Rural-Urban Disparities in Obesity Prevalence Among Working Age Adults in the United States: Exploring the Mechanisms

Food deserts exposure, density of fast-food restaurants, and park access: Exploring the association of food and recreation environments with obesity and diabetes using global and local regression models

To prevent obesity and diabetes environmental interventions such as eliminating food deserts, restricting proliferation of food swamps, and improving park access are essential. In the United States, however, studies that examine the food and park access relationship with obesity and diabetes using both global and local regression are lacking. To guide county, state, and federal policy in combating obesity and diabetes, there is a need for cross-scale analyses to identify that relationship at national and local levels. This study applied spatial regression and geographically weighted regression to the 3,108 counties in the contiguous United States. Global regression show food deserts exposure and density of fast-food restaurants have non-significant association with obesity and diabetes while park access has a significant inverse association with both diseases. Geographically weighted regression that takes into account spatial heterogeneity shows that, among southern states that show high prevalence of obesity and diabetes, Alabama and Mississippi stand out as having opportunity to improve park access. Results suggest food deserts exposure are positively associated with obesity and diabetes in counties close to Alabama, Georgia, and Tennessee while density of fast-food restaurants show positive association with two diseases in counties of western New York and northwestern Pennsylvania. These findings will help policymakers and public health agencies in determining which geographic areas need to be prioritized when implementing public interventions such as promoting healthy food access, limiting unhealthy food options, and increasing park access.

Rural disparities impact response to a web-based physical activity self-management intervention in COPD: A secondary analysis

PURPOSE

This secondary exploratory analysis examined rural-urban differences in response to a web-based physical activity self-management intervention for chronic obstructive pulmonary disease (COPD).

METHODS

Participants with COPD (N = 239 US Veterans) were randomized to either a multicomponent web-based intervention (goal setting, iterative feedback of daily step counts, motivational and educational information, and an online community forum) or waitlist-control for 4 months with a 12-month follow-up. General linear modeling estimated the impact of rural/urban status (using Rural-Urban Commuting Area [RUCA] codes) on (1) 4- and 12-month daily step-count change compared to waitlist-control, and (2) intervention engagement (weekly logons and participant feedback).

FINDINGS

Rural (n = 108) and urban (n = 131) participants' mean age was 66.7±8.8 years. Rural/urban status significantly moderated 4-month change in daily step counts between randomization groups (p = 0.041). Specifically, among urban participants, intervention participants improved by 1500 daily steps more than waitlist-control participants (p = 0.001). There was no difference among rural participants. In the intervention group, rural participants engaged less with the step-count graphs on the website than urban participants at 4 months (p = 0.019); this difference dissipated at 12 months. More frequent logons were associated with greater change in daily step counts (p = 0.004); this association was not moderated by rural/urban status.

CONCLUSIONS

The web-based intervention was effective for urban, but not rural, participants at 4 months. Rural participants were also less engaged at 4 months, which may explain differences in effectiveness. Technology-based interventions can help address urban-rural disparities in patients with COPD, but may also contribute to them unless resources are available to support engagement with the technology.

Social Determinants of Cancer Disparities

Cancer is a major public health issue that is associated with significant morbidity and mortality across the globe. At its root, cancer represents a genetic aberration, but socioeconomic, environmental, and geographic factors contribute to different cancer outcomes for selected population subsets. The disparities in the delivery of healthcare affect all aspects of cancer management from early prevention to end-of-life care. In an effort to address the inequality in the delivery of healthcare among socioeconomically disadvantaged populations, the World Health Organization defined social determinants of health (SDOH) as conditions in which people are born, live, work, and age. These factors play a significant role in the disproportionate cancer burden among different population groups. SDOH are associated with disparities in risk factor burden, screening modalities, diagnostic testing, treatment options, and quality of life of patients with cancer. The purpose of this article is to describe a more holistic and integrated approach to patients with cancer and address the disparities that are derived from their socioeconomic background.

Increasing the reach of evidence-based interventions for weight management and diabetes prevention among Medicaid patients: study protocol for a pilot Sequential Multiple Assignment Randomised Trial

INTRODUCTION

Over 40% of US adults meet criteria for obesity, a major risk factor for chronic disease. Obesity disproportionately impacts populations that have been historically marginalised (eg, low socioeconomic status, rural, some racial/ethnic minority groups). Evidence-based interventions (EBIs) for weight management exist but reach less than 3% of eligible individuals. The aims of this pilot randomised controlled trial are to evaluate feasibility and acceptability of dissemination strategies designed to increase reach of EBIs for weight management.

METHODS AND ANALYSIS

This study is a two-phase, Sequential Multiple Assignment Randomized Trial, conducted with 200 Medicaid patients. In phase 1, patients will be individually randomised to single text message (TM1) or multiple text messages (TM+). Phase 2 is based on treatment response. Patients who enrol in the EBI within 12 weeks of exposure to phase 1 (ie, responders) receive no further interventions. Patients in TM1 who do not enrol in the EBI within 12 weeks of exposure (ie, TM1 non-responders) will be randomised to either TM1-Continued (ie, no further TM) or TM1 & MAPS (ie, no further TM, up to 2 Motivation And Problem Solving (MAPS) navigation calls) over the next 12 weeks. Patients in TM+ who do not enrol in the EBI (ie, TM+ non-responders) will be randomised to either TM+Continued (ie, monthly text messages) or TM+ & MAPS (ie, monthly text messages, plus up to 2 MAPS calls) over the next 12 weeks. Descriptive statistics will be used to characterise feasibility (eg, proportion of patients eligible, contacted and enrolled in the trial) and acceptability (eg, participant opt-out, participant engagement with dissemination strategies, EBI reach (ie, the proportion of participants who enrol in EBI), adherence, effectiveness).

ETHICS AND DISSEMINATION

Study protocol was approved by the University of Utah Institutional Review Board (#00139694). Results will be disseminated through study partners and peer-reviewed publications.

TRIAL REGISTRATION NUMBER

clinicaltrials.gov; NCT05666323.

