Regional disparities in obesity prevalence in the United States: A spatial regime analysis

Unearthing Inequities in the Relationship between Multiple Sociodemographic Factors and Diverse Elements of Park Availability and Quality in a Major Southern Metropolitan Region

Parks are critical components of healthy communities. This study explored neighborhood socioeconomic and racial/ethnic inequalities in park access and quality in a large U.S. southeastern metropolitan region. A total of 241 block groups were examined, including 77 parks. For each block group, we obtained multiple sociodemographic indicators, including unemployment rate, education level, renter-occupied housing, poverty rate, and racial/ethnic minority composition. All parks were mapped using geographical information systems and audited via the Community Park Audit Tool to evaluate their features and quality. We analyzed seven diverse elements of park quality (transportation access, facility availability, facility quality, amenity availability, park aesthetics, park quality concerns, and neighborhood quality concerns), as well as an overall park quality score by calculating the mean for all parks within each block group. The mean percent of residents below 125% of the poverty level and the percentage of renter-occupied housing units were significantly higher among block groups with any parks in comparison to block groups with no parks. In addition, there were significant positive associations between park transportation access scores and both the percentage of residents with less than high school education and the percent identifying as non-Hispanic white. Moreover, there was a significant negative association between park amenity availability and the block group's unemployed population. Further, a significant negative association between park aesthetics and the population with a lower than high school education percentage was observed. Revealed differences in park availability, park acreage, and park quality dimensions emphasized the need for targeted policy, programmatic, and infrastructure interventions to improve park access and quality and address health disparities.

Longitudinal Study of Comorbidities and Clinical Outcomes in Persons with Gallstone Disease Using Electronic Health Records

BACKGROUND

Gallstone disease (GSD) is common and leads to significant morbidity, mortality, and health care utilization in the USA. We examined comorbidities and clinical outcomes among persons with GSD using electronic health records (EHR).

METHODS

In this retrospective study of 1,381,004 adults, GSD was defined by ICD-9 code 574 or ICD-10 code K80 using Optum® longitudinal EHR from January 2007 to March 2021. We obtained diagnosis, procedure, prescription, and vital sign records and evaluated associations between demographics, comorbidities, and medications with cholecystectomy, digestive cancers, and mortality.

RESULTS

Among persons with GSD, 30% had a cholecystectomy and were more likely to be women, White, and younger, and less likely to have comorbidities, except for obesity, gastroesophageal reflux disease (GERD), abdominal pain, hyperlipidemia, and pancreatitis. Among persons with GSD, 2.2% had a non-colorectal digestive cancer diagnosis during follow-up and risk was 40% lower among persons with a cholecystectomy. Non-colorectal digestive cancer predictors included older age, male sex, non-White race-ethnicity, lower BMI, other cancers, diabetes, chronic liver disease, pancreatitis, GERD, and abdominal pain. Among persons with GSD, mortality was 15.1% compared with 9.7% for the whole EHR sample. Persons with a cholecystectomy had 40% lower mortality risk and mortality predictors included older age, male sex, Black race, lower BMI, and most comorbidities.

CONCLUSIONS

In this EHR analysis of persons with GSD, 30% had a cholecystectomy. Mortality was higher compared with the whole EHR sample. Persons with cholecystectomy were less likely to have non-colorectal digestive cancer or to die.

An interpretable machine learning model of cross-sectional U.S. county-level obesity prevalence using explainable artificial intelligence

BACKGROUND

There is considerable geographic heterogeneity in obesity prevalence across counties in the United States. Machine learning algorithms accurately predict geographic variation in obesity prevalence, but the models are often uninterpretable and viewed as a black-box.

OBJECTIVE

The goal of this study is to extract knowledge from machine learning models for county-level variation in obesity prevalence.

METHODS

This study shows the application of explainable artificial intelligence methods to machine learning models of cross-sectional obesity prevalence data collected from 3,142 counties in the United States. County-level features from 7 broad categories: health outcomes, health behaviors, clinical care, social and economic factors, physical environment, demographics, and severe housing conditions. Explainable methods applied to random forest prediction models include feature importance, accumulated local effects, global surrogate decision tree, and local interpretable model-agnostic explanations.

RESULTS

The results show that machine learning models explained 79% of the variance in obesity prevalence, with physical inactivity, diabetes, and smoking prevalence being the most important factors in predicting obesity prevalence.

CONCLUSIONS

Interpretable machine learning models of health behaviors and outcomes provide substantial insight into obesity prevalence variation across counties in the United States.

Changes of Grocery Shopping Frequencies and Associations with Food Deserts during the COVID-19 Pandemic in the United States

The COVID-19 pandemic has dramatically altered people's lives in multiple aspects, including grocery shopping behaviors. Yet, the changing trend of grocery shopping frequencies during the COVID-19 and its associations with food deserts remain unclear. We aimed to (1) examine variations of grocery shopping frequencies at county level in the USA during the COVID-19 pandemic from March 2020 to December 2021; (2) investigate associations between grocery shopping frequencies and food deserts during the COVID-19 pandemic; and (3) explore heterogeneity in grocery shopping frequencies-food desert associations across urban and rural areas. The county-level grocery shopping frequencies were derived from a grocery pattern dataset obtained from SafeGraph. We divided the 22-month period into 5 stages and employed the growth curve modeling to estimate the trajectories of grocery shopping frequencies and the associations between grocery shopping frequencies and food deserts in each stage, separately. Results revealed that grocery shopping frequencies experienced a "W-shaped" pattern from March 2020 to December 2021. Counties with the least percent of food deserts had slower decrease in grocery shopping frequencies at the initial stage and recovered more rapidly at later stages. Counties with the highest percent of food deserts were subject to deprivation amplification as a result of the pandemic. We also found differences existed in the grocery shopping frequencies-food desert associations between metropolitan counties and rural counties. Our findings suggest the impacts of COVID-19 on grocery shopping frequencies varied across different time periods, shedding light on designing different strategies to reduce the risk of contagion while shopping inside of grocery stores. Further, our findings highlight an urgent need to help people living in food deserts (especially in rural counties) to procure healthy foods safely during health emergencies like COVID-19 pandemic which disrupt mobility and social behaviors.

Referent Values for Commonly Used Clinical Mobility Tests in Black and White Adults Aged 50-95 Years

OBJECTIVE

To estimate referent values for performance on clinical mobility tests conducted amongst racially diverse adults aged 50-95 years in the Southeast US.

DESIGN

This is an observational study of community-dwelling older adults from diverse racial groups who participated in observational and rehabilitative studies conducted from 2011-2019.

SETTING

Rehabilitation clinics around the greater metropolitan Atlanta, Georgia, region.

PARTICIPANTS

A total of 314 adults (N=314; 222 women). Individuals were predominantly Black (n=121) or White (n=164), with some participants from other racial groups (n=29).

INTERVENTIONS

Clinical and demographic data were collected at individual visits for each participant.

MAIN OUTCOME MEASURES

Four Square Step Test (FSST), timed Up and Go (TUG) test, dual TUG test, 6-minute walk test (6MWT), 30-second chair stand, and gait speed were all used as assessments in each cohort.

RESULTS

Performance slowly declines with increasing age, with a sharp drop in the ninth decade for preferred forward, backward, and fast gait speed; backward gait cadence; 6MWT, TUG test, dual-task TUG-Cognitive, and the 360° turn test. Declines were also seen in the eighth and ninth decades in the FSST. Among White participants, there were significant overall differences across age groups except in the assessment variable, preferred gait cadence. For Black individuals, there were significant overall differences across age groups for backward gait speed, fast gait speed, TUG-Cognitive, dual task, 6MWT, FSST, and 30-second chair stand.

