Low-poverty Areas Research Articles

Enabling a Learning Public Health System: Enhanced Surveillance of HIV and Other Sexually Transmitted Infections.

Sexually transmitted infections (STIs) continue to pose a substantial public health challenge in the United States (US). Surveillance, a cornerstone of disease control and prevention, can be strengthened to promote more timely, efficient, and equitable practices by incorporating health information exchange (HIE) and other large-scale health data sources into reporting. New York City patient-level electronic health record data between January 1, 2018 and June 30, 2023 were obtained from Healthix, the largest US public HIE. Healthix data were linked to neighborhood-level information from the American Community Survey. In this cross-sectional study, we compared patients who received a test or tested positive for chlamydia, gonorrhea, and/or HIV with patients who were untested or tested negative, respectively, using generalized estimating equations with logit function and robust standard errors. Among 1,519,121 tests performed for chlamydia, 1,574,772 for gonorrhea, and 1,200,560 for HIV, 2%, 0.6% and 0.3% were positive for chlamydia, gonorrhea, and HIV, respectively. Chlamydia and gonorrhea co-occurred in 1,854 cases (7% of chlamydia and 21% of gonorrhea total cases). Testing behavior was often incongruent with geographic and sociodemographic patterns of positive cases. For example, people living in areas with the highest levels of poverty were less likely to test for gonorrhea but almost twice as likely to test positive compared to those in low poverty areas. Regional HIE enabled review of testing and cases using granular and complementary data not typically available given existing reporting practices. Enhanced surveillance spotlights potential incongruencies between testing patterns and STI risk in certain populations, signaling potential under- and over-testing. These and future insights derived from HIE data may be used to continuously inform public health practice and drive further improvements in provision and evaluation of services and programs.

Rural-urban disparities in cardiovascular disease mortality vary by poverty level and region.

To examine rural and urban disparities in cardiovascular disease (CVD) death rates by poverty level and region. Using 2021 county-level population and mortality data for CVD deaths listed as the underlying cause among adults aged 35-64 years, we calculated age-standardized CVD death rates and rate ratios (RR) for 4 categories of counties: high-poverty rural, high-poverty urban, low-poverty rural, and low-poverty urban (referent). Results are presented nationally and by US Census region. Rural and urban disparities in CVD mortality varied markedly by poverty and region. Nationally, the CVD death rate was highest among high-poverty rural areas (191 deaths per 100,000, RR: 1.76, CI: 1.73-1.78). By region, Southern high-poverty rural areas had the highest CVD death rate (256 deaths per 100,000) and largest disparity relative to low-poverty urban areas (RR: 2.05; CI: 2.01-2.09). In the Midwest and West, CVD death rates among high-poverty areas were higher than low-poverty areas, regardless of rural or urban classification. Results reinforce the importance of prioritizing high-poverty rural areas, especially in the South, in efforts to reduce CVD mortality. These efforts may need to consider socioeconomic conditions and region, in addition to rural and urban disparities.

Accuracy of Cancer Registry Primary Payer Information and Implications for Policy Research.

Cancer registry-based "primary payer at diagnosis" (PPDx) data are commonly used to evaluate the effect of insurance on cancer care outcomes, yet little is known about how well they capture Medicaid or Medicare enrollment. We linked the National Cancer Institute's Surveillance, Epidemiology, and End Results registry data to monthly Centers for Medicare and Medicaid Services (CMS) Medicaid and Medicare enrollment records, state-year Medicaid policy, and managed care enrollment. We selected adults aged 19-64 years diagnosed between 2007 and 2011. We used bivariate analyses to compare PPDx to CMS enrollment at diagnosis month and assessed underreporting rates by patient characteristics and state-year policy. PPDx reported 7.8% Medicare and 10.1% Medicaid, whereas CMS enrollment indicated 5.5% Medicare, 10.4% Medicaid, and 3.4% dual Medicare-Medicaid (N = 896,031). Positive predictive values for PPDx assignment to Medicaid and Medicare were 65.3% and 75.4%, with false negative rates of 52.0% and 33.8%, respectively. Medicaid underreporting was higher in low (56.5%) versus high (50.8%) poverty areas, for males (56.1%) versus females (48.9%), for Medicaid poverty expansion or waiver enrolled (63.8%) versus cash assistance-related eligibility (47.3%), and in states with large managed care enrollment (all P < 0.001). If Medicaid and Medicare enrollment data were used to edit PPDx, 12.0% of persons would switch primary payer assignment. Registry-reported PPDx fails to fully capture Medicaid and Medicare enrollment, which may result in biased estimates of insurance-related policy impacts. Enhancement with objective enrollment data could reduce measurement error and bias in estimates necessary to support policy assessment.

