Neighborhood disadvantage and firearm injury: does shooting location matter?

Abstract Background Firearm violence is a public health problem that disparately impacts areas of economic and social deprivation. Despite a growing literature on neighborhood characteristics and injury, few studies have examined the association between neighborhood disadvantage and fatal and nonfatal firearm assault using data on injury location. We conducted an ecological Bayesian spatial analysis examining neighborhood disadvantage as a social determinant of firearm injury in Seattle, Washington. Methods Neighborhood disadvantage was measured using the National Neighborhood Data Archive disadvantage index. The index includes proportion of female-headed households with children, proportion of households with public assistance income, proportion of people with income below poverty in the past 12 months, and proportion of the civilian labor force aged 16 and older that are unemployed at the census tract level. Firearm injury counts included individuals with a documented assault-related gunshot wound identified from medical records and supplemented with the Gun Violence Archive between March 20, 2016 and December 31, 2018. Available addresses were geocoded to identify their point locations and then aggregated to the census tract level. Besag-York-Mollie (BYM2) Bayesian Poisson models were fit to the data to estimate the association between the index of neighborhood disadvantage and firearm injury count with a population offset within each census tract. Results Neighborhood disadvantage was significantly associated with the count of firearm injury in both non-spatial and spatial models. For two census tracts that differed by 1 decile of neighborhood disadvantage, the number of firearm injuries was higher by 21.0% (95% credible interval: 10.5, 32.8%) in the group with higher neighborhood disadvantage. After accounting for spatial structure, there was still considerable residual spatial dependence with 53.3% (95% credible interval: 17.0, 87.3%) of the model variance being spatial. Additionally, we observed census tracts with higher disadvantage and lower count of firearm injury in communities with proximity to employment opportunities and targeted redevelopment, suggesting other contextual protective factors. Conclusions Even after adjusting for socioeconomic factors, firearm injury research should investigate spatial clustering as independence cannot be able to be assumed. Future research should continue to examine potential contextual and environmental neighborhood determinants that could impact firearm injuries in urban communities.

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Abstract P873: Structural Racism in Columbus, Ohio Associated With Stroke Prevalence

Stroke ◽

10.1161/str.52.suppl_1.p873 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Jeffrey J Wing ◽

Emily E Lynch ◽

Sarah E Laurent ◽

Bruce C Mitchell ◽

Jason Richardson ◽

...

Keyword(s):

Census Tract ◽

Sociodemographic Factors ◽

Structural Racism ◽

Stroke Outcomes ◽

Census Tracts ◽

Census Tract Level ◽

Stroke Prevalence ◽

Level Information ◽

Fundamental Cause ◽

Loan Corporation

Introduction: Racial disparities exist in stroke and stroke outcomes. However, the fundamental cause for these disparities are not biological differences, but structural racism. Using the Home Owners’ Loan Corporation (HOLC) ‘redlining’ scores, as indicator of structural lending practices from middle of the last century, we hypothesize that census tracts with high historic redlining are associated with higher stroke prevalence. Methods: Weighted historic redlining scores (HRS) were calculated using the proportion of 1930s HOLC residential security grades contained within 2010 census tract boundaries of Columbus, Ohio. Stroke prevalence (adults >=18) was obtained at the census tract-level from the CDC’s 500 Cities Project. Sociodemographic factors, as measured by census tract level information (American Community Survey 2014-2018), were considered mediators in the causal association between historic redlining (measured in 1936) and stroke prevalence (measured in 2017) and were not controlled for in regression analysis. The functional form of the association was non-linear, so stroke prevalence within quartiles of the HRS were compared using linear regression instead of a continuous score. Results: Higher HRS, representing greater redlining, were associated with greater prevalence of stroke when comparing the highest to the lowest quartile of HRS (Figure). Census tracts in the highest quartile of HRS had 1.48% higher stroke prevalence compared to those in the lowest quartile (95% CI: 0.23-2.74). No other interquartile differences were observed. Conclusions: Historic redlining practices are a form of structural racism that established geographic systems of disadvantage and consequently, poor health outcomes. Our findings demonstrate disparate stroke prevalence by degree of historic redlining in census tracts across Columbus, Ohio. While ecologic, this study demonstrates the need to acknowledge that racism, not race, drive stroke disparities.

