Association of Obesity and Diabetes With the Incidence of Breast Cancer in Louisiana.

INTRODUCTION: Breast cancer is a heterogeneous disease, consisting of multiple molecular subtypes. Obesity has been associated with an increased risk for postmenopausal breast cancer, but few studies have examined breast cancer subtypes separately. Obesity is often complicated by type 2 diabetes, but the possible association of diabetes with specific breast cancer subtypes remains poorly understood. METHODS: In this retrospective case-control study, Louisiana Tumor Registry records of primary invasive breast cancer diagnosed in 2010-2015 were linked to electronic health records in the Louisiana Public Health Institute's Research Action for Health Network. Controls were selected from Research Action for Health Network and matched to cases by age and race. Conditional logistic regression was used to identify metabolic risk factors. Data analysis was conducted in 2020‒2021. RESULTS: There was a significant association between diabetes and breast cancer for Luminal A, Triple-Negative Breast Cancer, and human epidermal growth factor 2‒positive subtypes. In multiple logistic regression, including both obesity status and diabetes as independent risk factors, Luminal A breast cancer was also associated with overweight status. Diabetes was associated with increased risk for Luminal A and Triple-Negative Breast Cancer in subgroup analyses, including women aged ≥50 years, Black women, and White women. CONCLUSIONS: Although research has identified obesity and diabetes as risk factors for breast cancer, these results underscore that comorbid risk is complex and may differ by molecular subtype. There was a significant association between diabetes and the incidence of Luminal A, Triple-Negative Breast Cancer, and human epidermal growth factor 2‒positive breast cancer in Louisiana.

Multiple mediation analysis with survival outcomes: With an application to explore racial disparity in breast cancer survival.

Mediation analysis allows the examination of effects of a third variable in the pathway between an exposure and an outcome. The general multiple mediation analysis method, proposed by Yu et al, improves traditional methods (eg, estimation of natural and controlled direct effects) to enable consideration of multiple mediators/confounders simultaneously and the use of linear and nonlinear predictive models for estimating mediation/confounding effects. In this paper, we extend the method for time-to-event outcomes and apply the method to explore the racial disparity in breast cancer survivals. Breast cancer is the most common cancer and the second leading cause of cancer death among women of all races. Despite improvement of survival rates of breast cancer in the US, a significant difference between white and black women remains. Previous studies have found that more advanced and aggressive tumors and less than optimal treatment may explain the lower survival rates for black women as compared to white women. Due to limitations of current analytic methods and the lack of comprehensive data sets, researchers have not been able to differentiate the relative effect each factor contributes to the overall racial disparity. We use the CDC-funded Patterns of Care study to examine the determinants of racial disparities in breast cancer survival using a novel multiple mediation analysis. Using the proposed method, we applied the Cox hazard model and multiple additive regression trees as predictive models and found that all racial disparity in survival among Louisiana breast cancer patients were explained by factors included in the study.

Using the emergency department to investigate smoking in young adults.

PURPOSE: Smoking in young adults identifies the population at risk for future tobacco-related disease. We investigated smoking in a young adult population and within high-risk groups using emergency department (ED) data in a metropolitan area. METHODS: Using the electronic health record, we performed a retrospective study of smoking in adults aged 18-30 years presenting to the ED. RESULTS: Smoking status was available for 55,777 subjects (90.9% of the total ED cohort); 60.8% were women, 55.0% were black, 35.3% were white, and 8.1% were Hispanic; 34.4% were uninsured. Most smokers used cigarettes (95.1%). Prevalence of current smoking was 21.7% for women and 42.5% for men. The electronic health record contains data about diagnosis and social history that can be used to investigate smoking status for high-risk populations. Smoking prevalence was highest for substance use disorder (58.0%), psychiatric illness (41.3%) and alcohol use (39.1%), and lowest for pregnancy (13.5%). In multivariable analyses, male gender, white race, lack of health insurance, alcohol use, and illicit drug use were independently associated with smoking. Smoking risk among alcohol and drug users varied by gender, race, and/or age. CONCLUSIONS: The ED provides access to a large, demographically diverse population, and supports investigation of smoking risk in young adults.

Absence of Adolescent Obesity in Grenada: Is This a Generational Effect?

