Epidemiology & Biostatistics Research Works

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    Census Tract Food Tweets and Chronic Disease Outcomes in the U.S., 2015–2018
    (MDPI, 2019-03-18) Huang, Yuru; Huang, Dina; Nguyen, Quynh C.
    There is a growing recognition of social media data as being useful for understanding local area patterns. In this study, we sought to utilize geotagged tweets—specifically, the frequency and type of food mentions—to understand the neighborhood food environment and the social modeling of food behavior. Additionally, we examined associations between aggregated food-related tweet characteristics and prevalent chronic health outcomes at the census tract level. We used a Twitter streaming application programming interface (API) to continuously collect ~1% random sample of public tweets in the United States. A total of 4,785,104 geotagged food tweets from 71,844 census tracts were collected from April 2015 to May 2018. We obtained census tract chronic disease outcomes from the CDC 500 Cities Project. We investigated associations between Twitter-derived food variables and chronic outcomes (obesity, diabetes and high blood pressure) using the median regression. Census tracts with higher average calories per tweet, less frequent healthy food mentions, and a higher percentage of food tweets about fast food had higher obesity and hypertension prevalence. Twitter-derived food variables were not predictive of diabetes prevalence. Food-related tweets can be leveraged to help characterize the neighborhood social and food environment, which in turn are linked with community levels of obesity and hypertension.
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    Google Street View Derived Built Environment Indicators and Associations with State-Level Obesity, Physical Activity, and Chronic Disease Mortality in the United States
    (MDPI, 2020-05-22) Phan, Lynn; Yu, Weijun; Keralis, Jessica M.; Mukhija, Krishay; Dwivedi, Pallavi; Brunisholz, Kimberly D.; Javanmardi, Mehran; Tasdizen, Tolga; Nguyen, Quynh C.
    Previous studies have demonstrated that there is a high possibility that the presence of certain built environment characteristics can influence health outcomes, especially those related to obesity and physical activity. We examined the associations between select neighborhood built environment indicators (crosswalks, non-single family home buildings, single-lane roads, and visible wires), and health outcomes, including obesity, diabetes, cardiovascular disease, and premature mortality, at the state level. We utilized 31,247,167 images collected from Google Street View to create indicators for neighborhood built environment characteristics using deep learning techniques. Adjusted linear regression models were used to estimate the associations between aggregated built environment indicators and state-level health outcomes. Our results indicated that the presence of a crosswalk was associated with reductions in obesity and premature mortality. Visible wires were associated with increased obesity, decreased physical activity, and increases in premature mortality, diabetes mortality, and cardiovascular mortality (however, these results were not significant). Non-single family homes were associated with decreased diabetes and premature mortality, as well as increased physical activity and park and recreational access. Single-lane roads were associated with increased obesity and decreased park access. The findings of our study demonstrated that built environment features may be associated with a variety of adverse health outcomes.
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    Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases
    (MDPI, 2020-09-01) Nguyen, Quynh C.; Huang, Yuru; Kumar, Abhinav; Duan, Haoshu; Keralis, Jessica M.; Dwivedi, Pallavi; Meng, Hsien-Wen; Brunisholz, Kimberly D.; Jay, Jonathan; Javanmardi, Mehran; Tasdizen, Tolga
    The spread of COVID-19 is not evenly distributed. Neighborhood environments may structure risks and resources that produce COVID-19 disparities. Neighborhood built environments that allow greater flow of people into an area or impede social distancing practices may increase residents’ risk for contracting the virus. We leveraged Google Street View (GSV) images and computer vision to detect built environment features (presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires). We utilized Poisson regression models to determine associations of built environment characteristics with COVID-19 cases. Indicators of mixed land use (non-single family home), walkability (sidewalks), and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were connected with fewer COVID-19 cases. Percent black and percent with less than a high school education were associated with more COVID-19 cases. Our findings suggest that built environment characteristics can help characterize community-level COVID-19 risk. Sociodemographic disparities also highlight differential COVID-19 risk across groups of people. Computer vision and big data image sources make national studies of built environment effects on COVID-19 risk possible, to inform local area decision-making.