CONCLUSIONS

These data enrich current referent values for brief, commonly used clinical tests in a diverse, older Southeast US cohort. These data include representatives of the oldest old cohort. This study will support race- and age-specific fall prevention and mobility-enhancing therapeutic application among older patients in clinical practice.

Associations of longitudinal BMI percentile classification patterns in early childhood with neighborhood-level social determinants of health

Background

Understanding social determinants of health (SDOH) that may be risk factors for childhood obesity is important to developing targeted interventions to prevent obesity. Prior studies have examined these risk factors, mostly examining obesity as a static outcome variable.

Objectives

This study aimed to identify distinct subpopulations based on BMI percentile classification or changes in BMI percentile classifications over time and explore these longitudinal associations with neighborhood-level SDOH factors in children from 0 to 7 years of age.

Methods

Using Latent Class Growth (Mixture) Modelling (LCGMM) we identify distinct BMI% classification groups in children from 0 to 7 years of age. We used multinomial logistic regression to study associations between SDOH factors with each BMI% classification group.

Results

From the study cohort of 36,910 children, five distinct BMI% classification groups emerged: always having obesity (n=429; 1.16%), overweight most of the time (n=15,006; 40.65%), increasing BMI% (n=9,060; 24.54%), decreasing BMI% (n=5,058; 13.70%), and always normal weight (n=7,357; 19.89%). Compared to children in the decreasing BMI% and always normal weight groups, children in the other three groups were more likely to live in neighborhoods with higher rates of poverty, unemployment, crowded households, and single-parent households, and lower rates of preschool enrollment.

Conclusions

Neighborhood-level SDOH factors have significant associations with children's BMI% classification and changes in classification over time. This highlights the need to develop tailored obesity interventions for different groups to address the barriers faced by communities that can impact the weight and health of the children living within them.

Outdoor air pollution and histologic composition of normal breast tissue

BACKGROUND

Biologic pathways underlying the association between outdoor air pollution and breast cancer risk are poorly understood. Breast tissue composition may reflect cumulative exposure to breast cancer risk factors and has been associated with breast cancer risk among patients with benign breast disease. Herein, we evaluated whether fine particulate matter (PM_2.5) was associated with the histologic composition of normal breast tissue.

METHODS

Machine-learning algorithms were applied to digitized hematoxylin and eosin-stained biopsies of normal breast tissue to quantify the epithelium, stroma, adipose and total tissue area from 3,977 individuals aged 18-75 years from a primarily Midwestern United States population who donated breast tissue samples to the Susan G. Komen Tissue Bank (2009-2019). Annual levels of PM_2.5 were assigned to each woman's residential address based on year of tissue donation. We applied predictive k-means to assign participants to clusters with similar PM_2.5 chemical composition and used linear regression to examine the cross-sectional associations between a 5-μg/m³ increase in PM_2.5 and square root-transformed proportions of epithelium, stroma, adipose, and epithelium-to-stroma proportion [ESP], overall and by PM_2.5 cluster.

RESULTS

Higher residential PM_2.5 was associated with lower proportion of breast stromal tissue [β = -0.93, 95% confidence interval: (-1.52, -0.33)], but was not related to the proportion of epithelium [β = -0.11 (-0.34, 0.11)]. Although PM_2.5 was not associated with ESP overall [β = 0.24 (-0.16, 0.64)], the association significantly differed by PM_2.5 chemical composition (p-interaction = 0.04), with a positive association evident only among an urban, Midwestern cluster with higher concentrations of nitrate (NO₃^-) and ammonium (NH₄⁺) [β = 0.49 (0.03, 0.95)].

CONCLUSIONS

Our findings are consistent with a possible role of PM_2.5 in breast cancer etiology and suggest that changes in breast tissue composition may be a potential pathway by which outdoor air pollution impacts breast cancer risk. This study further underscores the importance of considering heterogeneity in PM_2.5 composition and its impact on breast carcinogenesis.

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.

Regional differences in intercohort and intracohort trends in obesity in the USA: evidence from the National Health Interview Survey, 1982-2018

OBJECTIVES

Obesity in the USA is more prevalent in younger cohorts than older cohorts and also more prevalent in the South and the Midwest than other regions. However, little research has examined the intersection of cohort patterns and regional differences in obesity. We address the knowledge gap by investigating net of age and period trends, how intercohort and intracohort patterns in obesity may depend on Census regions for black and white men and women.

DESIGN, SETTING AND PARTICIPANTS

A total of 1 020 412 non-Hispanic black and white respondents aged 20-69 were included from the 1982-2018 National Health Interview Survey.

OUTCOME MEASURES

Obesity is defined as body mass index ≥30 kg/m² based on participant self-reported weight and height. Obesity ORs were calculated to estimate region-specific age, period and cohort patterns for each demographic group.

RESULTS

Although age and period trends in obesity were similar across regions for all demographic groups, cohort patterns depended on region of residence for white women. Specifically, for the white women cohorts born in 1955 or later, living in the South and the Midwest implied higher likelihood of obesity than their peers in other regions even after accounting for average regional differences. These cohorts' disadvantage seemed to persist and/or accumulate over the life course. Socioeconomic factors explained little average regional differences or region-specific cohort variation.

CONCLUSIONS

Our findings highlight the interdependence of the temporal and geographical processes in shaping obesity disparities.

Evaluation of Regional Geospatial Clusters in Inguinal Hernia Repair

Introduction

There is significant variation in how inguinal hernia repairs are conducted across the United States (US). This study seeks to utilize national public data on inguinal hernia repair to determine regional differences in the use of ambulatory surgical centers (ASC) and in the choice of laparoscopic or open technique.

Methods

Medicare provider billing and enrollee demographic data were merged with US census and economic data to create a county-level database for the years 2014-2019. Location, technique, and total count of all inguinal hernia repair billing were recorded for 1286 counties. Moran’s I cluster analysis for inguinal hernia repairs, percent laparoscopic technique, and percent ACS were conducted. Subsequent hotspot and coldspot clusters identified in geospatial analysis were compared using ANOVA across 50 socioeconomic variables with a significance threshold of 0.001. 

Results 

There were 292,870 inguinal hernia repairs, of which 39.8% were conducted laparoscopically and 21.3% of which were in an ACS. Inguinal hernia repair coldspots were in the Mid-Atlantic and Northern Midwest, while hotspots were in Nebraska, Kansas, and Maryland (3.85 and 36.53 repairs per 1000 beneficiaries, respectively). Compared to coldspots, hotspot areas of repair were less obese, had less tobacco use, older, and less insured; there were no differences in gender, white population, or county urbanization (p<0.001). Laparoscopic technique coldspots were in the Mid-Atlantic, Michigan, and Great Plains, while hotspots were in the Rocky Mountains and contiguous states from Florida to Wisconsin (6.14% and 75.39%, respectively). ACS coldspots were diffusely scattered between Oklahoma and New Hampshire, while hotspots were in California, Colorado, Maryland, Tennessee, and Indiana (0.51% and 48.71%, respectively).

Conclusions

Inguinal hernia repair, the surgical setting, and the choice of technique demonstrated interesting geospatial trends in our population of interest that have not been previously characterized.

