The lifestyle health index in the context of COVID-19 mortality and vaccination in the United States: A syndemic not to be repeated.

Public health, personal/community health behaviors, health care delivery, and the scientific community have all been impacted by the COVID-19 pandemic and are consequently poised to consider substantial paradigm shifts that will enhance disease prevention and public health resilience. The current analysis compares the newly developed Lifestyle Health Index (LHI) to U.S. county-level COVID-19 vaccination, infection, and mortality rates. We linked Centers of Disease Control PLACES, the U.S. Community Profile Report, and Nationhood lab databases through common zip-code identifiers to determine the association between county-level LHI scores and COVID-19 outcomes and vaccination status against the backdrop of U.S. regions with distinct cultural phenotypes. There was a statistically significant relationship between a poor LHI, lower COVID-19 vaccination rates and higher COVID-19 infection and mortality rates. There were clear differences in outcomes across the U.S. regions, suggesting distinct regional cultural characteristics may significantly influence health behaviors and outcomes. In the U.S., a syndemic comprising unhealthy lifestyle, chronic disease, and COVID-19 resulted in unnecessary hospitalizations and deaths. Politicization of the pandemic, socioeconomic inequity and regional cultural values meaningfully contributed to the uneven distribution of poor outcomes during this syndemic. Components of the syndemic were avoidable and should not be repeated. Condensed Abstract: The unhealthy lifestyle - chronic disease - COVID-19 U.S. syndemic resulted in unnecessary hospitalizations and deaths. Politicization of the pandemic, socioeconomic inequity and regional cultural values meaningfully contributed to the uneven distribution of poor outcomes during this syndemic. Components of the syndemic were avoidable and should not be repeated.

Applying Meaning and Self-Determination Theory to the Development of a Web-Based mHealth Physical Activity Intervention: Proof-of-Concept Pilot Study.

BACKGROUND: Meaning in life is positively associated with health, well-being, and longevity, which may be partially explained by engagement in healthier behaviors, including physical activity (PA). However, promoting awareness of meaning is a behavior change strategy that has not been tested in previous PA interventions. OBJECTIVE: This study aims to develop, refine, and pilot-test the Meaningful Activity Program (MAP; MAP to Health), a web-based mobile health PA intervention, theoretically grounded in meaning and self-determination theory, for insufficiently active middle-aged adults. METHODS: Following an iterative user-testing and refinement phase, we used a single-arm double baseline proof-of-concept pilot trial design. Participants included 35 insufficiently active adults in midlife (aged 40-64 years) interested in increasing their PA. After a 4-week baseline period, participants engaged in MAP to Health for 8 weeks. MAP to Health used a web-based assessment and just-in-time SMS text messaging to individualize the intervention; promote meaning salience; support the basic psychological needs of autonomy, competence, and relatedness; and increase PA. Participants completed measures of the hypothesized mechanisms of behavior change, including meaning salience, needs satisfaction, and autonomous motivation at pretest (-4 weeks), baseline (0 weeks), midpoint (4 weeks), and posttest (8 weeks) time points, and wore accelerometers for the study duration. At the end of the intervention, participants completed a qualitative interview. Mixed models compared changes in behavioral mechanisms during the intervention to changes before the intervention. Framework matrix analyses were used to analyze qualitative data. RESULTS: Participants were aged 50.8 (SD 8.2) years on average; predominantly female (27/35, 77%); and 20% (7/35) Asian, 9% (3/35) Black or African American, 66% (23/35) White, and 6% (2/35) other race. Most (32/35, 91%) used MAP to Health for ≥5 of 8 weeks. Participants rated the intervention as easy to use (mean 4.3, SD 0.8 [out of 5.0]) and useful (mean 4.3, SD 0.6). None of the hypothesized mechanisms changed significantly during the preintervention phase (Cohen d values <0.15). However, autonomy (P<.001; Cohen d=0.76), competence (P<.001; Cohen d=0.65), relatedness (P=.004; Cohen d=0.46), autonomous motivation (P<.001; Cohen d=0.37), and meaning salience (P<.001; Cohen d=0.40) increased significantly during the intervention. Comparison of slopes before the intervention versus during the intervention revealed that increases during the intervention were significantly greater for autonomy (P=.002), competence (P<.001), and meaning salience (P=.001); however, slopes were not significantly different for relatedness (P=.10) and autonomous motivation (P=.17). Qualitative themes offered suggestions for improvement. CONCLUSIONS: MAP to Health was acceptable to participants, feasible to deliver, and associated with increases in the target mechanisms of behavior change. This is the first intervention to use meaning as a behavior change strategy in a PA intervention. Future research will test the efficacy of the intervention in increasing PA compared to a control condition.

Unhealthy dietary patterns in the American Nations: A crisis with cultural distinctions.

