Minority Residents Research Articles

Cleaning Up the Neighborhood: White Influx and Differential Requests for Services

Visible signs of disorder serve as markers of difference across urban space. Sociological theory suggests that variation in collective social control efforts contributes to variation in physical disorder. However, how structural characteristics shape differences in informal social control remains underexplored because of limited data on disorder and social control. Using city service request data and a novel dataset drawing on Google Street View imagery and computer vision methods, the authors examine the neighborhood characteristics associated with propensities to request trash-related services across five large U.S. cities. The authors find that socioeconomically advantaged neighborhoods and those with fewer minority and foreign-born residents have higher propensities. However, an increase in White residents, but not necessarily an increase in high–socioeconomic status residents, is strongly associated with greater propensities. The authors argue that incoming White residents introduce unique dynamics of social control that are not necessarily collective, thereby affecting spatial inequality and power relations within their new neighborhoods.

County Mammogram Uptake can be Predicted from Social Determinants of Health, but Patterns Do Not Hold for Individual Patients.

The objective of this study is to describe patterns in barriers to breast cancer screening uptake with the end goal of improving screening adherence and decreasing the burden of mortality due to breast cancer. This study looks at social determinants of health and their association to screening and mortality. It also investigates the extent that models trained on county data are generalizable to individuals. County level screening uptake and age adjusted mortality due to breast cancer are combined with the Centers for Disease Controls Social Vulnerability Index (SVI) to train a model predicting screening uptake rates. Patterns learned are then applied to de-identified electronic medical records from individual patients to make predictions on mammogram screening follow through. Accurate predictions can be made about a county's breast cancer screening uptake with the SVI. However, the association between increased screening, and decreased age adjusted mortality, doesn't hold in areas with a high proportion of minority residents. It is also shown that patterns learned from county SVI data have little discriminative power at the patient level. This study demonstrates that social determinants in the SVI can explain much of the variance in county breast cancer screening rates. However, these same patterns fail to discriminate which patients will have timely follow through of a mammogram screening test. This study also concludes that the core association between increased screening and decreased age adjusted mortality does not hold in high proportion minority areas. The objective of this study is to describe patterns in social determinants of health and their association with female breast cancer screening uptake, age adjusted breast cancer mortality rate and the extent that models trained on county data are generalizable to individuals.

Relationship between dietary nutrition and chronic disease of Jinuo Minority residents aged 20-80 in Jinghong District in 2020

To analyze the relationship between food intake and chronic diseases of Jinuo Minority residents living in Yunnan Province. A total of 392 Jinuo Minority residents 20-80-year-old among 304 families(male 135, female 257; aged 20-49 years old 140, aged 50-59 years old 136, aged 60-80 years old 116)in Jinghong District in Yunnan Province were selected with stratified multistage cluster sampling method. To apply the method of food frequency questionnaire and questionnaire survey obtain the condition of dietary structure and overweight or obesity, diabetes and dyslipidemia among Jinuo Minority in the past 12 months. Non-conditional Logistic regression analysis was utilized to analyze the correlation between food intake and chronic diseases. In 2020, the prevalence of overweight/obesity, hypertension, diabetes and dyslipidemias among Jinuo adults in Jinghong District were 38.8%(n=152), 19.1%(n=75), 3.6%(n=14)and 26.3%(n=103). Jinuo residents aged 20 and above who have consumed noodle and instant noodle(OR=1.677, 95%CI 1.028-2.736), fermented soybean curd(OR=3.056, 95%CI 1.853-5.038), grass carp(OR=2.245, 95%CI 1.270-3.971), ethnic food/peanut(OR=1.975, 95%CI 1.162-3.355) were more likely to experience overweight/obesity compared to those who did not consume them. On the other hand, individuals who consumed snacks/bread(OR=0.322, 95%CI 0.190-0.545) were less likely to develop overweight/obesity compared to those who did not consume them. Jinuo residents aged 20 and above who have consumed other cereals and cereals products, such as buckwheat(OR=7.029, 95%CI 1.494-33.070), were more likely to develop diabetes than those who did not consume them. And those who have eaten cabbage vegetables(such as cauliflower/cabbage)(OR=0.155, 95%CI 0.034-0.708), and kernel fruits(such as apple/pear)(OR=0.227, 95% CI 0.069-0.743) were less likely to develop diabetes than those who did not consume them. Adults who consumed cooked meat and other livestock and poultry, such as donkey/horse meat(OR=9.676, 95% CI 1.418-66.027), were more likely to cause dyslipidemias compared to did not consume them. Conversely, individuals who consumed root vegetables(such as radish/lotus root)(OR=0.405, 95%CI 0.204-0.803), cooked pork from animal foods(OR=0.482, 95%CI 0.263-0.885), snacks/snack bread(OR=0.590, 95%CI 0.357-0.974) and plum blossom(OR=0.173, 95%CI 0.038-0.793) were less likely to develop dyslipidemia than those who did not consume them. In Jinghong District, the overweight/obesity of Jinuo adults aged 20-80 was positively correlated to the consumption of noodles and instant noodles, fermented bean curd, grass carp, and ethnic food/peanut. And there was a negative correlation with the consumption of snacks/bread. Regarding diabetes, a positive correlation was observed with the consumption of other grains and products, while negative correlations were found with the consumption of cabbage vegetables and kernel fruits. For dyslipidemias, there was a positive correlation with the consumption of cooked meat and other livestock and poultry, and negative correlations were identified with the consumption of root vegetables, cooked pork from animal foods, snacks/snack bread, and prunes.

