Epidemiology & Biostatistics Research Works

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Allostatic load amplifies the effect of blood lead levels on elevated blood pressure among middle-aged U.S. adults: a cross-sectional study
(Springer Nature, 2013-08-16) Zota, Ami R; Shenassa, Edmond D; Morello-Frosch, Rachel
Scientists and regulators have sought to understand whether and how physiologic dysregulation due to chronic stress exposure may enhance vulnerability to the adverse health effects of toxicant exposures. We conducted a cross-sectional study to determine whether allostatic load (AL), a composite measure of physiologic response to chronic exposure to stress, amplifies the effect of lead exposure on blood pressure among middle-aged adults. We analyzed associations between blood lead levels and blood pressure in a nationally representative sample of 8,194 U.S. adults (aged 40-65 years) participating in the National Health and Nutritional Examination Survey, 1999--2008. Outcomes were elevated systolic (≥ 140 mm Hg) and diastolic (≥ 90 mm Hg) blood pressure. AL was defined as the aggregate score of seven components, reflecting dysregulation of the cardiovascular, inflammatory, and endocrine systems. Logistic regression models showed a linear dose-response relationship for quintiles of blood lead and elevated systolic blood pressure in the high AL group (p = 0.03) but not the low AL group (p = 0.24). Similarly, the relationship between lead exposure and elevated diastolic blood pressure was stronger among the high AL group than the low AL group. Within the high AL group, the fourth and fifth quintiles had significantly elevated odds of elevated blood pressure compared to lowest quintile [OR = 1.92, (95% CI, 1.07, 3.47) and OR =2.28 (95% CI, 1.33, 3.91), respectively]. In the low AL group, none of the quintile effects were significantly different than the referent group although there was evidence of a linear trend (p =0.03). The lead by AL interaction term was not statistically significant for either systolic or diastolic blood pressure models. Results suggest that higher AL may amplify the adverse effects of lead on blood pressure. Future research should assess the implications of cumulative exposures to environmental and social stressors for regulatory decision-making.
Assessing Health Concerns and Barriers in a Heterogeneous Latino Community
(The Johns Hopkins University Press, 2006) Martinez, Iveris L.; Carter-Pokras, Olivia
Introduction. Major health issues and barriers to health services for Latino immigrants were identified through community-based participatory research in Baltimore city. Methods. In collaboration with community partners, five focus groups were conducted among Latino adults from 10 countries and health service providers. Findings. Priorities across groups included chronic diseases, HIV/AIDS and STDs, mental health, and the need for ancillary services. Community members and providers did not always agree on what health matters were of primary concern. Participants expected to receive health information at the point of service. Barriers to receiving health services and information span linguistic, financial, logistical, legal, and cultural matters. Conclusions. This formative research illustrates the complexity and interrelatedness of health priorities and barriers created by social issues such as employment, legal status, and related stressors.
Association between an Internet-Based Measure of Area Racism and Black Mortality
(PLOS (Public Library of Science), 2015-04-24) Chae, David H.; Clouston, Sean; Hatzenbuehler, Mark L.; Kramer, Michael R.; Cooper, Hannah L. F.; Wilson, Sacoby M.; Stephens-Davidowitz, Seth I.; Gold, Robert S.; Link, Bruce G.
Racial disparities in health are well-documented and represent a significant public health concern in the US. Racism-related factors contribute to poorer health and higher mortality rates among Blacks compared to other racial groups. However, methods to measure racism and monitor its associations with health at the population-level have remained elusive. In this study, we investigated the utility of a previously developed Internet search-based proxy of area racism as a predictor of Black mortality rates. Area racism was the proportion of Google searches containing the “N-word” in 196 designated market areas (DMAs). Negative binomial regression models were specified taking into account individual age, sex, year of death, and Census region and adjusted to the 2000 US standard population to examine the association between area racism and Black mortality rates, which were derived from death certificates and mid-year population counts collated by the National Center for Health Statistics (2004–2009). DMAs characterized by a one standard deviation greater level of area racism were associated with an 8.2% increase in the all-cause Black mortality rate, equivalent to over 30,000 deaths annually. The magnitude of this effect was attenuated to 5.7% after adjustment for DMA-level demographic and Black socioeconomic covariates. A model controlling for the White mortality rate was used to further adjust for unmeasured confounders that influence mortality overall in a geographic area, and to examine Black-White disparities in the mortality rate. Area racism remained significantly associated with the all-cause Black mortality rate (mortality rate ratio = 1.036; 95% confidence interval = 1.015, 1.057; p = 0.001). Models further examining cause-specific Black mortality rates revealed significant associations with heart disease, cancer, and stroke. These findings are congruent with studies documenting the deleterious impact of racism on health among Blacks. Our study contributes to evidence that racism shapes patterns in mortality and generates racial disparities in health.
