Application of a Novel Method for Assessing Cumulative Risk Burden by County

The purpose of this study is to apply the Human Security Index (HSI) as a tool to detect social and economic cumulative risk burden at a county-level in the state of Texas. The HSI is an index comprising a network of three sub-components or “fabrics”; the Economic, Environmental, and Social Fabrics. We hypothesized that the HSI will be a useful instrument for identifying and analyzing socioeconomic conditions that contribute to cumulative risk burden in vulnerable counties. We expected to identify statistical associations between cumulative risk burden and (a) ethnic concentration and (b) geographic proximity to the Texas-Mexico border. Findings from this study indicate that the Texas-Mexico border region did not have consistently higher total or individual fabric scores as would be suggested by the high disease burden and low income in this region. While the Economic, Environmental, Social Fabrics (including the Health subfabric) were highly associated with Hispanic ethnic concentration, the overall HSI and the Crime subfabric were not. In addition, the Education, Health and Crime subfabrics were associated with African American racial composition, while Environment, Economic and Social Fabrics were not. Application of the HSI to Texas counties provides a fuller and more nuanced understanding of socioeconomic and environmental conditions, and increases awareness of the role played by environmental, economic, and social factors in observed health disparities by race/ethnicity and geographic region

Dissecting The Influence of Perceived Discrimination and Genetic Liability on Mental Health

Background: Underrepresented groups are disproportionally affected by discrimination, which can have long-lasting influences on the individual’s wellbeing and mental health. This study leverages the diversity of the All of Us cohort to investigate the interplay between genetic risk factors and perceived discrimination in the context of mental health disorders. This study aims to shed light into the underlying biological and environmental risk factors, and its interplay, of mental health disorders in underrepresented populations. Methods: Data on perceived discrimination was retreived from the the All of Us (AoU) COVID-19 Participant Experience (COPE) questionnaire and matched with sociodemographic and phenotypic data. Perceived discrimination was considered as a binary variable (has the individual experienced discrimination in the past or not) thus including various types/sources of discrimination (e.g., racial, age, gender, economic status, etc.). Two major mood disorders: anxiety and depression were considered, phenotypes for these disorders were defined for each individual based on prescription medication use. ANOVA, CHI2, and regression models were implemented using python to further delve into the underlying risk factors in the population of study. Linear regression models were also constructed using a calculated discrimination score. Results: Preliminary results showed a total of 69,464 AoU participants who answered the discrimination questions within the COPE survey at any point. First survey responses for those participants were selected to be used for the data analysis. Medication use (anxiolytics and antidepressants) was assessed through participants medical records where 21,618 participants were prescribed one or more medications of the above two categories. The everyday discrimination score was constructed by summing the responses across all of the nine questions/ items assessing exposure, scores were then transformed to a mean item score by dividing the sum by number of completed items. Dose dependent associations reveal the impact of discrimination frequency on the individual’s wellbeing and mental health. Conclusion: The study uncovers a different perspective about the biological and environmental risk factors of mental health disorders in underrepresented populations. Mobilization of more resources to address the mental health burden in underrepresented populations is warranted

Cardiovascular disease risk among the Mexican American population in the Texas-Mexico border region, by age and length of residence in United States

Introduction: Although the relationship between health behaviors and outcomes such as smoking and obesity with longer residence in the United States among Mexican American immigrants is established, the relationship between length of residency in the United States and risk for cardiovascular disease (CVD) is not fully understood. The objective of this study was to determine the relationship between immigrant status, length of residence in the United States, age, and CVD markers in a sample of Mexican American adults living in Brownsville, Texas. Methods: We categorized participants in the Cameron County Hispanic Cohort study as immigrants in the United States for 10 years or less, immigrants in the United States for more than 10 years, or born in the United States. We conducted logistic and ordinary least squares regression for self-reported chronic conditions and CVD biomarkers. Results: We found bivariate differences in the prevalence of self-reported conditions and 1 CVD biomarker (low-density lipoprotein cholesterol) by length of residence in the middle (41-64 y) and younger (18-40 y) age groups. After adjusting for covariates, the following varied significantly by immigrant status: stroke and high cholesterol (self-reported conditions) and diastolic blood pressure, systolic blood pressure, total cholesterol, and low-density lipoprotein cholesterol (CVD biomarkers). Conclusion: The association between immigrant status, length of residence in the United States, and CVD markers varied. The effect of length of residence in the United States or immigrant status may depend on age and may be most influential in middle or older age

Using the Framingham Risk Score to Evaluate Immigrant Effect on Cardiovascular Disease Risk in Mexican Americans