The effect of various social determinants of health on overall survival in the SCLC population.

8588 Background: Small cell lung cancer (SCLC) comprises 10-15% of all lung cancers yet little is known about the impact of social determinants of health (SDOH) on outcomes in patients with SCLC. This study aims to assess the impact of various SDOH on overall survival (OS) in patients diagnosed with SCLC at a single institution. Methods: We have established a large clinical/pathologic/genomic database of all patients diagnosed and treated for SCLC between 1998-2022 at our institution for retrospective study. Demographic data including sex, race, age, stage, address, and smoking status were collected. Poverty index was assessed by percent of school-aged children in poverty at the school district level based off 2021 census using the SAIPE tool and stratified as low (poverty index &lt;=15.1) and high (poverty index &gt;15.1). Water/Air carcinogens were obtained by zip code through EPA TRI Explorer database at year of SCLC diagnosis. Food desert designation was acquired through USDA low income and low access atlas at 0.5 miles for urban residences and 10 miles for rural residences respectively. Violent crime rates were obtained from the FBI Crime Data Explorer by year of diagnosis and police department jurisdiction. OS was computed from date of diagnosis to death or last known follow up date, and univariate Cox proportional hazards (PH) regression analysis was performed. Factors that were significant at significance level of 0.25 in univariate analysis were further evaluated using multivariable Cox PH model. Results: A total of 982 patients with SCLC were included. Univariate PH analysis demonstrated statistically significant improvement in OS with younger age (HR = 1.03, 95% CI 1.02-1.03, p &lt;0.0001), female sex (HR = 0.8, 95% CI 0.7-0.92, p 0.001), low poverty index (HR = 1.12, 95% CI 0.98-1.12, p = 0.097), limited stage disease (HR = 3.12, 95% CI 2.66-3.66, p = &lt;0.0001), and lack of air pollution exposure (HR = 1.09, 95% CI 0.95-1.24, p = 0.227). Multivariable PH analysis showed statistically significant OS improvement for those from lower poverty areas (HR = 1.22, 95% CI: 1.07- 1.4, p = 0.004) as well as in those without air pollution exposure (HR = 1.21, 95% CI: 1.05- 1.39, p = 0.008), controlling for age, sex, stage and smoking. Exposure to water pollution, violent crime rate, food desert designation and pack years smoked were not found to be independent predictors of OS. Conclusions: In this large detailed cohort of 982 patients with SCLC, there was a significantly lower OS for patients living in high poverty areas and for patients exposed to air pollutants. This effect was durable even after for controlling for age, sex, stage, and smoking status, demonstrating that these are independent risk factors associated with poorer OS. Our next research steps will be to examine the biologic basis for these disparities through genomic and transcriptomic analysis.

Estimated Costs of Intervening in Health-Related Social Needs Detected in Primary Care

