Obesity among black women in food deserts: An "omnibus" test of differential risk

Neighborhood factors and triple negative breast cancer: The role of cumulative exposure to area-level risk factors

BACKGROUND

Despite similar incidence rates among Black and White women, breast cancer mortality rates are 40% higher among Black women. More than half of the racial difference in breast cancer mortality can be attributed to triple negative breast cancer (TNBC), an aggressive subtype of invasive breast cancer that disproportionately affects Black women. Recent research has implicated neighborhood conditions in the etiology of TNBC. This study investigated the relationship between cumulative neighborhood-level exposures and TNBC risk.

METHODS

This single-institution retrospective study was conducted on a cohort of 3316 breast cancer cases from New Castle County, Delaware (from 2012 to 2020), an area of the country with elevated TNBC rates. Cases were stratified into TNBC and "Non-TNBC" diagnosis and geocoded by residential address. Neighborhood exposures included census tract-level measures of unhealthy alcohol use, metabolic dysfunction, breastfeeding, and environmental hazards. An overall cumulative risk score was calculated based on tract-level exposures.

RESULTS

Univariate analyses showed each tract-level exposure was associated with greater TNBC odds. In multivariate analyses that controlled for patient-level race and age, tract-level exposures were not associated with TNBC odds. However, in a second multivariate model that included patient-level variables and considered tract-level risk factors as a cumulative exposure risk score, each one unit increase in cumulative exposure was significantly associated with a 10% increase in TNBC odds. Higher cumulative exposure risk scores were found in census tracts with relatively high proportions of Black residents.

CONCLUSIONS

Cumulative exposure to neighborhood-level risk factors that disproportionately affect Black communities was associated with greater TNBC risk.

Meta-Analysis and Systematic Review of Resting-State High-Frequency Heart Rate Variability in Binge-Eating Disorder

Abstract. Binge-eating disorder (BED) is associated with a greater risk for cardiac problems and co-occurring health conditions. Resting-state measures of high-frequency heart rate variability (HF-HRV), which is a physiological proxy of self-regulatory neural functioning, may aid understanding of health risks. We systematically reviewed and meta-analyzed the literature on HF-HRV in individuals with BED and without BED. Six studies were reviewed in the qualitative synthesis, and five studies assessing HRV in individuals with BED ( n = 153) and without BED ( n = 124) were included in the meta-analysis. A non-significant effect size (Hedges’ g = .08, SE = 0.36, 95% CI [−0.62, 0.78]; z = 0.23, p = .82) was found, suggesting no difference in HF-HRV between groups. Age, BMI, and BMI-matched control status were not significant covariates. Synthesizing the five studies with available data, we found no difference in resting-state HF-HRV between individuals with and without BED. There was high heterogeneity in the sample, suggesting potential moderators. We discuss potential mechanisms, methodological and demographic confounds, and future directions for study.

A Population Health Assessment in a Community Cancer Center Catchment Area: Triple negative breast cancer, alcohol use, and obesity in New Castle County, Delaware

BACKGROUND

The National Cancer Institute (NCI) requires designated cancer centers to conduct catchment area assessments to guide cancer control and prevention efforts designed to reduce the local cancer burden. We extended and adapted this approach to a community cancer center catchment area with elevated rates of triple negative breast cancer (TNBC).

METHODS

Cancer registry data for 462 TNBC and 2,987 Not-TNBC cases diagnosed between 2012 and 2020 at the Helen F. Graham Cancer Center & Research Institute (HFGCCRI), located in New Castle County, Delaware, were geocoded to detect areas of elevated risk ('hot spots') and decreased risk ('cold spots'). Next, electronic health record (EHR) data on obesity and alcohol use disorder (AUD) and catchment-area measures of fast-food and alcohol retailers were used to assess for spatial relationships between TNBC hot spots and potentially modifiable risk factors.

RESULTS

Two hot and two cold spots were identified for TNBC within the catchment area. The hot spots accounted for 11% of the catchment area but nearly a third of all TNBC cases. Higher rates of unhealthy alcohol use and obesity were observed within the hot spots.

CONCLUSIONS

The use of spatial methods to analyze cancer registry and other secondary data sources can inform cancer control and prevention efforts within community cancer center catchment areas, where limited resources can preclude the collection of new primary data.

IMPACT

Targeting community outreach and engagement activities to TNBC hot spots offers the potential to reduce the population-level burden of cancer efficiently and equitably.

Racial Disparities in Stillbirth Risk Factors among non-Hispanic Black Women and non-Hispanic White Women in the United States

INTRODUCTION

Historically, stillbirth risk factors are more prevalent among non-Hispanic Black women than non-Hispanic White women, including age < 20, lower formal educational attainment, prepregnancy obesity, smoking, hypertension, diabetes, short interpregnancy interval, small for gestational age newborn, late prenatal care, and previous cesarean birth. We examined whether these disparities have changed since 2011 and identified a group of risk factors that differed between Black women and White women when accounting for correlations among variables.