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    Racial and Sex Differences between Urinary Phthalates and Metabolic Syndrome among U.S. Adults: NHANES 2005–2014
    (MDPI, 2021-06-26) Ghosh, Rajrupa; Haque, Mefruz; Turner, Paul C.; Cruz-Cano, Raul; Dallal, Cher M.
    Phthalates, plasticizers ubiquitous in household and personal care products, have been associated with metabolic disturbances. Despite the noted racial differences in phthalate exposure and the prevalence of metabolic syndrome (MetS), it remains unclear whether associations between phthalate metabolites and MetS vary by race and sex. A cross-sectional analysis was conducted among 10,017 adults from the National Health and Nutritional Examination Survey (2005–2014). Prevalence odds ratios (POR) and 95% confidence intervals (CIs) were estimated for the association between 11 urinary phthalate metabolites and MetS using weighted sex and race stratified multivariable logistic regression. Higher MCOP levels were significantly associated with increased odds of MetS among women but not men, and only remained significant among White women (POR Q4 vs. Q1 = 1.68, 95% CI: 1.24, 2.29; p-trend = 0.001). Similarly, the inverse association observed with MEHP among women, persisted among White women only (POR Q4 vs. Q1 = 0.53, 95% CI: 0.35, 0.80; p-trend = 0.003). However, ΣDEHP metabolites were associated with increased odds of MetS only among men, and this finding was limited to White men (POR Q4 vs. Q1 = 1.54, 95% CI: 1.01, 2.35; p-trend = 0.06). Among Black men, an inverse association was observed with higher MEP levels (POR Q4 vs. Q1 = 0.43, 95% CI: 0.24, 0.77; p-trend = 0.01). The findings suggest differential associations between phthalate metabolites and MetS by sex and race/ethnicity.
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    Google Street View-Derived Neighborhood Characteristics in California Associated with Coronary Heart Disease, Hypertension, Diabetes
    (MDPI, 2021-10-03) Nguyen, Thu T.; Nguyen, Quynh C.; Rubinsky, Anna D.; Tasdizen, Tolga; Deligani, Amir Hossein Nazem; Dwivedi, Pallavi; Whitaker, Ross; Fields, Jessica D.; DeRouen, Mindy C.; Mane, Heran; Lyles, Courtney R.; Brunisholz, Kim D.; Bibbins-Domingo, Kirsten
    Characteristics of the neighborhood built environment influence health and health behavior. Google Street View (GSV) images may facilitate measures of the neighborhood environment that are meaningful, practical, and adaptable to any geographic boundary. We used GSV images and computer vision to characterize neighborhood environments (green streets, visible utility wires, and dilapidated buildings) and examined cross-sectional associations with chronic health outcomes among patients from the University of California, San Francisco Health system with outpatient visits from 2015 to 2017. Logistic regression models were adjusted for patient age, sex, marital status, race/ethnicity, insurance status, English as preferred language, assignment of a primary care provider, and neighborhood socioeconomic status of the census tract in which the patient resided. Among 214,163 patients residing in California, those living in communities in the highest tertile of green streets had 16–29% lower prevalence of coronary artery disease, hypertension, and diabetes compared to those living in communities in the lowest tertile. Conversely, a higher presence of visible utility wires overhead was associated with 10–26% more coronary artery disease and hypertension, and a higher presence of dilapidated buildings was associated with 12–20% greater prevalence of coronary artery disease, hypertension, and diabetes. GSV images and computer vision models can be used to understand contextual factors influencing patient health outcomes and inform structural and place-based interventions to promote population health.