Background: Low- and middle-income countries are affected disproportionately by the ongoing global obesity pandemic. Representing a middle income country, the high prevalence of obesity among Grenadian adults as compared to US adults is expected as part of global obesity trends. The objective of this study was to determine if Grenadian adolescents have a higher prevalence of overweight compared to their US counterparts, and if a disparity exists between urban and rural adolescents. Methods: Using a subcohort of participants in the Grenadian Nutrition Student Survey, diet quality and anthropometric measures were collected from 55% of the classrooms of first year secondary students in Grenada (n = 639). Rural or urban designations were given to each school. Body Mass Index (BMI) was calculated and categorized as overweight or obese for each student following CDC classification cutoffs. A standardized BMI (BMIz) was calculated for each school. Sex-specific BMI and overall BMIz were compared to a 1980s US cohort. Multilevel models, overall and stratified by sex, of students nested within schools were conducted to determine if BMIz differed by rural or urban locality, gender, and diet quality. Results: The mean age of this cohort was 12.7 (SD = 0.8) years with 83.8% of the cohort identifying as Afro-Caribbean. Females had nearly twice the prevalence of overweight when compared to males (22.7 vs. 12.2%) but a similar prevalence of obesity (8.2 vs. 6.8%). Grenadian adolescents had lower prevalence of overweight (females: 22.7 vs. 44.7%; males: 12.2 vs. 38.8%, respectively) as compared to US counterparts. Eating a traditional diet was negatively associated with BMIz score among females ( ß^ = -0.395; SE = 0.123) in a stratified, multilevel analysis. BMIz scores did not differ significantly by rural or urban school designation. Conclusions: Among Grenadian adolescents, this study identified a lower overweight prevalence compared to US counterparts and no difference in overweight prevalence by urban or rural location. We hypothesize that the late introduction of processed foods to Grenada protected this cohort from obesogenic promoters due to a lack of fetal overnutrition. However, further research in subsequent birth cohorts is needed to determine if adolescent obesity will increase due to a generational effect.

Neighborhood disadvantage and racial disparities in colorectal cancer incidence: a population-based study in Louisiana.

PURPOSE: Colorectal cancer (CRC) continues to demonstrate racial disparities in incidence and survival in the United States. This study investigates the role of neighborhood concentrated disadvantage in racial disparities in CRC incidence in Louisiana. METHODS: Louisiana Tumor Registry and U.S. Census data were used to assess the incidence of CRC diagnosed in individuals 35 years and older between 2008 and 2012. Neighborhood concentrated disadvantage index (CDI) was calculated based on the PhenX Toolkit protocol. The incidence of CRC was modeled using multilevel binomial regression with individuals nested within neighborhoods. RESULTS: Our study included 10,198 cases of CRC. Adjusting for age and sex, CRC risk was 28% higher for blacks than whites (risk ratio [RR] = 1.28; 95% confidence interval [CI] = 1.22-1.33). One SD increase in CDI was associated with 14% increase in risk for whites (RR = 1.14; 95% CI = 1.10-1.18) and 5% increase for blacks (RR = 1.05; 95% CI = 1.02-1.09). After controlling for differential effects of CDI by race, racial disparities were not observed in disadvantaged areas. CONCLUSION: CRC incidence increased with neighborhood disadvantage and racial disparities diminished with mounting disadvantage. Our results suggest additional dimensions to racial disparities in CRC outside of neighborhood disadvantage that warrants further research.

Neighborhood Environment Measurements and Anthropometric Indicators of Obesity: Results from the Women and Their Children's Health (WaTCH) Study.

We compared geographic information system (GIS)- and Census-based approaches for measuring the physical and social neighborhood environment at the census tract-level versus and audit approach on associations with body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR). Data were used from the 2012-2014 Women and Their Children's Health (WaTCH) Study (n=940). Generalized linear models were used to obtain odds ratios (ORs) for BMI (≥30 kg/m2), WC (>88 cm), and WHR (>0.85). Using an audit approach, more adverse neighborhood characteristics were associated with a higher odds of WC (OR: 1.10; 95% CI: 1.05, 1.15) and WHR (OR: 1.09; 95% CI: 1.05, 1.14) after adjustment for age, race/ethnicity, income, and oil spill exposure. There were no significant associations between GIS- and Census- based measures with obesity in adjusted models. Quality aspects of the neighborhood environment captured by audits at the individual-level may be more relevant to obesity than physical or social aspects at the census-tract level.