Buried but not dead: The impact of stream and wetland loss on flood risk in redlined neighborhoods

The United States government sponsored the Home Owners’ Loan Corporation (HOLC) in the 1930s to assess and grade neighborhoods based on perceived financial risk. The grades were influenced by the presence of minority racial groups, immigrants, and residents with lower socioeconomic statuses and, even though the practice was eventually outlawed, the impact on low income and underrepresented minorities is still prevalent today. This study was designed to assess spatial patterns and intensity of flood risk to (a) HOLC grade, (b) proximity to coastal zones, (c) intensity of vegetative cover, and (d) relationship to buried (ghost) streams and wetlands to determine which variable has the most impact on flood risk. Flood risk data, acquired from First Street Foundation’s Flood Factor dataset, was summarized by HOLC grade, and ghost streams and wetlands were digitized from historical maps and aggregated by HOLC grade. The results show flood risk is higher in C and D graded neighborhoods, compared to A and B. Regardless of HOLC grade, neighborhoods near the Detroit River and Lake St. Claire have 10 times higher flood risk than inland neighborhoods. Interestingly, B-graded neighborhoods exhibit minimal impact from buried rivers and wetlands, but that risk increases substantially if there is a history of stream or wetland burial within a D graded neighborhood. Flood risk is disproportionately distributed, caused in part by outlawed, racist housing policies. Understanding where risk is highest can help identify optimum locations for adaptation measures to minimize flood damage in these neighborhoods.

California’s zero-emission vehicle adoption brings air quality benefits yet equity gaps persist

Zero-emission vehicle (ZEV) adoption is a key climate mitigation tool, but its environmental justice implications remain unclear. Here, we quantify ZEV adoption at the census tract level in California from 2015 to 2020 and project it to 2035 when all new passenger vehicles sold are expected to be ZEVs. We then apply an integrated traffic model together with a dispersion model to simulate air quality changes near roads in the Greater Los Angeles. We found that per capita ZEV ownership in non-disadvantaged communities (non-DACs) as defined by the state of California is 3.8 times of that in DACs. Racial and ethnic minorities owned fewer ZEVs regardless of DAC designation. While DAC residents receive 40% more pollutant reduction than non-DACs due to intercommunity ZEV trips in 2020, they remain disproportionately exposed to higher levels of traffic-related air pollution. With more ZEVs in 2035, the exposure disparity narrows. However, to further reduce disparities, the focus must include trucks, emphasizing the need for targeted ZEV policies that address persistent pollution burdens among DAC and racial and ethnic minority residents.

