Associations between obesity and neighborhood socioeconomic status: Variations by gender and family income status

The association of socioeconomic status with semen parameters in a cohort of men in the United States

BACKGROUND

Socioeconomic differences are present within the population of men who experience infertility and seek treatment.

OBJECTIVE

To study the association of socioeconomic status with semen parameters in a group of men using mail-in semen analyses.

MATERIALS AND METHODS

The records of 11,134 men that used mail-in semen analyses from a fertility company were identified. Their demographic information, semen parameters, and ZIP codes were collected. Area deprivation index (ADI) was used as a proxy for socioeconomic status and was calculated for each individual using their ZIP codes in order to measure their level of socioeconomic deprivation. A higher ADI signifies a more deprived area. The association between ADI and the semen parameters of this group was measured using linear regression analysis adjusted for age.

RESULTS

11,134 men were included in the study with a median age of 35 years (interquartile range (IQR): 32-40) and a median ADI of 83 (IQR: 68-97). The cohort had a median sperm concentration of 31 million/mL (IQR: 14-59), median total sperm count of 123 million (IQR: 57-224), median total motile sperm of 35 million (IQR: 9-95), median total motility of 32% (IQR: 15-52), progressive motility of 22% (IQR: 9-38), and morphology percent normal of 4% (IQR: 2-7). Higher ADI, indicating lower socioeconomic status, was negatively associated with various semen parameters, including sperm concentration, total sperm count, total motile sperm, and total and progressive motility.

DISCUSSION AND CONCLUSION

Men who live in more deprived areas are more likely to have worse semen parameters. Further research is needed to thoroughly examine the impact of socioeconomic status on male fertility. A comprehensive approach that targets upstream social, economic, and healthcare factors can possibly alleviate the negative association of socioeconomic status with fertility and semen parameters.

Childhood obesity's influence on socioeconomic disparities in young adolescents' mental health

PURPOSE

We investigated whether socioeconomic inequalities in young adolescents' mental health are partially due to the unequal distribution of childhood obesity across socioeconomic positions (SEP), i.e. differential exposure, or due to the effect of obesity on mental health being more detrimental among certain SEPs, i.e. differential impact.

METHODS

We studied 4660 participants of the Generation R study, a population-based study in the Netherlands. SEP was estimated by mother's education and household income at age five of the child. We estimated the contribution of the mediating and moderating effects of high body fat percentage to the disparity in mental health. This was done through a four-way decomposition using marginal structural models with inverse probability of treatment weighting.

RESULTS

Comparing children with the least to most educated mothers and the lowest to highest household income, the total disparity in emotional problems was 0.98 points (95%CI:0.35-1.63) and 1.68 points (95%CI:1.13-2.19), respectively. Of these total disparities in emotional problems, 0.50 points (95%CI:0.15-0.85) and 0.24 points (95%CI:0.09-0.46) were due to the differential exposure to obesity. Obesity did not contribute to disparities in behavioural problems.

CONCLUSION

Addressing the heightened obesity prevalence among children in low SEP families may reduce inequalities in emotional problems in early adolescence.

Association between Fine Particulate Matter Exposure and Cerebrospinal Fluid Biomarkers of Alzheimer's Disease among a Cognitively Healthy Population-Based Cohort

BACKGROUND

Epidemiological evidence suggests air pollution adversely affects cognition and increases the risk of Alzheimer's disease (AD), but little is known about the biological effects of fine particulate matter (PM 2.5 , particulate matter with aerodynamic diameter ≤ 2.5 μ m ) on early predictors of future disease risk.

OBJECTIVES

We investigated the association between 1-, 3-, and 5-y exposure to ambient and traffic-related PM 2.5 and cerebrospinal fluid (CSF) biomarkers of AD.

METHODS

We conducted a cross-sectional analysis using data from 1,113 cognitively healthy adults (45-75 y of age) from the Emory Healthy Brain Study in Georgia in the United States. CSF biomarker concentrations of A β 42 , tTau, and pTau, were collected at enrollment (2016-2020) and analyzed with the Roche Elecsys system. Annual ambient and traffic-related residential PM 2.5 concentrations were estimated at a 1 -km and 250 -m resolution, respectively, and computed for each participant's geocoded address, using three exposure time periods based on specimen collection date. Associations between PM 2.5 and CSF biomarker concentrations, considering continuous and dichotomous (dichotomized at clinical cutoffs) outcomes, were estimated with multiple linear/logistic regression, respectively, controlling for potential confounders (age, gender, race, ethnicity, body mass index, and neighborhood socioeconomic status).