Health-related social needs are increasingly being screened for in primary care practices, but it remains unclear how much additional financing is required to address those needs to improve health outcomes. To estimate the cost of implementing evidence-based interventions to address social needs identified in primary care practices. A decision analytical microsimulation of patients seen in primary care practices, using data on social needs from the National Center for Health Statistics from 2015 through 2018 (N = 19 225) was conducted. Primary care practices were categorized as federally qualified health centers (FQHCs), non-FQHC urban practices in high-poverty areas, non-FQHC rural practices in high-poverty areas, and practices in lower-poverty areas. Data analysis was performed from March 3 to December 16, 2022. Simulated evidence-based interventions of primary care-based screening and referral protocols, food assistance, housing programs, nonemergency medical transportation, and community-based care coordination. The primary outcome was per-person per-month cost of interventions. Intervention costs that have existing federally funded financing mechanisms (eg, the Supplemental Nutrition Assistance Program) and costs without such an existing mechanism were tabulated. Of the population included in the analysis, the mean (SD) age was 34.4 (25.9) years, and 54.3% were female. Among people with food and housing needs, most were program eligible for federally funded programs, but had low enrollment (eg, due to inadequate program capacity), with 78.0% of people with housing needs being program eligible vs 24.0% enrolled, and 95.6% of people with food needs being program eligible vs 70.2% enrolled. Among those with transportation insecurity and care coordination needs, eligibility criteria limited enrollment (26.3% of those in need being program eligible for transportation programs, and 5.7% of those in need being program eligible for care coordination programs). The cost of providing evidence-based interventions for these 4 domains averaged $60 (95% CI, $55-$65) per member per month (including approximately $5 for screening and referral management in clinics), of which $27 (95% CI, $24-$31) (45.8%) was federally funded. While disproportionate funding was available to populations seen at FQHCs, populations seen at non-FQHC practices in high-poverty areas had larger funding gaps (intervention costs not borne by existing federal funding mechanisms). In this decision analytical microsimulation study, food and housing interventions were limited by low enrollment among eligible people, whereas transportation and care coordination interventions were more limited by narrow eligibility criteria. Screening and referral management in primary care was a small expenditure relative to the cost of interventions to address social needs, and just under half of the costs of interventions were covered by existing federal funding mechanisms. These findings suggest that many resources are necessary to address social needs that fall largely outside of existing federal financing mechanisms.

Cancer disparities related to poverty and rurality for 22 top cancers in Florida

We aimed to examine poverty and rurality as potential predictors of cancer health disparities. This cross-sectional study used data from the Florida Cancer Data System on all cancer diagnoses in the years 2014–2018 to determine age-adjusted incidence and mortality (per 100,000 population) for the 22 most common cancer sites within rural and urban counties, and high poverty and low poverty communities. Rural/urban and high/low poverty related cancer disparities were tested for statistical significance using the Rate Ratio statistical test. Overall cancer incidence was significantly lower in rural areas than in urban, but significantly higher in high poverty communities. Rurality and poverty were both associated with disparity in cancer incidence risk for tobacco-related cancers. The overall mortality was 22% higher in high poverty areas compared to low poverty areas. Ten cancer sites had mortality disparity from 83% to 17% higher in high poverty areas. Only three cancer sites, all tobacco-related, had higher mortality in rural areas than urban areas, demonstrating the intersectional nature of inhaled and smokeless tobacco use in rural low-income communities. Cancer and mortality rates in rural and urban areas may be largely driven by poverty. The high disparities related to high poverty areas reflects poor access to preventative care and treatment. Low income communities, rural or urban, will require focused efforts to address challenges specific to each population.

Reliability of cancer registry primary payer information and implications for policy research.

1587 Background: Researchers commonly use “Primary Payer at Diagnosis” measured in cancer registry data to assess the impact of health policy, such as the Affordable Care Act, on insurance, and the impact of insurance on cancer care and outcomes. Measurement error may bias estimated effect size and significance. Little is known about patterns of Medicaid or Medicare misreporting in registry databases commonly used for policy analysis. Methods: We used the National Cancer Institute’s Surveillance, Epidemiology and End Results registry data for adults aged 19-64 years at diagnosis with known cancer stage, linked to most recently available (2007-2011) CMS records on Medicaid and Medicare enrollment at diagnosis month. We recoded the registry Primary Payer variable into 6 categories: private/managed care, Medicare, Medicaid, other government, status unknown, uninsured. State-year policy data regarding Medicaid eligibility and managed care enrollment were also linked. We compared the registry data to Medicaid and/or Medicare enrollment data, and calculated underreporting rates by patient characteristics and state policy. Results: The linked sample (N = 896,031) was 68% non-Hispanic white, 49% male. Overall, the registry data reported 7.8% Medicare and 10.1% Medicaid, while enrollment was 5.5% Medicare, 10.4% Medicaid, and 3.4% dual Medicare-Medicaid. The registry data concordantly identified 61.4% and 57.7% of persons identified per enrollment data to be Medicaid-only and Medicare-only, respectively (Table). Most Medicaid-only enrollees without concordant registry information were reported to have private insurance or be uninsured. Medicaid underreporting (39% overall), was higher for males (43%) vs females (37%), in low (46%) vs high (38%) poverty areas, for Medicaid poverty expansion or waiver enrolled (50%) vs cash assistance related eligibility (33%), and in states with large managed care enrollment, all at p&lt;.001. If Medicaid and Medicare enrollment data were used to edit the registry data, 8% of persons would switch insurance assignment. Conclusions: Primary Payer data reported by cancer registries are subject to measurement error and may result in biased estimates of insurance-related policy impacts. Enhancement with objective Medicaid and Medicare enrollment data will reduce measurement error and may result in unbiased estimates necessary to support policy assessment. [Table: see text]

Risk Factors for COVID-19 Positivity and Hospital Admission Among Arab American Adults in Southern California.