Estimates of Childhood Overweight and Obesity at the Region, State, and County Levels: A Multilevel Small-Area Estimation Approach

Local-level childhood overweight and obesity data are often used to implement and evaluate community programs, as well as allocate resources to combat overweight and obesity. The most current substate estimates of US childhood obesity use data collected in 2007. Using a spatial multilevel model and the 2016 National Survey of Children's Health, we estimated childhood overweight and obesity prevalence rates at the Census regional division, state, and county levels using small-area estimation with poststratification. A sample of 24,162 children aged 10-17 years was used to estimate a national overweight and obesity rate of 30.7% (95% confidence interval: 27.0%, 34.9%). There was substantial county-to-county variability (range, 7.0% to 80.9%), with 31 out of 3,143 counties having an overweight and obesity rate significantly different from the national rate. Estimates from counties located in the Pacific region had higher uncertainty than other regions, driven by a higher proportion of underrepresented sociodemographic groups. Child-level overweight and obesity was related to race/ethnicity, sex, parental highest education (P < 0.01 for all), county-level walkability (P = 0.03), and urban/rural designation (P = 0.02). Overweight and obesity remains a vital issue for US youth, with substantial area-level variability. The additional uncertainty for underrepresented groups shows surveys need to better target diverse samples.

Spatial clustering patterns and regional variations for food and physical activity environments across the United States

This study examined spatial patterns of obesogenic environments for US counties. We mapped the geographic dispersion of food and physical activity (PA) environments, assessed spatial clustering, and identified food and PA environment differences across U.S. regions and rurality categories. Substantial low food score clusters were located in the South and high score clusters in the Midwest and West. Low PA score clusters were located in the South and high score clusters in the Northeast and Midwest (p < .0001). For region, the South had significantly lower food and PA environment scores. For rurality, rural counties had significantly higher food environment scores and metropolitan counties had significantly higher PA environment scores (p < .0001). This study highlights geographic clustering and disparities in food and PA access nationwide. State and region-wide environmental inequalities may be targeted using structural interventions and policy initiatives to improve food and PA access.

Regional and sociodemographic differences in average BMI among US children in the ECHO program

OBJECTIVE

The aim of this study was to describe the association of individual-level characteristics (sex, race/ethnicity, birth weight, maternal education) with child BMI within each US Census region and variation in child BMI by region.

METHODS

This study used pooled data from 25 prospective cohort studies. Region of residence (Northeast, Midwest, South, West) was based on residential zip codes. Age- and sex-specific BMI z scores were the outcome.

RESULTS

The final sample included 14,313 children with 85,428 BMI measurements, 49% female and 51% non-Hispanic White. Males had a lower average BMI z score compared with females in the Midwest (β = -0.12, 95% CI: -0.19 to -0.05) and West (β = -0.12, 95% CI: -0.20 to -0.04). Compared with non-Hispanic White children, BMI z score was generally higher among children who were Hispanic and Black but not across all regions. Compared with the Northeast, average BMI z score was significantly higher in the Midwest (β = 0.09, 95% CI: 0.05 to 0.14) and lower in the South (β = -0.12, 95% CI: -0.16 to -0.08) and West (β = -0.14, 95% CI: -0.19 to -0.09) after adjustment for age, sex, race/ethnicity, and birth weight.

CONCLUSIONS

Region of residence was associated with child BMI z scores, even after adjustment for sociodemographic characteristics. Understanding regional influences can inform targeted efforts to mitigate BMI-related disparities among children.

Evaluating incidence, prevalence, and treatment trends in adult men with hypogonadism in the United States

No extensive studies have investigated current diagnosis and treatment trends of hypogonadism (HG) in adult men in the United States. Using a comprehensive commercial insurance database, we surveyed current trends in incidence, prevalence, and treatment of hypogonadism in the United States. We analyzed insurance claims data from 2008-2017 using the IBM MarketScan™ Commercial Claims and Encounters database for men ≥18. Overall, we estimated annual incidence at 16.1 cases per 100,000 person-years, with the highest incidence seen among men 35-44 years at 21.5 cases per 100,000 person-years (IRR 1.83; 95% CI 1.63, 2.06, p < 0.001) and among those living in the Southern United States at 22.6 cases per 100,000 person-years (IRR 1.96; 95% CI 1.76, 2.18, p < 0.001). The prevalence of HG across the study period increased from 0.78% to 5.4%, while treatment rates decreased from 32.9% to 20.8%. These study findings provide a large-scale view of current diagnosis rates and treatment of hypogonadism in adult men in the United States. Despite the increase in prevalence of disease, there is an observed decline in treatment rates after diagnosis. Further investigations are needed to identify factors driving the observed decline in healthcare utilization among men with hypogonadism.

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.

Built environment, physical activity, and obesity of adults in Pingshan District, Shenzhen City in Southern China

BACKGROUND

The relation between neighbourhood built environment and obesity has been described as both nuanced and complex.

AIM

The objective of this study was to examine the relationship between the built environment, physical activity, and obesity in a rapidly urbanised area of China.

SUBJECTS AND METHODS

This is a cross-sectional study. Descriptive statistics were used to describe the socio-demographic variables, physical activity levels and BMI status. Multivariable logistic regression models were used to examine the association between neighbourhood environment, the likelihood of engaging in different types of physical activity, and BMI.

RESULTS

A total of 842 respondents completed the questionnaires and were included (84.1% response rate). Among them, 56.4% reported meeting high physical activity levels, while 40.7% were overweight or obese. Multivariable regression analysis showed that better road conditions (β = 0.122, t = 2.999, p = 0.003) and access to physical activity facilities (β = 0.121, t = 3.193, p = 0.001) were significantly associated with higher levels of physical activity. Physical activity levels were inversely associated with the likelihood of being overweight (OR = 0.565, 95%CI: 0.3 4 9-0.917) or obese (OR = 0.614, 95%CI: 0.3 9 0-0.966).

CONCLUSION

The built environment has an important impact on physical activity. However, the direct impact of leisure physical activity on BMI is not significant. This research provides a summary of recent evidence in Pingshan District on built environments that are most favourable for physical activity and obesity.

Has the prevalence of overweight, obesity and central obesity levelled off in the United States? Trends, patterns, disparities, and future projections for the obesity epidemic

BACKGROUND

Obesity (OB) is a serious epidemic in the United States.

METHODS

We examined OB patterns and time trends across socio-economic and geographic parameters and projected the future situation. Large national databases were used. Overweight (OW), OB and severe obesity (SOB) were defined using body mass index cut-points/percentiles; central obesity (CO), waist circumference cut-point in adults and waist:height ratio cutoff in youth. Various meta-regression analysis models were fit for projection analyses.

RESULTS

OB prevalence had consistently risen since 1999 and considerable differences existed across groups and regions. Among adults, men's OB (33.7%) and OW (71.6%) levelled off in 2009-2012, resuming the increase to 38.0 and 74.7% in 2015-2016, respectively. Women showed an uninterrupted increase in OB/OW prevalence since 1999, reaching 41.5% (OB) and 68.9% (OW) in 2015-2016. SOB levelled off in 2013-2016 (men: 5.5-5.6%; women: 9.7-9.5%), after annual increases of 0.2% between 1999 and 2012. Non-Hispanic Blacks had the highest prevalence in women's OB/SOB and men's SOB. OB prevalence in boys rose continuously to 20.6% and SOB to 7.5% in 2015-2016, but not in girls. By 2030, most Americans will be OB/OW and nearly 50% of adults OB, whereas ∼33% of children aged 6-11 and ∼50% of adolescents aged 12-19 will be OB/OW. Since 1999, CO has risen steadily, and by 2030 is projected to reach 55.6% in men, 80.0% in women, 47.6% among girls and 38.9% among boys. Regional differences exist in adult OB prevalence (2011-2016) and across ethnicities; South (32.0%) and Midwest (31.4%) had the highest rates.

