Neighborhood Socioeconomic Status and Primary Health Care: Usual Points of Access and Temporal Trends in a Major US Urban Area

Socioeconomic barriers to prenatal diagnosis of critical congenital heart disease

OBJECTIVE

The study was designed to assess the impact of socioeconomic barriers on the rate of prenatal diagnosis of critical congenital heart disease (CCHD).

METHODS

This was a retrospective review of the Medicaid analytic extract (MAX) dataset, a national Medicaid administrative claims database with linked maternal-infant claims, from 2007 to 2012. Infants with CCHD were identified by searching for International Classification of Diseases (ICD) 9 codes and Procedural Coding System (PCS) codes for CCHD within the first 6 months after the delivery date. Multivariate logistic regression was used to evaluate the effect of maternal and socioeconomic factors on the prenatal diagnosis rate.

RESULTS

There were 4702 mother-infant dyads included in the analysis. The prenatal diagnosis rate of CCHD was 27.9%. Factors independently associated with odds of prenatal diagnosis of CCHD were presence of maternal diabetes (OR, 2.055; P < .001), ZIP code level median household income (OR, 1.005; P = .015), sonographer labor quotient (OR, 1.804; P = .047), the year of the delivery (OR, 1.155; P < .001), and needing a view other than a 4 chamber or outflow tract view to obtain the diagnosis (OR, 0.383; P < .001).

CONCLUSION

Maternal health, diabetes, socioeconomic factors, and access to sonographers impacts prenatal diagnosis of CCHD.

Experiment To Decrease Neighborhood Poverty Had Limited Effects On Emergency Department Use

Neighborhood environments are increasingly thought to affect emergency department (ED) use. However, because people decide where to live based on a range of factors, it can be challenging to identify the causal impact of living in higher-poverty neighborhoods on increased rates of ED visits. Our study leveraged the Moving to Opportunity for Fair Housing Demonstration Program, a social experiment beginning in 1994 that randomly assigned approximately 4,600 households that received federal housing assistance to different neighborhood conditions. We linked program participants in four states with an average of twelve years of administrative data on ED use (up to twenty-one years after randomization). Contrary to our expectations, we did not find a consistently significant connection between neighborhood poverty and overall ED use during this follow-up period. This result was observed for both adults and people who were children at the time of randomization, as well as for various classifications of ED visits. The findings can help direct future research that seeks to clarify the relationship between neighborhood environments and health care use.

Acute and outpatient service utilisation prior to, during, and following enrolment in community-based mental health treatment among children and youth in Central Ontario: A proof of concept for cross-sectoral data linkage

AIM

Given the fragmentation of mental health and addictions (MHA) services for children and youth, comprehensive data on utilisation patterns are lacking. We sought to describe MHA-related service use across the community, acute and outpatient sectors.

METHODS

We used linked health-administrative data sets to identify a cohort of individuals aged <18 who received MHA treatment in a large community organisation in Ontario, Canada between 1 April 2007 and 31 March 2012. We described their socio-demographic characteristics, examined their MHA-related concurrent service use in acute care and outpatient physician settings (primary care providers, paediatricians and psychiatrists), and compared service utilisation prior to, during and following enrolment using Poisson regressions.

RESULTS

Among 7285 children and youth receiving community MHA treatment, there were 481 concurrent MHA-related emergency department visits, 173 hospitalisations and 12140 outpatient physician visits. The average age at enrolment was 10.5 years, and 64% of clients were enrolled for ≥3 months. MHA-related emergency department use significantly declined from 1 year prior, compared to 1 year following receipt of community MHA treatment (112 vs. 82 visits per 1000 person-years, P < 0.001), particularly in females, ages 10-14, those living in higher-income neighbourhoods and urban areas, and those with anxiety disorders. MHA hospitalisations also declined (45 vs. 32, P < 0.001), while outpatient physician visits increased (1750 vs. 1874, P < 0.001).

CONCLUSIONS

Our study suggests that community-based MHA treatment may be effective in diverting children and youth away from acute care and highlights the importance of data linkage as a means to better understand the complexity of cross-sectoral MHA service use.

Psychological and neighborhood factors associated with urban women's preventive care use

Women are more likely than men to forego care-including preventive care. Understanding which factors influence women's preventive care use has the potential to improve health. This study focuses on the largely understudied areas of psychological barriers (depression) and neighborhood factors (support and stressors) that may be associated with women's preventive care use through secondary analysis of the Chicago Community Adult Health Study. Across models, 30-40% of the variance in preventive care adherence was explained by the neighborhood. Depressive symptoms were not associated with preventive care use when neighborhood factors were included. However, stratified models showed that associations varied by race/ethnicity. Previous research has tended to focus on individual determinants of care, but this study suggests that barriers to care are far more complex. Efforts aimed at improving care utilization need to be multipronged and interventions need to take an individual's demographics, mental health, and context into account.