Exploring racial disparity in obesity: A mediation analysis considering geo-coded environmental factors.

Research shows aconsistent racial disparity in obesity between white and black adults in the United States. Accounting for the disparity is a challenge given the variety of the contributing factors, the nature of the association, and the multilevel relationships among the factors. We used the multivariable mediation analysis (MMA) method to explore the racial disparity in obesity considering not only the individual behavior but also geospatially derived environmental risk factors. Results from generalized linear models (GLM) were compared with those from multiple additive regression trees (MART) which allow for hierarchical data structure, and fitting of nonlinear and complex interactive relationships. As results, both individual and geographically defined factors contributed to the racial disparity in obesity. MART performed better than GLM models in that MART explained a larger proportion of the racial disparity in obesity. However, there remained disparities that cannot be explained by factors collected in this study.

A Reliable, Feasible Method to Observe Neighborhoods at High Spatial Resolution.

INTRODUCTION: Systematic social observation (SSO) methods traditionally measure neighborhoods at street level and have been performed reliably using virtual applications to increase feasibility. Research indicates that collection at even higher spatial resolution may better elucidate the health impact of neighborhood factors, but whether virtual applications can reliably capture social determinants of health at the smallest geographic resolution (parcel level) remains uncertain. This paper presents a novel, parcel-level SSO methodology and assesses whether this new method can be collected reliably using Google Street View and is feasible. METHODS: Multiple raters (N=5) observed 42 neighborhoods. In 2016, inter-rater reliability (observed agreement and kappa coefficient) was compared for four SSO methods: (1) street-level in person; (2) street-level virtual; (3) parcel-level in person; and (4) parcel-level virtual. Intra-rater reliability (observed agreement and kappa coefficient) was calculated to determine whether parcel-level methods produce results comparable to traditional street-level observation. RESULTS: Substantial levels of inter-rater agreement were documented across all four methods; all methods had >70% of items with at least substantial agreement. Only physical decay showed higher levels of agreement (83% of items with >75% agreement) for direct versus virtual rating source. Intra-rater agreement comparing street- versus parcel-level methods resulted in observed agreement >75% for all but one item (90%). CONCLUSIONS: Results support the use of Google Street View as a reliable, feasible tool for performing SSO at the smallest geographic resolution. Validation of a new parcel-level method collected virtually may improve the assessment of social determinants contributing to disparities in health behaviors and outcomes.

The Social Determinants of Health Core: Taking a Place-Based Approach.

INTRODUCTION: There is growing recognition that health disparities research needs to incorporate social determinants in the local environment into explanatory models. In the transdisciplinary setting of the Mid-South Transdisciplinary Collaborative Center (TCC), the Social Determinants of Health (SDH) Core developed an approach to incorporating SDH across a variety of studies. This place-based approach, which is geographically based, transdisciplinary, and inherently multilevel, is discussed. METHODS: From 2014 through 2016, the SDH Core consulted on a variety of Mid-South TCC research studies with the goal of incorporating social determinants into their research designs. The approach used geospatial methods (e.g., geocoding) to link individual data files with measures of the physical and social environment in the SDH Core database. Once linked, the method permitted various types of analysis (e.g., multilevel analysis) to determine if racial disparities could be explained in terms of social determinants in the local environment. RESULTS: The SDH Core consulted on five Mid-South TCC research projects. In resulting analyses for all the studies, a significant portion of the variance in one or more outcomes was partially explained by a social determinant from the SDH Core database. CONCLUSIONS: The SDH Core approach to addressing health disparities by linking neighborhood social and physical environment measures to an individual-level data file proved to be a successful approach across Mid-South TCC research projects.

Street Connectivity and Obesity Risk: Evidence From Electronic Health Records.

