

Among local policymakers in this study there was no dominant format or type of policy brief; all brief types were rated similarly highly. This highlights the importance of carefully crafting clear, succinct, credible, and understandable policy briefs, using different formats depending on communication objectives. Participants indicated a strong preference for receiving materials incorporating local data. To ensure maximum effect, every effort should be made to include data relevant to a policymaker's local area in policy communications.

Grouping Public Health Skills to Facilitate Workforce Development: A Factor Analysis of PH WINS

OBJECTIVES

This study examined whether distinct factors exist among public health skills, measured through the Public Health Workforce Interests and Needs Survey (PH WINS). Understanding how workforce training needs group is important for developing targeted and appropriate public health workforce training sessions.

DESIGN

Exploratory factor analysis was used to examine public health skills among tier 1 staff (nonmanagers) and a combined group of tier 2 and 3 staff (managers and executives).

SETTING

Data for this study come from the 2017 PH WINS, which assessed public health workforce perceptions of training needs, workplace environment, job satisfaction, perceptions about national trends, and demographics. The analysis included 22 items.

PARTICIPANTS

All public health staff in participating agencies were eligible to complete the survey. The national data set included participants from 47 state health agencies, 26 large local health departments (LHDs), and 71 mid-sized LHDs across all 10 Health and Human Services regions in the United States (including LHDs from all states). The analytic sample was n = 9630 in tier 1, n = 4829 in tier 2, and n = 714 in tier 3 staff.

MAIN OUTCOME MEASURE

Three factors were identified within the skills portion of PH WINS, using exploratory factor analysis. To interpret retained factors, the following parameters were used: factor loadings greater than 0.4, factor cross-loadings less than 0.4 or higher than loadings on other factors, and communalities greater than 0.5.

RESULTS

Factors included (1) data and systems thinking, (2) planning and management, and (3) community collaboration, with slight variation in item loadings between tier 1 and tier 2 and 3 staff analyses.

CONCLUSION

This study was the first known factor analysis of the training needs and workforce skills portion of PH WINS in the published literature. This study advances our conceptualization of public health workforce skills and has the potential to shape future critical workforce training development.

The DASH model: Data for addressing social determinants of health in local health departments

Recent frameworks, models, and reports highlight the critical need to address social determinants of health for achieving health equity in the United States and around the globe. In the United States, data play an important role in better understanding community-level and population-level disparities particularly for local health departments. However, data-driven decision-making-the use of data for public health activities such as program implementation, policy development, and resource allocation-is often presented theoretically or through case studies in the literature. We sought to develop a preliminary model that identifies the factors that contribute to data-driven decision-making in US local health departments and describe relationships between them. Guided by implementation science literature, we examined organizational-level capacity and individual-level factors contributing to using data for decision-making related to social determinants of health and the reduction of county-level disparities. This model has the potential to improve implementation of public health interventions and programs aimed at upstream structural factors, by elucidating the factors critical to incorporating data in decision-making.

Involvement of Local Health Departments in Obesity Prevention: A Scoping Review

INTRODUCTION

Local health department (LHD) obesity prevention (OP) efforts, particularly by rural LHDs, are seemingly uncommon, in part, due to limited infrastructure, workforce capacity, accessible data, and available population-level interventions aimed at social determinants of health (SDOH).

METHODS

We conducted a scoping review to determine LHD roles in OP efforts and interventions. Inclusion criteria were articles including evidence-based OP and LHD leaders or staff. Articles were coded by type of LHD involvement, data use, intervention characteristics, use of an SDOH lens, and urban or rural setting.

RESULTS

We found 154 articles on LHD OP-52 articles met inclusion criteria. Typically, LHDs engaged in only surveillance, initial intervention development, or evaluation and were not LHD led. Data and SDOH lens use were infrequent, and interventions typically took place in urban settings.

CONCLUSION

LHDs could likely play a greater role in OP and population-level interventions and use data in intervention decision making. However, literature is limited. Future research should focus on LHD capacity building, including academic-public health partnerships. Studies should include rural populations, data, and SDOH frameworks addressing "upstream" factors.

Obesity prevalence in large US cities: association with socioeconomic indicators, race/ethnicity and physical activity

BACKGROUND

Obesity has a complex association with socioeconomic factors. Further clarification of this association could guide population interventions.