CONCLUSIONS

US obesity prevalence has been rising, despite a temporary pause in 2009-2012. Wide disparities across groups and geographical regions persist. Effective, sustainable, culturally-tailored interventions are needed.

The Hispanic paradox in the prevalence of obesity at the county-level

Objective

The percentage of Hispanics in a county has a negative association with prevalence of obesity. Because Hispanic individuals are unevenly distributed in the United States, this study examined whether this protective association persists when stratifying counties into quartiles based on the size of the Hispanic population and after adjusting for county‐level demographic, socioeconomic, healthcare, and environmental factors.

Methods

Data were extracted from the 2018 Robert Wood Johnson Foundation County Health Rankings. Counties were categorized into quartiles based on their percentage of Hispanics, 0%–5% (n = 1794), 5%–20% (n = 962), 20%–50% (n = 283), and >50% (n = 99). For each quartile, univariate and multivariate regression models were used to evaluate the association between prevalence of obesity and demographic, socioeconomic, healthcare, and environmental factors.

Results

Counties with the top quartile of Hispanic individuals had the lowest prevalence of obesity compared to counties at the bottom quartile (28.4 ± 3.6% vs. 32.7 ± 4.0%). There was a negative association between county‐level percentage of Hispanics and prevalence of obesity in unadjusted analyses that persisted after adjusting for all county‐level factors.

Conclusions

Counties with a higher percentage of Hispanics have lower levels of obesity, even after controlling for demographic, socioeconomic, healthcare, and environmental factors. More research is needed to elucidate why having more Hispanics in a county may be protective against county‐level obesity.

Regional Differences in Height, Weight, and Body Composition may Result from Photoperiodic Responses: An Ecological Analysis of Japanese Children and Adolescents

This ecological study examined whether geographical differences in the physique of Japanese children and adolescents can be explained from the perspective of photoperiodicity induced by effective day length (light duration exceeding a certain threshold of illuminance) using prefecture-level anatomical data and Mesh Climatic Data. Multiple regression analysis for height prediction demonstrated that when controlled by weight, effective day lengths of the longest and shortest months were inversely correlated with height distribution. Conversely, for weight prediction, when controlled by height, the effective day lengths of the longest and shortest months were positively correlated with weight distribution. The regression coefficients were greater for the effective day length of the shortest month in both height and weight prediction. This phenomenon where the same two explanatory variables are negatively correlated with height and positively correlated with weight in a significant manner is rare, and there may be no physiological interpretation of this phenomenon other than one based on changes in thyroid hormone signaling. These distribution characteristics are common to the photoperiodicity by which seasonal breeding vertebrates reciprocally switch thyroid hormone signaling according to prior photoperiodic history through epigenetic functions. From these perspectives, thyroid hormone signaling in a certain region was assumed to be activated in summer according to the prior shorter winter day length and inactivated in winter according to the prior longer summer day length. Regarding the prevalence of obesity, the coexistence of longer summer and winter day lengths was thought to set body composition to be short and fat in early adolescence.

Understanding the Heterogeneity of Obesity and the Relationship to the Brain-Gut Axis

Obesity is best understood as a multifactorial metabolic imbalances disorder. In a cross-sectional study, we aimed to explore sociodemographic and dietary determinants of obesity in relation to brain-gut homeostasis among overweight and obese individuals. Multivariate logistic regression models were used to examine obesity and its association with sociodemographic and dietary factors. Biological variables examined included the gut microbiome, fecal amino acid metabolites and brain structural volumes. Among 130 participants, there were higher odds of obesity if individuals were Hispanic (adjusted odds ratio (aOR) 1.56, p = 0.014). Compared to non-Hispanics, Hispanics differed in gut microbial composition (p = 0.046) with lower microbial species richness (Chao1) (p = 0.032) and evenness (Shannon) (p = 0.0029). Fourteen of the twenty fecal amino acids including branch-chain- and aromatic- amino acids were increased among Hispanics (q < 0.05). Brain structural volumes in reward regions were decreased in Hispanics (pallidum, q = 0.036; brainstem, q = 0.011). Correlation patterns suggest complex brain-gut interactions differ by Hispanic ethnicity. In conclusion, Hispanics expressed a unique brain-gut microbial signature, which was associated with obesity despite sociodemographic and dietary differences. Addressing ethnic disparities guided by biologic phenotypes may unlock novel understanding of obesity heterogeneity and treatment strategies.

Sociodemographic Predictors of Adherence to National Diet and Physical Activity Guidelines at Age 5 Years: The Healthy Start Study

PURPOSE

To assess adherence to the 2015-2020 Dietary Guidelines for Americans and 2018 Physical Activity Guidelines, and identify sociodemographic predictors of adherence among children.

DESIGN

Cross sectional.

SETTING

Colorado, United States.

PARTICIPANTS

Children aged 5 (n = 482).

MEASURES

Sex, race/ethnicity, maternal education, maternal employment, maternal subjective social status and household income were assessed via questionnaires. Diet was assessed via 2 interviewer-administered 24-hour dietary recalls. Physical activity was objectively-measured with accelerometry for 7 days. Adherence was defined as a Healthy Eating Index-2015 score of ≥70 and/or ≥6 hours/day of light, moderate and vigorous activity.

ANALYSIS

For each predictor, logistic regression was used to estimate odds ratios for adherence to the diet guidelines only, the activity guidelines only or both guidelines.

RESULTS

In the full sample, 29% of children were non-adherent to both guidelines, 6% adhered to the dietary guidelines only, 50% adhered to the activity guidelines only and 14% adhered to both. Girls had a 41% lower odds of adhering to the physical activity guidelines than boys (p = 0.01), after adjustment for race/ethnicity, household income and maternal education level, perceived social status and employment status.

CONCLUSION

Efforts to improve the health of young children should promote adherence to the Dietary Guidelines for Americans among all children. Targeted interventions that increase physical activity among girls may help to mitigate health disparities.

Sudden Cardiac Death in the Young: Incidence, Trends, and Risk Factors in a Nationwide Study

BACKGROUND

Sudden cardiac death (SCD) in the young is devastating. Contemporary incidence remains unclear with few recent nationwide studies and limited data addressing risk factors for causes. We aimed to determine incidence, trends, causes, and risk factors for SCD in the young.

METHODS AND RESULTS

The National Coronial Information System registry was reviewed for SCD in people aged 1 to 35 years from 2000 to 2016 in Australia. Subjects were identified by the International Classification of Diseases, Tenth Revision code relating to circulatory system diseases (I00-I99) from coronial reports. Baseline demographics, circumstances, and cause of SCD were obtained from coronial and police reports, alongside autopsy and toxicology analyses where available. During the study period, 2006 cases were identified (median age, 28±7 years; men, 75%; mean body mass index, 29±8 kg/m²). Annual incidence ranged from 0.91 to 1.48 per 100 000 age-specific person-years, which was the lowest in 2013 to 2015 compared with previous 3-year intervals on Poisson regression model (P=0.001). SCD incidence was higher in nonmetropolitan versus metropolitan areas (0.99 versus 0.53 per 100 000 person-years; P<0.001). The most common cause of SCD was coronary artery disease (40%), followed by sudden arrhythmic death syndrome (14%). Incidence of coronary artery disease-related SCD decreased from 2001-2003 to 2013-2015 (P<0.001). Proportion of SCD related to sudden arrhythmic death syndrome increased during the study period (P=0.02) although overall incidence was stable (P=0.22). Residential remoteness was associated with coronary artery disease-related SCD (odds ratio, 1.44 [95% CI, 1.24-1.67]; P<0.001). For every 1-unit increase, body mass index was associated with increased likelihood of SCD from cardiomegaly (odds ratio, 1.08 [95% CI, 1.05-1.11]; P<0.001) and dilated cardiomyopathy (odds ratio, 1.04 [95% CI, 1.01-1.06]; P=0.005).