Associations of Neighborhood Gentrification Status and Cognitive Decline in the Health and Retirement Study

AbstractBackgroundGentrification, characterized by in‐migration of high socioeconomic (SES) residents into formerly disinvested neighborhoods, may impair late‐life cognitive function of existing residents. We hypothesized that disinvestment of neighborhood economic resources and reinvestment via gentrification both increase risk of cognitive decline among marginalized older adults.MethodWe analyzed 17,613 Health and Retirement Study participants (aged 51‐101), 67% Non‐Hispanic White) with data on our outcomes of interest: biennial scores on immediate and delayed word recall batteries (2010‐2016). With 2000 Census data, we operationalized census tract disinvestment based on disproportionately high proportions of minority residents, low SES, and renters for the corresponding county. We defined gentrification among disinvested tracts as greater than county‐median increases in White and college‐educated residents, household income, and housing costs between the 2000 Census and 2008‐2012 American Community Survey. We fit linear mixed models to evaluate associations of gentrification with cognitive level and change. We also evaluated racial‐ethnic differences in cognitive function by residence in tracts that were 1) not disinvested in 2000, 2) remained disinvested, or 3) gentrified by 2012. All models were adjusted by individual‐level age, gender, race‐ethnicity, educational attainment, marital status, home ownership, health insurance coverage, and memory score practice effects.Result56% of participants lived tracts that were disinvested in 2000; by 2012, 34% of disinvested tracts gentrified. Baseline memory performance was worse in invested (e.g., mean immediate = 4.9) than in initially disinvested tracts that either gentrified (mean = 5.3) or remained disinvested (mean = 5.4) (p<0.02 for test of mean differences). Neighborhood disinvestment from 2000‐2012 compared to investment in 2000 was associated with better 6‐year immediate recall trajectories among White participants (β; 95% CI: 0.18; 0.01, 0.39) but not among their Hispanic/Latino counterparts (‐0.14; ‐0.29, ‐0.01; p‐value for interaction compared to White participants = 0.04). We observed similar patterns for delayed recall (p‐value for interaction comparing Hispanic/Latino to White participants = 0.05). Neighborhood disinvestment or gentrification was not associated with recall trajectories among Black participants.ConclusionDifferential findings by race in this nationally representative sample indicate that disinvestment and gentrification do not equally impact older adult cognitive health.

Police Violence as Containment of Black Bodies during Urban Renewal: A Spatial Analysis of Civilian Deaths by Police in Florida

abstract: This study presents a geospatial analysis of police killings within two areas in Florida over a twenty-year period. Fatalities were mapped against social and economic characteristics of neighborhoods to ascertain if police violence ending in civilian death was concentrated in areas with high-minority and low-income populations, and those areas in proximity to gentrifying neighborhoods. We evaluated the theory that police violence against minority residents serves as a process of containment and ultimately supports the continued generation of wealth by a specific sector of society through the process of gentrification. The cycle of destruction and renewal in the urban landscape is deeply intertwined with processes of capital accumulation, class differentiation, and racial subordination. Both the West Florida and Southeast Florida areas contained a significantly higher proportion of fatal encounters occurring within tracts that were eligible to gentrify than in tracts that were in the process of gentrifying. Fort Lauderdale in particular had little overlap despite containing concentrated hotspots of incidents in combination with high-minority and low–NSES tracts. This same pattern is apparent in the Lakeland area in west Florida. Our findings are consistent with Laniyonu's observation that police interactions tend to increase in tracts just outside of gentrified areas, but seldom within them.

California Civil Asset Forfeiture and the Policing of Minority Residents

In Who Are the Criminals?, John Hagan argues that legislators use “crisis framing” to influence how the general public thinks about crime. President Ronald Reagan used reports of a drug use epidemic fueled by organized crime as part of his crisis framing. In 1984, he signed the Comprehensive Crime Control Act (CCCA) as part of his “war on drugs.” The CCCA allowed law enforcement to use civil asset forfeiture (CAF) to keep or sell property that it suspected was connected to illegal activity. State legislators followed suit and passed their own CAF laws. Some critics argue that law enforcements’ use of CAF has disproportionately targeted minority populations. We draw on racial threat theory to examine connections between the size of minority populations and the use of CAF in California. Our analysis uses nineteen years of CAF cases filed with the California Attorney General’s Office. Consistent with racial threat theory, we find a positive association between the number of forfeitures in a jurisdiction and a logged measure of the percentage of Black residents, net of crime, and other jurisdiction attributes. Our results support concerns that law enforcement has incorporated CAF as a technique used disproportionately against some minority communities.