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    Meta-Analysis of Transcriptome-Wide Association Studies across 13 Brain Tissues Identified Novel Clusters of Genes Associated with Nicotine Addiction
    (MDPI, 2021-12-23) Ye, Zhenyao; Mo, Chen; Ke, Hongjie; Yan, Qi; Chen, Chixiang; Kochunov, Peter; Hong, L. Elliot; Mitchell, Braxton D.; Chen, Shuo; Ma, Tianzhou
    Genome-wide association studies (GWAS) have identified and reproduced thousands of diseases associated loci, but many of them are not directly interpretable due to the strong linkage disequilibrium among variants. Transcriptome-wide association studies (TWAS) incorporated expression quantitative trait loci (eQTL) cohorts as a reference panel to detect associations with the phenotype at the gene level and have been gaining popularity in recent years. For nicotine addiction, several important susceptible genetic variants were identified by GWAS, but TWAS that detected genes associated with nicotine addiction and unveiled the underlying molecular mechanism were still lacking. In this study, we used eQTL data from the Genotype-Tissue Expression (GTEx) consortium as a reference panel to conduct tissue-specific TWAS on cigarettes per day (CPD) over thirteen brain tissues in two large cohorts: UK Biobank (UKBB; number of participants (N) = 142,202) and the GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN; N = 143,210), then meta-analyzing the results across tissues while considering the heterogeneity across tissues. We identified three major clusters of genes with different meta-patterns across tissues consistent in both cohorts, including homogenous genes associated with CPD in all brain tissues; partially homogeneous genes associated with CPD in cortex, cerebellum, and hippocampus tissues; and, lastly, the tissue-specific genes associated with CPD in only a few specific brain tissues. Downstream enrichment analyses on each gene cluster identified unique biological pathways associated with CPD and provided important biological insights into the regulatory mechanism of nicotine dependence in the brain.
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    Google Street View Images as Predictors of Patient Health Outcomes, 2017–2019
    (MDPI, 2022-01-27) Nguyen, Quynh C.; Belnap, Tom; Dwivedi, Pallavi; Deligani, Amir Hossein Nazem; Kumar, Abhinav; Li, Dapeng; Whitaker, Ross; Keralis, Jessica; Mane, Heran; Yue, Xiaohe; Nguyen, Thu T.; Tasdizen, Tolga; Brunisholz, Kim D.
    Collecting neighborhood data can both be time- and resource-intensive, especially across broad geographies. In this study, we leveraged 1.4 million publicly available Google Street View (GSV) images from Utah to construct indicators of the neighborhood built environment and evaluate their associations with 2017–2019 health outcomes of approximately one-third of the population living in Utah. The use of electronic medical records allows for the assessment of associations between neighborhood characteristics and individual-level health outcomes while controlling for predisposing factors, which distinguishes this study from previous GSV studies that were ecological in nature. Among 938,085 adult patients, we found that individuals living in communities in the highest tertiles of green streets and non-single-family homes have 10–27% lower diabetes, uncontrolled diabetes, hypertension, and obesity, but higher substance use disorders—controlling for age, White race, Hispanic ethnicity, religion, marital status, health insurance, and area deprivation index. Conversely, the presence of visible utility wires overhead was associated with 5–10% more diabetes, uncontrolled diabetes, hypertension, obesity, and substance use disorders. Our study found that non-single-family and green streets were related to a lower prevalence of chronic conditions, while visible utility wires and single-lane roads were connected with a higher burden of chronic conditions. These contextual characteristics can better help healthcare organizations understand the drivers of their patients’ health by further considering patients’ residential environments, which present both risks and resources.
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    Pre-Exposure Prophylaxis Interventions among Black Sexual Minority Men: A Systematic Literature Review
    (MDPI, 2022-02-09) Turpin, Rodman E.; Hawthorne, David J.; Rosario, Andre D.
    Background: Interventions to promote HIV pre-exposure prophylaxis (PrEP) among Black sexual minority men (BSMM) are especially important, given the disproportionate HIV incidence and relatively low uptake of PrEP among BSMM. Methods: We conducted a systematic literature review to identify the characteristics of interventions between 2016 and 2021 promoting PrEP use among BSMM. We synthesized these studies based on sample size, location, the use of peer-based delivery, and key intervention targets. Results: Of the starting total 198 articles, 10 were included in the final review, with the majority of included studies being randomized controlled trials. We identified providing PrEP access, PrEP counseling, HIV and PrEP education, linkage to general health care, and peer-based support as key successful intervention components. The starkest difference between interventions with and without demonstrated PrEP improvements was the outcome: all interventions focused on PrEP initiation led to large improvements, but those focused on PrEP adherence did not. No other factors demonstrated distinct differences between successful and unsuccessful interventions. Conclusion: We identified notable differences in intervention efficacy between PrEP initiation and PrEP adherence outcomes; PrEP adherence is necessary for optimal HIV prevention. Future interventions promoting and measuring PrEP adherence, with a focus on cultural competence and peer components, are recommended.