Rural-Urban Differences in Cognition: Findings From the Advanced Cognitive Training for Independent and Vital Elderly Trial

ObjectivesWe examined associations between three geographic areas (urban, suburban, rural) and cognition (memory, reasoning, processing speed) over a 10-year period. Methods: Data were obtained from 2539 participants in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial. Multilevel, mixed-effects linear regression was used to estimate cognitive trajectories by geographical areas over 10 years, after adjusting for social determinants of health. Results: Compared to urban and suburban participants, rural participants fared worse on all cognitive measures-memory (B = -1.17 (0.17)), reasoning (B = -1.55 (0.19)), and processing speed (B = 0.76 (0.19)) across the 10-year trajectory. Across geographic areas, greater economic stability, health care access and quality, and neighborhood resources were associated with better cognition over time. Discussion: Findings highlight the importance of geographical location when examining cognition later in life. More research examining place-based life experiences is needed to make the greatest impact on geographically diverse communities.

Dietary Pattern Indicators among Healthy and Unhealthy Weight Adolescents Residing in Different Contexts across the Otago Region, New Zealand

Reported obesity rates for adolescents in different urban and rural areas are inconsistent. We examined indicators of healthy and unhealthy dietary patterns among 1863 adolescents aged 13-18 years with a healthy or excess body weight attending 23 secondary schools in four different settlement types across the Otago region, New Zealand. An online survey included demographics and dietary behaviours. Height and weight were measured, and body mass index was calculated. New Zealand defined urban and rural settlement types were used. Home addresses determined a small area-level index of deprivation. Data were analysed using Chi-square tests and ANOVA. A logistic model was fitted to estimate adjusted odds ratios of excess weight. The proportion of adolescents with a healthy weight differed (p < 0.001) between the most (64.9%) and least (76.4%) deprived neighbourhood areas. There was only indicative evidence of differences between settlement types (p = 0.087). Sugar-sweetened beverage and fast-food consumption was more frequent in the most deprived areas (p < 0.001), and in urban versus rural settlements (p < 0.001). The most important associations with excess weight were area-level deprivation and ethnicity, but not settlement type. Prioritising socioeconomic factors irrespective of settlement type is necessary when developing interventions to improve dietary patterns and body weight status among adolescents.

Spatial analysis of overweight prevalence in China: exploring the association with air pollution

BACKGROUND

Overweight is a known risk factor for various chronic diseases and poses a significant threat to middle-aged and elderly adults. Previous studies have reported a strong association between overweight and air pollution. However, the spatial relationship between the two remains unclear due to the confounding effects of spatial heterogeneity.

METHODS

We gathered height and weight data from the 2015 China Health and Retirement Long-term Survey (CHARLS), comprising 16,171 middle-aged and elderly individuals. We also collected regional air pollution data. We then analyzed the spatial pattern of overweight prevalence using Moran's I and Getis-Ord Gi* statistics. To quantify the explanatory power of distinct air pollutants for spatial differences in overweight prevalence across Southern and Northern China, as well as across different age groups, we utilized Geodetector's q-statistic.

RESULTS

The average prevalence of overweight among middle-aged and elderly individuals in each city was 67.27% and 57.39%, respectively. In general, the q-statistic in southern China was higher than that in northern China. In the north, the prevalence was significantly higher at 54.86% compared to the prevalence of 38.75% in the south. SO2 exhibited a relatively higher q-statistic in middle-aged individuals in both the north and south, while for the elderly in the south, NO2 was the most crucial factor (q = 0.24, p < 0.01). Moreover, fine particulate matter (PM2.5 and PM10) also demonstrated an important effect on overweight. Furthermore, we found that the pairwise interaction between various risk factors improved the explanatory power of the prevalence of overweight, with different effects for different age groups and regions. In northern China, the strongest interaction was found between NO2 and SO2 (q = 0.55) for middle-aged individuals and PM2.5 and SO2 (q = 0.27) for the elderly. Conversely, in southern China, middle-aged individuals demonstrated the strongest interaction between SO2 and PM10 (q = 0.60), while the elderly showed the highest interaction between NO2 and O3 (q = 0.42).

CONCLUSION

Significant spatial heterogeneity was observed in the effects of air pollution on overweight. Specifically, air pollution in southern China was found to have a greater impact on overweight than that in northern China. And, the impact of air pollution on middle-aged individuals was more pronounced than on the elderly, with distinct pollutants demonstrating significant variation in their impact. Moreover, we found that SO2 had a greater impact on overweight prevalence among middle-aged individuals, while NO2 had a greater impact on the elderly. Additionally, we identified significant statistically interactions between O3 and other pollutants.

A quasi-experimental study on adult weight loss using a multidimensional approach among a rural population

Objectives

The study aimed to investigate the effectiveness of a yearlong digital multidimensional weight-loss intervention among residents in a southern rural community. The intervention utilized a quasi-experimental design to assess weight loss and lifestyle habit changes in volunteer individuals living in a rural community in western North Carolina.

Methods

The quasi-experimental design featured pre- and post-in-person health assessments, including anthropometric measures such as body composition, blood pressure, and lifestyle habits, through a health risk questionnaire. Upon completion of the in-person pre-assessment, participants received digital health education and challenges via email and challenge runner for 1 year. Following 12 months, participants were asked to complete the post-assessment to review their results. The multidimensional weight-loss intervention was communicated via newspaper and social media to promote participation among community members, utilizing a volunteer sample. Univariate analyses were conducted to determine age, weight, BMI, and body fat percentage. A paired sample t-test was conducted on pre- and post-weight as well as pre- and post-health scores. The health score was derived from the health risk questionnaire. A bivariate Pearson correlation was conducted for post-weight and post-health score analyses.

Results

The average participant was female in their mid-40s (N = 67). Results showed insignificant statistical mean differences between pre- and post-weight and pre- and post-health scores. A Pearson correlation indicated a moderate correlation r = -0.36, p = 0.003) between post-weight and post-health score. The negative correlation indicates changes in health behavior reflected in the health score improving as weight decreased.