METHODS

To determine the relationship between obesity prevalence, socioeconomic indicators, race/ethnicity, and physical activity, we performed a cross-sectional, multivariable linear regression, with data from large US cities participating in the Big Cities Health Inventory.

RESULTS

Increased household income was significantly associated with decreased obesity prevalence, for White (-1.97% per 10 000USD), and Black (-3.02% per 10 000USD) populations, but not Hispanic. These associations remained significant when controlling for the proportion of the population meeting physical activity guidelines. Educational attainment had a co-linear relationship with income, and only a bachelor's degree or higher was associated with a lower prevalence of obesity in White (-0.30% per percentage) and Black (-0.69% per percentage) populations. No association was found between obesity prevalence and the proportion of the population meeting physical activity guidelines for any race/ethnicity grouping.

CONCLUSION

At the population level of large US cities, obesity prevalence is inversely associated with median household income in White and Black populations. Strategies to increase socioeconomic status may also decrease obesity. Targeting attainment of physical activity guidelines as an obesity intervention needs further appraisal.

The impact of change in neighborhood poverty on BMI trajectory of 37,544 New York City youth: a longitudinal study

BACKGROUND

Neighborhood poverty may increase childhood obesity risk. However, evidence for the neighborhood poverty-obesity relationship is limited. The purpose of this study was to examine how moving to a higher or lower poverty neighborhood impacts body mass index (BMI) z-score trajectories among youth, with the goal of informing policy change, interventions, and clinical practices to reduce childhood obesity.

METHODS

Methods entailed secondary analysis of existing longitudinal data. The sample included youth attending New York City public schools in grades kindergarten through twelfth from school years 2006/2007 through 2016/2017. Eligibility criteria included moving to a higher or lower poverty neighborhood during the data midpoint [school years 2010/2011 through 2013/2014] of the 12-year data-period; New York City-specific metrics were used to define both neighborhood (Neighborhood Tabulation Area) and relevant neighborhood poverty levels (< 5, 5 to < 10%, 10 to < 20%, 20 to < 30%, 30 to < 40% and ≥ 40% of individuals below Federal Poverty Level). Two-piece latent growth curve models were used to describe BMI z-score trajectories of youth who moved to higher versus lower poverty neighborhoods, with propensity score weighting to account for preexisting differences between the two groups. Primary analyses were stratified by sex and exploratory subgroup analyses were stratified by sex and developmental stage (early childhood, middle childhood, and adolescence) to explore sensitive periods for neighborhood poverty exposure.

RESULTS

Of 532,513 youth with home address data, 18,370 youth moved to a higher poverty neighborhood and 19,174 moved to a lower poverty neighborhood (n = 37,544). Females and males who moved to a higher poverty neighborhood experienced less favorable BMI z-score trajectories for obesity risk, though effects were small. Exploratory subgroup analyses demonstrated that negative effects of neighborhood poverty were most pronounced among young and adolescent females and young males, whereas effects were mixed for other subgroups.

CONCLUSIONS

Youth who moved to higher poverty neighborhoods experienced less favorable BMI z-score trajectories for obesity risk, though effects were small and most consistent for females and younger youth. Additional research is needed to illuminate neighborhood poverty's impact on obesity, in order to inform policy, intervention, clinical, and research efforts to reduce obesity and improve child well-being.

Factors Facilitating or Hindering Use of Evidence-Based Diabetes Interventions Among Local Health Departments

OBJECTIVE

The objective of this study was to assess facilitators, barriers, and capacities to use of evidence-based programs and policies (EBPPs) in local health departments (LHDs).

DESIGN

A qualitative study design was used to elicit a contextual understanding of factors. One-hour interviews were conducted among directors and diabetes/chronic disease practitioners from LHDs. A consensus coding approach was used to identify themes.

SETTING AND PARTICIPANTS

Twenty-four participants from 14 Missouri LHDs completed interviews.