RESULTS

Interquartile range (IQR; IQR = 0.845 ) increases in 1-y [β : - 0.101 ; 95% confidence interval (CI): - 0.18 , - 0.02 ] and 3-y (β : - 0.078 ; 95% CI: - 0.15 , - 0.00 ) ambient PM 2.5 exposures were negatively associated with A β 42 CSF concentrations. Associations between ambient PM 2.5 and A β 42 were similar for 5-y estimates (β : - 0.076 ; 95% CI: - 0.160 , 0.005). Dichotomized CSF variables revealed similar associations between ambient PM 2.5 and A β 42 . Associations with traffic-related PM 2.5 were similar but not significant. Associations between PM 2.5 exposures and tTau, pTau tTau / A β 42 , or pTau / A β 42 levels were mainly null.

CONCLUSION

In our study, consistent trends were found between 1-y PM 2.5 exposure and decreased CSF A β 42 , which suggests an accumulation of amyloid plaques in the brain and an increased risk of developing AD. https://doi.org/10.1289/EHP13503.

Cost-Effectiveness Analysis of a Community-Based Telewellness Weight Loss Program

Introduction

The purpose of this study was to perform a cost-effectiveness analysis of the Koa Family Program, a community-based telewellness weight reduction intervention for overweight and obese women aged 21-45 years with low income. The Koa Family Program resulted in an approximately 8-pound weight loss as demonstrated in an RCT published previously.

Methods

Estimates for the cost-effectiveness were derived from the prospective 25-week RCT including 70 women (25 kg/m2≤BMI<40 kg/m2). The analysis was from a program-funder perspective. Base case costs, as well as low and high scenario costs, were estimated from the services provided to intervention participants. The incremental costs were compared with the incremental effectiveness, with weight loss being the outcome of interest. Costs were in 2021 U.S. dollars. Cost-effectiveness was assessed using the incremental cost-effectiveness ratio and the incremental net benefit. The statistical uncertainty was characterized using an incremental net benefit by willingness-to-pay plot and a cost-effectiveness acceptability curve.

Results

The base case average cost per participant was $564.39. The low and high scenario average costs per participant were $407.34 and $726.22, respectively. Over the 25-week study timeframe, participants lost an average 7.7 pounds, yielding a base case incremental cost-effectiveness ratio of approximately $73 per extra pound lost. The probability that the Koa Family Program is cost-effective is 90%, assuming a willingness-to-pay of $115 for a 1-pound reduction, and is 95%, assuming a willingness-to-pay of $140.

Conclusions

The Koa Family Program provides good value with cost-effectiveness in line with other weight-loss interventions. This is a striking finding given that the Koa Family Program serves a more vulnerable population than is typically engaged in weight loss research studies.

Race- and Gender-Specific Associations between Neighborhood-Level Socioeconomic Status and Body Mass Index: Evidence from the Southern Community Cohort Study

Obesity and a low socioeconomic status (SES), measured at the neighborhood level, are more common among Americans of Black race and with a low individual-level SES. We examined the association between the neighborhood SES and body mass index (BMI) using data from 80,970 participants in the Southern Community Cohort Study, a cohort that oversamples Black and low-SES participants. BMI (kg/m2) was examined both continuously and categorically using cut points defined by the CDC. Neighborhood SES was measured using a neighborhood deprivation index composed of census-tract variables in the domains of education, employment, occupation, housing, and poverty. Generally, the participants in lower-SES neighborhoods were more likely to have a higher BMI and to be considered obese. We found effect modification by race and sex, where the neighborhood-BMI association was most apparent in White female participants in all the quintiles of the neighborhood SES (ORQ2 = 1.55, 95%CI = 1.34, 1.78; ORQ3 = 1.71, 95%CI = 1.48, 1.98; ORQ4 = 1.76, 95%CI = 1.52, 2.03; ORQ5 = 1.64, 95%SE = 1.39, 1.93). Conversely, the neighborhood-BMI association was mostly null in Black male participants (ORQ2 = 0.91, 95%CI = 0.72, 1.15; ORQ3 = 1.05, 95%CI = 0.84, 1.31; βQ4 = 1.00, 95%CI = 0.81, 1.23; ORQ5 = 0.76, 95%CI = 0.63, 0.93). Within all the subgroups, the associations were attenuated or null in participants residing in the lowest-SES neighborhoods. These findings suggest that the associations between the neighborhood SES and BMI vary, and that other factors aside from the neighborhood SES may better predict the BMI in Black and low-SES groups.