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Pediatric Firearm Injuries, Kansas City, 1992: A Population-Based Study

PEDIATRICS ◽

10.1542/peds.94.6.867 ◽

1994 ◽

Vol 94 (6) ◽

pp. 867-873 ◽

Cited By ~ 1

Author(s):

M. Denise Dowd ◽

Jane F. Knapp ◽

Laura S. Fitzmaurice

Keyword(s):

Kansas City ◽

Population Based ◽

Case Definition ◽

Medical Examiner ◽

Care Providers ◽

Unintentional Injuries ◽

Permanent Disability ◽

Census Tracts ◽

Firearm Injury ◽

Firearm Injuries

Objective. To determine the morbidity, mortality, and epidemiologic features of pediatric powder-firearm injuries in a defined urban population. Design and setting. A population-based, descriptive epidemiologic study was conducted of firearm injuries to children in a mid-size urban community (total population: 435 178) in 1992. The population was 56% white and 39% black. Data from prehospital care providers, all city and adjacent community hospitals, and medical examiner and police records were searched for cases of firearm injury. The 1990 United States census provided denominator data. Case definition. Subjects were all 0- to 16-year-old residents of Kansas City, Missouri who sought medical treatment at a hospital for a powder-firearm injury or who presented to the medical examiner with a fatal firearm injury in calendar year 1992. Results. Seventy-two children met the case definition, for an incidence of 70 per 100 000 persons per year. There were 12 (16.7%) fatalities, for a mortality rate of 11.7 per 100 000 persons per year. Almost 10% of the patients sustained permanent disability. Mean and median ages of the patients were 14.9 years and 15.8 years, respectively; 79% were male and 82% were black. The majority of the children (63%) lived in census tracts with a high proportion of families in poverty. Black males had the highest rates of firearm injury, with a 1-year incidence of 233 per 100 000 persons per year. At younger than 12 years, the rates were equal among the races; however, for those 12 years and older, black adolescents had 13 times the risk of white adolescents (541 compared to 42 per 100 000 persons per year). The majority (71%) of injuries were due to assaults, with drive-by shootings the most frequent circumstance. The majority of unintentional injuries occurred to adolescents as the result of an unplanned discharge of a handgun as it was being placed in or removed from concealment. Among the patients, 39% were admitted to the hospital and 26% required surgery. Conclusions. 1) Black male adolescents had the highest risk of firearm injury or fatality. 2) The majority of victims lived in census tracts characterized by poverty. 3) Injuries were alarmingly severe. 4) Interpersonal violence was the leading contributor to fatal and nonfatal injuries. 5) Unintentional injuries characteristically occurred during the process of weapon concealment. 6) The leading contributor to injury and death was the interaction of adolescents and guns, particularly handguns. The main implication for firearm-injury prevention in this population is the limiting of access to guns by adolescents. In addition, measures aimed at preventing violent behavior, such as education in nonviolent methods of conflict resolution, should be explored.

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Pattern of firearm injuries managed at rural tertiary centre in Western Uttar Pradesh, North India

International Surgery Journal ◽

10.18203/2349-2902.isj20173205 ◽

2017 ◽

Vol 4 (8) ◽

pp. 2677

Author(s):

Shailendra Pal Singh ◽

Pradeep Kumar Singh ◽

Manas Prakash ◽

Praveen Singh ◽

Gyanendra Chaudhary

Keyword(s):