RESULTS

Themes were identified as facilitators, barriers, or capacities that enhance EBPP use. Facilitators included awareness of EBPPs, leadership and supervisor support of EBPP use, and facilitators to increase capacity to implement EBPPs. Skills development, targeted messaging, and understanding of evidence-based decision-making (EBDM) terminology were needed. Barriers to EBPPs use were described at the individual, organizational, and interorganizational levels and included community buy-in, limited resources, relevance to partners, and time scarcity. Capacities included the ways LHDs learn about EBPPs, methods that influence the use of EBPPs, and resources needed to sustain EBPPs. Top ways to learn about EBPPs were in-person interactions. Staff meetings, meetings with decision makers, and relevant evidence influenced decision making. Resources needed were funding, organizational capacity, and partnerships. Directors' and practitioners' views differed on type of agency culture that promoted EBPP use, preferences for learning about EBPPs, ways to influence decisions, needs, and barriers to EBPPs.

CONCLUSIONS

These findings can inform future strategies to support uptake of EBPPs in diabetes and chronic disease control in LHDs. LHDs have a good understanding of EBPPs, but subtle differences in perception of EBPPs and needs exist between directors and practitioners. Investment in capacity building and fostering an organizational culture supportive of EBDM were key implications for practice. By investing in employee skill development, LHDs may increase agency capacity. Researchers should use preferred channels and targeted messaging to disseminate findings.

Fighting obesity at the local level? An analysis of predictors of local health departments' policy involvement

Obesity is a critical public health issue in the United States. Local health departments (LHDs) can play a crucial role in public health policy, and are well-positioned to address obesity in their communities. We assess the obesity policy involvement among LHDs across the United States and the factors associated with increased involvement. Data come from 1803 LHDs in the 2016 National Profile of Local Health Department survey, supplemented with county-level obesity prevalence and political ideology. Negative binomial regressions examined LHD and regional characteristics associated with the number of obesity policies with which LHDs were involved. Almost half (46.1%) of LHDs reported no involvement with local obesity policies. Several factors were associated with increased policy involvement: having local boards of health with advisory (IRR = 1.31, p < 0.05) or governance roles (IRR = 1.27, p < 0.01), larger workforces (IRR = 1.34, p < 0.001), accreditation (IRR = 1.40, p < 0.001), higher obesity prevalence (IRR = 1.03, p < 0.01), and being politically more liberal (IRR = 1.01, p < 0.05). Overall, the large number of LHDs with no or limited involvement in obesity policies is a missed opportunity for local action. A better understanding of LHD policy involvement, how organizational and political factors enable or constrain their actions, and how they can leverage their current authority is needed to help LDHs serve local needs.

SIPsmartER delivered through rural, local health districts: adoption and implementation outcomes

BACKGROUND

SIPsmartER is a 6-month evidenced-based, multi-component behavioral intervention that targets sugar-sweetened beverages among adults. It consists of three in-person group classes, one teach-back call, and 11 automated phone calls. Given SIPsmartER's previously demonstrated effectiveness, understanding its adoption, implementation, and potential for integration within a system that reaches health disparate communities is important to enhance its public health impact. During this pilot dissemination and implementation trial, SIPsmartER was delivered by trained staff from local health districts (delivery agents) in rural, Appalachian Virginia. SIPsmartER's execution was supported by consultee-centered implementation strategies.

METHODS

In this mixed-methods process evaluation, adoption and implementation indicators of the program and its implementation strategy (e.g., fidelity, feasibility, appropriateness, acceptability) were measured using tracking logs, delivery agent surveys and interviews, and fidelity checklists. Quantitative data were analyzed with descriptive statistics. Qualitative data were inductively coded.

RESULTS

Delivery agents implemented SIPsmartER to the expected number of cohorts (n = 12), recruited 89% of cohorts, and taught 86% of expected small group classes with > 90% fidelity. The planned implementation strategies were also executed with high fidelity. Delivery agents completing the two-day training, pre-lesson meetings, fidelity checklists, and post-lesson meetings at rates of 86, 75, 100, and 100%, respectively. Additionally, delivery agents completed 5% (n = 3 of 66) and 10% (n = 6 of 59) of teach-back and missed class calls, respectively. On survey items using 6-point scales, delivery agents reported, on average, higher feasibility, appropriateness, and acceptability related to delivering the group classes (range 4.3 to 5.6) than executing missed class and teach-back calls (range 2.6 to 4.6). They also, on average, found the implementation strategy activities to be helpful (range 4.9 to 6.0). Delivery agents identified strengths and weakness related to recruitment, lesson delivery, call completion, and the implementation strategy.