Patterns in Geographic Access to Health Care Facilities Across Neighborhoods in the United States Based on Data From the National Establishment Time-Series Between 2000 and 2014

IMPORTANCE

The association between proximity to health care facilities and improved disease management and population health has been documented, but little is known about small-area health care environments and how the presence of health care facilities has changed over time during recent health system and policy change.

OBJECTIVE

To examine geographic access to health care facilities across neighborhoods in the United States over a 15-year period.

DESIGN, SETTING, AND PARTICIPANTS

Using longitudinal business data from the National Establishment Time-Series, this cross-sectional study examined the presence of and change in ambulatory care facilities and pharmacies and drugstores in census tracts (CTs) throughout the continental United States between 2000 and 2014. Between January and April 2019, multinomial logistic regression was used to estimate associations between health care facility presence and neighborhood sociodemographic characteristics over time.

MAIN OUTCOMES AND MEASURES

Change in health care facility presence was measured as never present, lost, gained, or always present between 2000 and 2014. Neighborhood sociodemographic characteristics (ie, CTs) and their change over time were measured from US Census reports (2000 and 2010) and the American Community Survey (2008-2012).

RESULTS

Among 72 246 included CTs, the percentage of non-US-born residents, residents 75 years or older, poverty status, and population density increased, and 8.1% of CTs showed a change in the racial/ethnic composition of an area from predominantly non-Hispanic (NH) white to other racial/ethnic composition categories between 2000 and 2010. The presence of ambulatory care facilities increased from a mean (SD) of 7.7 (15.9) per CT in 2000 to 13.0 (22.9) per CT in 2014, and the presence of pharmacies and drugstores increased from a mean (SD) of 0.6 (1.0) per CT in 2000 to 0.9 (1.4) per CT in 2014. Census tracts with predominantly NH black individuals (adjusted odds ratio [aOR], 2.37; 95% CI, 2.03-2.77), Hispanic/Latino individuals (aOR 1.30; 95% CI, 1.00-1.69), and racially/ethnically mixed individuals (aOR, 1.53; 95% CI, 1.33-1.77) in 2000 had higher odds of losing health care facilities between 2000 and 2014 compared with CTs with predominantly NH white individuals, after controlling for other neighborhood characteristics. Census tracts of geographic areas with higher levels of poverty in 2000 also had higher odds of losing health care facilities between 2000 and 2014 (aOR, 1.12; 95% CI, 1.05-1.19).

CONCLUSIONS AND RELEVANCE

Differential change was found in the presence of health care facilities across neighborhoods over time, indicating the need to monitor and address the spatial distribution of health care resources within the context of population health disparities.

Association of neighbourhood migrant density and risk of non-affective psychosis: a national, longitudinal cohort study

BACKGROUND

Elevated risk of psychotic disorders in migrant groups is a public mental health priority. We investigated whether living in areas of high own-region migrant density was associated with reduced risk of psychotic disorders among migrants and their children, and whether generation status, probable visible minority status, or region-of-origin affected this relationship.

METHODS

We used the Swedish registers to identify migrants and their children born between Jan 1, 1982, and Dec 31, 1996, and living in Sweden on or after their 15th birthday. We tracked all included participants from age 15 years or date of migration until emigration, death, or study end (Dec 31, 2016). The outcome was an ICD-10 diagnosis of non-affective psychosis (F20-29). We calculated own-region and generation-specific own-region density within the 9208 small areas for market statistics neighbourhoods in Sweden, and estimated the relationship between density and diagnosis of non-affective psychotic disorders using multilevel Cox proportional hazards models, adjusting for individual confounders (generation status, age, sex, calendar year, lone dwelling, and time since migration [migrants only]), family confounders (family income, family unemployment, and social welfare), and neighbourhood confounders (deprivation index, population density, and proportion of lone dwellings), and using the Akaike information criterion (AIC) to compare model fit.

FINDINGS

Of 468 223 individuals included in the final cohort, 4582 (1·0%) had non-affective psychotic disorder. Lower own-region migrant density was associated with increased risk of psychotic disorders among migrants (hazard ratio [HR] 1·05, 95% CI 1·02-1·07 per 5% decrease) and children of migrants (1·03, 1·01-1·06), after adjustment. These effects were stronger for probable visible minority migrants (1·07, 1·04-1·11), including migrants from Asia (1·42, 1·15-1·76) and sub-Saharan Africa (1·28, 1·15-1·44), but not migrants from probable non-visible minority backgrounds (0·99, 0·94-1·04). Among migrants, adding generation status to the measure of own-region density provided a better fit to the data than overall own-region migrant density (AIC 36 103 vs 36 106, respectively), with a 5% decrease in generation-specific migrant density corresponding to a HR of 1·07 (1·04-1·11).