Background—This study uses the Framingham Risk Score (FRS) for 10-year cardiovascular disease (CVD) to evaluate differences between Mexican American immigrants and the U.S.-born population. Methods and Results—Data from the Cameron County Hispanic Cohort (N=1,559). Average total risk scores were generated by age group for each gender. Regression analysis was conducted adjusting for covariates and interaction effects. Both women and men in the CCHC sample who were long-term immigrant residents (mean FRS scores women 4.2 with p\u3c.001 vs. men 4.0 with p\u3c.001) or born in the U.S. (mean FRS scores women 4.6 with p\u3c.001 vs. men 3.3 with p\u3c.001) had significantly higher risk scores than immigrants who had only been in this country for less than 10 years. The interaction model indicates that differences between immigrant and native-born Mexican Americans are most greatly felt at lowest levels of socioeconomic status for men in the CCHC. Conclusions—This study suggests that in terms of immigrant advantage in CVD risk, on whom, where, and how the comparisons are being made have important implications for the degree of difference observed

Diabetes screen during tuberculosis contact investigations highlights opportunity for new diabetes diagnosis and reveals metabolic differences between ethnic groups

Type 2 diabetes (T2D) is a prevalent risk factor for tuberculosis (TB), but most studies on TB-T2D have focused on TB patients, been limited to one community, and shown a variable impact of T2D on TB risk or treatment outcomes. We conducted a cross-sectional assessment of sociodemographic and metabolic factors in adult TB contacts with T2D (versus no T2D), from the Texas-Mexico border to study Hispanics, and in Cape Town to study South African Coloured ethnicities. The prevalence of T2D was 30.2% in Texas-Mexico and 17.4% in South Africa, with new diagnosis in 34.4% and 43.9%, respectively. Contacts with T2D differed between ethnicities, with higher smoking, hormonal contraceptive use and cholesterol levels in South Africa, and higher obesity in Texas-Mexico (p \u3c 0.05). PCA analysis revealed striking differences between ethnicities in the relationships between factors defining T2D and dyslipidemias. Our findings suggest that screening for new T2D in adult TB contacts is effective to identify new T2D patients at risk for TB. Furthermore, studies aimed at predicting individual TB risk in T2D patients, should take into account the heterogeneity in dyslipidemias that are likely to modify the estimates of TB risk or adverse treatment outcomes that are generally attributed to T2D alone

Application of a Novel Method for Assessing Cumulative Risk Burden by County

The purpose of this study is to apply the Human Security Index (HSI) as a tool to detect social and economic cumulative risk burden at a county-level in the state of Texas. The HSI is an index comprising a network of three sub-components or “fabrics”; the Economic, Environmental, and Social Fabrics. We hypothesized that the HSI will be a useful instrument for identifying and analyzing socioeconomic conditions that contribute to cumulative risk burden in vulnerable counties. We expected to identify statistical associations between cumulative risk burden and (a) ethnic concentration and (b) geographic proximity to the Texas-Mexico border. Findings from this study indicate that the Texas-Mexico border region did not have consistently higher total or individual fabric scores as would be suggested by the high disease burden and low income in this region. While the Economic, Environmental, Social Fabrics (including the Health subfabric) were highly associated with Hispanic ethnic concentration, the overall HSI and the Crime subfabric were not. In addition, the Education, Health and Crime subfabrics were associated with African American racial composition, while Environment, Economic and Social Fabrics were not. Application of the HSI to Texas counties provides a fuller and more nuanced understanding of socioeconomic and environmental conditions, and increases awareness of the role played by environmental, economic, and social factors in observed health disparities by race/ethnicity and geographic region

Diabetes screen during tuberculosis contact investigations highlights opportunity for new diabetes diagnosis and reveals metabolic differences between ethnic groups

Type 2 diabetes (T2D) is a prevalent risk factor for tuberculosis (TB), but most studies on TB-T2D have focused on TB patients, been limited to one community, and shown a variable impact of T2D on TB risk or treatment outcomes. We conducted a cross-sectional assessment of sociodemographic and metabolic factors in adult TB contacts with T2D (versus no T2D), from the Texas-Mexico border to study Hispanics, and in Cape Town to study South African Coloured ethnicities. The prevalence of T2D was 30.2% in Texas-Mexico and 17.4% in South Africa, with new diagnosis in 34.4% and 43.9%, respectively. Contacts with T2D differed between ethnicities, with higher smoking, hormonal contraceptive use and cholesterol levels in South Africa, and higher obesity in Texas-Mexico (p < 0.05). PCA analysis revealed striking differences between ethnicities in the relationships between factors defining T2D and dyslipidemias. Our findings suggest that screening for new T2D in adult TB contacts is effective to identify new T2D patients at risk for TB. Furthermore, studies aimed at predicting individual TB risk in T2D patients, should take into account the heterogeneity in dyslipidemias that are likely to modify the estimates of TB risk or adverse treatment outcomes that are generally attributed to T2D alone