Financial Burden ◽

Winter Season ◽

Public Health Problem ◽

Legal Aspects ◽

North India ◽

Physical Factors ◽

Global Public Health ◽

Firearm Injury ◽

Wound Debridement ◽

Firearm Injuries

Background: Firearm injuries are associated with substantial emotional, physical and financial burden on community and hospital resources leads to profound morbidity. It is a global public health problem and pose therapeutic challenges to surgeons. Proper management of firearm wounds requires a working knowledge of physical factors involved in the creation of such injuries. Regional variations of the parameters of medico legal aspects of firearm injuries are still lacking. Objective is to analyse pattern of firearm injuries managed at rural tertiary hospital.Methods: All firearm injury cases brought to the emergency department of Hospital, from January 2016 to December 2016 were included in the study.Results: In this study 108 (83.7%) victims were males and 21 (16.3%) were female. Most common age group victimized was 20-29 year (33.3%). Most cases occurred in winter season.113 cases (87.3%) victim were unemployed.81 cases (62.8%) had below intermediate education. 110 (85.3%) cases were of homicidal motive. Shotgun/ ‘kattas’ outnumbered the rifled firearm injuries (109) cases (84.5%). Trunk was involved in 45 cases (34.8%) and lower extremity in (32.6%) 42 cases,) Exit wound found in 93(72.2%) cases only. The fatality rate was 3.9% (5 cases). . Wound debridement was performed for 48 cases (37.2%) of patients, while emergency exploration was done for 30 cases (23.3%). The hospital stay of 49 cases (37.9%) of patients was more than one week. 111 cases (86.1%) were discharged.Conclusions: Addressing the root causes of violence such as poverty, unemployment, substance abuse will reduce the incidence of firearm injuries in our environment. Establishment of efficient emergency health care services for pre-hospital care and effective ambulance system for rapid transport of injured victims to hospital will reduce morbidity and mortality. Management requires knowledge ATLS protocols, mode, presentation and ballistic of firearm. Authorities issuing license for possession of firearms need to be more strict and vigilant.

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2325. Relationship Between Neighborhood Census-Tract-Level Poverty and Respiratory Syncytial Virus Infection in hospitalized Adults in the San Francisco Bay area, CA 2015–2017

Open Forum Infectious Diseases ◽

10.1093/ofid/ofz360.2003 ◽

2019 ◽

Vol 6 (Supplement_2) ◽

pp. S798-S798

Author(s):

Jenna Holmen ◽

Bryanna Cikesh ◽

Lindsay Kim ◽

Art Reingold

Keyword(s):

Respiratory Syncytial Virus ◽

San Francisco ◽

Census Tract ◽

San Francisco Bay ◽

San Francisco Bay Area ◽

Poverty Level ◽

Census Tracts ◽

Bay Area ◽

Census Tract Level ◽

Syncytial Virus

Abstract Background In the United States, respiratory syncytial virus (RSV) is a leading cause of admission for adults with respiratory illness. In adults > 50 years of age, it accounts for up to 12% of medically-attended acute respiratory illnesses and has a case fatality proportion of ~6–8%. Poverty can have an important influence on health. Few studies have evaluated the relationship of RSV incidence and poverty level, and no identified studies have evaluated this relationship among adults. We evaluated the incidence of RSV-associated hospitalizations in adults in the San Francisco Bay Area, CA by census-tract-level poverty. Methods Medical record data abstraction was conducted for all adults with a laboratory-confirmed RSV infection who were admitted to a hospital within the 3 counties comprising the catchment area (Alameda, Contra Costa, and San Francisco counties) during the 2015–2016 and 2016–2017 RSV seasons. Patient addresses were geocoded to their corresponding census-tract (CT). Census tracts were divided into four levels of poverty based on American Community Survey data of percentage of people living below the poverty level: 0–4.9%, 5–9.9%, 10-–9.9%, and ³20%. Incidence rates were calculated by dividing the number of RSV cases in each CT poverty-level (numerator) by the number of adults living in each CT poverty level (denominator), as determined from the 2010 US census, and standardized for age. Results There were 526 RSV case-patients with demographic characteristics as outlined in Table 1. The highest incidence of RSV-associated hospitalization was in CTs associated with the highest levels of poverty (>20%). However, the second highest incidence of RSV-associated hospitalization occurred among adults living in CTs with <5% poverty (Figure 1 and Table 2). Conclusion The incidence rate of RSV-associated hospitalization in adults appears to be positively correlated with highest census-tract level of poverty; however, there is a high incidence among adults living in the lowest poverty census-tracts. Disclosures All authors: No reported disclosures.