Decoding Genetics, Ancestry, and Geospatial Context for Precision Health

Mass General Brigham, an integrated healthcare system based in the Greater Boston area of Massachusetts, annually serves 1.5 million patients. We established the Mass General Brigham Biobank (MGBB), encompassing 142,238 participants, to unravel the intricate relationships among genomic profiles, environmental context, and disease manifestations within clinical practice. In this study, we highlight the impact of ancestral diversity in the MGBB by employing population genetics, geospatial assessment, and association analyses of rare and common genetic variants. The population structures captured by the genetics mirror the sequential immigration to the Greater Boston area throughout American history, highlighting communities tied to shared genetic and environmental factors. Our investigation underscores the potency of unbiased, large-scale analyses in a healthcare-affiliated biobank, elucidating the dynamic interplay across genetics, immigration, structural geospatial factors, and health outcomes in one of the earliest American sites of European colonization.

Accelerating the healing of hard-to-heal wounds with food supplements: nutritional analysis in the Côte d'Ivoire

OBJECTIVE

Hard-to-heal wounds are an important, yet often neglected, public health issue in low- and middle-income countries (LMICs). Malnutrition has been identified as a risk factor for prolonged healing times. However, nutritional supplements are not routinely provided for patients with hard-to-heal wounds, and so this study aimed to investigate their benefits.

METHOD

This 9-month study was conducted in the Taabo Health and Demographic Surveillance System in the south-central part of Côte d'Ivoire. Patients with wounds (≥30mm2) were recruited. Treatment was standardised for inpatients (72%) and outpatients (28%). There were three intervention groups: supplemented with soy; orange flesh sweet potato (OFSP); or both. Another group was included without supplement, serving as control. General linear models were employed to assess the effects of log initial wound size, type of wound, food treatment group, haemoglobin, sex, age, place of treatment and body mass index on the rate of wound closure.

RESULTS

The cohort consisted of 56 patients, 41 of whom were placed in intervention groups, and the remainder as controls. Within the cohort, 37 (66%) patients suffered from Buruli ulcer, 15 (27%) from traumatic wounds and four (7%) from erysipelas. We found a significant effect (p=0.004) of diet supplemented with OFSP on the wound healing rate.

CONCLUSION

OFSP is a nutritional rehabilitation supplement, characterised by a high content of beta-carotene and carbohydrates. It is associated with shortened wound healing times, reduced discomfort and reduced cost of wound care. Further research should investigate the effect of a diet rich in beta-carotene, in combination with standard medical care, on hard-to-heal wound healing in LMICs.

Social determinants of health, health disparities, and adiposity

Social determinants of health (SDoH), or the socioeconomic, environmental, and psychosocial conditions in which individuals spend their daily lives, substantially influence obesity as a cardiovascular disease (CVD) risk factor. The coronavirus disease 2019 (COVID-19) pandemic highlighted the converging epidemics of obesity, CVD, and social inequities globally. Obesity and CVD serve as independent risk factors for COVID-19 severity and lower-resourced populations most impacted by adverse SDoH have the highest COVID-19 mortality rates. Better understanding the interplay between social and biologic factors that contribute to obesity-related CVD disparities are important to equitably address obesity across populations. Despite efforts to investigate SDoH and their biologic effects as drivers of health disparities, the connections between SDoH and obesity remain incompletely understood. This review aims to highlight the relationships between socioeconomic, environmental, and psychosocial factors and obesity. We also present potential biologic factors that may play a role in the biology of adversity, or link SDoH to adiposity and poor adipo-cardiology outcomes. Finally, we provide evidence for multi-level obesity interventions targeting multiple aspects of SDoH. Throughout, we emphasize areas for future research to tailor health equity-promoting interventions across populations to reduce obesity and obesity-related CVD disparities.