Conclusion

The weight-loss intervention proved unsuccessful in clinical weight loss but demonstrated an association between healthy behavior changes and weight loss. However, further research is needed to solidify the current findings, as there were limitations identified in COVID-19.

Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments

BACKGROUND

The complex nature of obesity increasingly requires a comprehensive approach that includes the role of environmental factors. For understanding contextual determinants, the resources provided by technological advances could become a key factor in obesogenic environment research. This study aims to identify different sources of non-traditional data and their applications, considering the domains of obesogenic environments: physical, sociocultural, political and economic.

METHODS

We conducted a systematic search in PubMed, Scopus and LILACS databases by two independent groups of reviewers, from September to December 2021. We included those studies oriented to adult obesity research using non-traditional data sources, published in the last 5 years in English, Spanish or Portuguese. The overall reporting followed the PRISMA guidelines.

RESULTS

The initial search yielded 1583 articles, 94 articles were kept for full-text screening, and 53 studies met the eligibility criteria and were included. We extracted information about countries of origin, study design, observation units, obesity-related outcomes, environment variables, and non-traditional data sources used. Our results revealed that most of the studies originated from high-income countries (86.54%) and used geospatial data within a GIS (76.67%), social networks (16.67%), and digital devices (11.66%) as data sources. Geospatial data were the most utilised data source and mainly contributed to the study of the physical domains of obesogenic environments, followed by social networks providing data to the analysis of the sociocultural domain. A gap in the literature exploring the political domain of environments was also evident.

CONCLUSION

The disparities between countries are noticeable. Geospatial and social network data sources contributed to studying the physical and sociocultural environments, which could be a valuable complement to those traditionally used in obesity research. We propose the use of information available on the Internet, addressed by artificial intelligence-based tools, to increase the knowledge on political and economic dimensions of the obesogenic environment.

Urban-rural disparities in childhood obesogenic environments in the United States: Application of differing rural definitions

BACKGROUND

Research is needed that identifies environmental resource disparities and applies multiple rural definitions. Therefore, this study aims to examine urban-rural differences in food and physical activity (PA) environment resource availability by applying several commonly used rural definitions. We also examine differences in resource availability within urban-rural categories that are typically aggregated.

METHODS

Six food environment variables (access to grocery/superstores, farmers' markets, fast food, full-service restaurants, convenience stores, and breastfeeding-friendly facilities) and 4 PA environment variables (access to exercise opportunities and schools, walkability, and violent crimes) were included in the childhood obesogenic environment index (COEI). Total COEI, PA environment, and food environment index scores were generated by calculating the average percentile for related variables. US Department of Agriculture Urban Influence Codes, Office of Management and Budget codes, Rural-Urban Continuum Codes, Census Bureau Population Estimates for percent rural, and Rural Urban Commuting Area Codes were used. One-way ANOVA was used to detect urban-rural differences.

RESULTS

The greatest urban-rural disparities in COEI (F=310.2, P<.0001) and PA environment (F=562.5, P<.0001) were seen using RUCC codes. For food environments, the greatest urban-rural disparities were seen using Census Bureau percent rural categories (food: F=24.9, P<.0001). Comparing remote rural categories, differences were seen for food environments (F=3.1, P=.0270) and PA environments (F=10.2, P<.0001). Comparing metro-adjacent rural categories, differences were seen for PA environment (F=4.7, P=.0090).

CONCLUSION

Findings inform future research on urban and rural environments by outlining major differences between urban-rural classifications in identifying disparities in access to health-promoting resources.

Parents of minor children lose less weight during a behavioral weight loss intervention: Findings from the Rural LEAP trial

Objective

The transition to parenthood is associated with worsening health behaviors, yet the impact of parental status on successful weight loss has rarely been examined. The purpose of this study was to examine the effect of parental status of minor children on weight loss and behavioral adherence in a rural community-based weight loss intervention.

Methods

Five hundred and twenty-eight adults (age 21-75 years, body mass index [BMI] 30-45 kg/m2) were enrolled in a group-based weight loss intervention consisting of 16 weekly sessions delivered in face-to-face group sessions at Cooperative Extension Service (CES) offices. Participants who were parents with at least one minor child (≤18 years old) in the home were compared to participants with no minor children in the home. Measures included percent weight loss, session attendance, adherence to self-monitoring, and achieving calorie and physical activity goals.

Results

Compared to participants without minor children, parents with minor children lost significantly less weight (7.5% vs. 6.2%, respectively; p = 0.01), and were less likely to lose ≥5% of baseline weight (59.2% vs. 70.2%, respectively; p = 0.02). In addition, parents with minor children attended significantly fewer sessions, had lower adherence to self-monitoring, and met calorie and step goals less often (all ps < 0.001). The association between parental status and percent weight loss was not significantly moderated by gender of the parent.

Conclusions

Parents of minor children had greater difficulty adhering to intervention goals and lost less weight than participants without minor children. Future research should investigate whether tailoring intervention to meet the unique needs of parents can enhance outcomes, especially given the large segment of the population represented by this group.

Targeting Nanotechnology and Nutraceuticals in Obesity: An Updated Approach

HYPOTHESIS

This review article represents a brief layout of the risk factors and pathophysiology responsible for obesity, customary treatment strategies, and nanotechnology-based nutraceutical for the therapeutics of obesity.

EXPERIMENTS

An exhaustive search of the literature was done for this purpose, using Google Scholar, PubMed, and ScienceDirect databases. A literature study was conducted using publications published in peer-reviewed journals between 2000 and 2022.

FINDINGS

This was revealed that risk factors responsible for obesity were genetic abnormalities and environmental and socio-economic factors. Several research articles published between 2000 and 2022 were based on phytoconstituents-based nanoformulation for obesity therapeutics and, therefore, have been systematically compiled in this review. Various nutraceuticals like Garcinia cambogia, quercetin, resveratrol, capsaicin, Capsicum, Curcuma longa, Camella Sinensis, Zingiber officinalis, Citrus aurantium, Aegle marmelos, Coffea canephora, Asparagus officinalis, Gardenia jasminoides, Catha edulis, Clusia nemroisa, Rosmarinus officinalis, Cirsium setidens, Betula platyphylla, Tripterygium wilfordi possessing anti-obesity actions are discussed in this review along with their patents, clinical trials as well as their nanoformulation available.