Objective:Little is known about risk factors associated with COVID-19 infection among Arab American people. We aimed to understand the predictors of receiving a positive COVID-19 test result and being admitted to the hospital for COVID-19 among Arab American adults using data from a hospital near an Arab ethnic enclave.Methods:We used electronic medical record data for Arab American adults aged ≥18 years from March 1, 2020, through January 31, 2021, at Sharp Grossmont Hospital in La Mesa, California. The primary outcomes were receiving a positive COVID-19 test result and being admitted to the hospital for COVID-19. We ran logistic regression models with individual- and population-level risk factors to determine the odds of each primary outcome.Results:A total of 2744 Arab American adults were tested for COVID-19, of whom 783 (28.5%) had a positive test result. In the fully adjusted model, women had lower odds of receiving a positive test result than men (adjusted odds ratio [aOR] = 0.77; 95% CI, 0.64-0.92), and adults living in high-poverty areas had higher odds of receiving a positive test result than adults in lower-poverty areas (aOR = 1.25; 95% CI, 1.04-1.51). Of the 783 Arab American adults with data on admission, 131 (16.7%) were admitted. For every 1-unit increase in the Charlson Comorbidity Index, the odds of admission increased by 66% (aOR = 1.66; 95% CI, 1.36-2.04).Conclusion:The risk of receiving a positive test result for COVID-19 was higher among Arab American adults living in high-poverty areas than in lower-poverty areas. The risk of admission was directly related to overall health status. Future work should aim to understand the barriers to prevention and testing in this population.

Trends in breast cancer incidence rates by race/ethnicity: Patterns by stage, socioeconomic position, and geography in the United States, 1999‐2017

The incidence rate of breast cancer has been increasing over time across race/ethnicity in the United States. It is unclear whether these trends differ among stage, poverty, and geography subgroups. Using data from the North American Association of Central Cancer Registries, this study estimated trends in age-adjusted breast cancer incidence rates among women aged 50 to 84 years from 1999 to 2017 by race/ethnicity (non-Hispanic Black, non-Hispanic White, and Hispanic) and across subgroups (stage, county-level poverty, county urban/rural status, and geographic region [West, Midwest, South, and Northeast]). From 2004 to 2017, breast cancer incidence rates increased across race/ethnicity and subgroups, with the greatest average annual percent increases observed for non-Hispanic Black women, overall (0.9%) and those living in lower poverty areas (0.8%), rural areas (1.2%), and all regions except the West (0.8%-1.0%). Stronger increases among non-Hispanic Black women were observed for local-stage disease and for some subgroups of distant-stage disease. Non-Hispanic Black women had the smallest decrease in regional-stage disease across most subgroups. Similarly, Hispanic women had the strongest increases in some subgroups, including areas with higher poverty (0.6%-1.2%) and in the West (0.8%), for local- and distant-stage disease. These trends highlight concerns for an increasing burden of breast cancer among subpopulations, with some already experiencing disparate breast cancer mortality rates, and they highlight the need for targeted breast cancer prevention and efforts to reduce mortality disparities in areas with increasing incidence.

Centralization and Subnational Capacity: The Struggle to Make Federalism Work Equitably in Public Education

Vast disparities between and within American states’ responses to the COVID-19 pandemic have evoked renewed attention to whether greater centralization might enhance investments in subnational capacity and remedy subnational inequalities or instead erode subnational organizational capacity. Developments in American public education (1997–2015) offer perspective on this puzzle, which we examine by applying interrupted time series analysis to a novel dataset to assess the implications of centralization on subnational investments in administrative and technical capacity, two dimensions of organizational capacity. We find simultaneous subnational erosion in administrative capacity and growth in technical capacity following centralization, both of which appear concentrated in low-poverty areas despite centralization’s explicit antipoverty purposes. Public education reforms highlight both the challenge of dismantling subnational inequality through centralization and the need for future research on policy designs that enable centralization to yield subnational capacity that is able to remedy inequality.