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    Multivariate Threshold Regression Models with Cure Rates: Identification and Estimation in the Presence of the Esscher Property
    (MDPI, 2022-02-11) Lee, Mei-Ling Ting; Whitmore, George A.
    The first hitting time of a boundary or threshold by the sample path of a stochastic process is the central concept of threshold regression models for survival data analysis. Regression functions for the process and threshold parameters in these models are multivariate combinations of explanatory variates. The stochastic process under investigation may be a univariate stochastic process or a multivariate stochastic process. The stochastic processes of interest to us in this report are those that possess stationary independent increments (i.e., Lévy processes) as well as the Esscher property. The Esscher transform is a transformation of probability density functions that has applications in actuarial science, financial engineering, and other fields. Lévy processes with this property are often encountered in practical applications. Frequently, these applications also involve a ‘cure rate’ fraction because some individuals are susceptible to failure and others not. Cure rates may arise endogenously from the model alone or exogenously from mixing of distinct statistical populations in the data set. We show, using both theoretical analysis and case demonstrations, that model estimates derived from typical survival data may not be able to distinguish between individuals in the cure rate fraction who are not susceptible to failure and those who may be susceptible to failure but escape the fate by chance. The ambiguity is aggravated by right censoring of survival times and by minor misspecifications of the model. Slightly incorrect specifications for regression functions or for the stochastic process can lead to problems with model identification and estimation. In this situation, additional guidance for estimating the fraction of non-susceptibles must come from subject matter expertise or from data types other than survival times, censored or otherwise. The identifiability issue is confronted directly in threshold regression but is also present when applying other kinds of models commonly used for survival data analysis. Other methods, however, usually do not provide a framework for recognizing or dealing with the issue and so the issue is often unintentionally ignored. The theoretical foundations of this work are set out, which presents new and somewhat surprising results for the first hitting time distributions of Lévy processes that have the Esscher property.
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    Sexual Risk Behavior and Lifetime HIV Testing: The Role of Adverse Childhood Experiences
    (MDPI, 2022-04-05) Dyer, Typhayne V.; Turpin, Rodman E.; Hawthorne, David J.; Jain, Vardhmaan; Sayam, Sonica; Mittal, Mona
    Despite the success of HIV prevention drugs such as PrEP, HIV incident transmission rates remain a significant problem in the United States. A life-course perspective, including experiences of childhood adversity, may be useful in addressing the HIV epidemic. This paper used 2019 BRFSS data to elucidate the role that childhood adversity plays in the relationship between HIV risk and HIV testing. Participants (n = 58,258) completed self-report measures of HIV risk behaviors, HIV testing, and adverse childhood experiences (ACEs). The median number ACEs in the sample was 1, with verbal abuse (33.9%), and parental separation (31.3%) being the most common ACEs reported. Bivariate findings showed that all ACEs were associated with increased HIV risk and testing. However, increased risk was not correlated with increased HIV testing, with the highest incongruence related to mental health problems of household member (53.48%). While both self-reported HIV risk and ACEs were positively associated with HIV testing, their interaction had a negative association with testing (aPR = 0.51, 95%CI 0.42, 0.62). The results highlight the need for targeted HIV prevention strategies for at-risk individuals with a history of childhood adversity.
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    Reducing Anxiety with Nature and Gardening (RANG): Evaluating the Impacts of Gardening and Outdoor Activities on Anxiety among U.S. Adults during the COVID-19 Pandemic
    (MDPI, 2022-04-22) Gerdes, Megan E.; Aistis, Lucy A.; Sachs, Naomi A.; Williams, Marcus; Roberts, Jennifer D.; Rosenberg, Goldstein Rachel E.