Association between cigarette smoking and the vaginal microbiota: a pilot study
(Springer Nature, 2014-08-28) Brotman, Rebecca M; He, Xin; Gajer, Pawel; Fadrosh, Doug; Sharma, Eva; Mongodin, Emmanuel F; Ravel, Jacques; Glover, Elbert D; Rath, Jessica M
Smoking has been identified in observational studies as a risk factor for bacterial vaginosis (BV), a condition defined in part by decimation of Lactobacillus spp. The anti-estrogenic effect of smoking and trace amounts of benzo[a]pyrene diol epoxide (BPDE) may predispose women to BV. BPDE increases bacteriophage induction in Lactobacillus spp. and is found in the vaginal secretions of smokers. We compared the vaginal microbiota between smokers and non-smokers and followed microbiota changes in a smoking cessation pilot study. In 2010–2011, 20 smokers and 20 non-smokers were recruited to a cross-sectional study (Phase A) and 9 smokers were enrolled and followed for a 12-week smoking cessation program (Phase B). Phase B included weekly behavioral counseling and nicotine patches to encourage smoking cessation. In both phases, participants self-collected mid-vaginal swabs (daily, Phase B) and completed behavioral surveys. Vaginal bacterial composition was characterized by pyrosequencing of barcoded 16S rRNA genes (V1-V3 regions). Vaginal smears were assigned Nugent Gram stain scores. Smoking status was evaluated (weekly, Phase B) using the semi-quantitative NicAlert® saliva cotinine test and carbon monoxide (CO) exhalation. In phase A, there was a significant trend for increasing saliva cotinine and CO exhalation with elevated Nugent scores (P value <0.005). Vaginal microbiota clustered into three community state types (CSTs); two dominated by Lactobacillus (L. iners, L. crispatus), and one lacking significant numbers of Lactobacillus spp. and characterized by anaerobes (termed CST-IV). Women who were observed in the low-Lactobacillus CST-IV state were 25-fold more likely to be smokers than those dominated by L. crispatus (aOR: 25.61, 95 % CI: 1.03-636.61). Four women completed Phase B. One of three who entered smoking cessation with high Nugent scores demonstrated a switch from CST-IV to a L.iners-dominated profile with a concomitant drop in Nugent scores which coincided with completion of nicotine patches. The other two women fluctuated between CST-IV and L. iners-dominated CSTs. The fourth woman had low Nugent scores with L. crispatus-dominated CSTs throughout. Smokers had a lower proportion of vaginal Lactobacillus spp. compared to non-smokers. Smoking cessation should be investigated as an adjunct to reducing recurrent BV. Larger studies are needed to confirm these findings.
Association between community socioeconomic factors, animal feeding operations, and campylobacteriosis incidence rates: Foodborne Diseases Active Surveillance Network (FoodNet), 2004–2010
(Springer Nature, 2016-07-22) Rosenberg Goldstein, Rachel E.; Cruz-Cano, Raul; Jiang, Chengsheng; Palmer, Amanda; Blythe, David; Ryan, Patricia; Hogan, Brenna; White, Benjamin; Dunn, John R.; Libby, Tanya; Tobin-D’Angelo, Melissa; Huang, Jennifer Y.; McGuire, Suzanne; Scherzinger, Karen; Ting Lee, Mei-Ling; Sapkota, Amy R.
Campylobacter is a leading cause of foodborne illness in the United States. Campylobacter infections have been associated with individual risk factors, such as the consumption of poultry and raw milk. Recently, a Maryland-based study identified community socioeconomic and environmental factors that are also associated with campylobacteriosis rates. However, no previous studies have evaluated the association between community risk factors and campylobacteriosis rates across multiple U.S. states. We obtained Campylobacter case data (2004–2010; n = 40,768) from the Foodborne Diseases Active Surveillance Network (FoodNet) and socioeconomic and environmental data from the 2010 Census of Population and Housing, the 2011 American Community Survey, and the 2007 U.S. Census of Agriculture. We linked data by zip code and derived incidence rate ratios using negative binomial regression models. Community socioeconomic and environmental factors were associated with both lower and higher campylobacteriosis rates. Zip codes with higher percentages of African Americans had lower rates of campylobacteriosis (incidence rate ratio [IRR]) = 0.972; 95 % confidence interval (CI) = 0.970,0.974). In Georgia, Maryland, and Tennessee, three leading broiler chicken producing states, zip codes with broiler operations had incidence rates that were 22 % (IRR = 1.22; 95 % CI = 1.03,1.43), 16 % (IRR = 1.16; 95 % CI = 0.99,1.37), and 35 % (IRR = 1.35; 95 % CI = 1.18,1.53) higher, respectively, than those of zip codes without broiler operations. In Minnesota and New York FoodNet counties, two top dairy producing areas, zip codes with dairy operations had significantly higher campylobacteriosis incidence rates (IRR = 1.37; 95 % CI = 1.22, 1.55; IRR = 1.19; 95 % CI = 1.04,1.36). Community socioeconomic and environmental factors are important to consider when evaluating the relationship between possible risk factors and Campylobacter infection.