INTRODUCTION: This study aimed to determine the feasibility of using electronic health record (EHR) data from a federally qualified health center (FQHC) to assess the association between street connectivity, a measure of walkability for the local environment, and BMI obtained from EHRs. METHODS: The study included patients who visited Daughters of Charity clinics in 2012-2013. A total of 31,297 patients were eligible, of which 28,307 were geocoded. BMI and sociodemographic information were compiled into a de-identified database. The street connectivity measure was intersection density, calculated as the number of three-way or greater intersections per unit area. Multilevel analyses of BMI, measured on 17,946 patients who were aged ≥20 years, not pregnant, had complete sociodemographic information, and a BMI value that was not considered an outlier, were conducted using random intercept models. RESULTS: Overall, on average, patients were aged 44.1 years, had a BMI of 30.2, and were mainly non-Hispanic black (59.4%). An inverse association between BMI and intersection density was observed in multilevel models controlling for age, gender, race, and marital status. Tests for multiple interactions were conducted and a significant interaction between race and intersection density indicated the decrease in BMI was strongest for non-Hispanic whites (decreased by 2) compared with blacks or Hispanics (decreased by 0.6) (p=0.0121). CONCLUSIONS: EHRs were successfully used to assess the relationship between street connectivity and BMI in a multilevel framework. Increasing street connectivity levels measured as intersection density were inversely associated with directly measured BMI obtained from EHRs, demonstrating the feasibility of the approach.

Assessing mediation of behavioral and stress pathways in the association between neighborhood environments and obesity outcomes.

Although many studies have reported associations between characteristics of the neighborhood environment and obesity, little is understood about the pathways or mechanisms through which these associations operate. The purpose of this study was to examine possible behavioral and stress pathways hypothesized to mediate the association between neighborhood environments and obesity and whether pathways contribute to different obesity outcomes. Cross-sectional data were used from the 2012-2014 Women and Their Children's Health Study (WaTCH) in Louisiana (N = 909). Participants' neighborhoods, body mass index (BMI) and waist circumference (WC) were objectively measured. The causal inference approach to mediation analysis was used to obtain indirect estimates for self-reported measures of physical activity, low access to food, and depression. The mean BMI was 32.0 kg/m(2) and the mean WC was 98.6 cm. The (adverse) neighborhood environment was significantly associated BMI (ß = 0.17 kg/m(2); 95% Confidence Interval (CI): 0.03, 0.31) and WC (ß = 0.64; 95% CI: 0.34, 0.95, after adjusting for covariates. Neither depression, physical activity, nor low food access mediated those associations. Further research that investigates and uses better measures of the behavioral and stress pathways through which the neighborhood environment influences obesity is warranted.

Alcohol prevention on college campuses: the moderating effect of the alcohol environment on the effectiveness of social norms marketing campaigns.

OBJECTIVE: Evaluations of social norms marketing campaigns to reduce college student drinking have produced conflicting results. This study examines whether the effectiveness of such campaigns may be moderated by on-premise alcohol outlet density in the surrounding community. METHOD: Multilevel analyses were conducted of student survey responses (N= 19,838) from 32 U.S. colleges that took part in one of two 4-year randomized, controlled trials completed for the Social Norms Marketing Research Project (SNMRP). In the models, students by year were nested within treatment (n = 16) and control group (n = 16) campuses, which were characterized by the on-premise outlet density in their surrounding community. The moderating effect of outlet density was introduced into the models as an interaction between the treatment effect (i.e., the effect of the social norms marketing campaigns over time) and outlet density. The models were also stratified by campus alcohol outlet density (high vs. low) to examine the effect of the intervention in each type of setting. RESULTS: There was a significant interaction between the treatment effect and on-premise alcohol outlet density for one of the drinking outcomes targeted by the SNMRP intervention, the number of drinks when partying, and marginal evidence of interaction effects for two other outcomes, maximum recent consumption and a composite drinking scale. In stratified analyses, an intervention effect was observed for three of the four outcomes among students from campuses with lower on-premise alcohol outlet density, whereas no intervention effect was observed among students from campuses with higher on-premise alcohol outlet density. CONCLUSIONS: The findings suggest that the campus alcohol environment moderates the effect of social norms marketing interventions. Social norms marketing intervention may be less effective on campuses with higher densities of on-sale alcohol outlets.

Heavy episodic drinking on college campuses: does changing the legal drinking age make a difference?