CONCLUSIONS

Incidence of SCD in the young and specifically coronary artery disease-related SCD has declined in recent years. Proportion of SCD related to sudden arrhythmic death syndrome increased over the study period. Geographic remoteness and obesity are risk factors for specific causes of SCD in the young.

A compendium of G-protein-coupled receptors and cyclic nucleotide regulation of adipose tissue metabolism and energy expenditure

With the ever-increasing burden of obesity and Type 2 diabetes, it is generally acknowledged that there remains a need for developing new therapeutics. One potential mechanism to combat obesity is to raise energy expenditure via increasing the amount of uncoupled respiration from the mitochondria-rich brown and beige adipocytes. With the recent appreciation of thermogenic adipocytes in humans, much effort is being made to elucidate the signaling pathways that regulate the browning of adipose tissue. In this review, we focus on the ligand-receptor signaling pathways that influence the cyclic nucleotides, cAMP and cGMP, in adipocytes. We chose to focus on G-protein-coupled receptor (GPCR), guanylyl cyclase and phosphodiesterase regulation of adipocytes because they are the targets of a large proportion of all currently available therapeutics. Furthermore, there is a large overlap in their signaling pathways, as signaling events that raise cAMP or cGMP generally increase adipocyte lipolysis and cause changes that are commonly referred to as browning: increasing mitochondrial biogenesis, uncoupling protein 1 (UCP1) expression and respiration.

Development of a national childhood obesogenic environment index in the United States: differences by region and rurality

Background

Diverse environmental factors are associated with physical activity (PA) and healthy eating (HE) among youth. However, no study has created a comprehensive obesogenic environment index for children that can be applied at a large geographic scale. The purpose of this study was to describe the development of a childhood obesogenic environment index (COEI) at the county level across the United States.

Methods

A comprehensive search of review articles (n = 20) and input from experts (n = 12) were used to identify community-level variables associated with youth PA, HE, or overweight/obesity for potential inclusion in the index. Based on strength of associations in the literature, expert ratings, expertise of team members, and data source availability, 10 key variables were identified – six related to HE (# per 1000 residents for grocery/superstores, farmers markets, fast food restaurants, full-service restaurants, and convenience stores; as well as percentage of births at baby (breastfeeding)-friendly facilities) and four related to PA (percentage of population living close to exercise opportunities, percentage of population < 1 mile from a school, a composite walkability index, and number of violent crimes per 1000 residents). Data for each variable for all counties in the U.S. (n = 3142) were collected from publicly available sources. For each variable, all counties were ranked and assigned percentiles ranging from 0 to 100. Positive environmental variables (e.g., grocery stores, exercise opportunities) were reverse scored such that higher values for all variables indicated a more obesogenic environment. Finally, for each county, a total obesogenic environment index score was generated by calculating the average percentile for all 10 variables.

Results

The average COEI percentile ranged from 24.5–81.0 (M = 50.02,s.d. = 9.01) across US counties and was depicted spatially on a choropleth map. Obesogenic counties were more prevalent (F = 130.43,p < .0001) in the South region of the U.S. (M = 53.0,s.d. = 8.3) compared to the Northeast (M = 43.2,s.d. = 6.9), Midwest (M = 48.1,s.d. = 8.5), and West (M = 48.4,s.d. = 9.8). When examined by rurality, there were also significant differences (F = 175.86,p < .0001) between metropolitan (M = 46.5,s.d. = 8.4), micropolitan (M = 50.3,s.d. = 8.1), and rural counties (M = 52.9,s.d. = 8.8) across the U.S.

Conclusion

The COEI can be applied to benchmark obesogenic environments and identify geographic disparities and intervention targets. Future research can examine associations with obesity and other health outcomes.

Chronic Disease, the Built Environment, and Unequal Health Risks in the 500 Largest U.S. Cities

Health is increasingly subject to the complex interplay between the built environment, population composition, and the structured inequity in access to health-related resources across communities. The primary objective of this paper was to examine cardiometabolic disease (diabetes, cardiovascular diseases, stroke) markers and their prevalence across relatively small geographic units in the 500 largest cities in the United States. Using data from the American Community Survey and the 500 Cities Project, the current study examined cardiometabolic diseases across 27,000+ census tracts in the 500 largest cities in the United States. Earlier works clearly show cardiometabolic diseases are not randomly distributed across the geography of the U.S., but rather concentrated primarily in Southern and Eastern regions of the U.S. Our results confirm that chronic disease is correlated with social and built environment factors. Specifically, racial concentration (%, Black), age concentration (% 65+), housing stock age, median home value, structural inequality (Gini index), and weight status (% overweight/obese) were consistent correlates (p < 0.01) of cardiometabolic diseases in the sample of census tracts. The paper examines policy-related features of the built and social environment and how they might play a role in shaping the health and well-being of America’s metropolises.

Trends of Burn Injury in the United States: 1990 to 2016

OBJECTIVE

The aim of this study is to report patterns of burn injury within the United States from 1990 to 2016 with regard to age, sex, geography, and year.

SUMMARY BACKGROUND DATA

Advances in the management of burn injuries as well as successful public health efforts have contributed to reductions in the annual incidence and mortality of burns. However, several studies suggest that these reductions are not equally distributed throughout the US population.

MAIN OUTCOMES AND MEASURES

The Global Burden of Disease Study 2016 was utilized to collect incidence, mortality, disability-adjusted life years (DALYs), and years lived with disability (YLD) from 1990 to 2016. All measures were computed with 95% uncertainty intervals (UI).

RESULTS

The overall incidence of burn injury in the United States has decreased from 215 (95% UI, 183-246) to 140 (95% UI, 117-161) per 100,000. However, the relative mortality of burn injury has been fixed over the 26-year study period. Alaska had the highest rates of burn incidence in 1990 and 2016, closely followed by southeastern states. When adjusted for incidence, relative mortality in 1990 was highest in Alabama and Mississippi and the mortality-incidence ratio increased for these states in 2016. In addition, 35 states also demonstrated an increase in the relative mortality of burn injury during the study period.

CONCLUSIONS

Regional trends of burn incidence and mortality are highly variable and are likely due to a multitude of factors. Addressing these disparities will require close examination of the contributing factors of burn injury and severity.

The WORD: Outcomes of a Behavioral Weight Loss Maintenance Effectiveness Trial in Rural Black Adults of Faith

OBJECTIVE

Rural black communities bear a disproportionate burden of obesity. To increase reach among underserved groups, community-based weight loss and maintenance interventions are crucial.