Association of Types of Life Events with Depressive Symptoms among Puerto Rican Youth
(PLoS (Public Library of Science), 2016-10-27) Jaschek, Graciela; Carter-Pokras, Olivia D.; He, Xin; Lee, Sunmin; Canino, Glorisa
The main objective of this study was to examine the association between four types of adverse life events (family environment, separation, social adversity, and death) and the development of depressive symptoms among Puerto Rican youth. This was a secondary analysis using three waves (2000-2004) of interview data from the Boricua Youth Study of 10-13 year old Puerto Rican youth residing in New York and Puerto Rico with no depressive symptoms at baseline (n = 977). Depressive symptoms increased with an increase in social adversity, separation, death, and death events. Youth support from parents was a significant protective factor for all adverse events and parent coping was a protective factor in social adversity events. Relying on standard diagnostic tools is ideal to identify youth meeting the criteria for a diagnosis of depression but not useful to detect youth who present with subclinical levels of depression. Youth with sub-clinical levels of depression will not get treated and are at increased risk of developing depression later in life. Adverse life events are potentially relevant to use in conjunction with other screening tools to identify Puerto Rican youth who have subclinical depression and are at risk of developing depression in later adolescence.
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.
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.
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.
Emergency Preparedness: Knowledge and Perceptions of Latin American Immigrants
(1999) Carter-Pokras, Olivia; Zambrana, Ruth E.; Mora, Sonia E.; Aaby, Katherine A.
This paper describes the level of public emergency knowledge and perceptions of risks among Latin American immigrants, and their preferred and actual sources of emergency preparedness information (including warning signals). Five Latino community member focus groups, and one focus group of community health workers, were conducted in a suburban county of Washington D.C. (N51). Participants came from 13 Latin American countries, and 64.7% immigrated during the previous five years. Participants had difficulty defining emergency and reported a wide range of perceived personal emergency risks: immigration problems; crime, personal insecurity, gangs; home/traffic accidents; home fires; environmental problems; and snipers. As in previous studies, few participants had received information on emergency preparedness, and most did not have an emergency plan. Findings regarding key messages and motivating factors can be used to develop clear, prioritized messages for communication regarding emergencies and emergency preparedness for Latin American immigrant communities in the U.S.
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.
Eplerenone for early cardiomyopathy in Duchenne muscular dystrophy: results of a two-year open-label extension trial
(Springer Nature, 2017-02-20) Raman, Subha V.; Hor, Kan N.; Mazur, Wojciech; He, Xin; Kissel, John T.; Smart, Suzanne; McCarthy, Beth; Roble, Sharon L.; Cripe, Linda H.
Cardiomyopathy is a leading cause of morbidity and mortality in boys with Duchenne muscular dystrophy (DMD). We recently showed in a 12-month double-blind randomized controlled trial that adding eplerenone to background medical therapy was cardioprotective in this population. The objective of this study was to evaluate the safety and efficacy of longer-term eplerenone therapy in boys with DMD. Eleven subjects (phase 1 baseline median [range] age: 13 [7 – 25] years) from the original 12-month trial at a single participating center were enrolled. Importantly, those who entered the extension study who had been on eplerenone previously were significantly older than those who had originally been on placebo (median age 10.5 vs. 18.0 years, p = 0.045). During an additional 24-month open-label extension study, all boys received eplerenone 25 mg orally once daily to treat preclinical DMD cardiomyopathy, defined as evident myocardial damage by late gadolinium enhancement cardiac magnetic resonance (LGE) with preserved ejection fraction (EF). The threshold for potassium level, the primary safety measure, was not exceeded in any non-hemolyzed blood sample. Over 24 months, left ventricular (LV) systolic strain, a more sensitive marker whose more negative values indicate greater contractility significantly improved (median change -4.4%, IQR -5.8 to -0.9%) in younger subjects whereas older subjects’ strain remained stable without significant worsening or improvement (median change 0.2%, IQR -1.1 to 4.3%). EF and extent of myocardial damage by LGE remained stable in both groups over 2 years. Eplerenone offers effective and safe cardioprotection for boys with DMD, particularly when started at a younger age. Eplerenone is a useful clinical therapeutic option, particularly if treatment is initiated earlier in life when cardiac damage is minimal.