Explaining obesity disparities by urbanicity, 2006 to 2016: A decomposition analysis

OBJECTIVE

A large, and potentially growing, disparity in obesity prevalence exists between large central metros and less urban United States counties. This study examines its key predictors.

METHODS

Using a rich county-year data set spanning 2006 to 2016, the authors conducted a Gelbach decomposition to examine the relative importance of demographic, socioeconomic, environmental, and behavioral factors in shaping the baseline obesity gap and the growth rate over time between large central metros and other counties.

RESULTS

Predictors included in this model explain almost the entire obesity gap between large central metros and other counties in the baseline year but can explain only ~32% of the growing gap. At baseline, demographic predictors explain more than half the obesity gap, and socioeconomic and behavioral predictors explain the other half. Behavioral and socioeconomic predictors explain more than half the growing gap over time whereas controlling for environmental and demographic predictors decreases the obesity gap by urbanicity over time.

CONCLUSIONS

Results suggest policy makers should prioritize interventions targeting health behaviors of residents in non-large central metros to slow the growth of the obesity gap between large central metros and other counties. However, to fundamentally eliminate the obesity gap, in addition to improving health behaviors, policies addressing socioeconomic inequalities are needed.

Neighborhood socioeconomic differences in BMI: The role of fast-food outlets and physical activity facilities

OBJECTIVE

The goal of this study was to investigate the association between neighborhood socioeconomic status (NSES) and BMI and to what extent this association is moderated by availability of fast-food (FF) outlets and pay-for-use physical activity (PA) facilities.

METHODS

Baseline data of adults in Lifelines (N = 146,629) were linked to Statistics Netherlands and a register using geocoding to compute, respectively, NSES (i.e., low, middle, high) and the number of FF outlets and PA facilities within 1 km of the residential address. Multivariable multilevel linear regression analyses were performed to examine the association between NSES and BMI. Two-way and three-way interaction terms were tested to examine moderation by FF outlets and PA facilities.

RESULTS

Participants living in low NSES areas had a higher BMI than participants living in high (B [95% CI]: 0.76 [0.65 to 0.87]) or middle NSES areas (B [95% CI]: 0.40 [0.28 to 0.51]), independent of individual socioeconomic status. Although two- and three-way interactions between NSES, FF outlets, and PA facilities were significant, stratified analyses did not show consistent moderation patterns.

CONCLUSIONS

People living in lower NSES areas had a higher BMI, independent of their individual socioeconomic status. The study found no clear moderation of FF outlets and PA facilities. Environmental factors that may mitigate NSES differences in BMI should be the subject of future research.

A cross-sectional study of smoking and depression among US adults: NHANES (2005-2018)

Background

The relationship between smoking and depression remains controversial. This study aimed to investigate the association between smoking and depression from three aspects: smoking status, smoking volume, and smoking cessation.

Methods

Data from adults aged ≥20 who participated in the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 were collected. The study gathered information about the participants' smoking status (never smokers, previous smokers, occasional smokers, daily smokers), smoking quantity per day, and smoking cessation. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9), with a score ≥10 indicating the presence of clinically relevant symptoms. Multivariable logistic regression was conducted to evaluate the association of smoking status, daily smoking volume, and smoking cessation duration with depression.

Results

Previous smokers [odds ratio (OR) = 1.25, 95% confidence interval (CI): 1.05-1.48] and occasional smokers (OR = 1.84, 95% CI: 1.39-2.45) were associated with a higher risk of depression compared with never smokers. Daily smokers had the highest risk of depression (OR = 2.37, 95% CI: 2.05-2.75). In addition, a tendency toward a positive correlation was observed between daily smoking volume and depression (OR = 1.65, 95% CI: 1.24-2.19) (P for trend < 0.05). Furthermore, the longer the smoking cessation duration, the lower the risk of depression (OR = 0.55, 95% CI: 0.39-0.79) (P for trend < 0.05).

Conclusions

Smoking is a behavior that increases the risk of depression. The higher the smoking frequency and smoking volume, the higher the risk of depression, whereas smoking cessation is associated with decreased risk of depression, and the longer the smoking cessation duration, the lower the risk of depression.