    The COVID-19 pandemic impacted mental health. Growing research has identified the mental health benefits of nature contact, including gardening. We used a cross-sectional survey to investigate the association between gardening and other outdoor activities with anxiety among U.S. adults. The RANG (Reducing Anxiety with Nature and Gardening) survey was distributed online from June–September 2020 through social media (Twitter and Facebook) and a national Master Gardeners listserv. Survey questions captured demographics, COVID-19 experiences, gardening, outdoor activities, and anxiety using the Generalized Anxiety Disorder 7-item scale. Data were analyzed using chi-square, Fisher’s exact, and Kruskal–Wallis tests, as well as logistic regression. Among participants, 46% reported anxiety symptoms. Participants who had gardened ≥ 15 years and those gardening > 8 h over two weeks had lower anxiety scores. Spending more time outdoors on weekdays also decreased anxiety scores. After adjusting for covariates, lower odds of anxiety were identified for 50–69 and 70–89-year-olds vs. 18–29-year-olds; males vs. females; and Texas vs. Maryland residents. These findings confirm increased anxiety during the COVID-19 pandemic and suggest that sustained gardening and other outdoor activities could help reduce anxiety.
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    Trends in Health Care Access/Experiences: Differential Gains across Sexuality and Sex Intersections before and after Marriage Equality
    (MDPI, 2022-04-21) Turpin, Rodman E.; Williams, Natasha D.; Akré, Ellesse-Roselee L.; Boekeloo, Bradley O.; Fish, Jessica N.
    Background: Sexual minority adults experience several health care access inequities compared to their heterosexual peers; such inequities may be affected by LGBTQ+ legislation, such as the 2015 national marriage equality ruling. Methods: Using population-based data (n = 28,463) from the Association of American Medical Colleges biannual Consumer Survey of Health Care Access, we calculated trend ratios (TR) for indicators of health care access (e.g., insurance coverage, delaying or forgoing care due to cost) and satisfaction (e.g., general satisfaction, being mistreated due to sexual orientation) from 2013 to 2018 across sexuality and sex. We also tested for changes in trends related to the 2015 marriage equality ruling using interrupted time series trend interactions (TRInt). Results: The largest increases in access were observed in gay men (TR = 2.42, 95% CI 1.28, 4.57). Bisexual men had decreases in access over this period (TR = 0.47, 95% CI 0.22, 0.99). Only gay men had a significant increase in the health care access trend after U.S. national marriage equality (TRInt = 5.59, 95% CI 2.00, 9.18), while other sexual minority groups did not. Conclusions: We found that trends in health care access and satisfaction varied significantly across sexualities and sex. Our findings highlight important disparities in how federal marriage equality has benefited sexual minority groups.
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    Emotions, Strategies, and Health: Examining the Impact of an Educational Program on Tanzanian Preschool Children
    (MDPI, 2022-05-12) Kauffman, Lauren E.; Dura, Elizabeth A.; Borzekowski, Dina L. G.
    Around the world, well-produced television programming can engage vulnerable, hard-to-reach audiences by offering informal education and enrichment. Akili and Me is an animated children’s educational program available in Sub-Saharan Africa that provides age and culturally appropriate lessons. In 2018, the producers created socio-emotional and health content. This study examines the relationship between children’s exposure to the new Akili and Me content and socio-emotional and health outcomes. Participants included low-income school children (mean age 5.32 years, SD = 0.82) from Arusha, Tanzania. Researchers conducted one-on-one baseline and post-intervention surveys with each participant. Over 12 weeks, the children attended afterschool sessions with screenings of Akili and Me, with distinct content screened on different days. The research team recorded children’s attendance and assessed children’s receptivity to the program through character identification. Using MLM regression models with data from 411 participants from 10 public schools, the analyses showed that a greater exposure and receptivity to Akili and Me predicted improved outcomes scores on the socio-emotional and health outcomes, controlling for sex, age, baseline scores, and general media receptivity (non-Akili and Me characters). Contributing to the literature on educational media, this study shows that exposure to an animated program can teach vulnerable preschool children socio-emotional and health content.
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    Social Network Analysis on the Mobility of Three Vulnerable Population Subgroups: Domestic Workers, Flight Crews, and Sailors during the COVID-19 Pandemic in Hong Kong
    (MDPI, 2022-06-21) Yu, Weijun; Alipio, Cheryll; Wan, Jia'an; Mane, Heran; Nguyen, Quynh C.