Modification of Asthma Clinical Trial Treatment Efficacy by Social and Environmental Exposures

BACKGROUND AND AIM: Randomized controlled trials (RCTs) are considered the gold standard for examining effectiveness of clinical interventions, though they rarely evaluate social and environmental exposures that may modify underlying disease states. This is a particular concern for asthma, which is consistently linked to air pollution and social stressors. METHODS: We reexamined the AsthmaNet Step-up Yellow Zone Inhaled Corticosteroids to Prevent Exacerbations (STICS) trial, in which participants were randomly assigned to low (44 ug/inhalation) or high (220 ug/inhalation) dose of fluticasone inhaled corticosteroid treatment (ICS) upon asthma exacerbation, and followed to assess subsequent exacerbations. AsthmaNet reported no significant differences between dose groups in number of exacerbations, or time to first rescue prednisone use (Jackson et al, NEJM 2018). We geocoded participant residences, estimated mean exposures over follow-up using a validated national spatiotemporal model for fine particles (PM2.5), and derived census tract-level indicators for poverty rates and medically-underserved areas (MUAs). We used Cox proportional hazard models to assess time-to-prednisone use, and tested whether co-exposures modified associations between treatment arm and outcomes. RESULTS:Individuals with above-median (7.4 µg/m3) PM2.5 exposures had, on average, more exacerbation events over the study, than did those with below-median PM2.5 [µ= 1.75 events (SD = 1.84) vs. µ= 1.45 events (SD = 1.71)]. The high ICS dose was associated with shorter time-to-prednisone-use, compared to low ICS dose, {only} among those with above-median PM2.5 exposure (p =.048), or living in lower-poverty areas (p =.08) or non-MUAs (p =.02). CONCLUSIONS:While the overall impact of quintupling ICS dose on exacerbations was null, specific social and environmental factors modified observed treatment effects. In high-PM2.5 or less-deprived areas, higher ICS doses conferred shorter times to exacerbation. Clinical trials should account for social and environmental exposures, to better understand intervention impacts and identify sub-groups for whom interventions may be particularly effective. KEYWORDS: asthma exacerbations, PM2.5, inhaled corticosteroids, RCT

Understanding the Relationship between Dominant Geo-Environmental Factors and Rural Poverty in Guizhou, China

Geo-environmental factors are believed to be major determinants of rural poverty. However, few studies have quantified the effects of these factors on rural poverty in China. In this paper, we used county-level poverty incidence data and geo-environmental factors to explore spatial patterns of the incidence of poverty using global and local spatial autocorrelation analysis and to investigate the effect of geo-environment factors on rural poverty using a geo-detector model. Our results demonstrated that there was spatial clustering of the incidence of poverty in the study area. The incidence of poverty decreased from south to north and from the east and west to the central area. The incidence of high–high poverty areas was mainly distributed in the southeast of Guizhou Province and the incidence of low–low poverty areas was distributed in the northeast. The results also demonstrated that percentage of effective irrigation on arable land, slope, elevation and vegetation cover were the dominant factors explaining the spatial pattern of poverty. Interaction analysis demonstrated that the slope non-linearly enhanced the percentage of effective irrigation on arable land. Our findings suggested that geo-environment is the fundamental control factor explaining the spatial pattern of rural poverty in China. Through analysis of the impact of the geo-environment on the spatial pattern of poverty, this study provides a reference for effectively implementing targeted alleviation of poverty.

The urban crime and heat gradient in high and low poverty areas

Using spatially disaggregated daily crime data for the City of Los Angeles, this paper estimates the impact of ambient temperature on crime, and how this relationship varies across neighborhoods. Our estimates suggest that, relative to cooler days, overall crime rates are 1.72% and 1.90% higher when daily maximum temperature exceeds 75 and 90 degrees Fahrenheit respectively. This heat-crime relationship is much stronger in low-income neighborhoods, and is largely driven by non-pecuniary crimes of passion, such as domestic crimes and crimes against intimate partners. Using internal policing data, we find that the surge in crime is not a result of reduced policing effort in low-income areas during hot days. Instead, we document that characteristics of the built environment such as housing age and urban greenery are highly correlated with the slope of the heat-crime relationship. Our estimates suggest that the monetary cost of heat-induced crime incurred by the highest poverty neighborhoods is five times larger than that incurred by more affluent areas, highlighting the starkly differential impact of extreme weather even over small geographies within cities.