Neighbourhood socioeconomic disadvantage and body size in Australia's capital cities: The contribution of obesogenic environments

Residents of socioeconomically disadvantaged neighbourhoods have higher rates of overweight and obesity and chronic disease than their counterparts from advantaged neighbourhoods. This study assessed whether associations between neighbourhood disadvantage and measured body mass index (BMI) and waist circumference, are accounted for by obesogenic environments (i.e., residential distance to the Central Business District [CBD], supermarket availability, access to walkable destinations). The study used 2017-18 National Health Survey data for working-aged adults (aged ≥18 years, n = 9,367) residing in 3,454 neighbourhoods across Australia's state and territory capital cities. In five of eight cities (i.e., Sydney, Melbourne, Brisbane, Adelaide, and Perth) residents of disadvantaged neighbourhoods had significantly higher BMI and a larger waist circumference than residents of more advantaged areas. There was no association between neighbourhood disadvantage and body size in Hobart, Darwin, and Canberra. Associations between neighbourhood disadvantage and body size were partially explained by neighbourhood differences in distance to the CBD but not supermarket availability or walkable amenities. The results of this study point to the role of urban design and city planning as mechanisms for addressing social and economic inequities in Australia's capital cities, and as solutions to this country's overweight and obesity epidemic and associated rising rates of chronic disease.

Associations between social determinants of health and abdominal solid organ transplant wait-lists in the United States

BACKGROUND

Societal factors that influence wait-listing for transplantation are complex and poorly understood. Social determinants of health (SDOH) affect rates of and outcomes after transplantation.

METHODS

This cross-sectional study investigated the impact of SDOH on additions to state-level, 2017-2018 kidney and liver wait-lists. Principal components analysis, starting with 127 variables among 3142 counties, was used to derive novel, comprehensive state-level composites, designated (1) health/economics and (2) community capital/urbanicity. Stepwise multivariate linear regression with backwards elimination (n = 51; 50 states and DC) tested the effects of these composites, Medicaid expansion, and center density on adult disease burden-adjusted wait-list additions.

RESULTS

SDOH related to increased community capital/urbanicity were independently associated with wait-listing (starting models: B = .40, P = .010 Kidney; B = .36, P = .038 Liver) (final models: B = .31, P = .027 Kidney, B = .34, P = .015 Liver). In contrast and surprisingly, no other covariates were associated with wait-listing (P ≥ .122).

CONCLUSIONS

These results suggest that deficits in community resources are important contributors to disparities in wait-list access. Our composite SDOH metrics may help identify at-risk communities, which can be the focus of local and national policy initiatives to improve access to organ transplantation.

Impact of land use and food environment on risk of type 2 diabetes: A national study of veterans, 2008-2018

BACKGROUND

Large-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent.

OBJECTIVE

To evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment.

METHODS

The Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum.

RESULTS

In adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001).

CONCLUSION

Among veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

Moderation of the Association between Primary Language and Health by Race and Gender: An Intersectional Approach

In the United States (US), limited English proficiency is associated with a higher risk of obesity and diabetes. “Intersectionality”, or the interconnected nature of social categorizations, such as race/ethnicity and gender, creates interdependent systems of disadvantage, which impact health and create complex health inequities. How these patterns are associated with language-based health inequities is not well understood. The study objective was to assess the potential for race/ethnicity, gender, and socioeconomic status to jointly moderate the association between primary language (English/Spanish) and having obesity and diabetes. Using the 2018 Behavioral Risk Factor Surveillance System (n = 431,045), weighted generalized linear models with a logistic link were used to estimate the associations between primary language (English/Spanish) and obesity and diabetes status, adjusting for confounders using stratification for the intersections of gender and race/ethnicity (White, Black, Other). Respondents whose primary language was Spanish were 11.6% more likely to have obesity (95% CI 7.4%, 15.9%) and 15.1% more likely to have diabetes (95% CI 10.1%, 20.3%) compared to English speakers. Compared to English speakers, Spanish speakers were more likely to have both obesity (p < 0.001) and diabetes (p < 0.001) among White females. Spanish speakers were also more likely to have obesity among males and females of other races/ethnicities (p < 0.001 for both), and White females (p = 0.042). Among males of other racial/ethnic classifications, Spanish speakers were less likely to have both obesity (p = 0.011) and diabetes (p = 0.005) than English speakers. Health promotion efforts need to recognize these differences and critical systems−change efforts designed to fundamentally transform underlying conditions that lead to health inequities should also consider these critical sociodemographic factors to maximize their effectiveness.