Exploring Overt Racial and Ethnic Conflict in Resident-to-Resident Aggression in Long-Term Care Facilities

ObjectivesResident-to-resident aggression (RRA) in long-term care facilities is gaining recognition as a serious problem. Racial/ethnic conflict may be a contributing factor to RRA incidents, but it remains insufficiently studied. Our goal was to explore overt racial/ethnic conflict in RRA. DesignWe used quantitative and qualitative secondary analyses of existing data from a large, rigorously conducted study of RRA to describe the involved residents and patterns of overt racial/ethnic conflicts. Setting and ParticipantsThe parent study included information of 2011 residents in 10 randomly selected New York State nursing homes with a wide range of racial/ethnic minority residents (4.2%–63.2%). A subset of 407 residents were involved in RRA. MethodsWe re-examined data from the parent study, which used an innovative approach to identify RRA incidents by reconstructing each incident based on residents’ self-reports, staff interviews, field observations, and medical chart review. Resident and facility information was collected. ResultsA total of 35 residents (8.6% of those involved in RRA incidents) were identified as involved in overt racial/ethnic conflicts. These residents were more likely to have had less education than residents involved in other types of RRA but not in overt racial/ethnic conflicts. More than half (56.9%) of the 51 incidents of RRA involving overt racial/ethnic conflict between a specific pair of residents occurred repeatedly. Manifestation of racial/ethnic conflicts included physical violence, discrimination, racial/ethnic slurs, stereotypes, and microaggression. Acute precipitants of these incidents included various communal-living challenges and unmet needs at the facility, relational, and individual levels. Psychological and behavioral consequences were also described. Conclusion and ImplicationsWe found a broad range of manifestations, acute precipitants, circumstances surrounding, and consequences of overt racial/ethnic conflicts in RRA. Additional research is needed to improve understanding of this phenomenon and how staff may effectively intervene and prevent it.

Beyond Residence: A Mobility-based Approach for Improved Evaluation of Human Exposure to Environmental Hazards.

Standard environmental hazard exposure assessment methods have been primarily based on residential places, neglecting individuals' hazard exposures due to activities outside home neighborhood and underestimating peoples' overall hazard exposures. To address this limitation, this study proposes a novel mobility-based index for the hazard exposure evaluation. Using large-scale human mobility data, we quantify the extent of population dwell time in high environmental hazard places in 239 US counties for three environmental hazards. We explore how human mobility extends the reach of environmental hazards and leads to the emergence of latent exposure for populations living outside high-hazard areas. Notably, neglect of mobility can lead to over 10% underestimation of hazard exposures. The interplay of spatial clustering in high-hazard regions and human movement trends creates "environmental hazard traps." Poor and ethnic minority residents disproportionately face multiple types of environmental hazards. This data-driven evidence supports the severity of these injustices. We also studied latent exposure arising from visits outside residents' home areas, revealing millions of the population having 5 to 10% of daily activities occur in high-exposure zones. Despite living in perceived safe areas, human mobility could expose millions of residents to different hazards. These findings provide crucial insights for targeted policies to mitigate these severe environmental injustices.

Retraction Note: Health-related quality of life among ethnic minority residents in remote Western China: a cross-sectional study

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s12889-023-16559-x.