CONCLUSIONS

In-person classes and the consultee-centered implementation strategies were viewed as acceptable, appropriate, and feasible and were executed with high fidelity. However, implementation outcomes for teach-back and missed class calls and recruitment were not as strong. Findings will inform the future full-scale dissemination and implementation of SIPsmartER, as well as other evidence-based interventions, into rural health districts as a means to improve population health.

Adults with diabetes residing in "food swamps" have higher hospitalization rates

Objective

To examine the relationship between food swamps and hospitalization rates among adults with diabetes.

Data Sources

Blue Cross Blue Shield Association Community Health Management Hub^® 2014, AHRQ Health Care Cost and Utilization Project state inpatient databases 2014, and HHS Area Health Resources File 2010‐2014.

Study Design

Cross‐sectional analysis of 784 counties across 15 states. Food swamps were measured using a ratio of fast food outlets to grocers. Multivariate linear regression estimated the association of food swamp severity and hospitalization rates. Population‐weighted models were controlled for comorbidities; Medicaid; emergency room utilization; percentage of population that is female, Black, Hispanic, and over age 65; and state fixed effects. Analyses were stratified by rural‐urban category.

Principal Findings

Adults with diabetes residing in more severe food swamps had higher hospitalization rates. In adjusted analyses, a one unit higher food swamp score was significantly associated with 49.79 (95 percent confidence interval (CI) = 19.28, 80.29) additional all‐cause hospitalizations and 19.12 (95 percent CI = 11.09, 27.15) additional ambulatory care‐sensitive hospitalizations per 1000 adults with diabetes. The food swamp/all‐cause hospitalization rate relationship was stronger in rural counties than urban counties.

Conclusions

Food swamps are significantly associated with higher hospitalization rates among adults with diabetes. Improving the local food environment may help reduce this disparity.

Enhancing evidence-based diabetes and chronic disease control among local health departments: a multi-phase dissemination study with a stepped-wedge cluster randomized trial component

BACKGROUND

The rates of diabetes and prediabetes in the USA are growing, significantly impacting the quality and length of life of those diagnosed and financially burdening society. Premature death and disability can be prevented through implementation of evidence-based programs and policies (EBPPs). Local health departments (LHDs) are uniquely positioned to implement diabetes control EBPPs because of their knowledge of, and focus on, community-level needs, contexts, and resources. There is a significant gap, however, between known diabetes control EBPPs and actual diabetes control activities conducted by LHDs. The purpose of this study is to determine how best to support the use of evidence-based public health for diabetes (and related chronic diseases) control among local-level public health practitioners.

METHODS/DESIGN

This paper describes the methods for a two-phase study with a stepped-wedge cluster randomized trial that will evaluate dissemination strategies to increase the uptake of public health knowledge and EBPPs for diabetes control among LHDs. Phase 1 includes development of measures to assess practitioner views on and organizational supports for evidence-based public health, data collection using a national online survey of LHD chronic disease practitioners, and a needs assessment of factors influencing the uptake of diabetes control EBPPs among LHDs within one state in the USA. Phase 2 involves conducting a stepped-wedge cluster randomized trial to assess effectiveness of dissemination strategies with local-level practitioners at LHDs to enhance capacity and organizational support for evidence-based diabetes prevention and control. Twelve LHDs will be selected and randomly assigned to one of the three groups that cross over from usual practice to receive the intervention (dissemination) strategies at 8-month intervals; the intervention duration for groups ranges from 8 to 24 months. Intervention (dissemination) strategies may include multi-day in-person workshops, electronic information exchange methods, technical assistance through a knowledge broker, and organizational changes to support evidence-based public health approaches. Evaluation methods comprise surveys at baseline and the three crossover time points, abstraction of local-level diabetes and chronic disease control program plans and progress reports, and social network analysis to understand the relationships and contextual issues that influence EBPP adoption.

TRIAL REGISTRATION

ClinicalTrial.gov, NCT03211832.

Five Community-wide Approaches to Physical Activity Promotion: A Cluster Analysis of These Activities in Local Health Jurisdictions in 6 States

OBJECTIVE

Local health departments (LHDs) have essential roles to play in ensuring the promotion of physical activity (PA) in their communities in order to reduce obesity. Little research exists, however, regarding the existence of these PA interventions across communities and how these interventions may impact community health.

DESIGN

In this exploratory study, we used cluster analysis to identify the structure of co-occurring PA interventions, followed by regression analysis to quantify the association between the patterns of PA interventions and prevalence of PA and obesity at a population level.