METHODS

The Diabetes Prevention Program (DPP) was adapted for rural black adults of faith to create The Wholeness, Oneness, Righteousness, Deliverance (WORD) trial, a group-based, community health worker-delivered weight loss intervention. A Weight Loss Only arm (16 sessions) was compared with a Weight Loss + Maintenance arm (16 + 12 sessions) in a cluster randomized controlled trial of 31 churches (n = 440). Weight and related behaviors were assessed at 0, 6, 12, and 18 months.

RESULTS

The WORD produced weight loss from baseline to 6 months (percentage body weight change -2.47 [-3.13 to -1.80]). Among those who lost 5% of their baseline weight, there was a statistical trend of lower weight regain in the Weight Loss + Maintenance arm compared with control. Maintenance arm participants reported higher activity at 12 months. There were no between-arm differences at 18 months.

CONCLUSIONS

The WORD produced weight loss from baseline to 6 months on par with that produced by other DPP adaptations for black communities, including adaptations using health professionals. Weight regain was also consistent with that reported in prior literature. Continuing sessions as part of the church's mission may foster adoption of DPP-based weight loss programs.

The Impact of Obesity and Smoking on Outcomes After Volar Plate Fixation of Distal Radius Fractures

PURPOSE

Distal radius fractures are common fractures of the upper extremity. Whereas surgical outcomes have been extensively investigated, the impact of risk factors such as body mass index (BMI) and smoking on patient outcomes has not been explored. We hypothesized that obesity and smoking would have a negative impact on the functional and radiographic outcomes of surgically treated patients with distal radius fractures.

METHODS

We performed a retrospective analysis of patients surgically treated for a distal radius fracture between 2006 and 2017 at 2 level 1 trauma centers. Patients were divided into obese (BMI ≥ 30) and nonobese (BMI < 30) groups according to the World Health Organization BMI Classification. Patients were also divided into current, former, and never smokers based on reported cigarette use. Primary outcomes included patient-reported outcome measures (Quick Disabilities of the Arm, Shoulder, and Hand [QuickDASH]), range of motion (ROM) arc (flexion-extension, pronation-supination), radiographic union (Radiographic Union Scoring System [RUSS] score), and change in radiographic alignment (radial height, radial inclination, volar tilt) between first and last follow-up. Multivariable models corrected for age, sex, comorbidities, fracture complexity, osteoporosis, and time to surgery.

RESULTS

Two hundred patients were identified, 39 with BMI of 30 or greater and 161 with BMI less than 30. Obese patients had more comorbidities but similar fracture types. At 3-month and 1-year follow-up, both groups achieved acceptable QuickDASH scores, close to those of the general population (21 vs 18, 14 vs 2, respectively). The 2 groups were similar in regard to motion, RUSS score, and alignment. There were 148 never smokers, 32 former smokers, and 20 current smokers. At 3 months, smokers demonstrated higher QuickDASH scores (42 vs 21-24) and a lower percentage of radiographically healed fractures (40% vs 69%-82%). At final follow-up, smokers reported small differences in patient-reported outcomes (QuickDASH 18 vs 9-13) whereas ROM, fracture healing, and complication rates were similar.

CONCLUSIONS

Both obese and nonobese patients can achieve excellent outcomes following surgical treatment of distal radius fracture with similar self-reported outcomes, motion, RUSS score, and alignment. Despite slower healing in the early postoperative period, smokers had similar QuickDASH scores, ROM, and union rates to past smokers and never smokers at final follow-up, with a similar complication profile.

TYPE OF STUDY/LEVEL OF EVIDENCE

Prognostic IV.

A Retrospective Study about the Differences in Cardiometabolic Risk Indicators and Level of Physical Activity in Bariatric Surgery Patients from Private vs. Public Units

Background: Obesity is a pathology with a growing incidence in developing countries. Objective: To evaluate the evolution of cardiometabolic, anthropometrics, and physical activity parameters in individuals undergoing bariatric surgery (BS) in the public healthcare system (PUS) and private healthcare system (PHS). Methods: A longitudinal, observational, and retrospective study was conducted with 111 bariatric patients on two different health systems, with 60 patients from the PUS and 51 from the PHS. Cardiometabolic risk (CR) was analyzed by the assessment of obesity-related comorbidities (AORC) on admission and 3, 6, and 12 months after BS, and the International Physical Activity Questionnaire (IPAQ) was surveyed before and 12 months after BS. In addition, cardiometabolic risk was also assessed by biochemical (fasting glucose and complete lipidogram) and anthropometric (weight, weight loss, waist circumference, and waist-to-height ratio) parameters. Results: On admission, the parameters of severe obesity, systemic arterial hypertension (SAH), Diabetes mellitus (DM), and waiting time to BS were higher in the PUS. Additionally, in the PUS, AORC was reduced only in the SAH parameter. However, in the post-surgery moment, AORC reduced, and there was no difference between the two groups after BS. Regarding physical activity, the IPAQ showed a higher level of activity in the PHS before and one year after BS. Conclusion: At the PUS, BS is performed in patients with a higher degree of comorbidities, but BS improved the reduction of the CR at a similar level to those observed in the PHS.

What Predicts a Mayoral Official's Opinion about the Role of Stress in Health Disparities?

High stress is a public health issue in the United States (US), that disproportionately affects socially-marginalized group members, including racial and ethnic minorities and those of low socioeconomic status. While city governments have the potential to reduce stress exposure and health disparities through municipal policies, very little is known about factors that are associated with mayor officials' beliefs about stress as a determinant of disparities. This information is important because it can inform the design of interventions to educate city policymakers about evidence related to stress and health disparities. Using data from a 2016 survey of 230 mayor officials (101 mayors, 129 senior staff), multivariable logistic regression was used to determine the extent to which respondents' individual characteristics (e.g., ideology, highest level of education) and the characteristics of their city's population (e.g., percentage of residents non-white) were associated with their identification of stress as a factor that has a "very strong effect" on health disparities. Forty-four percent of respondents identified stress as having a very strong effect on health disparities. In the fully adjusted model, every percentage point increase in the proportion of a respondent's city population that was non-White increased the odds of identifying stress as having a very strong effect on health disparities by 2% [adjusted odds ratio (aOR) = 1.02; 95% CI = 1.00,1.04]. Interventions are needed to increase city policymakers' knowledge about the role of stress in the production of health disparities, which could, in turn, help cultivate political will for city policies that reduce disparities.

The Role of Built Environment on Health of Older Adults in Korea: Obesity and Gender Differences

This study examines the effect of the built environment on obesity in older adults, taking into consideration gender difference. In this regard, we ask two questions: (1) How does the built environment affect obesity in older adults? (2) Is there a gender difference in the effect of the built environment? To examine the research questions, this study uses the 2015 Korean National Health and Nutrition Survey and geographically weighted regression (GWR) analysis. The empirical analyses show that environmental factors have stronger effects on local obesity rates for older men than for older women, which indicates a gender difference in obesity. Based on these findings, we suggest that public health policies for obesity should consider the built environment as well as gender difference.

An Area-Level Indicator of Latent Soda Demand: Spatial Statistical Modeling of Grocery Store Transaction Data to Characterize the Nutritional Landscape in Montreal, Canada

Measurement of neighborhood dietary patterns at high spatial resolution allows public health agencies to identify and monitor communities with an elevated risk of nutrition-related chronic diseases. Currently, data on diet are obtained primarily through nutrition surveys, which produce measurements at low spatial resolutions. The availability of store-level grocery transaction data provides an opportunity to refine the measurement of neighborhood dietary patterns. We used these data to develop an indicator of area-level latent demand for soda in the Census Metropolitan Area of Montreal in 2012 by applying a hierarchical Bayesian spatial model to data on soda sales from 1,097 chain retail food outlets. The utility of the indicator of latent soda demand was evaluated by assessing its association with the neighborhood relative risk of prevalent type 2 diabetes mellitus. The indicator improved the fit of the disease-mapping model (deviance information criterion: 2,140 with the indicator and 2,148 without) and enables a novel approach to nutrition surveillance.