    Background: Domestic workers, flight crews, and sailors are three vulnerable population subgroups who were required to travel due to occupational demand in Hong Kong during the COVID-19 pandemic. Objective: The aim of this study was to explore the social networks among three vulnerable population subgroups and capture temporal changes in their probability of being exposed to SARS-CoV-2 via mobility. Methods: We included 652 COVID-19 cases and utilized Exponential Random Graph Models to build six social networks: one for the cross-sectional cohort, and five for the temporal wave cohorts, respectively. Vertices were the three vulnerable population subgroups. Edges were shared scenarios where vertices were exposed to SARS-CoV-2. Results: The probability of being exposed to a COVID-19 case in Hong Kong among the three vulnerable population subgroups increased from 3.38% in early 2020 to 5.78% in early 2022. While domestic workers were less mobile intercontinentally compared to flight crews and sailors, domestic workers were 1.81-times in general more likely to be exposed to SARS-CoV-2. Conclusions: Vulnerable populations with similar ages and occupations, especially younger domestic workers and flight crew members, were more likely to be exposed to SARS-CoV-2. Social network analysis can be used to provide critical information on the health risks of infectious diseases to vulnerable populations.
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    Using Convolutional Neural Networks to Derive Neighborhood Built Environments from Google Street View Images and Examine Their Associations with Health Outcomes
    (MDPI, 2022-09-24) Yue, Xiaohe; Antonietti, Anne; Alirezaei, Mitra; Tasdizen, Tolga; Li, Dapeng; Nguyen, Leah; Mane, Heran; Sun, Abby; Hu. Ming; Whitaker, Ross T.; Nguyen, Quynh C.
    Built environment neighborhood characteristics are difficult to measure and assess on a large scale. Consequently, there is a lack of sufficient data that can help us investigate neighborhood characteristics as structural determinants of health on a national level. The objective of this study is to utilize publicly available Google Street View images as a data source for characterizing built environments and to examine the influence of built environments on chronic diseases and health behaviors in the United States. Data were collected by processing 164 million Google Street View images from November 2019 across the United States. Convolutional Neural Networks, a class of multi-layer deep neural networks, were used to extract features of the built environment. Validation analyses found accuracies of 82% or higher across neighborhood characteristics. In regression analyses controlling for census tract sociodemographics, we find that single-lane roads (an indicator of lower urban development) were linked with chronic conditions and worse mental health. Walkability and urbanicity indicators such as crosswalks, sidewalks, and two or more cars were associated with better health, including reduction in depression, obesity, high blood pressure, and high cholesterol. Street signs and streetlights were also found to be associated with decreased chronic conditions. Chain link fence (physical disorder indicator) was generally associated with poorer mental health. Living in neighborhoods with a built environment that supports social interaction and physical activity can lead to positive health outcomes. Computer vision models using manually annotated Google Street View images as a training dataset were able to accurately identify neighborhood built environment characteristics. These methods increases the feasibility, scale, and efficiency of neighborhood studies on health.
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    Examination of the Public’s Reaction on Twitter to the Over-Turning of Roe v Wade and Abortion Bans
    (MDPI, 2022-11-29) Mane, Heran; Yue, Xiaohe; Yu, Weijun; Doig, Amara Channell; Wei, Hanxue; Delcid, Nataly; Harris, Afia-Grace; Nguyen, Thu T.; Nguyen, Quynh C.
    The overturning of Roe v Wade reinvigorated the national debate on abortion. We used Twitter data to examine temporal, geographical and sentiment patterns in the public’s reaction. Using the Twitter API for Academic Research, a random sample of publicly available tweets was collected from 1 May–15 July in 2021 and 2022. Tweets were filtered based on keywords relating to Roe v Wade and abortion (227,161 tweets in 2021 and 504,803 tweets in 2022). These tweets were tagged for sentiment, tracked by state, and indexed over time. Time plots reveal low levels of conversations on these topics until the leaked Supreme Court opinion in early May 2022. Unlike pro-choice tweets which declined, pro-life conversations continued with renewed interest throughout May and increased again following the official overturning of Roe v Wade. Conversations were less prevalent in some these states had abortion trigger laws (Wyoming, North Dakota, South Dakota, Texas, Louisiana, and Mississippi). Collapsing across topic categories, 2022 tweets were more negative and less neutral and positive compared to 2021 tweets. In network analysis, tweets mentioning woman/women, supreme court, and abortion spread faster and reached to more Twitter users than those mentioning Roe Wade and Scotus. Twitter data can provide real-time insights into the experiences and perceptions of people across the United States, which can be used to inform healthcare policies and decision-making.