INTRODUCTION: Food insecurity and limited healthful food access are critical public health issues in the United States (U.S), with unequal distribution across regions. This report tracked the prevalence of food insecurity, healthful food access, and the food environment, as cultural experiences according to the American Nations Model. METHODS: Data from the County Health Rankings & Roadmaps program on food insecurity, insufficient healthy food access, and the food environment index were matched at the zip-code level with the American Nations dataset from the Nationhood Lab. Percentages for all three food indicators were estimated based on the population of each American Nation region. RESULTS: Results show significant disparities across regional cultures. The First Nation, heavily populated by American Indian and Alaska Native communities, reports the highest prevalence of food insecurity (17 %), lowest healthful food access (21 %) and food environment index (4.6 out of 10). New France, Deep South, Great Polynesia, Greater Appalachia, El Norte and Far West, areas with higher minority populations, also show elevated food insecurity rates (range, 11-14 %) and reduced healthful food access (5-9 %). Regions with more favorable metrics across all three indicators include the Spanish Caribbean, Midlands, Yankeedom, Left Coast, Tidewater, and the New Netherlands. CONCLUSIONS: Disparities in food insecurity, healthful food access, and food environments appear to stem from geographical diversity and cultural history, underscoring the need to recognize and address cultural differences among the American Nations. This insight can inform policy and practices aimed at achieving food security and health equity across the country.

Qualitative systems mapping in promoting physical activity and cardiorespiratory fitness: Perspectives and recommendations.

The purpose of this report is to provide a perspective on the use of qualitative systems mapping, provide examples of physical activity (PA) systems maps, discuss the role of PA systems mapping in the context of iterative learning to derive breakthrough interventions, and provide actionable recommendations for future work. Systems mapping methods and applications for PA are emerging in the scientific literature in the study of complex health issues and can be used as a prelude to mathematical/computational modeling where important factors and relationships can be elucidated, data needs can be prioritized and guided, interventions can be tested and (co)designed, and metrics and evaluations can be developed. Examples are discussed that describe systems mapping based on Group Model Building or literature reviews. Systems maps are highly informative, illustrate multiple components to address PA and physical inactivity issues, and make compelling arguments against single intervention action. No studies were identified in the literature scan that considered cardiorespiratory fitness the focal point of a systems maps. Recommendations for future research and education are presented and it is concluded that systems mapping represents a valuable yet underutilized tool for visualizing the complexity of PA promotion.

Predicting life expectancy in the united states: The importance of healthy living behaviors and residential geography.

According to the World Health Organization, 30 countries currently have a life expectancy of ≥80 years: the United States (U.S.) is not among this group of countries. The current analysis assesses the ability of key lifestyle behaviors and characteristics to predict a life expectancy of ≥80 years. Only 577 (19%) of the 3066 U.S. Counties assessed had a life expectancy ≥80 years. These counties had significantly higher life expectancy (81 ± 3 vs. 76 ± 2 years) and lower percent of the population who are physically inactive (20.7 ± 3.9 vs. 27.0 ± 4.7%), actively smoke (15.9 ± 3.1 vs. 21.1 ± 3.6%), obese (31.7 ± 4.7 vs. 37.3 ± 3.9%) and have limited access to healthy food (7.1 ± 6.8 vs. 8.4 ± 6.6%) (all p < 0.001). Binary logistic regression revealed percent adults who currently smoke, percent obese, percent physically inactive, and percent with limited access to healthy food were all significant univariate predictors of

Evidence to support health system prioritization of health behaviors in the COVID-19 era.

BACKGROUND: Since the COVID-19 pandemic health systems have shifted necessarily from chronic to infectious disease treatment, but chronic disease remains critical. One large health system uniquely tracks member health behaviors. This analysis compares data from select months of an ongoing monthly cross-sectional survey before and during the pandemic. METHODS: Responses in April 2019 (pre-pandemic), April 2020 (early pandemic) or April 2021 (later pandemic) were included in the primary analysis (N = 252). Differences in meeting health behavior guidelines were analyzed via logistic regression. RESULTS: A significant decline was seen for physical activity (19% not meeting guidelines pre-pandemic vs. 41% later pandemic) but not fruit/vegetable, alcohol, or sleep from early to later pandemic. Prevalence of women not meeting tobacco guidelines increased from early (5%) to later pandemic (10%) while prevalence in men decreased (10% vs 4% respectively). The percent of people not thinking about the good things that happen to them fluctuated closely with reports of new COVID-19 cases. CONCLUSIONS: Findings show the nuance of changing health behaviors throughout the pandemic. Results should be used by health systems to tailor support based on insights from the pandemic experience.

The Potential Influence of Firearm Violence on Physical Inactivity in the United States.

BACKGROUND: Despite broad recognition of the physical inactivity pandemic, little to no progress has been made in the past decade in mitigating the problem. The current analysis builds upon previous research into the drivers of physical inactivity to assess the potential interactions with firearm violence in the United States. METHODS: We merged county-level data on firearm fatality rates, physical inactivity prevalence, the Social Vulnerability Index, and the American nations regional cultures schematic. RESULTS: Counties with a physical inactivity prevalence currently above the federal government's 2030 goal (ie, ≥21.8%) had a significantly higher firearm fatality rate per 100,000 population. This finding was consistent for both the overall rate and race-based subgroups. The overall White, Hispanic, and Black firearm fatality rates were also significantly higher in the American nations group comprising Greater Appalachia, Deep South, El Norte, New France, and First Nation. Stepwise linear regression analysis revealed that the Social Vulnerability Index, American nations dichotomous grouping, and firearm fatality rate were all retained (P < .001) in predicting physical inactivity prevalence as a continuous variable. CONCLUSION: In conclusion, the United States faces myriad health and societal challenges. Unhealthy lifestyles and gun violence are two of the leaders. The current analysis in conjunction with previous findings demonstrates that solving these challenges by interacting, create complexity to finding solutions that has not been thoroughly considered.