CONCLUSION

This review illustrates that nanotechnology has a great propensity to impart a promising role in delivering phytochemicals and nutraceuticals in managing obesity conditions and other related disorders.

Contribution of environmental factors and female reproductive history to hypertension and obesity incidence in later life

BACKGROUND

Hypertension (HT) and obesity, which are important risk factors for cardiovascular diseases, are complex traits determined by multiple biological and behavioural factors. However, the role of female reproductive history in evaluating HT and obesity is still unclear.

AIM

To investigate the long-term effects of reproductive factors on the probability of obesity and HT in later life after adjusting for socio-demographic and lifestyle behaviour factors.

SUBJECTS AND METHODS

A total of 503 women (39 - 65 years) were recruited from different localities in Slovakia. Multivariable logistic regression analyses were performed to test the associations.

RESULTS

Early menarche age of 11 years and under was associated with twice higher probability of obesity at midlife, independent of environmental confounders (OR = 2.27, CI = 1.35 - 3.81, p = 0.002). Breastfeeding (Bf) women had a lower likelihood of obesity in later life than non-Bf parous women, independent of environmental confounders (OR = 0.35, CI = 0.17 - 0.72, p = 0.004). Finally, age at menarche was associated with obesity-associated HT.

CONCLUSION

Reproductive factors are significantly associated with obesity and obesity-associated HT in later life. The age at menarche and Bf can be risk factors for early identification of women with increased likelihood of adult cardiovascular risk.

Attitudes, Perceptions, and Practices in Managing Obesity Among Endocrinologists

OBJECTIVE

Obesity is globally recognized as a critically important disease by professional medical organizations in addition to the World Health Organization and American Medical Association, but the health care systems, medical teams, and the public have been slow to embrace this concept.

METHODS

American Association of Clinical Endocrinology (AACE) staff drafted the survey, and two endocrinologists independently reviewed the survey questions and modified the survey instrument. The survey included inquiries related to practice and patient demographics, awareness of obesity, treatment of obesity, barriers to improving obesity outcomes, digital health, cognitive behavioral therapy, lifestyle medicine, anti-obesity medications, weight stigma, and social determinants of health. The survey was emailed to 493 endocrinologists, with 305 completing the study (62%).

RESULTS

Ninety-eight percent of the responders agree that obesity is a disease, while 2% neither agree nor disagree. 53% of respondents are familiar with the term "adiposity-based chronic disease." 13% of the respondents are certified by the American Board of Obesity Medicine (ABOM). 57% of the respondents use published obesity guidelines as a resource for treating patients with obesity. Most endocrinologists recommend dietary and lifestyle changes, but fewer prescribe anti-obesity medication (AOM) or recommend bariatric surgery. ABOM-certified endocrinologists are more likely to use a multidisciplinary approach.

CONCLUSION

Self-reported knowledge and practices in the management of obesity highlight the importance of a multimodal approach to obesity and foster collaboration among healthcare professionals. It is necessary to raise awareness about obesity among clinicians, identify knowledge gaps and create educational tools to address those gaps.

Physical Activity Barriers and Assets in Rural Appalachian Kentucky: A Mixed-Methods Study

Obesity is an increasing public health concern in the U.S. and a contributor to chronic illness, with trends revealing a rise in adult obesity and chronic disease rates among the most vulnerable and disadvantaged populations, including those in rural communities. A mixed-methods approach was used to examine perspectives on perceived physical activity barriers, resources, and level of community support. Researchers utilized the socioecological model to examine the multiple domains that support physical activity in rural Appalachia. The present study focuses on baseline data, including a cohort survey to assess physical activity, health status, and barriers to physical activity, and five focus groups with elected community leaders, community residents, members, and key stakeholders to assess perspectives on physical activity barriers and resources within the county. The cohort survey sample (N = 152) reported a median of 6 barriers (range 0–13) to participating in at least 30 min of physical activity daily. The qualitative analysis yielded three overarching themes related to physical activity participation: lack of motivation, physical environment, and cultural barriers. This mixed-methods study revealed the challenges and perceptions among rural residents across the socioecological model when assessing physical inactivity. Findings can be used to tailor future interventions focused on expanding social support, designing infrastructure, and creating policies that promote physical activity.

Incongruency of youth food and physical activity environments in the United States: Variations by region, rurality, and income

Local environments are increasingly the focus of health behavior research and practice to reduce gaps between fruit/vegetable intake, physical activity (PA), and related guidelines. This study examined the congruency between youth food and PA environments and differences by region, rurality, and income across the United States. Food and PA environment data were obtained for all U.S. counties (N = 3142) using publicly available, secondary sources. Relationships between the food and PA environment tertiles was represented using five categories: 1) congruent-low (county falls in both the low food and PA tertiles), 2) congruent-high (county falls in both the high food and PA tertiles), 3) incongruent-food high/PA low (county falls in high food and low PA tertiles), 4) incongruent-food low/PA high (county falls in low food and high PA tertiles), and 5) intermediate food or PA (county falls in the intermediate tertile for food and/or PA). Results showed disparities in food and PA environment congruency according to region, rurality, and income (p < .0001 for each). Nearly 25% of counties had incongruent food and PA environments, with food high/PA low counties mostly in rural and low-income areas, and food low/PA high counties mostly in metropolitan and high-income areas. Approximately 8.7% of counties were considered congruent-high and were mostly located in the Northeast, metropolitan, and high-income areas. Congruent-low counties made up 10.0% of counties and were mostly in the South, rural, and low-income areas. National and regional disparities in environmental obesity determinants were identified that can inform targeted public health interventions.