Neighborhood deprivation and obesity: Sex-specific effects of cross-sectional, cumulative and residential trajectory indicators

Obesity is a long-term health issue that is becoming increasingly prevalent. Very few studies have considered the life course effects of neighborhood characteristics on obesity. In a sample of 35,856 adult participants (representative of the population of the Province of Quebec in Canada), we measured the association between neighborhood deprivation and obesity using logistic modelling on indicators of cross-sectional neighborhood deprivation, cumulative neighborhood deprivation and trajectories of neighborhood deprivation. For cross-sectional exposure, we found that females in our sample had higher odds of being affected by obesity when living in high-deprivation (OR 1.73, CI 1.41-2.13) or medium-deprivation neighborhoods (OR 1.27, CI 1.07-1.51) compared to females living in low-deprivation neighborhoods. Males also had higher odds of being affected by obesity when living in medium or high deprivation. For cumulative exposure to neighborhood deprivation, only females in the second highest category for longitudinal exposure to deprived neighborhoods had significantly higher odds of living with obesity (OR 1.89 CI 1.12-3.19) compared to females in the low cumulative exposure category. Using sequence analysis to determine neighborhood deprivation trajectories for up to 17 years, we found that females with a Deprived upward (OR 1.75 CI 1.10-2.78), an Average downward (OR 1.75 CI 1.08-2.84) or a Deprived trajectory (OR 1.81 CI 1.45-2.86) had higher odds of living with obesity compared to the Privileged trajectory. For males, there were no significant associations. Using trajectory indicators was beneficial to our analyses because this method shows that not only are individuals in low socioeconomic status neighborhoods at the end of their trajectory more susceptible to living with obesity, but so are those exposed to neighborhood deprivation at the beginning of their trajectory. These results could help to more precisely identify individuals at higher risk of developing obesity-related health issues.

Addressing Structural Racism Is Critical for Ameliorating the Childhood Obesity Epidemic in Black Youth

Racism and childhood obesity are both pervasive factors adversely affecting the health and wellbeing of children and adolescents in the United States. The association between racism and obesity has been touched upon in the literature; yet most work has focused on a few dimensions of intersectionality of these two domains at one time. The renewed focus on structural racism as the primary contributor to distress of Black individuals in the United States has highlighted the urgency of identifying the contributions of racism to the childhood obesity epidemic. The current article is not a complete review of the literature, rather, it is meant to take a broad narrative review of the myriad ways in which racism contributes to the obesity epidemic in Black youth to serve as a call to action for more research, prevention, and intervention. The current article illustrates how a number of mechanisms for the etiology and maintenance of obesity are heavily influenced by racism and how addressing racism is critical for ameliorating the childhood obesity epidemic.

Examining the impacts of neighborhood poverty on bodyweight across the BMI distribution: a quantile and MSM modeling approach

PURPOSE

Given that the relationships between higher BMI and adverse health outcomes are nonconstant and most pronounced at either ends of the BMI distribution, we assess the association between neighborhood poverty and BMI at multiple points along the BMI distribution.

METHODS

Using data from the 1999 to 2015 Panel Study of Income Dynamics of Black and White adults in the United States, we estimate quantile regression models while jointly applying a marginal structural modeling approach to account for time-varying individual-level factors that may be simultaneously mediators as well as confounders.

RESULTS

Neighborhood poverty was not found to be associated with bodyweight at any point along the BMI distribution for Black or White males. However, high neighborhood poverty, compared to low neighborhood poverty, predicted increases in bodyweight for Black females at the lower end of the BMI distribution and for White females at the higher end of the BMI distribution. No association was found between neighborhood poverty and BMI at the mean.

CONCLUSIONS

Results identify the most vulnerable subgroups, suggesting that White females at the higher end of the BMI distribution as well as Black females at the lower end of the BMI distribution are particularly sensitive to obesogenic environments.

Socioeconomic inequalities in co-morbidity of overweight, obesity and mental ill-health from adolescence to mid-adulthood in two national birth cohort studies

AIM

To examine socioeconomic inequalities in comorbidity risk for overweight (including obesity) and mental ill-health in two national cohorts. We investigated independent effects of childhood and adulthood socioeconomic disadvantage on comorbidity from childhood to mid-adulthood, and differences by sex and cohort.