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Using the Poisson Distribution for Estimating Households by Household Size

10.31219/osf.io/v67k9 ◽

2017 ◽

Author(s):

Beth Jarosz

Keyword(s):

Poisson Distribution ◽

Census Tract ◽

Census Data ◽

Statistical Technique ◽

Household Size ◽

Size Distributions ◽

Census Tracts ◽

Reliable Tool ◽

Census Tract Level ◽

Simplified Method

Infrastructure planners often require detail about the number of households by household size at very small levels of geography (census tract or smaller) to calibrate their models. In addition, these data must also be projected into the future in order to support planning efforts.This paper documents a statistical technique for estimating the distribution of households by household size using a modified application of the Poisson distribution. This technique is valuable to demographers as it provides a simple and reliable tool for estimating the distribution of household sizes at nearly any level of geography for a given point in time.There are a wide variety of applications of the Poisson distribution in biology and engineering. However, there are only few documented applications in demographics. This article puts forth two key advancements over prior published work:(1) an entirely new, and greatly simplified method for applying the distribution,(2) evidence of the reliability of the technique for estimating household size distributions in small geographic areas (e.g. counties and census tracts).Tests on U.S. Census data (1990-2010) suggest that the model is suitable for use in estimating the distribution of households by household size at the state, county, and census tract level.

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Understanding Pediatric Surgery Cancellation: Geospatial Analysis (Preprint)

10.2196/preprints.26231 ◽

2020 ◽

Author(s):

Lei Liu ◽

Yizhao Ni ◽

Andrew F Beck ◽

Cole Brokamp ◽

Ryan C Ramphul ◽

...

Keyword(s):

Linear Regression ◽

Regression Model ◽

Linear Regression Model ◽

Census Tract ◽

Geospatial Analysis ◽

Community Level ◽

Minority Status ◽

Data Set ◽

Census Tracts ◽

Census Tract Level

BACKGROUND Day-of-surgery cancellation (DoSC) represents a substantial wastage of hospital resources and can cause significant inconvenience to patients and families. Cancellation is reported to impact between 2% and 20% of the 50 million procedures performed annually in American hospitals. Up to 85% of cancellations may be amenable to the modification of patients’ and families’ behaviors. However, the factors underlying DoSC and the barriers experienced by families are not well understood. OBJECTIVE This study aims to conduct a geospatial analysis of patient-specific variables from electronic health records (EHRs) of Cincinnati Children’s Hospital Medical Center (CCHMC) and of Texas Children’s Hospital (TCH), as well as linked socioeconomic factors measured at the census tract level, to understand potential underlying contributors to disparities in DoSC rates across neighborhoods. METHODS The study population included pediatric patients who underwent scheduled surgeries at CCHMC and TCH. A 5-year data set was extracted from the CCHMC EHR, and addresses were geocoded. An equivalent set of data >5.7 years was extracted from the TCH EHR. Case-based data related to patients’ health care use were aggregated at the census tract level. Community-level variables were extracted from the American Community Survey as surrogates for patients’ socioeconomic and minority status as well as markers of the surrounding context. Leveraging the selected variables, we built spatial models to understand the variation in DoSC rates across census tracts. The findings were compared to those of the nonspatial regression and deep learning models. Model performance was evaluated from the root mean squared error (RMSE) using nested 10-fold cross-validation. Feature importance was evaluated by computing the increment of the RMSE when a single variable was shuffled within the data set. RESULTS Data collection yielded sets of 463 census tracts at CCHMC (DoSC rates 1.2%-12.5%) and 1024 census tracts at TCH (DoSC rates 3%-12.2%). For CCHMC, an L2-normalized generalized linear regression model achieved the best performance in predicting all-cause DoSC rate (RMSE 1.299%, 95% CI 1.21%-1.387%); however, its improvement over others was marginal. For TCH, an L2-normalized generalized linear regression model also performed best (RMSE 1.305%, 95% CI 1.257%-1.352%). All-cause DoSC rate at CCHMC was predicted most strongly by <i>previous no show</i>. As for community-level data, the proportion of African American inhabitants per census tract was consistently an important predictor. In the Texas area, the proportion of overcrowded households was salient to DoSC rate. CONCLUSIONS Our findings suggest that geospatial analysis offers potential for use in targeting interventions for census tracts at a higher risk of cancellation. Our study also demonstrates the importance of home location, socioeconomic disadvantage, and racial minority status on the DoSC of children’s surgery. The success of future efforts to reduce cancellation may benefit from taking social, economic, and cultural issues into account.