Longitudinal Spatial Trends in U.S. Pedestrian Fatalities, 1999–2020

The number of pedestrian deaths from motor vehicle crashes in the U.S. has risen 59% since 2009. Several studies have researched crash characteristics—such as the people, vehicles, and roadways involved—when examining this sharp increase. But where are these fatalities occurring and what spatial characteristics of these locations could be influencing this trend? We looked at pedestrian fatality data from the National Highway Traffic Safety Administration’s Fatality Analysis Reporting System and socioeconomic, demographic, and built environment data from the U.S. Census and the U.S. Environmental Protection Agency’s Smart Location Database for the study period of 1999–2020. After inputting the data into QGIS, we made graphs with 95% confidence intervals to analyze longitudinal trends in crash location characteristics and created heat maps of pedestrian fatality locations in nine large U.S. cities to compare clustering in the beginning of the study period (1999–2002) with clustering at the end (2017–2020). The results of this study indicate that pedestrian fatalities are moving away from downtown areas (with a 63.0% decrease in study cities’ downtowns) and are now happening more in suburbs (a 32.1% increase outside downtowns). Many of these suburbs are post-war suburbs that were built in the 1950s, 1960s, and 1970s and have low population and road densities and low levels of pedestrian commuting. Additionally, these fatalities are happening in neighborhoods with high proportions of minority residents, low educational attainment, and high poverty rates that are more than 60% above the national average.

Using Bandit Algorithms to Maximize SARS-CoV-2 Case-Finding: Evaluation and Feasibility Study.

The Flexible Adaptive Algorithmic Surveillance Testing (FAAST) program represents an innovative approach for improving the detection of new cases of infectious disease; it is deployed here to screen and diagnose SARS-CoV-2. With the advent of treatment for COVID-19, finding individuals infected with SARS-CoV-2 is an urgent clinical and public health priority. While these kinds of Bayesian search algorithms are used widely in other settings (eg, to find downed aircraft, in submarine recovery, and to aid in oil exploration), this is the first time that Bayesian adaptive approaches have been used for active disease surveillance in the field. This study's objective was to evaluate a Bayesian search algorithm to target hotspots of SARS-CoV-2 transmission in the community with the goal of detecting the most cases over time across multiple locations in Columbus, Ohio, from August to October 2021. The algorithm used to direct pop-up SARS-CoV-2 testing for this project is based on Thompson sampling, in which the aim is to maximize the average number of new cases of SARS-CoV-2 diagnosed among a set of testing locations based on sampling from prior probability distributions for each testing site. An academic-governmental partnership between Yale University, The Ohio State University, Wake Forest University, the Ohio Department of Health, the Ohio National Guard, and the Columbus Metropolitan Libraries conducted a study of bandit algorithms to maximize the detection of new cases of SARS-CoV-2 in this Ohio city in 2021. The initiative established pop-up COVID-19 testing sites at 13 Columbus locations, including library branches, recreational and community centers, movie theaters, homeless shelters, family services centers, and community event sites. Our team conducted between 0 and 56 tests at the 16 testing events, with an overall average of 25.3 tests conducted per event and a moving average that increased over time. Small incentives-including gift cards and take-home rapid antigen tests-were offered to those who approached the pop-up sites to encourage their participation. Over time, as expected, the Bayesian search algorithm directed testing efforts to locations with higher yields of new diagnoses. Surprisingly, the use of the algorithm also maximized the identification of cases among minority residents of underserved communities, particularly African Americans, with the pool of participants overrepresenting these people relative to the demographic profile of the local zip code in which testing sites were located. This study demonstrated that a pop-up testing strategy using a bandit algorithm can be feasibly deployed in an urban setting during a pandemic. It is the first real-world use of these kinds of algorithms for disease surveillance and represents a key step in evaluating the effectiveness of their use in maximizing the detection of undiagnosed cases of SARS-CoV-2 and other infections, such as HIV.

“Going Back in the Closet”: Addressing Discrimination Against Sexual and Gender Minority Residents in Long-Term Services and Supports by Providing Culturally Responsive Care

ABSTRACT Sexual and gender minority (SGM) older adults face discrimination in long-term services and supports (LTSS). Yet, SGM older adults use LTSS disproportionately higher relative to their non-SGM counterparts. The discrimination is compounded by existing disparities, resulting in worse health outcomes and well-being for SGM older adults. Guided by socioecological model, we posit that training LTSS staff in SGM responsive care and implementing SGM anti-discrimination policies will be needed to improve care. Considering accessibility and turnover challenges, training should be online, interactive, and easily accessible. Studies that assess interventions for SGM responsive care are needed to guide policy and practice.