OBJECTIVE: This article extends the compartmental model previously developed by Scribner et al. in the context of college drinking to a mathematical model of the consequences of lowering the legal drinking age. METHOD: Using data available from 32 U.S. campuses, the analyses separate underage and legal age drinking groups into an eight-compartment model with different alcohol availability (wetness) for the underage and legal age groups. The model evaluates the likelihood that underage students will incorrectly perceive normative drinking levels to be higher than they actually are (i.e., misperception) and adjust their drinking accordingly by varying the interaction between underage students in social and heavy episodic drinking compartments. RESULTS: The results evaluate the total heavy episodic drinker population and its dependence on the difference in misperception, as well as its dependence on underage wetness, legal age wetness, and drinking age. CONCLUSIONS: Results suggest that an unrealistically extreme combination of high wetness and low enforcement would be needed for the policies related to lowering the drinking age to be effective.

An ecological analysis of alcohol-outlet density and campus-reported violence at 32 U.S. colleges.

OBJECTIVE: The purpose of this study was to assess the relationships among campus violence, student drinking levels, and the physical availability of alcohol at off-campus outlets in a multisite design. METHOD: An ecological analysis of on-campus violence was conducted at 32 U.S. colleges. Dependent variables included campus-reported rates of rape, robbery, assault, and burglary obtained from a U.S. Department of Education online database for the years 2000-2004. Measures of student alcohol use and demographics were obtained from student surveys conducted for the Social Norms Marketing Research Project from 2000 to 2004. Measures of alcohol-outlet density within 3 miles of each campus were obtained from state alcohol-licensing authorities for 2004. RESULTS: Both on- and off-premise alcohol-outlet densities were associated with the campus rape-offense rate but not with the assault or robbery rates. Student drinking level was associated with both campus rape and assault rates but not with the campus robbery rate. The apparent effect of on-premise outlet density on campus rape-offense rates was reduced when student drinking level was included in the model, suggesting that the effect of on-premise outlet density may be mediated by student drinking level. Separate analyses revealed a similar mediational role for off-premise outlet density. CONCLUSIONS: These findings demonstrate that there is a campus-level association between sexual violence and the campus-community alcohol environment.

A multisite randomized trial of social norms marketing campaigns to reduce college student drinking: a replication failure.

A 14-site randomized trial tested the effectiveness of social norms marketing (SNM) campaigns, which present accurate student survey data in order to correct misperceptions of subjective drinking norms and thereby drive down alcohol use. Cross-sectional student surveys were conducted by mail at baseline and at posttest 3 years later. Hierarchical linear modeling was applied to examine multiple drinking outcomes, taking into account the nonindependence of students grouped in the same college. Controlling for other predictors, having a SNM campaign was not significantly associated with lower perceptions of student drinking levels or lower self-reported alcohol consumption. This study failed to replicate a previous multisite randomized trial of SNM campaigns, which showed that students attending institutions with a SNM campaign had a lower relative risk of alcohol consumption than students attending control group institutions (W. DeJong et al. J Stud Alcohol. 2006;67:868-879). Additional research is needed to explore whether SNM campaigns are less effective in campus communities with relatively high alcohol retail outlet density.

Geospatial methods for identification of core groups for HIV/AIDS.

OBJECTIVES: Disease transmission dynamics among members of a sexual network's core group make the group an ideal target for prevention for positives. Identifying the geographic territory of an HIV/AIDS core group is complicated by the numerous factors that may spatially structure cases including alcohol availability. We employ spatial analytic methods in an attempt to identify the geographic distribution of the core HIV/AIDS group. METHODS: Five year HIV/AIDS detection rates were analyzed for each HIV/AIDS risk category (i.e., MSM, IDU, HRH) at the census tract level (n = 164) in New Orleans using spatial analytic techniques in multivariate models. RESULTS: MSM was the most common risk category for newly detected HIV cases. Both MSM and IDU cases appeared to decline or enter an endemic phase. Each risk category exhibited unique spatial structure. Among IDUs and HRHs nearly all the spatial structure was explained in terms of the independent variables. However, among MSMs residual spatial structure remained after controlling for independent variables. CONCLUSIONS: Residual spatial structure in the MSM HIV/AIDS detection rates after controlling for social structure could be explained by the presence of core group members. The study's limitations are noted.

A multisite randomized trial of social norms marketing campaigns to reduce college student drinking.