INTERPRETATION

Migrant density was associated with non-affective psychosis risk in migrants and their children. Stronger protective effects of migrant density were found for probable visible minority migrants and migrants from Asia and sub-Saharan Africa. For migrants, this risk intersected with generation status. Together, these results suggest that this health inequality is socially constructed.

FUNDING

Wellcome Trust, Royal Society, Mental Health Research UK, University College London, National Institute for Health Research, Swedish Research Council, and FORTE.

Association of Socioeconomic Status With Ischemic Stroke Survival

Background and Purpose- The aim of the study was to determine the impact of individuals' socioeconomic status and their Primary Care Service Area Socioeconomic Index on survival after ischemic stroke. Methods- We conducted a nationwide population-based cohort study in Catalonia, Spain. We included all patients with first ischemic stroke admitted to a public hospital between January 1, 2015, and December 31, 2016. We measured both individual socioeconomic status (categorized as exempts, <€18 000 [$US 20 468] income per year, and >€18 000 income per year) and Primary Care Service Area Socioeconomic Index (from 0 to 100 categorized in quartiles). We used mixed-effects logistic and survival models to estimate odds ratios and hazard ratios for the short- (30 days) and the long-term (3 years) all-cause case fatality rates by individuals' socioeconomic status groups. Results- The cohort consisted of 16 344 ischemic stroke patients with 24 638 person-years of follow-up. We did not find an association between the lowest socioeconomic individual status and short-term survival (odds ratio, 1.03; 95% CI, 0.76-1.40), although we found it in patients with <€18 000 income/year (odds ratio, 1.26; 95% CI, 1.10-1.45). At long-term, after adjustment, we observed a gradient in mortality risk with decreasing individual socioeconomic status (hazard ratio, 1.52; 95% CI, 1.30-1.77). The Primary Care Service Area Socioeconomic Index had only an influence on short-term survival (odds ratio, 1.19; 95% CI, 1.03-1.37). Conclusions- Individuals' socioeconomic status was associated with short- and long-term survival in patients with ischemic stroke. Conversely, Primary Care Service Area Socioeconomic Index measures had an influence only in short-term survival. A small fraction of this association is due to differences in comorbidity and cardiovascular risk factors. Interventions addressing both individuals' and primary care service socioeconomic aspects might eventually affect differently short- and long-term survival.

Personal and Neighborhood Attributes Associated with Cervical and Colorectal Cancer Screening in an Urban African American Population

Introduction

Assessing individual social determinants of health in primary care might be complemented by consideration of population attributes in patients’ neighborhoods. We studied associations between cervical and colorectal cancer screening and neighborhood attributes among an African American population in Philadelphia.

Methods

We abstracted demographic and cancer screening information from records of patients seen during 2006 at 3 federally qualified health centers and characterized patients’ census tracts of residence by using census, survey, and other data to define population metrics for poverty, racial segregation, educational attainment, social capital, neighborhood safety, and violent crime. We used generalized estimating equations to obtain adjusted relative risks of screening associated with individual and census tract attributes.

Results

Among 1,708 patients for whom colorectal cancer screening was recommended, screening was up to date for 41%, and among 4,995 women for whom cervical cancer screening was recommended, screening was up to date for 75%. After controlling for age, sex (for colorectal cancer screening), insurance coverage, and clinic site, people living in the most racially segregated neighborhoods were nearly 10% more likely than others to be unscreened for colorectal cancer. Other census tract population attributes were not associated with differences in screening levels for either cancer.

Conclusions

The association between lower rates of colorectal cancer screening and neighborhood racial segregation is consistent with known barriers to colonoscopy among African Americans combined with effects of segregation on health-related behaviors. Recognition of the association between segregation and lower colorectal cancer screening rates might be useful in informing and targeting community outreach to improve screening.