Novel Approaches to Addressing the US Physical Inactivity and Obesity Pandemics: An Opportunity for Religious Organizations.

BACKGROUND: Physical inactivity and obesity crises persist in the United States despite substantial mitigation efforts. The primary goal of this analysis is to determine whether the geographic concentration of religious institutions overlaps with geographic patterns for physical inactivity and obesity prevalence. METHODS: We obtained 2021 county-level, age-adjusted physical inactivity ("no leisure time physical activity") and obesity prevalence from the 2023 Centers for Disease Control and Prevention PLACES database. Data on number of congregations per 100,000 individuals and adherents as a percentage of the population were obtained from the 2020 US Religion Census. The American Nations regional cultures model was obtained from the Nationhood Lab. RESULTS: On a national level, all correlations were statistically significant between health factors and religious infrastructure-higher physical inactivity and obesity were related to more congregations per 100,000 population on a county level. The strength of correlations between congregations per 100,000 county population and both physical inactivity and obesity prevalence was greatest in the American Nations model's Deep South and Tidewater regions. CONCLUSIONS: Approaches to addressing the pandemics of unhealthy lifestyle-related health factors of physical inactivity and obesity in the United States have, in large part, been unsuccessful. Church-based healthy lifestyle programs, particularly in areas where a high concentration of congregations align with high physical inactivity and obesity, may offer a novel and effective approach to addressing this issue.

The Influence of Social Vulnerability and Culture on Physical Inactivity in the United States - Identifying Hot Spots in Need of Attention.

BACKGROUND: In the United States, ongoing efforts to increase individual- and population-level physical activity have made little to no progress over the past decade in reducing the percentage of individuals who report no leisure-time physical activity. The purpose of the current study is to further assess the relationship between social vulnerability and the prevalence of physical inactivity at the county level. METHODS: We merged county-level data on physical inactivity prevalence, the Social Vulnerability Index (SVI), and the American Nations regional cultures schematic. RESULTS: Physical inactivity significantly correlated (P < .001) with the overall SVI score and all subtheme scores to varying levels of strength. Clear and statistically significant heterogeneity in the SVI scores was apparent across distinct regions using the American Nations model, consistent with previously demonstrated patterns of physical inactivity prevalence. CONCLUSIONS: On a national level, physical inactivity prevalence is unacceptably high and has not appreciably improved over the past decade. Within the United States, high levels of social vulnerability and physical inactivity are concentrated within specific geographic regions that need tailored solutions to resolve health disparities.

Physical Inactivity and Obesity in the United States Through the Lens of the 2012 and 2016 Presidential Elections.

The physical inactivity (PI) and obesity pandemics in the United States (U.S.) have undauntingly persisted in recent history. We have previously demonstrated differences in PI, obesity, socioeconomics, race, and regional culture according to county-level results for the 2020 presidential election. This commentary extends this analysis by considering if the 2020 trend is consistent with the 2 previous presidential election cycles. On a national level, during both the 2012 and 2016 presidential elections, counties where the Democratic candidate received more votes than the Republican one had a significantly lower PI and obesity prevalence. Counties where the Democratic candidate received more votes also had higher median national incomes, a higher proportion of the population who identify as Black, and a higher percentage of people who had completed at least some college. However, at a U.S. regional level, unique, region-specific cultural identities and partisan coalition demographics were apparent and showed some variation between election cycles. In most of the distinct U.S. cultural regions defined by the American Nations model, PI and obesity prevalence were lower in democratic-majority counties, although there were exceptions. These results support our previous findings demonstrating PI and obesity trends in the U.S. are influenced by cultural and political factors that are likely interrelated and which warrant further attention.

Physical Inactivity and Obesity in the United States: At the Intersection of Politics, Socioeconomics, Race, and Culture.

Efforts to reverse the physical inactivity (PI) and obesity pandemics in the United States (U.S.) have been unsuccessful. This commentary provides a view of PI and obesity in the U.S. from the intersection of politics, socioeconomics, race, and culture. On a national level, counties where the Democratic presidential candidate received more votes in 2020 than the Republican candidate had a lower PI and obesity prevalence. The percentage completing some college and Black individuals as well as median household income were higher in counties where the Democratic candidate received more votes. Regionally, unique, region-specific cultural identities and partisan coalition demographics were apparent and serve as potential explanations for inconsistencies in PI and obesity prevalence across the U.S. Identifying the driving forces of PI and obesity within specific U.S. regions and crafting messaging that has optimal efficacy on a local level is essential to reducing the burden of cardiovascular disease and other chronic conditions.