OBJECTIVE: An 18-site randomized trial was conducted to determine the effectiveness of social norms marketing (SNM) campaigns in reducing college student drinking. The SNM campaigns are intended to correct misperceptions of subjective drinking norms and thereby drive down alcohol consumption. METHOD: Institutions of higher education were randomly assigned to treatment and control groups. At the treatment group institutions, SNM campaigns delivered school-specific, data-driven messages through a mix of campus media venues. Cross-sectional student surveys were conducted by mail at baseline (n = 2,771) and at posttest 3 years later (n = 2,939). Hierarchical linear modeling was applied to examine multiple drinking outcomes, taking intraclass correlation into account. RESULTS: Controlling for other predictors, having an SNM campaign was significantly associated with lower perceptions of student drinking levels and lower alcohol consumption, as measured by a composite drinking scale, recent maximum consumption, blood alcohol concentration for recent maximum consumption, drinks consumed when partying, and drinks consumed per week. A moderate mediating effect of normative perceptions on student drinking was demonstrated by an attenuation of the Experimental Group x Time interaction, ranging from 16.4% to 39.5% across measures. Additional models that took into account the intensity of SNM campaign activity at the treatment institutions suggested that there was a dose-response relationship. CONCLUSIONS: This study is the most rigorous evaluation of SNM campaigns conducted to date. Analysis revealed that students attending institutions that implemented an SNM campaign had a lower relative risk of alcohol consumption than students attending control group institutions.

Hierarchical modeling and other spatial analyses in prostate cancer incidence data.

BACKGROUND: State central cancer registries are often asked to respond to questions about the spatial distribution of cancer cases. Spatial analysis methods and technology are evolving rapidly, and can be a considerable challenge to registries that do not have staff with training in this area. The purpose of this article is to describe a general methodological approach that potentially might be a starting point for many cancer registry spatial analyses at the county level. METHODS: Prostate cancer incident cases (N=31,159) from the Louisiana Tumor Registry from 1988 to 1999 were used for illustrative purposes. To explore spatio-temporal patterns, analyses focused on four time periods, each 3 years in length: 1998-1990, 1991-1993, 1994-1996, and 1997-1999. For each time period, race-specific (white and black), direct age-adjusted incidence rates and indirect standardized incidence ratios (SIRs) were calculated, smoothed using Bayesian methods, and assessed for evidence of spatial autocorrelation using global and local Moran's I. Hierarchical generalized linear models (HGLM) were fitted to identify significant covariates. Clusters of elevated and lower rates were identified using a spatial scan statistic (SaTScan). RESULTS: Temporal trends in SIRs in both race groups were consistent with the introduction of prostate specific antigen (PSA) testing in Louisiana during the late 1980s and early 1990s, but possibly with a lag in black males. Clusters of lower than expected values were observed for white males in the central (p=0.001) and southeastern coastal areas (p=0.001), and to a greater extent for black males in the central (p=0.001), southwestern and southeastern coastal parishes (p=0.001). CONCLUSIONS: Mapping disease occurrence by time period is an effective way to explore spatio-temporal patterns. HGLM models and software are available to control for covariates and for unstructured and spatially structured variability that may confound spatial variability patterns.

Fast food, race/ethnicity, and income: a geographic analysis.

BACKGROUND: Environmental factors may contribute to the increasing prevalence of obesity, especially in black and low-income populations. In this paper, the geographic distribution of fast food restaurants is examined relative to neighborhood sociodemographics. METHODS: Using geographic information system software, all fast-food restaurants within the city limits of New Orleans, Louisiana, in 2001 were mapped. Buffers around census tracts were generated to simulate 1-mile and 0.5-mile "shopping areas" around and including each tract, and fast food restaurant density (number of restaurants per square mile) was calculated for each area. Using multiple regression, the geographic association between fast food restaurant density and black and low-income neighborhoods was assessed, while controlling for environmental confounders that might also influence the placement of restaurants (commercial activity, presence of major highways, and median home values). RESULTS: In 156 census tracts, a total of 155 fast food restaurants were identified. In the regression analysis that included the environmental confounders, fast-food restaurant density in shopping areas with 1-mile buffers was independently correlated with median household income and percent of black residents in the census tract. Similar results were found for shopping areas with 0.5-mile buffers. Predominantly black neighborhoods have 2.4 fast-food restaurants per square mile compared to 1.5 restaurants in predominantly white neighborhoods. CONCLUSIONS: The link between fast food restaurants and black and low-income neighborhoods may contribute to the understanding of environmental causes of the obesity epidemic in these populations.