The Impact of Socioeconomic Status on the Clinical Outcomes of COVID-19; a Retrospective Cohort Study.

There have been limited data assessing the influence of disadvantaged socioeconomic status (SES) on the incidence and clinical outcomes of COVID-19 patients within the diverse communities of the United States. Here, we aim to investigate the association between poverty level, as an indicator of SES, and COVID-19 related clinical outcomes including hospitalization and all-cause mortality. This retrospective cohort study included 3528 patients with laboratory confirmed COVID-19 seen at a large New York City health system between March 1, 2020 and April 1, 2020. Data for neighborhood level poverty was acquired from the American Community Survey 2014–2018 and defined as the percent of residents in each ZIP code whose household income was below the federal poverty threshold (FPT): 0% to < 20% below FPT (low poverty) and > 20% below FPT (high poverty). COVID-19 positive patients who resided in high poverty areas were significantly younger, had a higher prevalence of comorbidities and were more likely to be of female gender or a racial minority when compared to individuals living in low poverty areas. Residence in a high poverty area was not associated with an increased risk of COVID-19 related hospitalization and was found to be associated with a decreased risk of in-hospital mortality. This study suggests the existence of an unequal socioeconomic gradient in the demographic and clinical presentation of COVID-19 patients including differences in age, gender and race between poverty groups. Further studies are needed to fully assess the intersectionality of SES with the COVID-19 pandemic.Electronic supplementary materialThe online version of this article (10.1007/s10900-020-00944-3) contains supplementary material, which is available to authorized users.

生态系统服务与贫困关联视角下生态扶贫策略的实施路径

生态文明建设与脱贫攻坚均是重要的国家战略。由于贫困与生态环境问题存在紧密耦合关系，在生态保护修复中探索生态扶贫措施的实施路径可获得生态环境改善与社会经济发展的双赢。构建生态系统服务-贫困关联分析模型，以山水林田湖草生态保护修复试点的山西省宁武县和静乐县为例，通过村级多维贫困指数（VPI）评价贫困程度，并结合生态系统服务识别出生态修复与生态系统服务提升的重点地区，最后在这些区域布局合适的生态扶贫措施。结果表明处于高贫困的区域占研究区总面积的41%，中贫困所占面积比例为47%，低贫困所占面积比例为12%，地形条件、劳动力状况、生活水平的差异构成了宁武县和静乐县贫困的空间分布格局。研究区水源涵养、土壤保持、食物供给等生态系统服务计算结果分别与贫困程度叠加出九种类型，并根据叠加结果将研究区划分为低贫困修复区、低贫困保护区、中贫困修复区、高贫困修复区和高贫困保护区五个区域，提出在高贫困保护区、低贫困保护区实施以保护为主的扶贫措施，在低贫困修复区、中贫困修复区、高贫困修复区要利用生态修复的契机解决乡镇的主要致贫因素。研究为贫困或欠发达的农村区域生态保护修复与生态扶贫的结合提供借鉴参考。;The ecological civilization and poverty alleviation are both important national strategies. Because there is a close coupling relationship between poverty and eco-environmental problems, exploring the implementation path of ecological poverty alleviation measures in ecological protection and restoration can achieve a win-win situation between ecological environment improvement and socio-economic development. In this paper, an analysis model of correlation between ecosystem service and poverty was constructed. Ningwu and Jingle counties in Shanxi Province was taken as the case area, where there are pilot projects of ecological protection and restoration of mountain-water-forests-cropland-lakes-grasses. The village-level multidimensional poverty indicators (VPI) is used to evaluate the poverty level and identify key areas for ecological restoration in conjunction with ecosystem services, and layout appropriate ecological poverty alleviation measures. The results show that high poverty areas account for 41% of the study area, middle poverty areas account for 47%, and low poverty areas account for 12%. Differences in terrain conditions, labor conditions, and living standards have formed the different spatial distribution pattern of poverty in Ningwu and Jingle County. The calculation results of ecosystem services such as water conservation, soil conservation, food supply in the study area were superimposed on the poverty level for each of the nine types. Based on the superimposed results, the study area is divided into five types of zones:low-poverty restoration area, low-poverty protection area, middle-poverty restoration area, high-poverty restoration area, and high-poverty protection area. The protection-oriented poverty alleviation measures will be implemented at the low-poverty protection area and high-poverty protection area. It shall use the opportunity of ecological restoration to solve the main poor factors at low-poverty restoration area, middle-poverty restoration area and high-poverty restoration area. This study provides a reference for the combination of ecological protection and restoration with ecological poverty alleviation in poor and underdeveloped rural areas.