SETTING

Our study setting included local health jurisdictions in Colorado, Florida, Minnesota, New Jersey, Tennessee, and Washington.

PARTICIPANTS

Participating jurisdictions were those 218 local health jurisdictions (mostly counties) from which LHD leaders had provided data in 2013 for the Multi-Network Practice and Outcome Variation Examination Study.

MAIN OUTCOME MEASURES

We obtained unique public health activities data on PA interventions conducted in 2012 from 218 LHDs in 6 participating states. We categorized jurisdictions using cluster analysis, based on PA intervention approaches indicated by LHD leaders as available in their communities and then examined associations between categories and prevalence of obesity and of residents engaged in PA.

RESULTS

We identified 5 distinct PA intervention categories representing community-wide approaches-Comprehensive Approach, Built Environment, Personal Health, School-Based Interventions, and No Apparent Activities. Prevalence rates of obesity and PA among jurisdictions in the intervention clusters were significantly different from jurisdictions with No Apparent Activities, with more population-level approaches most significantly related to beneficial outcomes.

CONCLUSION

Our findings suggest the importance of standardized public health services data for generating evidence regarding health-related outcomes. The intervention categories we identified appear to reflect broad, local community-wide prevention approaches and demonstrated that population-level PA interventions can be testable and may have particularly beneficial relationships to community health. Widespread adoption of such standardized data depicting local public health prevention activity could support monitoring practice change, performance improvement, comparisons across communities that could reduce unnecessary variation, and the generation of evidence for public health practice and policy-making.

Anthropometric predictive equations for estimating body composition

Background:

Precise and accurate measurements of body composition are useful in achieving a greater understanding of human energy metabolism in physiology and in different clinical conditions, such as, cardiovascular disease and overall mortality. Dual-energy x-ray absorptiometry (DXA) can be used to measure body composition, but the easiest method to assess body composition is the use of anthropometric indices. This study has been designed to evaluate the accuracy and precision of body composition prediction equations by various anthropometric measures instead of a whole body DXA scan.

Materials and Methods:

We identified 143 adult patients underwent DXA evaluation of the whole body. The anthropometric indices were also measured. Datasets were split randomly into two parts. Multiple regression analysis with a backward stepwise elimination procedure was used as the derivation set and then the estimates were compared with the actual measurements from the whole-body scans for a validation set. The SPSS version 20 for Windows software was used in multiple regression and data analysis.

Results:

Using multiple linear regression analyses, the best equation for predicting the whole-body fat mass (R² = 0.808) included the body mass index (BMI) and gender; the best equation for predicting whole-body lean mass (R² = 0.780) included BMI, WC, gender, and age; and the best equation for predicting trunk fat mass (R² = 0.759) included BMI, WC, and gender.

Conclusions:

Combinations of anthropometric measurements predict whole-body lean mass and trunk fat mass better than any of these single anthropometric indices. Therefore, the findings of the present study may be used to verify the results in patients with various diseases or diets.

State practitioner insights into local public health challenges and opportunities in obesity prevention: a qualitative study

INTRODUCTION

The extent of obesity prevention activities conducted by local health departments (LHDs) varies widely. The purpose of this qualitative study was to characterize how state obesity prevention program directors perceived the role of LHDs in obesity prevention and factors that impact LHDs' success in obesity prevention.

METHODS

From June 2011 through August 2011, we conducted 28 semistructured interviews with directors of federally funded obesity prevention programs at 22 state and regional health departments. Interviews were transcribed verbatim, coded, and analyzed to identify recurring themes and key quotations.

RESULTS

Main themes focused on the roles of LHDs in local policy and environmental change and on the barriers and facilitators to LHD success. The role LHDs play in obesity prevention varied across states but generally reflected governance structure (decentralized vs centralized). Barriers to local prevention efforts included competing priorities, lack of local capacity, siloed public health structures, and a lack of local engagement in policy and environmental change. Structures and processes that facilitated prevention were having state support (eg, resources, technical assistance), dedicated staff, strong communication networks, and a robust community health assessment and planning process.

CONCLUSIONS

These findings provide insight into successful strategies state and local practitioners are using to implement innovative (and evidence-informed) community-based interventions. The change in the nature of obesity prevention requires a rethinking of the state-local relationship, especially in centralized states.