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    Deciphering the causal relationship between blood pressure and regional white matter integrity: A two-sample Mendelian randomization study
    (Wiley, 2023-06-18) Ye, Zhenyao; Mo, Chen; Liu, Song; Gao, Si; Feng, Li; Zhao, Boao; Canida, Travis; Wu, Yu-Chia; Hatch, Kathryn S.; Ma, Yizhou; Mitchell, Braxton D.; Hong, Elliot L.; Kochunov, Peter; Chen, Chixiang; Zhao, Bingxin; Chen, Shuo; Ma, Tianzhou
    Elevated arterial blood pressure (BP) is a common risk factor for cerebrovascular and cardiovascular diseases, but no causal relationship has been established between BP and cerebral white matter (WM) integrity. In this study, we performed a two-sample Mendelian randomization (MR) analysis with individual-level data by defining two nonoverlapping sets of European ancestry individuals (genetics–exposure set: N = 203,111; mean age = 56.71 years, genetics–outcome set: N = 16,156; mean age = 54.61 years) from UK Biobank to evaluate the causal effects of BP on regional WM integrity, measured by fractional anisotropy of diffusion tensor imaging. Two BP traits: systolic and diastolic blood pressure were used as exposures. Genetic variant was carefully selected as instrumental variable (IV) under the MR analysis assumptions. We existing large-scale genome-wide association study summary data for validation. The main method used was a generalized version of inverse-variance weight method while other MR methods were also applied for consistent findings. Two additional MR analyses were performed to exclude the possibility of reverse causality. We found significantly negative causal effects (FDR-adjusted p < .05; every 10 mmHg increase in BP leads to a decrease in FA value by .4% ~ 2%) of BP traits on a union set of 17 WM tracts, including brain regions related to cognitive function and memory. Our study extended the previous findings of association to causation for regional WM integrity, providing insights into the pathological processes of elevated BP that might chronically alter the brain microstructure in different regions.
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    Leveraging 13 million responses to the U.S. COVID-19 Trends and Impact Survey to examine vaccine hesitancy, vaccination, and mask wearing, January 2021-February 2022
    (Springer Nature, 2022-10-13) Nguyen, Quynh C.; Yardi, Isha; Gutierrez, Francia Ximena Marin; Mane, Heran; Yue, Xiaohe
    The urgency of the COVID-19 pandemic called upon the joint efforts from the scientific and private sectors to work together to track vaccine acceptance and prevention behaviors. Our study utilized individual responses to the Delphi Group at Carnegie Mellon University U.S. COVID-19 Trends and Impact Survey, in partnership with Facebook. We retrieved survey data from January 2021 to February 2022 (n = 13,426,245) to examine contextual and individual-level predictors of COVID-19 vaccine hesitancy, vaccination, and mask wearing in the United States. Adjusted logistic regression models were developed to examine individual and ZIP code predictors of COVID-19 vaccine hesitancy and vaccination status. Given the COVID-19 vaccine was rolled out in phases in the U.S. we conducted analyses stratified by time, January 2021-May 2021 (Time 1) and June 2021-February 2022 (Time 2). In January 2021 only 9% of U.S. Facebook respondents reported receiving the COVID-19 vaccine, and 45% were vaccine hesitant. By February 2022, 80% of U.S. Facebook respondents were vaccinated and only 18% were vaccine hesitant. Individuals who were older, held higher educational degrees, worked in white collar jobs, wore a mask most or all the time, and identified as white and Asian had higher COVID-19 vaccination rates and lower vaccine hesitancy across Time 1 and Time 2. Essential workers and blue-collar occupations had lower COVID vaccinations and higher vaccine hesitancy. By Time 2, all adults were eligible for the COVID-19 vaccine, but blacks and multiracial individuals had lower vaccination and higher vaccine hesitancy compared to whites. Those 55 years and older and females had higher odds of wearing masks most or all the time. Protective service, construction, and installation and repair occupations had lower odds of wearing masks. ZIP Code level percentage of the population with a bachelors’ which was associated with mask wearing, higher vaccination, and lower vaccine hesitancy. Associations found in earlier phases of the pandemic were generally found to also be present later in the pandemic, indicating stability in inequities. Additionally, inequities in these important outcomes suggests more work is needed to bridge gaps to ensure that the burden of COVID-19 risk does not disproportionately fall upon subgroups of the population.