Community-Based Efforts Aim to Improve the Food Environment within a Highly Obese Rural Appalachian County

Rural communities in Appalachia are displaying increased obesity prevalence, yet traditional interventions have not provided a broad enough impact to improve dietary consumption patterns. Therefore, expanding efforts that address the food environment and incorporate behavioral nudges through community-developed marketing strategies may be a viable mechanism to improve food and beverage choices within this unique population. This study installed shelf-wobblers across n = 5 gas stations in one rural Appalachian county in Kentucky. Smart Snacks were identified from store inventory lists utilizing the CDC Food Service Guideline for Federal Facilities calculator and were categorized into high-protein snacks, low-fat carbohydrate snacks, meal replacement snacks, and no-calorie beverages. NEMS-CS audits were conducted, and monthly sales data was collected at baseline and for six months thereafter for each store location. A difference-in-difference model was used, adjusting for total sales or total mean sales for each Smart Snack model to assess the percentage change within and between stores. Overall, percent change in mean sales and total sales across all stores resulted in a percentage increase of sales of Smart Snack items following wobbler installment. This study provides unique insight into how a community-driven approach to marketing can influence the sale of healthier food and beverage items.

The Influence of Rurality on Fruit and Vegetable Intake and BMI: Findings in Mississippi Are Not Consistent with Those at the National Level

Sixty percent of Americans have at least one chronic disease that is both diet-related and preventable. Those living in rural areas often experience a greater burden of disease than those who live near a city center. The purpose of this study is to determine the influence of rurality on fruit and vegetable (FV) consumption and BMI. Additionally, the study compares national results to those in Mississippi, a state with an aging population, and high rates of poverty, rurality, poor diet, and obesity. Data utilized were from the 2017 Behavioral Risk Factor Surveillance System. One-way analyses of covariance were performed to determine impact of rurality on nutritional intake and BMI, while controlling for age, income, education, race, and the presence of children in the home. At the national level, rurality had a significant impact on BMI, and the daily intake of fruit juice, fruits, dark green vegetables, French fries, potatoes, other vegetables, and total daily vegetable intake. BMI and nutritional intake of those living in Mississippi was significantly poorer than those living in other states. More research is needed to determine how to best facilitate access to healthy FVs for those living in rural communities.

A life course perspective on BMI in rural America

Rural Americans are substantially more likely to be obese than their urban counterparts. A life course perspective offers insights into how growing up in rural areas may affect weight in young adulthood. Using data from the Panel Survey of Income Dynamics, this study follows the residential trajectories of 3157 respondents since birth. Living in a rural area during the critical period of early childhood (before age two) is predictive of higher BMI, while residence in later childhood and adolescence is not. Improving the health and wellbeing of rural mothers and infants could potentially help address the roots of rural obesity.

Prevalence of obesity and associated cardiovascular risk factors in the Spanish population: the ENPE study

INTRODUCTION AND OBJECTIVES

Obesity is a significant public health problem associated with an increased risk of cardiovascular risk factors (CVRF). The aim of this study was to determine the prevalence of overweight and abdominal obesity (AO) in the Spanish population aged ≥ 3 years and to analyze the influence of sociodemographic and lifestyle factors and their association with CVRF.

METHODS

The sample was drawn from the ENPE study (n=6800). The study protocol included individual anthropometric measurements, sociodemographic factors, food intake (food frequency questionnaire), physical activity, lifestyles, and health problems.

RESULTS

The estimated overall prevalence of obesity (22.0%; 95%CI, 21.0-23.0) and AO (64.7%; 95%CI, 63.5-65.8) was higher in men, in persons aged ≥ 65 years, and in those with a lower socioeconomic level or from southern regions. Lifestyle pattern was significantly associated with obesity and AO (P=.011), which were less likely in people with an active lifestyle pattern (P <.0001). Obesity (OR, 1.85; 95%CI, 1.24-2.78) and AO (OR, 2.16; 95%CI, 1.1-4.24) were positively associated with CVRF. Clustering of CVRF with obesity and/or AO was higher in women (12.6%; 95%CI, 11.4-13.9) and in persons aged ≥ 65 years (32.7%; 95%CI, 30.0-35.4).

CONCLUSIONS

The prevalence of obesity and AO in the Spanish population is high; it is higher in men, increases with age, and is inversely related to socioeconomic status. A lifestyle pattern combining a higher level of physical activity, moderate sedentariness and a Mediterranean dietary pattern is associated with a lower probability of obesity, AO, and CVRF.

Trends of biomarkers of cardiovascular disease in the United States by income: Disparities between the richest 20% and the poorest 80%,1999-2018

INTRODUCTION

Income inequality between the richest 20% and the poorest 80% in the United States has been increasing over the past two decades. Emerging evidence indicates widening disparities between the two groups in cardiovascular disease prevalence as well. However, the mechanisms behind this trend remains unclear. This analysis examines whether a similar trend exists in the levels of biomarkers and risk factors of cardiovascular disease in the United States.

METHODS

We conducted a serial cross-sectional analysis of a nationally representative data from the National Health and Nutrition Examination Survey (NHANES) for participants age 20 or older between 1999 and 2018. We calculated trends in age-standardized means of body mass index (BMI), systolic blood pressure (SBP), and high-density lipoproteins (HDL) and the trend in prevalence of obesity, high SBP, and low HDL by income group.

RESULTS

This analysis included 49,764 participants. Age-standardized mean BMI increased every two years by an average of 0.15 kg/m 2 among the richest 20% and by an average of 0.21 kg/m 2 among the poorest 80%. Age-standardized mean SBP decreased every two years by an average of 0.13 mm Hg among the richest 20% and by an average of 0.10 mm Hg among the poorest 80%. Age-standardized mean HDL increased every two years by an average of 0.39 mg/dL among the richest 20% and by an average of 0.19 mg/dL among the poorest 80%. When adjusted for demographic factors and time, the richest 20% had lower mean BMI (OR = -0.67, 95% CI: -0.89, - 0.44), lower mean SBP (OR = -0.72, 95% CI: -1.24, -0.20), and higher mean HDL (OR = 3.04, 95% CI: 2.46, 3.62) compared to the poorest 80.