Socioeconomic Status and Determinants of Pediatric Antibiotic Use.

Introduction. Evidence suggests that early-life antibiotic use can alter gut microbiome, predisposing children to obesity. The obesity epidemic has a disproportionate effect on individuals from lower socioeconomic status (SES). Thus, this study aims to explore the link between SES and antibiotic use. Design. We performed a retrospective cohort study of all babies born at and receiving 2 or more outpatient visits at a large, suburban health system in Illinois (United States) between 2007 and 2017. We collected data on zip code as a proxy for SES and antibiotic use in the first year of life. We also obtained comorbid diagnosis codes, race/ethnicity, gender, and number of inpatient, outpatient, and emergency department visits. Results. A total of 7224 patients met our study criteria. Children from low-poverty areas received a lifetime average of 4.28 prescriptions, while those from high-poverty neighborhoods received an average of 3.31 prescriptions. This was statistically significant in our unadjusted analysis but not after adjusting for covariates. Children from high-poverty areas were significantly more likely to receive more antibiotics at 48 hours, 1 week, and 1 month of life in our unadjusted analysis, but not after adjusting for covariates. In our unadjusted and adjusted analyses, children from high-poverty areas were significantly more likely to have received antibiotics at 1 week of life. Conclusion. The relationship between SES and antibiotic use warrants further investigation to help elucidate possible causes of the disproportionate impact obesity has in low-income communities.

Concomitant exposure to area-level poverty, ambient air volatile organic compounds, and cardiometabolic dysfunction: a cross-sectional study of U.S. adolescents

PurposeA key to better understanding the influence of the place of residence on cardiometabolic function is the effect of concomitant exposure to both air pollution and residence in economically marginalized areas. We hypothesized that, among adolescents, the association between air pollution and cardiometabolic function is exacerbated among residents of economically marginalized areas. MethodsIn this cross-sectional study, individual-level data on cardiometabolic function collected from a representative sample of U.S. adolescents in the National Health and Nutrition Examination Survey (n = 10,415) were merged with data on area-level poverty (U.S. decennial survey and American Community Survey) and air pollution levels (National-Scale Air Toxics Assessment ) using contemporary census-tract identifiers. We excluded respondents who were pregnant, had hypertension or diabetes or using medication for hypertension or diabetes, or with missing data on outcome variables. ResultsWe observed a significant interaction between area-level poverty and air pollution. Among residents of high-poverty areas, exposure to high levels of air pollution predicted a 30% elevated odds of cardiometabolic dysfunction (OR = 1.30; 95% CI: 1.04, 1.61), whereas in low-poverty areas, exposure to high levels of air pollution was not associated with elevated odds of cardiometabolic dysfunction (OR = 1.04; 95% CI: 0.85, 1.28). ConclusionsOur findings suggest that the cardiometabolic consequences of air pollution are more readily realized among residents of economically marginalized areas. Structural remedies are discussed.

Sex-Specific Associations Between Area-Level Poverty and Cardiometabolic Dysfunction Among US Adolescents.