Misrecognition and Well‐being in Culturally White Northern New England☆

AbstractRural America is undergoing a demographic transition, as the white population decline is matched by a growing movement of racialized minorities into small towns. In the current study, I examine processes of belonging among middle‐class racialized minorities living in predominantly white and rural Northern New England. Through an analysis of in‐depth interviews with n = 58 individuals of color, I show how “misrecognition,” or the processes through which community members fail to affirm the humanity of others, can lead to diminished well‐being. I elaborate a novel conceptual model linking a stigmatizing cultural context (chilly social climate; ignorance and racism) with misrecognition (social distancing; having to prove oneself) and well‐being (unease; weariness). The study's main contribution is the generation of theory regarding symbolic boundary processes that undergird racialized minority residents' negotiation of the right to belong in a rapidly changing rural America.

Social vulnerability predictors of drug poisoning mortality: A machine learning analysis in the United States.

Drug poisoning is a leading cause of unintentional deaths in the United States. Despite the growing literature, there are a few recent analyses of a wide range of community-level social vulnerability features contributing to drug poisoning mortality. Current studies on this topic face three limitations: often studying a limited subset of vulnerability features, focusing on small sample sizes, or solely including local data. To address this gap, we conducted a national-level analysis to study the impacts of several social vulnerability features in predicting drug mortality rates in the United States. We used machine learning to investigate the role of 16 social vulnerability features in predicting drug mortality rates for US counties in 2014, 2016, and 2018-the most recent available data. We estimated each vulnerability feature's gain relative contribution in predicting drug poisoning mortality. Among all social vulnerability features, the percentage of noninstitutionalized persons with a disability is the most influential predictor, with a gain relative contribution of 18.6%, followed by population density and the percentage of minority residents (13.3% and 13%, respectively). Percentages of households with no available vehicles, mobile homes, and persons without a high school diploma are the following features with gain relative contributions of 6.3%, 5.8%, and 5.1%, respectively. We identified social vulnerability features that are most predictive of drug poisoning mortality. Public health interventions and policies targeting vulnerable communities may increase the resilience of these communities and mitigate the overdose death and drug misuse crisis.

Mixed and worried? Examining the association between locality type and worrying about social phenomena in Arab citizens of Israel

This study examined the association between the type of locality ethnic minorities reside in and their worrying about social phenomena through the lens of the social capital theory. The study aimed at showing that worry profiles, as well the extent of being concerned about various social phenomena, are not the same for the minority residents of ethnically homogeneous and of ethnically heterogeneous localities. Moreover, the main assumption was that residing in heterogeneous locality corresponds to an increase in concerns about social phenomena. The data were obtained from the Personal and Community Security Index Survey which was conducted among the Arab citizens of Israel in 2020 (N = 947). The data were analyzed using multinomial and linear regression models. The results show that residing in ethnically mixed localities was associated with having a highly worried profile. Residing in mixed localities also related to a greater worry about the general social and the violence-related phenomena. The results supported the social capital theory. The results suggest that residing in ethnically homogeneous localities plays a protective role with respect to being concerned about social phenomena. The results imply that public decision makers should develop long-term plans to reduce worry levels in minority residents of ethnically mixed localities which will include provision of tailored services, fighting against violence, and informing about the proposed solutions for each phenomenon of concern.

The economic impact of the COVID-19 pandemic on ethnic minorities in Manchester: lessons from the early stage of the pandemic.