CONCLUSION

There are increasing disparities in cardiovascular disease biomarkers by income in the US. Between 1999 and 2018, improvement in biomarkers overwhelmingly occurred among the richest 20.

Nutrition Interventions in Low-Income Rural and Urban Retail Environments: A Systematic Review

BACKGROUND

Nutrition interventions promoting healthy food choices aim to address health challenges of residents in low-income environments. Research about the effectiveness of nutrition interventions in low-income populations is limited, particularly for those in rural areas. Behavioral economics (BE) strategies demonstrate effectiveness for improving eating behaviors in some settings. However, the efficacy of BE interventions in retail food stores serving low-income populations residing in rural and urban geographies is nascent.

OBJECTIVE

This systematic literature review aims to identify and compare nutrition interventions implemented in rural and urban low-income retail food stores, including BE strategies when applied.

METHODS

This review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Reviewers searched five databases for peer-reviewed publications from October 2010 to October 2019. Included studies implemented a nutrition intervention in low-income retail food stores and provided a quantitative outcome evaluation with results separated by rural and urban geography. BE interventions were analyzed based on the MINDSPACE framework for behavior change.

RESULTS

Forty-six separate publications (n = 20 rural, n = 26 urban) in the United States, Canada, Europe, New Zealand, and Australia were included. Researchers independently rated publications as low risk of bias (n = 4), moderate (n = 18), or high risk of bias (n = 24) using the Quality Assessment Tool for Quantitative Studies. Studies (n = 18) demonstrated positive outcomes for customer purchases, store sales, or participant intake of targeted healthy foods. Overall, most effective interventions included point-of-purchase signage (n = 16) and product placement strategies (n = 4 urban). Rural studies included financial incentives combined with participant education (n = 2) and incorporated culturally appropriate messengers and/or symbols (n = 5) to improve healthy food purchases and intake.

CONCLUSIONS

Improved research quality and tailored evidence-based interventions, including BE strategies, are necessary in retail food environments to promote healthy eating behaviors in low-income populations.

Rural-urban health disparities for mood disorders and obesity in a midwestern community

INTRODUCTION

Prior studies indicate greater disease burden for obesity among rural compared with urban residents but no differences for mood disorder based on geographic location. Recent attention has focused on the need to examine regional rural-urban disparities in disease burden. We focused on mood disorders and obesity prevalence within three southeastern Minnesota counties served by the Mayo Clinic Center for Translational Science Award, in Rochester, Minnesota, as these were top priorities identified in community health needs assessments.

METHODS

Cross-sectional study to assess the association of rural-urban locality on 5-year (2009-2014) prevalence of mood disorder and obesity obtained using the Rochester Epidemiological Project medical records linkage system, among subjects residing in three mixed rural-urban counties on April 1, 2014. Multivariable analyses adjusted for demographics, socioeconomic status using an individual housing-based measure, and counties.

RESULTS

The study cohort (percent rural location) included 91,202 (15%) for Olmsted, 10,197 (51%) in Dodge, and 10,184 (57%) in Wabasha counties. On multivariate analysis, 5-year prevalence of mood disorders and obesity was significantly greater for urban compared with rural residents, after adjusting for confounders; odds ratios (95% confidence intervals): 1.21 (1.17-1.26), P < 0.001, and 1.05 (1.01-1.10), P = 0.016, respectively. Observed effects were not modified in additional models adjusted for health care utilization (HCU; ≥1 general medical examination visit and flu vaccination).

CONCLUSIONS

Rural-urban health disparities for burden of mood disorders and obesity are independent of socioeconomic status and HCU in a Midwestern community. It is important to assess potential regional heterogeneity of rural-urban disparities on health outcomes.

Knowledge Visualizations to Inform Decision Making for Improving Food Accessibility and Reducing Obesity Rates in the United States

The aim of this article is to promote the use of knowledge visualization frameworks in the creation and transfer of complex public health knowledge. The accessibility to healthy food items is an example of complex public health knowledge. The United States Department of Agriculture Food Access Research Atlas (FARA) dataset contains 147 variables for 72,864 census tracts and includes 16 food accessibility variables with binary values (0 or 1). Using four-digit and 16-digit binary patterns, we have developed data analytical procedures to group the 72,684 U.S. census tracts into eight and forty groups respectively. This value-added FARA dataset facilitated the design and production of interactive knowledge visualizations that have a collective purpose of knowledge transfer and specific functions including new insights on food accessibility and obesity rates in the United States. The knowledge visualizations of the binary patterns could serve as an integrated explanation and prediction system to help answer why and what-if questions on food accessibility, nutritional inequality and nutrition therapy for diabetic care at varying geographic units. In conclusion, the approach of knowledge visualizations could inform coordinated multi-level decision making for improving food accessibility and reducing chronic diseases in locations defined by patterns of food access measures.

Evaluating Ten Top Tips (10TT): Brief Dietary and Physical Activity Counseling in Rural Overweight and Obese Adults

Adults living in rural areas are at greater risk of becoming overweight and obese due to health care disparities. A pre-/postmatched cohort design was used to evaluate a brief weight-loss counseling intervention, Ten Top Tips (10TT), in a rural primary care setting. The rank sum scores for total weight-loss behaviors and the subscales for dietary changes, self-monitoring, physical activity, and psychological coping taken before and 12 weeks after the intervention differed significantly (P = .0001). Ten Top Tips offers rural community clinics an effective weight-loss intervention.

Obesity among U.S. rural adults: Assessing selection and causation with prospective cohort data

Rural adults in the U.S. have disproportionately high rates of obesity, but it is unclear whether this association exists because of selective migration or a contextual effect of the rural environment. Using nationally representative longitudinal data, this study investigates: (1) whether people with obesity select into rural counties, and (2) whether living in a rural area increases body weight after accounting for selection bias. Results indicate that people with obesity are less likely to move to a different county than people without obesity even after controlling for individual and household differences. Next, individual fixed effects regression models, which implicitly control for all time-constant variables, are used to produce a more robust estimate of the effect of rural residence on body weight. Rural residence predicts a significant increase in probability of obesity and body mass index. These results suggest that the association between rural residence and obesity in the United States is likely bidirectional.