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ASSOCIATION BETWEEN NEIGHBORHOOD CHARACTERISTICS AND DEMENTIA: AN ECOLOGICAL ANALYSIS

Innovation in Aging ◽

10.1093/geroni/igz038.3209 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

pp. S875-S876

Author(s):

Dana M AlHasan ◽

Matthew Lohman ◽

Maggi Miller ◽

Jana A Hirsch ◽

Bo Cai

Keyword(s):

South Carolina ◽

Census Tract ◽

Rural Areas ◽

Negative Binomial ◽

Negative Relationship ◽

Future Research ◽

Neighborhood Characteristics ◽

Detection Rates ◽

Census Tracts ◽

Dementia Incidence

Abstract Research has examined the relationship between neighborhood environments and cognitive decline, yet few have investigated the role of neighborhood characteristics specifically on dementia. This ecologic study examined the geographic distribution of dementia incidence and investigated ecologic associations between census-tract neighborhood characteristics and diagnosed dementia case incidence from 2010-2014 in the South Carolina (SC) Alzheimer’s Disease Registry. Analyses took place on the census-tract level (n=1089) with population ≥1. Neighborhood measures came from the Decennial Census, American Community Survey, Rural Commuting Area Code, and County Health Rankings. To estimate the ecologic association between neighborhood characteristics and dementia incidence, we conducted a zero-inflated, negative binomial mixed-effects model. The overall age-sex standardized dementia incidence rate was 2,885.4 per 100,000 people per census tract from 2010-2014 in SC (95% CI: 2857-2913.7). In an adjusted model, neighborhood characteristics had a significant association with dementia incidence. Rural and small urban census tracts had 62% (IRR=0.38; 95% CI= 0.27-0.54) and 58% (IRR=0.42; 95% CI= 0.29-0.60) lower dementia incidence, respectively, among ≥50 years old compared to urban census tracts while adjusting for neighborhood median-household income, racial composition, commute time, and age structure. The results from this study show a negative relationship between rural neighborhoods and dementia, contrary to previous findings. However, lower access to care in rural neighborhoods can result in lower detection rates and thus could present a reporting bias. Future research should investigate additional census-tract neighborhood characteristics (e.g. green space, pollution rates or psychosocial stress) that contribute to lower dementia rates in rural areas.

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Association of perceived neighborhood problems and census tract income with poor self-rated health in adults: a multilevel approach

Cadernos de Saúde Pública ◽

10.1590/0102-311x00210913 ◽

2015 ◽

Vol 31 (suppl 1) ◽

pp. 79-91 ◽

Cited By ~ 7

Author(s):

Doroteia Aparecida Höfelmann ◽

Ana V. Diez Roux ◽

José Leopoldo Ferreira Antunes ◽

Marco Aurélio Peres

Keyword(s):

Mental Health ◽

Census Tract ◽

Multilevel Models ◽

Physical Problem ◽

Social Disorder ◽

Census Tracts ◽

Neighborhood Problems ◽

Self Rated Health ◽

Census Tract Level ◽

Health Related

Abstract Neighborhood problems constitute sources of chronic stress that may increase the risk of poor self-rated health. The associations of census tract level income and perceived neighborhood problems with self-rated health were examined in Florianópolis, Santa Catarina State, Brazil (1,720 adults). Odds ratios (OR) and their 95% confidence intervals (95%CI) of poor self-rated health were estimated through multilevel models. Residents in census tracts in the lower and intermediate tertiles of income reported poorer health than those in the highest tertile. OR of reporting poorer health was 2.44 (95%CI: 2.35- 2.54) in the higher tertile of social disorder (adjusting for mental health). The chances of reporting the poorer health with neighborhood problems ranged from 1.07 (95%CI: 1.03-1.11) to 2.02 (95%CI: 1.95-2.10) for the higher tertile of social disorder (physical health) and physical problem (health-related variables). Perceived neighborhood problems were independently associated with poor health. The perception of a neighborhood among its residents should be considered by health policymakers.