This review summarizes the economic impacts of the pandemic on ethnic minorities, focusing on the city of Manchester. It utilizes multiple reporting sources to explore various dimensions of the economic shock in the UK, linking this to studies of pre-COVID-19 economic and ethnic composition in Manchester and in the combined authority area of Greater Manchester. We then make inferences about the pandemic's short-term impact specific to the city region. Greater Manchester has seen some of the highest rates of COVID-19 and as a result faced particularly stringent "lockdown" regulations. Manchester is the sixth most deprived Local Authority in England, according to 2019 English Indices of Multiple Deprivation. As a consequence, many neighborhoods in the city were always going to be less resilient to the economic shock caused by the pandemic compared with other, less-deprived, areas. Particular challenges for Manchester include the high rates of poor health, low-paid work, low qualifications, poor housing conditions and overcrowding. Ethnic minority groups also faced disparities long before the onset of the pandemic. Within the UK, ethnic minorities were found to be most disadvantaged in terms of employment and housing-particularly in large urban areas containing traditional settlement areas for ethnic minorities. Further, all Black, Asian, and Minority ethnic (BAME) groups in Greater Manchester were less likely to be employed pre-pandemic compared with White people. For example, people of Pakistani and Bangladeshi ethnic backgrounds, especially women, have the lowest levels of employment in Greater Manchester. Finally, unprecedented cuts to public spending as a result of austerity have also disproportionately affected women of an ethnic minority background alongside disabled people, the young and those with no or low-level qualifications. This environment has created and sustained a multiplicative disadvantage for Manchester's ethnic minority residents through the course of the COVID-19 pandemic.

Transportation-related Environmental Mixtures and Diabetes Prevalence and Control in Urban/Metropolitan Counties in the United States.

Diabetes rates in the United States are staggering and climbing. Importantly, traditional risk factors fail to completely account for the magnitude of the diabetes epidemic. Environmental exposures, including urban and metropolitan transportation quality, are implicated as contributors to disease. Using data from the county-level Environmental Quality Index (EQI) developed for the United States, we analyzed associations between transportation and air quality environmental metrics with overall diabetes prevalence and control within urban/metropolitan counties in the United States from 2006 to 2012. Additionally, we examined effect modification by race/ethnicity through stratification based on the county-level proportion of minority residents. Last, we applied mixture methods to evaluate the effect of simultaneous poor transportation factors and worse air quality on the same outcomes. We found that increased county-level particulate matter air pollution and nitrogen dioxide along with reduced public transportation usage and lower walkability were all associated with increased diabetes prevalence. The minority proportion of the population influences some of these relationships as some of the effects of air pollution and the transportation-related environment are worse among counties with more minority residents. Furthermore, the transportation and air quality mixtures were found to be associated with increased diabetes prevalence and reduced diabetes control. These data further support the burgeoning evidence that poor environments amplify diabetes risk. Future cohort studies should explore the utility of environmental policies and urban planning as tools for improving metabolic health.

RETRACTED ARTICLE: Health-related quality of life among ethnic minority residents in remote Western China: a cross-sectional study

BackgroundPaying attention to the health-related quality of life (HRQOL) of rural residents in poverty-stricken areas is an important part of China's poverty alleviation, but most studies on health-related quality of life have focused on rural residents, elderly individuals, and patients; evidence on the HRQOL of rural minority residents is limited. Thus, this study aimed to assess the HRQOL of rural Uighur residents in remote areas of Xinjiang, China, and determine its influencing factors to provide policy opinions for realizing a healthy China strategy.MethodsA cross-sectional study was performed on 1019 Uighur residents in rural areas. The EQ-5D and self-administered questionnaires were used to assess HRQOL. We applied Tobit and binary logit regression models to analyse the factors influencing HRQOL among rural Uighur residents.ResultsThe health utility index of the 1019 residents was − 0.197,1. The highest proportion of respondents reporting any problem was for mobility (57.5%), followed by usual activity (52.8%). Low levels of the five dimensions were related to age, smoking, sleep time, Daily intake of vegetables and fruit per capita. Gender, age, marital status, physical exercise, sleep duration, daily intake of cooking oil per capita, daily intake of fruit per capita, distance to the nearest medical institution, non-infectious chronic diseases (NCDs), self-rated health score, and participation in community activities were correlated with the health utility index of rural Uighur residents.ConclusionsHRQOL was lower for rural Uyghur residents than for the general population. Improving health behavioural lifestyles and reducing the incidence of poverty (return to poverty) due to illness are effective means of promoting the health in Uyghur residents. The region must fulfil the health poverty alleviation policy and focus on vulnerable groups and low-income residents to improve the health, ability, opportunity, and confidence of this population to live well.