The moderating role of race/ethnicity and nativity in the relationship between perceived discrimination and overweight and obesity: results from the National Epidemiologic Survey on Alcohol and Related Conditions

BACKGROUND

The overweight/obesity epidemic is a public health issue in the United States (US), that disproportionately affect certain racial/ethnic minority groups. Perceived discrimination has been implicated as a health risk factor. However, research on race/ethnicity, perceived discrimination, and obesity has been mixed. Researchers suggest that perceptions of discrimination may be dependent upon nativity status. This study evaluated the role that nativity status and race/ethnicity play in the relationship between perceived discrimination and overweight/obesity.

METHODS

We used Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (2004-2005) [N = 33,319]). Multinomial logistic regression assessed a three-way interaction (perceived discrimination × race/ethnicity × nativity) on overweight and obesity, adjusting for sociodemographic factors and health-related behaviors.

RESULTS

The three-way interaction was significant for overweight [F (17, 49) = 3.35; p < 0.001] and obesity [F (17, 49) = 5.05; p < 0.001]. Among US-born individuals, US-born non-Hispanic Blacks had a decreased risk of being obese compared to US-born non-Hispanic Whites at mean levels of perceived discrimination [aRRR = 0.71; 95% CI (0.51-0.98); p = 0.04). Among foreign-born individuals, foreign-born South Americans had an increased risk of being overweight at mean levels of perceived discrimination compared to foreign-born non-Hispanic Whites [aRRR = 8.07; 95% CI (1.68-38.77); p = 0.01], whereas foreign-born Dominicans had a decreased risk of being obese compared to foreign-born non-Hispanic Whites [aRRR = 0.05; 95% CI (0.01-0.20); p < 0.001].

CONCLUSION

Perceived racial discrimination is a risk factor for overweight/obesity for certain groups. Race/ethnicity and nativity may play important roles in the relationship between perceived discrimination and overweight/obesity. Future research is needed to identify the behavioral and psychological pathways that link perceived discrimination and overweight/obesity.

Translating Urban Walkability Initiatives for Older Adults in Rural and Under-Resourced Communities

The built environment can promote physical activity in older adults by increasing neighborhood walkability. While efforts to increase walkability are common in urban communities, there is limited data related to effective implementation in rural communities. This is problematic, as older adults make up a significant portion of rural inhabitants and exhibit lower levels of physical activity. Translating lessons from urban strategies may be necessary to address this disparity. This review examines best practices from urban initiatives that can be implemented in rural, resource-limited communities. The review of the literature revealed that simple, built environment approaches to increase walkability include microscale and pop-up infrastructure, municipal parks, and community gardens, which can also increase physical activity in neighborhoods for urban older adults. These simple and cost-effective strategies suggest great potential for rural communities.

Distance to Specialist Medical Care and Diagnosis of Obstructive Sleep Apnea in Rural Saskatchewan

Obstructive sleep apnea (OSA) is the most common sleep-disordered breathing condition. Patients with OSA symptoms are often not diagnosed clinically, which is a concern, given the health and safety risks associated with unmanaged OSA. The availability of fewer practicing medical specialists combined with longer travel distances to access health care services results in barriers to diagnosis and treatment in rural communities. This study aimed to (1) determine whether the proportion of adults reporting OSA symptoms in the absence of a sleep apnea diagnosis in rural populations varied by travel distance to specialist medical care and (2) assess whether any distance-related patterns were attributable to differences in the frequency of diagnosis among adults who likely required this specialist medical care. We used a cross-sectional epidemiologic study design, augmented by analysis of follow-up survey data. Our study base included adults who completed a 2010 baseline questionnaire for the Saskatchewan Rural Health Study. Follow-up occurred until 2015. 6525 adults from 3731 households constituted our sample. Statistical models used log-binomial regression. Rural adults who reported the largest travel distances (≥250 km) to specialist medical care were 1.17 (95% CI: 1.07, 1.29) times more likely to report OSA symptoms in the absence of a sleep apnea diagnosis than those who reported the smallest (<100 km; referent) distances. However, the proportion of sleep apnea diagnoses was low and unaffected by reported travel distance among adults who likely required this specialist medical care. Our findings suggest factors other than travel distance may be contributing to the low sleep apnea diagnostic rate. This remains important as undiagnosed and untreated OSA has serious implications on the health of people and populations, but effective treatments are available. Health care access barriers to the diagnosis and treatment of OSA require evaluation to inform health care planning and delivery.

Depression and obesity, data from a national administrative database study: Geographic evidence for an epidemiological overlap

Background

Depression and obesity are two major conditions with both psychological and somatic burdens. Some data suggest strong connections between depression and obesity and more particularly associated prevalence of both disorders. However, little is known about the geographical distribution of these two diseases. This study aimed to determine if there is spatial overlap between obesity and depression using data from the entire French territory.

Methods

Data for 5,627 geographic codes for metropolitan France were collected from the two national hospital databases (PMSI-MCO and RIM-P) for the year 2016. We identified people who were depressed, obese or both registered in the two public medico-administrative databases, and we assessed their location. In addition, a multivariable analysis was performed in order to determine geographic interactions between obesity and depression after controlling for age, sex, environmental and socio-economic factors (social/material deprivation, urbanicity/rurality).

Results

1,045,682 people aged 18 years and older were identified. The mapping analysis showed several cold and hot regional clusters of coinciding obesity and depression. The multivariable analysis demonstrated significant geographic interactions, with an increasing probability of finding a high prevalence of obesity in regions with major depression (OR 1.29 95% CI 1.13–1.49, p = 0.0002) and an increased probability of finding a high prevalence of depression in regions with a high ration of obesity (OR 1.32, 95% CI 1.15–1.52, p<0.0001).