METHODS

Data were from 1958 National Child Development Study (NCDS58) and 1970 British Cohort Study (BCS70) [total N=30,868, 51% males] assessed at ages 10, 16, 23/26, 34 and 42 years. Socioeconomic indicators included childhood and adulthood social class and educational level. Risk for i. having healthy BMI and mental ill-health, ii. overweight and good mental health, and iii. overweight and mental ill-health was analysed using multinomial logistic regression.

FINDINGS

Socioeconomic disadvantage was consistently associated with greater risk for overweight-mental ill-health comorbidity at all ages (RRR 1.43, 2.04, 2.38, 1.64 and 1.71 at ages 10, 16, 23, 34 and 42 respectively for unskilled/skilled vs. professional/managerial class). The observed inequalities in co-morbidity were greater than those observed for either condition alone (overweight; RRR 1.39 and 1.25, mental ill-health; 1.36 and 1.22 at ages 16 and 42 respectively, for unskilled/skilled vs. professional/managerial class). In adulthood, both childhood and adulthood socioeconomic disadvantage were independently associated with comorbid overweight-mental ill-health, with a clear inverse gradient between educational level and risk for comorbidity. For instance, for the no education group (compared to university education) the RRR is 6.11 (95% CI 4.31-8.65) at age 34 and 4.42 (3.28-5.96) at age 42. There were no differences observed in the extent of inequalities by sex and differences between cohorts were limited.

INTERPRETATION

While socioeconomic disadvantage in childhood and adulthood are consistently and independently associated with greater risk for mental ill-health and being overweight separately, these associations are even larger for their comorbidity across the lifecourse. These findings are significant given the increasing global prevalence of obesity and mental ill-health, and their implications for lifelong health and mortality.

FUNDING

This research was supported by grants from the Wellcome Trust (ISSF3/ H17RCO/NG1) and Medical Research Council (MRC) [MC_UU_00019/3].

Adolescent Participation in Research, Policies and Guidelines for Chronic Disease Prevention: A Scoping Review Protocol

Adolescents (10-24 years old) account for 23% of the global population. Physical inactivity, suboptimal dietary intake, overweight, and obesity during adolescence are risk factors associated with chronic disease development into adulthood. Research, policies, and guidelines that seek to prevent chronic disease risk factor development rarely engage adolescents in planning and decision-making processes. The aims of this review are to investigate (i) how adolescents currently participate in research, policy, and guidelines for reduction of chronic disease risk factors, and (ii) provide recommendations to optimize adolescent participation in future research, policy, and guideline decision making for chronic disease prevention. A systematic scoping review of the health peer-review research, policy, and guidelines, using Arksey and O'Malley's six-stage framework, will be conducted. Participatory outcomes will be assessed based on the Lansdown-UNICEF conceptual framework for measuring adolescent participation. Classified as consultative, collaborative, or adolescent-led according to the degree of influence and power adolescents possess in the decision- making processes. Consultation with adolescents via digital surveys and focus groups will provide further information, perspective, and insight. Qualitative data will be analyzed by descriptive numerical summary and qualitative content analytical techniques. The title of this protocol is registered with Joanna Briggs Institute and Open Science Framework, doi:10.17605/OSF.IO/E3S64.

Using Electronic Medical Record Data to Better Understand Obesity in Hispanic Neighborhoods in El Paso, Texas

The prevalence of obesity has been persistent amongst Hispanics over the last 20 years. Socioeconomic inequities have led to delayed diagnosis and treatment of chronic medical conditions related to obesity. Factors contributing include lack of insurance and insufficient health education. It is well-documented that obesity amongst Hispanics is higher in comparison to non-Hispanics, but it is not well-understood how the socioeconomic context along with Hispanic ethnic concentration impact the prevalence of obesity within a community. Specifically studying obesity within Hispanic dominant regions of the United States, along the Texas–Mexico border will aid in understanding this relationship. El Paso, Texas is predominantly Mexican-origin Hispanic, making up 83% of the county’s total population. Through the use of electronic medical records, BMI averages along with obesity prevalence were analyzed for 161 census tracts in the El Paso County. Geographic weighted regression and Hot Spot technology were used to analyze the data. This study did identify a positive association between Hispanic ethnic concentration and obesity prevalence within the El Paso County. Median income did have a direct effect on obesity prevalence while evidence demonstrates that higher education is protective for health.