Mobile Health and Technology Usage by Patients in the Diabetes, Nutrition, and Weight Management Clinic at an Urban Academic Medical Center

Background: Low-income, minority, and underserved populations are often excluded from mobile health (mHealth) research. This cross-sectional study sought to define how patients at an urban, academic safety net hospital use technology in their daily lives in an effort to incorporate mHealth into clinical care and research. Methods: Patients receiving care in the Diabetes and Weight Management subspecialty clinic at Boston Medical Center were asked to complete a 17-question survey on technology usage. It was modeled on a Pew Research Center survey and available in English, Portuguese, and Spanish. Results: Of the 394 survey respondents, 279 (70.8%) completed all questions. Majority of respondents were female (76.4%) and between 30 and 49 years old (42.9%). Respondents self-identified primarily as black/African American (35.8%), white/Caucasian (28.2%), and not Hispanic/Latino (46.4%). Over 90% owned a smartphone and more than 85% accessed the Internet on a mobile device at least once per day. Regarding mHealth usage, 33.5% and 23.1% reported current use of health- and weight loss-centric applications (apps), respectively, while only 19.6% of patients with diabetes used smartphone apps as diabetes self-management tools. Nearly three-quarters (73.3%) reported interest in using apps to manage health. Respondents preferred e-mail (48.7%), phone (39.6%), and in-person communication (36.3%) as research recruitment tools. Conclusions: The overwhelming majority of an urban, underserved minority population cared for in a subspecialty clinic have access to mHealth-compatible devices and are either using or interested in using mHealth technology.

Individual and Neighborhood Factors Associated with Undiagnosed Asthma in a Large Cohort of Urban Adolescents

Undiagnosed asthma adds to the burden of asthma and is an especially significant public health concern among urban adolescents. While much is known about individual-level demographic and neighborhood-level factors that characterize those with diagnosed asthma, limited data exist regarding these factors and undiagnosed asthma. This observational study evaluated associations between undiagnosed asthma and individual and neighborhood factors among a large cohort of urban adolescents. We analyzed data from 10,295 New York City adolescents who reported on asthma symptoms and diagnosis; a subset (n = 6220) provided addresses that we were able to geocode into US Census tracts. Multivariable regression models estimated associations between undiagnosed asthma status and individual-level variables. Hierarchical linear modeling estimated associations between undiagnosed asthma status and neighborhood-level variables. Undiagnosed asthma prevalence was 20.2%. Females had higher odds of being undiagnosed (adjusted odds ratio (AOR) = 1.25; 95% confidence interval (CI) = 1.13-1.37). Compared to White, non-Hispanic adolescents, Asian-Americans had higher risk of being undiagnosed (AOR = 1.41; 95% CI = 1.01-1.95); Latinos (AOR = 0.67; 95% CI = 0.45-0.83); and African-Americans/Blacks (AOR = 0.66; 95% CI = 0.52-0.87) had lower risk; Latinos and African-Americans/Blacks did not differ significantly. Living in a neighborhood with a lower concentration of Latinos relative to White non-Latinos was associated with lower risk of being undiagnosed (AOR = 0.66; CI = 0.43-0.95). Living in a neighborhood with health care provider shortages was associated with lower risk of being undiagnosed (AOR = 0.80; 95% CI =0.69-0.93). Public health campaigns to educate adolescents and their caregivers about undiagnosed asthma, as well as education for health care providers to screen adolescent patients for asthma, are warranted.

Neighborhood characteristics as determinants of healthcare utilization - a theoretical model

BACKGROUND

We propose using neighborhood characteristics as demand-related morbidity adjusters to improve prediction models such as the risk equalization model.

RESULTS

Since the neighborhood has no explicit 'place' in healthcare demand models, we have developed the "Neighborhood and healthcare utilization model" to show how neighborhoods matter in healthcare utilization. Neighborhood may affect healthcare utilization via (1) the supply-side, (2) need, and (3) demand for healthcare - irrespective of need. Three pathways are examined in detail to explain how neighborhood characteristics influence healthcare utilization via need: the physiological, psychological and behavioral pathways. We underpin this theoretical model with literature on all relevant neighborhood characteristics relating to health and healthcare utilization.

CONCLUSION

Potential neighborhood characteristics for the risk equalization model include the degree of urbanization, public and open space, resources and facilities, green and blue space, environmental noise, air pollution, social capital, crime and violence, socioeconomic status, stability, and ethnic composition. Air pollution has already been successfully tested as an important predictive variable in a healthcare risk equalization model, and it might be opportune to add more neighborhood characteristics.

There and Back Again: How the Repeal of ACA Can Impact Community Health Centers and the Populations They Serve

We examined the impact of Medicaid expansion on rates of the remaining uninsured at the federally qualified health center level by race/ethnicity, limited English proficiency, and poverty status of their patients. Results indicated a systematic disadvantage in nonexpansion states for federally qualified health centers with high concentrations of these populations and an advantage in expansion states for federally qualified health centers with fewer limited English proficiency patients. Our findings highlight the importance of maintaining the Affordable Care Act in reducing disparities in coverage and the importance of federal funding to continue services for the remaining uninsured and vulnerable populations in both expansion and nonexpansion states.