Evidence-Based Strategies to Enhance Weight Management Programs for Adult Military Beneficiaries: A Narrative Review.

INTRODUCTION: Overweight and obesity trends are on the rise among both civilian and military beneficiaries. The purpose of this narrative review was to evaluate nutrition, behavioral, lifestyle, pharmacotherapy, and alternative approaches to weight management (WM) among adults with a focus toward identifying gaps and evidence-based strategies that could support or enhance current and future WM programming among military adult beneficiaries. MATERIALS AND METHODS: A trained research team identified publications (January 2013-January 2020) for abstract review using key search terms and inclusion criteria. Two independent researchers conducted both the abstract review and full-paper bias scoring using selected Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. All eligible studies were assessed for bias and categorized based on key themes. The study was registered in PROSPERO, the international prospective register of systematic reviews. RESULTS: The research team identified 741 articles, with 278 meeting final inclusion criteria. The mean bias score was 7.5 ± 3.9 (score of 0-13; higher indicating fewer bias factors), with 64% scoring ≥9. Factors contributing to low bias included intervention compliance, dropout rate, and inability to blind participants. The most common published weight-loss interventions included a combination of therapies (59%), diet/supplement (17%), other approaches (12%), behavior change (7%), and exercise (6%). Themes identified to improve WM outcomes included leveraging technology, increasing intervention interactions, community support, emphasis on early weight loss, pharmacotherapy risk-benefit, enhanced behavioral component, resistance exercise, mindfulness, and benefits of quality-of-life measures. CONCLUSIONS: Reviewers identified several validated tools and techniques to augment and update existing WM programming to improve health and weight outcomes. The review affirmed use of individualized dietary patterns and not a "one-size-fits-all approach" as well as incorporating more comprehensive and team-approached treatments to make the best use of tools and strategies to enhance outcomes.

Rural-urban disparities in health outcomes, clinical care, health behaviors, and social determinants of health and an action-oriented, dynamic tool for visualizing them.

While rural-urban disparities in health and health outcomes have been demonstrated, because of their impact on (and intervenability to improve) health and health outcomes, we sought to examine cross-sectional and longitudinal inequities in health, clinical care, health behaviors, and social determinants of health (SDOH) between rural and non-rural counties in the pre-pandemic era (2015 to 2019), and to present a Health Equity Dashboard that can be used by policymakers and researchers to facilitate examining such disparities. Therefore, using data obtained from 2015-2022 County Health Rankings datasets, we used analysis of variance to examine differences in 33 county level attributes between rural and non-rural counties, calculated the change in values for each measure between 2015 and 2019, determined whether rural-urban disparities had widened, and used those data to create a Health Equity Dashboard that displays county-level individual measures or compilations of them. We followed STROBE guidelines in writing the manuscript. We found that rural counties overwhelmingly had worse measures of SDOH at the county level. With few exceptions, the measures we examined were getting worse between 2015 and 2019 in all counties, relatively more so in rural counties, resulting in the widening of rural-urban disparities in these measures. When rural-urban gaps narrowed, it tended to be in measures wherein rural counties were outperforming urban ones in the earlier period. In conclusion, our findings highlight the need for policymakers to prioritize rural settings for interventions designed to improve health outcomes, likely through improving health behaviors, clinical care, social and environmental factors, and physical environment attributes. Visualization tools can help guide policymakers and researchers with grounded information, communicate necessary data to engage relevant stakeholders, and track SDOH changes and health outcomes over time.

An observational, sequential analysis of the relationship between local economic distress and inequities in health outcomes, clinical care, health behaviors, and social determinants of health.

BACKGROUND: Socioeconomic status has long been associated with population health and health outcomes. While ameliorating social determinants of health may improve health, identifying and targeting areas where feasible interventions are most needed would help improve health equity. We sought to identify inequities in health and social determinants of health (SDOH) associated with local economic distress at the county-level. METHODS: For 3,131 counties in the 50 US states and Washington, DC (wherein approximately 325,711,203 people lived in 2019), we conducted a retrospective analysis of county-level data collected from County Health Rankings in two periods (centering around 2015 and 2019). We used ANOVA to compare thirty-three measures across five health and SDOH domains (Health Outcomes, Clinical Care, Health Behaviors, Physical Environment, and Social and Economic Factors) that were available in both periods, changes in measures between periods, and ratios of measures for the least to most prosperous counties across county-level prosperity quintiles, based on the Economic Innovation Group's 2015-2019 Distressed Community Index Scores. RESULTS: With seven exceptions, in both periods, we found a worsening of values with each progression from more to less prosperous counties, with least prosperous counties having the worst values (ANOVA p < 0.001 for all measures). Between 2015 and 2019, all except six measures progressively worsened when comparing higher to lower prosperity quintiles, and gaps between the least and most prosperous counties generally widened. CONCLUSIONS: In the late 2010s, the least prosperous US counties overwhelmingly had worse values in measures of Health Outcomes, Clinical Care, Health Behaviors, the Physical Environment, and Social and Economic Factors than more prosperous counties. Between 2015 and 2019, for most measures, inequities between the least and most prosperous counties widened. Our findings suggest that local economic prosperity may serve as a proxy for health and SDOH status of the community. Policymakers and leaders in public and private sectors might use long-term, targeted economic stimuli in low prosperity counties to generate local, community health benefits for vulnerable populations. Doing so could sustainably improve health; not doing so will continue to generate poor health outcomes and ever-widening economic disparities.

Trends in Characteristics of Adults Enrolled in Traditional Fee-for-Service Medicare and Medicare Advantage, 2011-2019.

BACKGROUND: While overall Medicare Part C (Medicare Advantage) enrollment has grown more rapidly than fee-for-service Medicare enrollment, changes in the growth and characteristics of different enrollee populations have not been examined. OBJECTIVES: For 2011-2019, to compare changes in the growth and characteristics of younger (age younger than 65) and older (age 65 and older) Medicare beneficiaries enrolled in Medicare Part A only, Medicare Parts A & B, and Medicare Part C. RESEARCH DESIGN: This was a retrospective, observational study. SUBJECTS: Medicare beneficiaries who were alive and enrolled in Medicare Part A only, Medicare Parts A & B, or Medicare Part C on June 30 of each year and in no other plan that year. MEASURES: For each plan type and age group the numbers and mean ages of enrollees and the proportion of enrollees who were: black, female, concurrently enrolled in Medicaid, and (for older enrollees), whose initial reason for eligibility was old age and survivors' benefits. RESULTS: Between 2011 and 2019, Medicare Part C experienced rapid expansions of 85.0% among older and 109.5% among younger enrollees. Part C enrollees were increasingly likely to be dually enrolled in Medicaid, Black and, among younger enrollees, female. CONCLUSIONS: Trends in demographic characteristics and changes in policy and growth in employer group plan offerings will likely continue to impact health care service utilization and costs in the Medicare population. Particularly as Medicare expansion to younger age groups is considered, future research should explore disparities in risk scores and care equity, quality, and costs across different Medicare enrollment options.

A Method for Examining Geographic Variation When Denominators Are Unknown, Populations Vary, and Time is of the Essence: Back Surgery as an Example.

: Level of Evidence: 3.