Multilevel Analysis of Socio-Demographic Disparities in Adulthood Obesity Across the United States Geographic Regions

Objectives

The objective of this study was to examine the socio-demographic disparities in obesity among US adults across 130 metropolitan and micropolitan statistical areas.

Methods

This study used data from the 2015 Behavioral Risk Factor Surveillance System and Selected Metropolitan/Micropolitan Area Risk Trend of 159,827 US adults aged 18 years and older. Data were analyzed using the multilevel linear regression models.

Results

According to individual level analyses, socio-demographic disparities in obesity exist in the United States. Individuals with low socioeconomic status were associated with a higher body mass index. The participants from the Midwest United States tend to have higher body mass index than those who from the South. According to metropolitan and micropolitan statistical area level analyses, secondly, there were significant differences in obesity status between different areas and the relation of obesity with 5 socio-demographic factors varied across different areas. According to geospatial mapping analyses, even though obesity status by metropolitan and micropolitan statistical area level has improved overtime, differences in body mass index between United States regions are increasing from 2007 to 2015.

Conclusion

Socio-demographic and regional disparities in obesity status persist among US adults. Hence, these findings underscore the need to take socio-environmental factors into account when planning obesity prevention on vulnerable populations and areas.

Obesity: global epidemiology and pathogenesis

The prevalence of obesity has increased worldwide in the past ~50 years, reaching pandemic levels. Obesity represents a major health challenge because it substantially increases the risk of diseases such as type 2 diabetes mellitus, fatty liver disease, hypertension, myocardial infarction, stroke, dementia, osteoarthritis, obstructive sleep apnoea and several cancers, thereby contributing to a decline in both quality of life and life expectancy. Obesity is also associated with unemployment, social disadvantages and reduced socio-economic productivity, thus increasingly creating an economic burden. Thus far, obesity prevention and treatment strategies - both at the individual and population level - have not been successful in the long term. Lifestyle and behavioural interventions aimed at reducing calorie intake and increasing energy expenditure have limited effectiveness because complex and persistent hormonal, metabolic and neurochemical adaptations defend against weight loss and promote weight regain. Reducing the obesity burden requires approaches that combine individual interventions with changes in the environment and society. Therefore, a better understanding of the remarkable regional differences in obesity prevalence and trends might help to identify societal causes of obesity and provide guidance on which are the most promising intervention strategies.

Identification of Factors Associated With Variation in US County-Level Obesity Prevalence Rates Using Epidemiologic vs Machine Learning Models

IMPORTANCE

Obesity is a leading cause of high health care expenditures, disability, and premature mortality. Previous studies have documented geographic disparities in obesity prevalence.

OBJECTIVE

To identify county-level factors associated with obesity using traditional epidemiologic and machine learning methods.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional study using linear regression models and machine learning models to evaluate the associations between county-level obesity and county-level demographic, socioeconomic, health care, and environmental factors from summarized statistical data extracted from the 2018 Robert Wood Johnson Foundation County Health Rankings and merged with US Census data from each of 3138 US counties. The explanatory power of the linear multivariate regression and the top performing machine learning model were compared using mean R2 measured in 30-fold cross validation.

EXPOSURES

County-level demographic factors (population; rural status; census region; and race/ethnicity, sex, and age composition), socioeconomic factors (median income, unemployment rate, and percentage of population with some college education), health care factors (rate of uninsured adults and primary care physicians), and environmental factors (access to healthy foods and access to exercise opportunities).

MAIN OUTCOMES AND MEASURES

County-level obesity prevalence in 2018, its association with each county-level factor, and the percentage of variation in county-level obesity prevalence explained by linear multivariate and gradient boosting machine regression measured with R2.

RESULTS

Among the 3138 counties studied, the mean (range) obesity prevalence was 31.5% (12.8%-47.8%). In multivariate regressions, demographic factors explained 44.9% of variation in obesity prevalence; socioeconomic factors, 33.0%; environmental factors, 15.5%; and health care factors, 9.1%. The county-level factors with the strongest association with obesity were census region, median household income, and percentage of population with some college education. R2 values of univariate regressions of obesity prevalence were 0.238 for census region, 0.218 for median household income, and 0.160 for percentage of population with some college education. Multivariate linear regression and gradient boosting machine regression (the best-performing machine learning model) of obesity prevalence using all county-level demographic, socioeconomic, health care, and environmental factors had R2 values of 0.58 and 0.66, respectively (P < .001).

CONCLUSIONS AND RELEVANCE

Obesity prevalence varies significantly between counties. County-level demographic, socioeconomic, health care, and environmental factors explain the majority of variation in county-level obesity prevalence. Using machine learning models may explain significantly more of the variation in obesity prevalence..

Area-Level Walkability and the Geographic Distribution of High Body Mass in Sydney, Australia: A Spatial Analysis Using the 45 and Up Study

Improving the walkability of built environments to promote healthy lifestyles and reduce high body mass is increasingly considered in regional development plans. Walkability indexes have the potential to inform, benchmark and monitor these plans if they are associated with variation in body mass outcomes at spatial scales used for health and urban planning. We assessed relationships between area-level walkability and prevalence and geographic variation in overweight and obesity using an Australian population-based cohort comprising 92,157 Sydney respondents to the 45 and Up Study baseline survey between January 2006 and April 2009. Individual-level data on overweight and obesity were aggregated to 2006 Australian postal areas and analysed as a function of area-level Sydney Walkability Index quartiles using conditional auto regression spatial models adjusted for demographic, social, economic, health and socioeconomic factors. Both overweight and obesity were highly clustered with higher-than-expected prevalence concentrated in the urban sprawl region of western Sydney, and lower-than-expected prevalence in central and eastern Sydney. In fully adjusted spatial models, prevalence of overweight and obesity was 6% and 11% lower in medium-high versus low, and 10% and 15% lower in high versus low walkability postcodes, respectively. Postal area walkability explained approximately 20% and 9% of the excess spatial variation in overweight and obesity that remained after accounting for other individual- and area-level factors. These findings provide support for the potential of area-level walkability indexes to inform, benchmark and monitor regional plans aimed at targeted approaches to reducing population-levels of high body mass through environmental interventions. Future research should consider potential confounding due to neighbourhood self-selection on area-level walkability relations.