METHODS

In a random sample of 315 stillbirths from the National Center for Health Statistics' 2016 fetal death data, Black women and White women were compared for each risk factor using t-tests or chi-square tests. Variables with p ≤ .20 were analyzed using multivariate analysis of variance.

RESULTS

In this sample, Black women experiencing stillbirth were less likely to have a Bachelor's degree (12.94% vs. 28.49%, p = .04), and more likely to be obese (44.5% vs. 29.1%, p = .01) than White women. Multivariate analysis accounting for correlations among variables showed a group of risk factors that differed between Black women and White women: age < 20, lower education, prepregnancy obesity, hypertension (chronic and pregnancy-associated), nulliparity before stillbirth, and earlier gestation.

CLINICAL IMPLICATIONS

Less formal education, obesity, age <20, hypertension, chronic and pregnancy-associated, nulliparity, and earlier gestation are important to consider in multilevel stillbirth prevention interventions to decrease racial disparity in stillbirth. Respectfully listening to women and taking their concerns seriously is one way nurses and other health care providers can promote equity in health outcomes for childbearing women.

Obesity and the Bidirectional Risk of Cancer and Cardiovascular Diseases in African Americans: Disparity vs. Ancestry

Cardiovascular disease (CVD) and cancer often occur in the same individuals, in part due to the shared risk factors such as obesity. Obesity promotes adipose inflammation, which is pathogenically linked to both cardiovascular disease and cancer. Compared with Caucasians, the prevalence of obesity is significantly higher in African Americans (AA), who exhibit more pronounced inflammation and, in turn, suffer from a higher burden of CVD and cancer-related mortality. The mechanisms that underlie this association among obesity, inflammation, and the bidirectional risk of CVD and cancer, particularly in AA, remain to be determined. Socio-economic disparities such as lack of access to healthy and affordable food may promote obesity and exacerbate hypertension and other CVD risk factors in AA. In turn, the resulting pro-inflammatory milieu contributes to the higher burden of CVD and cancer in AA. Additionally, biological factors that regulate systemic inflammation may be contributory. Mutations in atypical chemokine receptor 1 (ACKR1), otherwise known as the Duffy antigen receptor for chemokines (DARC), confer protection against malaria. Many AAs carry a mutation in the gene encoding this receptor, resulting in loss of its expression. ACKR1 functions as a decoy chemokine receptor, thus dampening chemokine receptor activation and inflammation. Published and preliminary data in humans and mice genetically deficient in ACKR1 suggest that this common gene mutation may contribute to ethnic susceptibility to obesity-related disease, CVD, and cancer. In this narrative review, we present the evidence regarding obesity-related disparities in the bidirectional risk of CVD and cancer and also discuss the potential association of gene polymorphisms in AAs with emphasis on ACKR1.

Green mobility and obesity risk: A longitudinal analysis in California

Previous work reports an inverse association between neighborhood greenness and obesity. Limitations of this work, which relies largely on cross-sectional data, include that studies often lack control for unmeasured genetic and sociodemographic factors that may confound associations, and cannot disentangle temporal order between neighborhood greenness and obesity. We move beyond a cross-sectional approach and leverage a longitudinal sibling-linked dataset with health, residential, and demographic information on women with two births in California between 2007 and 2015 (N = 552,929). We used a sibling comparison design to control for unmeasured stable characteristics of women and tested whether a positive change in neighborhood greenness (i.e., "upward green mobility") precedes a reduction in obesity risk. Models also adjusted for baseline obesity risk and time-varying individual- and neighborhood-level socioeconomic factors. As hypothesized, we find that upward green mobility varies inversely with the odds of obesity. Results indicate that small decreases in neighborhood greenness may also show protective associations with obesity risk. Our findings, if replicated, suggest that changing levels (particularly increases) of greenness in the residential environment may combat the rise of obesity.

Effects of a food hub initiative in a disadvantaged community: A quasi-experimental evaluation

A quasi-experiment evaluated a food hub's (FH) impact in a low-income/low-access (food desert) setting on fruit and vegetable (F&V) intake, diet quality, kilocalories, perceived food environment, BMI, and farmers' market shopping versus a matched community (n = 265 FH, n = 262 Comparison). Comparison shoppers had better baseline perceptions of their food environment, but FH shoppers improved significantly more than Comparison shoppers. Comparison shoppers significantly increased F&V intake versus FH shoppers. Effects were not significant for other diet outcomes, BMI, or farmers' market shopping. Factors besides spacial access to healthy food need consideration to address dietary intake and obesity in disadvantaged communities.

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

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