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Abstract 005: Violent Crime, Physical Inactivity, And Obesity: Examining Differences In Spatial Relationships By Racial/ethnic Composition Of Community Residents

Circulation ◽

10.1161/circ.143.suppl_1.005 ◽

2021 ◽

Vol 143 (Suppl_1) ◽

Author(s):

Chelsea R Singleton ◽

Fikriyah Winata ◽

Oluwafikayo S Adeyemi ◽

Kaustubh V Parab ◽

Susan Aguiñaga

Keyword(s):

Violent Crime ◽

Census Tract ◽

Crime Rate ◽

Physical Inactivity ◽

Ethnic Composition ◽

Census Tracts ◽

Census Tract Level ◽

Violent Crime Rate ◽

Community Residents ◽

Racial Ethnic

Introduction: Violent crime (e.g., homicide, aggravated assault) is a major public health issue that disproportionately affects communities of color in large urban centers. Studies have reported that residents in high crime communities are less likely to engage in physical activity. There is limited understanding of how violent crime influences physical inactivity and obesity at the community level. We aimed to address this gap by examining differences in spatial relationships between violent crime rate, physical inactivity, and obesity by racial/ethnic composition of community residents in Chicago, IL. Hypothesis: We assessed the hypothesis that violent crime rate is associated with the prevalence of physical inactivity and obesity at the census tract level in Chicago, IL. Methods: We conducted an ecological assessment of 2018 census tract data obtained from various sources. We used data from the City of Chicago to calculate per capita violent crime rate (number of incidents per 1,000 residents) for all census tracts (N = 801). Data on physical inactivity and obesity prevalence (%) were acquired from the CDC. Socio-demographic data (i.e., % Non-Hispanic (NH) White, % NH Black, % Hispanic, median household income) were obtained from the census bureau. We examined spatial lag and error models to determine if violent crime rate is associated with % physical inactivity and % obesity after controlling for socio-demographic characteristics and amenity availability (i.e., per capita outdoor parks and grocery stores). Stratified models were examined to identify differences in associations among majority NH White, NH Black, and Hispanic census tracts (defined as ≥ 50% representation). Results: NH Black census tracts (n = 278) had significantly higher rates of violent crime, physical inactivity, and obesity than Hispanic (n = 169) and NH White tracts (n = 240). Overall, violent crime rate was positivity associated with % physical inactivity (p<0.001) but not % obesity (p=0.77) in Chicago after controlling for covariates. Stratified models revealed that violent crime rate was positively associated with % physical inactivity (p<0.001) and % obesity (p=0.01) among NH Black tracts. Violent crime rate was not associated with % physical inactivity or % obesity among Hispanic and NH White census tracts. Conclusions: Racial/ethnic composition of residents appears to influence census-tract level associations between violent crime rate, physical inactivity, and obesity. Violent crime appears to be more relevant to physical inactivity and obesity in Chicago’s NH Black communities compared to Hispanic and NH White communities.

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An Examination of Geographic Differences in Social Determinants of Health Among Women with Diagnosed HIV in the United States and Puerto Rico, 2017

The Open AIDS Journal ◽

10.2174/1874613602115010010 ◽

2021 ◽

Vol 15 (1) ◽

pp. 10-20

Author(s):

Ndidi Nwangwu-Ike ◽

Chan Jin ◽

Zanetta Gant ◽

Shacara Johnson ◽

Alexandra B. Balaji

Keyword(s):

United States ◽

Puerto Rico ◽

Health Insurance ◽

Social Determinants ◽

Census Tract ◽

The United States ◽

Adult Women ◽

Hiv Diagnosis ◽

Census Tracts ◽

Census Tract Level

Objective: To examine differences, at the census tract level, in the distribution of human immunodeficiency virus (HIV) diagnoses and social determinants of health (SDH) among women with diagnosed HIV in 2017 in the United States and Puerto Rico. Background: In the United States, HIV continues to disproportionately affect women, especially minority women and women in the South. Methods: Data reported in the National HIV Surveillance System (NHSS) of the Centers for Disease Control and Prevention were used to determine census tract-level HIV diagnosis rates and percentages among adult women (aged ≥18 years) in 2017. Data from the American Community Survey were combined with NHSS data to examine regional differences in federal poverty status, education level, income level, employment status, and health insurance coverage among adult women with diagnosed HIV infection in the United States and Puerto Rico. Results: In the United States and Puerto Rico, among 6,054 women who received an HIV diagnosis in 2017, the highest rates of HIV diagnoses generally were among those who lived in census tracts where the median household income was less than $40,000; at least 19% lived below the federal poverty level, at least 18% had less than a high school diploma, and at least 16% were without health insurance. Conclusion: This study is the first of its kind and gives insight into how subpopulations of women are affected differently by the likelihood of an HIV diagnosis. The findings show that rates of HIV diagnosis were highest among women who lived in census tracts having the lowest income and least health coverage.

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