Tuberculosis as a re-emerging disease and the risk in diabetics on the Texas Mexico border

Tuberculosis (TB) is the second cause of death worldwide due to a single infectious agent. The Texas- Mexico border has higher TB incidence rates (12/100,000 in the south Texas border with Mexico, and 30/100,000 in Tamaulipas in 2014) than the corresponding national averages of 2.96/100,000 for the US and 21/100,000 for Mexico. Chronic diseases such as diabetes mellitus (DM) compromise immunity and increase the risk of acquiring TB. DM is also associated with adverse TB treatment outcomes in those who have both diseases. As a follow-up of a previous study in 1998-2004, we reassessed the prevalence of DM and its associated factors among 8,431 TB patients using surveillance data from 2006-2013 for the Mexican state of Tamaulipas, across the border with Texas. Prevalence of DM was 25.2%, with an increase of at least 2.8% over the study period. Newly discovered factors associated with TB-DM (versus no DM) were lower education and higher unemployment (p\u3c 0.001), which are reportedly associated with poorer DM management. TB-DM patients were more likely to have smear-positive, pulmonary (versus extra-pulmonary) and drug-resistant TB (1.9-, 3.8- and 1.4-fold, respectively). During treatment, TB-DM patients were more likely to be smear-positive, and less likely to die or abandon TB treatment. Additionally, we assessed demographic and other clinical differences by adverse outcome status (treatment failure or death). Drug resistance was also assessed to detect those with a higher risk profile. We developed a risk score based on predictive modeling to assess the demographics and clinical presentation that distinguished those who later presented with adverse events. Final predictive models revealed that TB patients who failed their treatment regimen with first-line antibiotics were more likely to have at most a primary school education, MDR-TB, and few to moderate bacilli on AFB smear. TB patients who died during treatment were more likely to be older males with MDR-TB, HIV, malnutrition, and reporting excessive alcohol use. TB patients showing resistance to any of the five tested drugs were more likely to be younger presenting with pulmonary TB and have an initial positive AFB smear. Modified risk scores were developed with strong predictability for treatment failure and death, and moderate predictability for drug resistance. A separate set of risk scores that was developed for TB-DM patients showed moderate predictability for death. The available variables were not robust predictors of drug resistance, indicating the need for prompt testing or further characterization of TB patients at the time of diagnosis

Socioeconomic Context and the Food Landscape in Texas: Results from Hotspot Analysis and Border/Non-Border Comparison of Unhealthy Food Environments

Purpose: The purpose of this paper is to describe the food landscape of Texas using the CDC’s Modified Retail Food Environment (mRFEI) and to make comparisons by border/non-border. Methods: The Modified Retail Food Environment index (mRFEI (2008)) is an index developed by the CDC that measures what percent of the total food vendors in a census track sell healthy food. The range of values is 0 (unhealthy areas with limited access to fruits and vegetables) to (100—Healthy). These data were linked to 2010 US Census socioeconomic and ethnic concentration data. Spatial analysis and GIS techniques were applied to assess the differences between border and non-border regions. Variables of interest were mRFEI score, median income, total population, percent total population less than five years, median age, % receiving food stamps, % Hispanic, and % with a bachelor degree. Results: Findings from this study reveal that food environment in Texas tends to be characteristic of a “food desert”. Analysis also demonstrates differences by border/non-border location and percent of the population that is foreign born and by percent of families who receive food stamps. Conclusions: Identifying the relationship between socioeconomic disparity, ethnic concentration and mRFEI score could be a fundamental step in improving health in disadvantage communities, particularly those on the Texas-Mexico border

Using the Framingham Risk Score to Evaluate Immigrant Effect on Cardiovascular Disease Risk in Mexican Americans

BACKGROUND: This study uses the Framingham Risk Score (FRS) for 10-year cardiovascular disease (CVD) to evaluate differences between Mexican American immigrants and the U.S.-born population. METHODS AND RESULTS: Data from the Cameron County Hispanic Cohort (N=1,559). Average total risk scores were generated by age group for each gender. Regression analysis was conducted adjusting for covariates and interaction effects. Both women and men in the CCHC sample who were long-term immigrant residents (mean FRS scores women 4.2 with p<.001 vs. men 4.0 with p<.001) or born in the U.S. (mean FRS scores women 4.6 with p<.001 vs. men 3.3 with p<.001) had significantly higher risk scores than immigrants who had only been in this country for less than 10 years. The interaction model indicates that differences between immigrant and native-born Mexican Americans are most greatly felt at lowest levels of socioeconomic status for men in the CCHC. CONCLUSIONS: This study suggests that in terms of immigrant advantage in CVD risk, on whom, where, and how the comparisons are being made have important implications for the degree of difference observed