Conclusion

Our study confirms the significant bidirectional relationships between obesity and depression at a group level. French geographic patterns reveal a partial overlap between obesity and depression, suggesting these two diseases can be included in a common approach. Further studies should be done to increase the understanding of this complex comorbidity.

Design of the Rural LEAP randomized trial: An evaluation of extended-care programs for weight management delivered via group or individual telephone counseling

Obesity is a major contributor to the greater prevalence of chronic disease morbidity and mortality observed in rural versus nonrural areas of the U.S. Nonetheless, little research attention has been given to modifying this important driver of rural/urban disparities in health outcomes. Although lifestyle treatments produce weight reductions of sufficient magnitude to improve health, the existing research is limited with respect to the long-term maintenance of treatment effects and the dissemination of services to underserved populations. Recent studies have demonstrated the feasibility of delivering lifestyle programs through the infrastructure of the U.S. Cooperative Extension Service (CES), which has >2900 offices nationwide and whose mission includes nutrition education and health promotion. In addition, several randomized trials have shown that supplementing lifestyle treatment with extended-care programs consisting of either face-to-face sessions or individual telephone counseling can improve the maintenance of weight loss. However, both options entail relatively high costs that inhibit adoption in rural communities. The delivery of extended care via group-based telephone intervention may represent a promising, cost-effective alternative that is well suited to rural residents who tend to be isolated, have heightened concerns about privacy, and report lower quality of life. The Rural Lifestyle Eating and Activity Program (Rural LEAP) is a randomized trial, conducted via CES offices in rural communities, targeted to adults with obesity (n = 528), and designed to evaluate the effectiveness and cost-effectiveness of extended-care programs delivered via group or individual telephone counseling compared to an education control condition on long-term changes in body weight.

Geographical variation of overweight, obesity and related risk factors: Findings from the European Health Examination Survey in Luxembourg, 2013-2015

The analyses of geographic variations in the prevalence of major chronic conditions, such as overweight and obesity, are an important public health tool to identify “hot spots” and inform allocation of funding for policy and health promotion campaigns, yet rarely performed. Here we aimed at exploring, for the first time in Luxembourg, potential geographic patterns in overweight/obesity prevalence in the country, adjusted for several demographic, socioeconomic, behavioural and health status characteristics. Data came from 720 men and 764 women, 25–64 years old, who participated in the European Health Examination Survey in Luxembourg (2013–2015). To investigate the geographical variation, geo-additive semi-parametric mixed model and Bayesian modelisations based on Markov Chain Monte Carlo techniques for inference were performed. Large disparities in the prevalence of overweight and obesity were found between municipalities, with the highest rates of obesity found in 3 municipalities located in the South-West of the country. Bayesian approach also underlined a nonlinear effect of age on overweight and obesity in both genders (significant in men) and highlighted the following risk factors: 1. country of birth for overweight in men born in a non-European country (Posterior Odds Ratio (POR): 3.24 [1.61–8.69]) and women born in Portugal (POR: 2.44 [1.25–4.43]), 2. low educational level (secondary or below) for overweight (POR: 1.66 (1.06–2.72)] and obesity (POR:2.09 [1.05–3.65]) in men, 3. single marital status for obesity in women (POR: 2.20 [1.24–3.91]), 4.fair (men: POR: 3.19 [1.58–6.79], women: POR: 2.24 [1.33–3.73]) to very bad health perception (men: POR: 15.01 [2.16–98.09]) for obesity, 5. sleeping more than 6 hours for obesity in unemployed men (POR: 3.66 [2.02–8.03]). Protective factors highlighted were: 1. single marital status against overweight (POR: [0.60 (0.38–0.96)]) and obesity (POR: 0.39 [0.16–0.84]) in men, 2. the fact to be widowed against overweight in women (POR: [0.30 (0.07–0.86)], as well as a non European country of birth (POR: 0.49 [0.19–0.98]), tertiary level of education (POR: 0.34 [0.18–0.64]), moderate alcohol consumption (POR: 0.54 [0.36–0.90]) and aerobic physical activity practice (POR: 0.44 [0.27–0.77]) against obesity in women. A double burden of environmental exposure due to historic mining and industrial activities and past economic vulnaribility in the South-West of the country may have participated to the higher prevalence of obesity found in this region. Other demographic, socioeconomic, behavioural and health status covariates could have been involved as well.

Secular Trends in Dementia and Cognitive Impairment of U.S. Rural and Urban Older Adults

INTRODUCTION

This is a nationally representative study of rural-urban disparities in the prevalence of probable dementia and cognitive impairment without dementia (CIND).

METHODS

Data on non-institutionalized U.S. adults from the 2000 (n=16,386) and 2010 (n=16,311) cross-sections of the Health and Retirement Study were linked to respective Census assessments of the urban composition of residential census tracts. Relative risk ratios (RRR) for rural-urban differentials in dementia and CIND respective to normal cognitive status were assessed using multinomial logistic regression. Analyses were conducted in 2016.

RESULTS

Unadjusted prevalence of dementia and CIND in rural and urban tracts converged so that rural disadvantages in the relative risk of dementia (RRR=1.42, 95% CI=1.10, 1.83) and CIND (RRR=1.35, 95% CI=1.13, 1.61) in 2000 no longer reached statistical significance in 2010. Adjustment for the strong protective role of educational attainment reduced rural disadvantages in 2000 to statistical nonsignificance, whereas adjustment for race/ethnicity resulted in a statistically significant increase in RRRs in 2010. Full adjustment for sociodemographic and health factors revealed persisting rural disadvantages for dementia and CIND in both periods with RRR in 2010 for dementia of 1.79 (95% CI=1.31, 2.43) and for CIND of 1.38 (95% CI=1.14, 1.68).

CONCLUSIONS

Larger gains in rural adults' cognitive functioning between 2000 and 2010 that are linked with increased educational attainment demonstrate long-term public health benefits of investment in secondary education. Persistent disadvantages in cognitive functioning among rural adults compared with sociodemographically similar urban peers highlight the importance of public health planning for more rapidly aging rural communities.