Incidence of Pancreatic Adenocarcinoma in the United States from 2001 to 2015: A United States Cancer Statistics Analysis of 50 States

Introduction Pancreatic cancer is one of the leading causes of death in both males and females in the United States. Nearly 85% of pancreatic cancer is adenocarcinoma. Given the silent disease progression of pancreatic cancer, identifying at-risk populations will help diagnose these fatal cancers as early as possible. Methods The United States Cancer Statistics (USCS) registry was used to obtain data for pancreatic adenocarcinoma from 2001 to 2015. The incidence analysis was stratified based on sex, race, stage, and US regional location. Results The overall incidence of pancreatic adenocarcinoma from 2001 to 2015 was 5.2 per 100,000 people per year. The overall incidence rates were the greatest for each stratification in males, blacks, distant disease, and in the Northeast. The incidence in blacks continued to rise with an annual percent change (APC) of 2.28 between 2001 and 2015. Between 2001 and 2006, the incidence of distant disease increased at a rapid rate (APC 5.34). However, after 2006, the incidence continued to increase but no longer at the previously rapid rate (APC 1.91). For incidence based on US regional location, the overall incidence was greatest in the Northeast and Midwest. The incidence in the South was increasing at an expeditious rate (APC 2.70). Conclusion In our study, we analyzed the incidence of pancreatic adenocarcinoma using data from all 50 states in the US. Our findings showed that there was a worsening incidence in blacks, those with a distant stage at diagnosis, and those in the North and Midwest. Ultimately our findings help identify at-risk populations and can contribute to improving surveillance of this deadly disease.

Geographic and Urban-Rural Differences in Walking for Leisure and Transportation

INTRODUCTION

Walking can serve many purposes, such as transportation (to get some place) or leisure (for fun, relaxation, or exercise); therefore, it provides many opportunities for people to be physically active. This study examines geographic and urban-rural differences in walking in the U.S.

METHODS

Adult respondents (aged ≥18 years) to the 2015 National Health Interview Survey reported participation in and time spent (minutes per week) walking for transportation and leisure in the past week. In 2017, prevalence and time spent walking (among walkers) for any, leisure, and transportation walking were estimated by nine expanded regions and urban-rural designation.

RESULTS

Prevalence of any walking ranged from 50.8% (East South Central) to 72.4% (Pacific); for leisure walking 43.9% (East South Central) to 60.6% (Pacific); and transportation walking 17.8% (East South Central) to 43.5% (New England). Among walkers, mean minutes spent walking per week ranged from 77.4 (East South Central) to 101.6 (Pacific); for leisure walking 70.5 (West South Central) to 85.9 (Mountain); and for transportation walking 47.4 (East South Central) to 66.4 (Middle Atlantic). Overall, there were urban-rural differences in prevalence of walking; however, differences depended on walking purpose and expanded region. Time spent walking was similar in urban and rural areas.

CONCLUSIONS

Regional differences in walking prevalence and time spent walking exist. Urban-rural differences in prevalence of walking differ based on region and purpose; however, rural areas had a lower prevalence of walking than urban areas regardless of purpose in southern regions. Opportunities exist to improve walking, particularly among southern regions with a focus on rural areas.

Association of community food environment and obesity among US adults: a geographical information system analysis

Background

Emerging studies have investigated the contribution of food environment to obesity in the USA. However, the findings were inconsistent. Methodological explanations for the inconsistent findings included: (1) using individual store/restaurant exposure as food environment indicator, and (2) not accounting for non-stationarity assumption. This study aimed to describe the spatial distribution of obesity and examine the association between community food environment and obesity, and the variation of magnitude and direction of this association across the USA.

Methods

Data from 20 897 adults who participated in the REasons for Geographic and Racial Differences in Stroke study and completed baseline assessment between January 2003 and October 2007 were eligible in analysis. Hot Spot analysis was used to assess the spatial distribution of obesity. The association between community food environment and obesity and the variation of this association across the USA were examined using global ordinary least squares regression and local geographically weighted regression.

Results

Higher body mass index (BMI) clusters were more likely to locate in socioeconomically disadvantaged, rural, minority neighbourhoods with a smaller population size, while lower BMI clusters were more likely to appear in more affluent, urban neighbourhoods with a higher percentage of non-Hispanic white residences. There was an overall significant, inverse association between community food environment and obesity (β=−0.0210; p<0.0001). Moreover, the magnitude and direction of this association varied significantly across the US regions.

Conclusions

The findings underscored the need for geographically tailored public health interventions and policies to address unique local food environment issues to achieve maximum effects on obesity prevention.

Regional differences in BMI, obesity, and exercise frequency in a large veteran service organization: A secondary analysis of new veteran member surveys from Team Red, White & Blue

The purpose of the present study was to examine regional differences in average self-reported BMI, obesity prevalence, and frequent exercise (FE) among members of Team Red, White, and Blue (Team RWB) – a military veteran service organization founded to increase physical activity in veterans. A total of 10,015 military veterans participated in a needs assessment conducted by Team RWB between December 2014 and August 2016. Multivariate regression analysis with bootstrapped coefficients revealed that: BMI was highest in the Midwest region (M = 28.282) of the United States, F_{(20, 9882)} = 105.560, p < 0.001; obesity prevalence was highest in the Southcentral (32.300%) and Southeast (32.200%) regions, x²₍₉₇₃₁₎ = 10,850, p < 0.001; and FE was most prevalent in the Mid-Atlantic region (67.3%), x²₍₉₈₈₂₎ = 11,291, p < 0.001.The results of this study closely mirror results found in studies of the general population. A better understanding of the geographic distribution of these outcomes could guide the targeting of sub-populations for public health programs. In particular, Team Red, White & Blue community growth and other fitness based public health programs could be expanded to reach more veterans.

All disease begins in the gut: Influence of gastrointestinal disorders and surgery on oral drug performance

The term "disease" conjures a plethora of graphic imagery for many, and the use of drugs to combat symptoms and treat underlying pathology is at the core of modern medicine. However, the effects of the various gastrointestinal diseases, infections, co-morbidities and the impact of gastrointestinal surgery on the pharmacokinetic and pharmacodynamic behaviour of drugs have been largely overlooked. The better elucidation of disease pathology and the role of underlying cellular and molecular mechanisms have increased our knowledge as far as diagnoses and prognoses are concerned. In addition, the recent advances in our understanding of the intestinal microbiome have linked the composition and function of gut microbiota to disease predisposition and development. This knowledge, however, applies less so in the context of drug absorption and distribution for orally administered dosage forms. Here, we revisit and re-evaluate the influence of a portfolio of gastrointestinal diseases and surgical effects on the functionality of the gastrointestinal tract, their implications for drug delivery and attempt to uncover significant links for clinical practice.

Body size reference norms and subjective weight status: A gender and life course approach

This paper uses data from The National Longitudinal Study of Adolescent to Adult Health (Add Health) to describe county-level variation in norms regarding physical weight among adolescents in the United States. We demonstrate that regardless of one's physical size, those residing in counties with a heavier weight norm are significantly less likely to see themselves as overweight than those residing in counties with a light weight norm. We further show that the local weight norm during adolescence (Wave 1) is associated with individuals' weight perceptions through adolescence and into young adulthood (Wave 4), though these associations attenuate in strength as respondents age. Our results suggest that weight norms have a stronger influence on weight perceptions among women compared to men and that the role of gender is particularly important during adolescence. We encourage life course researchers to consider the normative health environment during adolescence as an important context for understanding disparities in health and health lifestyles as people age.

Gender Difference and Spatial Heterogeneity in Local Obesity

This study asks if there is gender-specific spatial heterogeneity in local obesity. By using the 2015 Korea Community Health Survey and employing spatial analyses, this study found that there is considerable gender-specific spatial heterogeneity in local obesity rates. More specifically, we found that: (1) local obesity rates are more spatially dependent for women than for men; (2) environmental factors, in general, have stronger effects on local obesity rates for women than for men; (3) environmental factors have more spatially varying effects on local obesity rates for women than for men. Based on these findings, we suggest that policies for obesity prevention should not be based on the assumption of spatial homogeneity and gender indifference, but rather should be refined based on gender-specific spatial heterogeneity in local obesity.