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.
Exposure to extreme heat and precipitation events associated with increased risk of hospitalization for asthma in Maryland, U.S.A.
(Springer Nature, 2016-04-27) Soneja, Sutyajeet; Jiang, Chengsheng; Fisher, Jared; Upperman, Crystal Romeo; Mitchell, Clifford; Sapkota, Amir
Several studies have investigated the association between asthma exacerbations and exposures to ambient temperature and precipitation. However, limited data exists regarding how extreme events, projected to grow in frequency, intensity, and duration in the future in response to our changing climate, will impact the risk of hospitalization for asthma. The objective of our study was to quantify the association between frequency of extreme heat and precipitation events and increased risk of hospitalization for asthma in Maryland between 2000 and 2012. We used a time-stratified case-crossover design to examine the association between exposure to extreme heat and precipitation events and risk of hospitalization for asthma (ICD-9 code 493, n = 115,923). Occurrence of extreme heat events in Maryland increased the risk of same day hospitalization for asthma (lag 0) by 3 % (Odds Ratio (OR): 1.03, 95 % Confidence Interval (CI): 1.00, 1.07), with a considerably higher risk observed for extreme heat events that occur during summer months (OR: 1.23, 95 % CI: 1.15, 1.33). Likewise, summertime extreme precipitation events increased the risk of hospitalization for asthma by 11 % in Maryland (OR: 1.11, 95 % CI: 1.06, 1.17). Across age groups, increase in risk for asthma hospitalization from exposure to extreme heat event during the summer months was most pronounced among youth and adults, while those related to extreme precipitation event was highest among ≤4 year olds. Exposure to extreme heat and extreme precipitation events, particularly during summertime, is associated with increased risk of hospitalization for asthma in Maryland. Our results suggest that projected increases in frequency of extreme heat and precipitation event will have significant impact on public health.
Externalizing behavior in early childhood and body mass index from age 2 to 12 years: longitudinal analyses of a prospective cohort study
(2010-07-14) Anderson, Sarah E; He, Xin; Schoppe-Sullivan, Sarah; Must, Aviva
Background: Some evidence suggests that obesity and behavior problems are related in children, but studies have been conflicting and have rarely included children under age 4. An association between behavior problems in early childhood and risk for obesity could suggest that a common set of factors contribute to both. Our research objectives were to determine the extent to which externalizing behavior in early childhood is related to body mass index (BMI) in early childhood and through age 12, and to evaluate whether these associations differ by sex and race. Methods: Data from the NICHD Study of Early Child Care and Youth Development were analyzed. Externalizing behaviors at 24 months were assessed by mothers using the Child Behavior Checklist. BMI was calculated from measured height and weight assessed 7 times between age 2 and 12 years. Linear mixed effects models were used to assess associations between 24 month externalizing behavior and BMI from 2 to 12 years, calculate predicted differences in BMI, and evaluate effect modification. Results: Externalizing behavior at 24 months was associated with a higher BMI at 24 months and through age 12. Results from a linear mixed effects model, controlling for confounding variables and internalizing behavior, predicted a difference in BMI of approximately 3/4 of a unit at 24 months of age comparing children with high levels of externalizing behavior to children with low levels of externalizing behavior. There was some evidence of effect modification by race; among white children, the average BMI difference remained stable through age 12, but it doubled to 1.5 BMI units among children who were black or another race. Conclusions: Our analyses suggest that externalizing behaviors in early childhood are associated with children's weight status early in childhood and throughout the elementary school years, though the magnitude of the effect is modest.
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.
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.
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.
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.
Health and the built environment in United States cities: measuring associations using Google Street View-derived indicators of the built environment
(Springer Nature, 2020-02-12) Keralis, Jessica M.; Javanmardi, Mehran; Khanna, Sahil; Dwivedi, Pallavi; Huang, Dina; Tasdizen, Tolga; Nguyen, Quynh C.
The built environment is a structural determinant of health and has been shown to influence health expenditures, behaviors, and outcomes. Traditional methods of assessing built environment characteristics are time-consuming and difficult to combine or compare. Google Street View (GSV) images represent a large, publicly available data source that can be used to create indicators of characteristics of the physical environment with machine learning techniques. The aim of this study is to use GSV images to measure the association of built environment features with health-related behaviors and outcomes at the census tract level.

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