Cardiometabolic disease is the leading cause of mortality in the United States. Cardiometabolic function during adolescence predicts future cardiometabolic disease, yet few studies have examined early determinants of cardiometabolic function. Informed by evidence of sex differences in the prevalence and severity of cardiometabolic disorders and evidence of sexual dimorphism in the stress response, we examined sex differences in the association between living in poverty and cardiometabolic function during adolescence, a precursor of later cardiometabolic disorders. We linked data from 10 415 adolescents aged 12-19 in the National Health and Nutrition Examination Survey (1999-2012) with US Census-tract data on area-level poverty (percentage of the population living in poverty, grouped into quartiles). We parameterized cardiometabolic dysfunction by summing the z scores of 6 cardiometabolic biomarkers, grouped into quintiles. Hierarchical ordinal models estimated associations. Compared with residents in low-poverty areas, residents in high-poverty areas had elevated odds of cardiometabolic dysfunction (highest quartile of poverty odds ratio [OR] = 1.27; 95% confidence interval [CI], 1.08-1.50). This association was more pronounced among boys than girls (highest quartile of poverty for boys: OR = 1.36; 95% CI, 1.10-1.70; highest quartile of poverty for girls: OR = 1.17; 95% CI, 0.94-1.47). Our study supports the existence of sex-specific associations. These results highlight the potential for community-based programs, such as housing assistance, to improve population health.

Immigrant enclaves and risk of drug involvement among asylum-seeking immigrants in Sweden: A quasi-experimental study

BackgroundSweden is a major host nation for asylum-seeking immigrants, and residential placement of these immigrants is an important policy concern. This quasi-experimental study estimated of the impact of being placed into an “immigrant enclave” on risk of officially-recognized drug involvement (ORDI) among asylum-seeking immigrants over a 15-year period. MethodsAll data come from Swedish registries. The sample consisted of (a) asylum-seeking immigrants aged 5–35 years old at arrival (N = 51,017) that were subject to a nationwide policy (enforced 1987–1991) that dispersed asylum-seeking immigrants across municipalities, and (b) native-born Swedes aged 15 and older during this same period (N = 1,040,311). Neighborhood immigrant composition was quantified using the Reardon Index; residents of “immigrant enclave” neighborhoods (n = 960) were compared to residents of all other neighborhoods (n = 2,471). Cox proportional hazards models assessed the relationship between living in an enclave and risk of ORDI, identified by national registries, through 2015. ResultsOverall, 29.7% of immigrants were assigned to, and 25.5% of Swedes lived in, an enclave. Cumulative incidence of ORDI in enclaves was 6.34% as compared to 6.89% in other neighborhoods. Immigrants living in an enclave had lower risk of ORDI (Hazard ratio (HR): 0.86, 95% Confidence Interval (CI): 0.77 – 0.96). This protective association was marginally stronger in lower poverty areas. Native-born Swedes living in an enclave had higher risk of ORDI (HR: 1.05, 95% CI: 1.03–1.08), a relationship that was exacerbated by neighborhood poverty. ConclusionsNeighborhood immigrant composition is associated with risk of ORDI, with differential associations for immigrants and native-born populations.

Operational efficiency, patient composition and regional context of U.S. health centers: Associations with access to early prenatal care and low birth weight

Community health centers (CHCs) provide comprehensive medical services to medically under-served Americans, helping to reduce health disparities. This study aimed to identify the unique compositions and contexts of CHCs to better understand variation in access to early prenatal care and rates of low birth weights (LBW). Data include CHC-level data from the Uniform Data System, and regional-level data from the US Census American Community Survey and Behavioral Risk Factor Surveillance System. First, latent class analysis was conducted to identify unobserved subgroups of CHCs. Second, data envelopment analysis was performed to evaluate the operational efficiency of CHCs. Third, we used generalized linear models to examine the associations between the CHC subgroups, efficiency, and perinatal outcomes. Seven classes of CHCs were identified, including two rural classes, one suburban, one with large centers serving poor minorities in low poverty areas, and three urban classes. Many of these classes were characterized by the racial compositions of their patients. Findings indicate that CHCs serving white patients in rural areas have greater access to early prenatal care. Health centers with greater efficiency have lower rates of LBW, as do those who serve largely white patient populations in rural areas. CHCs serving poor racial minorities living in low-poverty areas had particularly low levels of access to early prenatal care and high rates of LBW. Findings highlight that significant diversity exists in the sociodemographic composition and regional context of US health centers, in ways that are associated with their operations, delivery of care, and health outcomes. Results from this study highlight that while the provision of early prenatal care and the efficiency with which a health center operates may improve the health of the women served by CHCs and their babies, the underlying social and economic conditions facing patients ultimately have a larger association with their health.