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    Food insecurity among African Americans in the United States: A scoping review
    (2022-09-12) Dennard, Elizabeth; Kristjansson, Elizabeth; Tchangalova, Nedelina; Totton, Sarah; Winham, Donna; O’Connor, Annette
    In 2019, the estimated prevalence of food insecurity for Black non-Hispanic households was higher than the national average due to health disparities exacerbated by forms of racial discrimination. During the COVID-19 pandemic, Black households have experienced higher rates of food insecurity when compared to other populations in the United States. The primary objectives of this review were to identify which risk factors have been investigated for an association with food insecurity, describe how food insecurity is measured across studies that have evaluated this outcome among African Americans, and determine which dimensions of food security (food accessibility, availability, and utilization) are captured by risk factors studied by authors. Food insecurity related studies were identified through a search of Google Scholar, PubMed, CINAHL Plus, MEDLINE®, PsycINFO, Health Source: Nursing/Academic Edition, and Web of Science™ (Clarivate), on May 20, 2021. Eligible studies were primary research studies, with a concurrent comparison group, published in English between 1995 and 2021. Ninety-eight relevant studies were included for data charting with 37 unique measurement tools, 115 risk factors, and 93 possible consequences of food insecurity identified. Few studies examined factors linked to racial discrimination, behaviour, or risk factors that mapped to the food availability dimension of food security. Infrequently studied factors, such as lifetime racial discrimination, socioeconomic status (SES), and income insecurity need further investigation while frequently studied factors such as age, education, race/ethnicity, and gender need to be summarized using a systematic review approach so that risk factor impact can be better assessed. Risk factors linked to racial discrimination and food insecurity need to be better understood in order to minimize health disparities among African American adults during the COVID-19 pandemic and beyond.
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    Strategies to increase happiness and wellbeing among public health students, faculty and staff
    (2022-07-01) Carter-Pokras, Olivia; Tchangalova, Nedelina; Puett, Robin
    BACKGROUND: Public health schools equip students with skills to promote and protect health, however, little is known about what is provided to support physical, mental and social wellbeing in academic public health. AIMS: To identify programs, interventions, strategies, and tools in medical and academic settings that could be applicable to supporting mental health and wellbeing of public health professionals, students, staff and faculty. METHOD: In November 2019 (updated in January 2022), 13 databases were searched: PubMed, 10 EBSCO databases(e.g., Academic Search Ultimate, APA PsycINFO, CINAHL Plus, Education Source, ERIC, Health Source: Nursing/Academic Edition, MEDLINE, SocINDEX), ProQuest Dissertations & Theses Global, and Web of Science. Inclusion criteria were randomized controlled trials, group interventions to support mental health curriculum, online tools, strategies, techniques, and programs of mindfulness, anxiety, depression, stress/distress, or burnout. Studies were limited to English and from 1998 to January 3, 2022. Websites for U.S. Schools of Public Health were searched. RESULTS: Out of 19,527 articles, 6,752 duplicates were removed. Following abstract and title screening, full-text articles will be screened for eligibility. The main themes from included studies will be shared. Preliminary findings show examples of activities to support well-being of public health professional students, staff, and faculty (e.g., providing free access to meditation apps, funding a dedicated wellness coordinator within the School). CONCLUSIONS: The literature on strategies to increase happiness and wellbeing among public health students, faculty, and staff is scarce and efforts to support physical mental, and social wellbeing for this community should be evaluated, and findings shared.