Immigration, Educational Attainment, and Subjective Health in the United States.

Objectives: Although educational attainment is a major social determinant of health, according to Marginalization-related Diminished Returns (MDRs), the effect of education tends to be weaker for marginalized groups compared to the privileged groups. While we know more about marginalization due to race and ethnicity, limited information is available on MDRs of educational attainment among US immigrant individuals. Aims: This study compared immigrant and non-immigrant US adults aged 18 and over for the effects of educational attainment on subjective health (self-rated health; SRH). Methods: Data came from General Social Survey (GSS) that recruited a nationally representative sample of US adults from 1972 to 2022. Overall, GSS has enrolled 45,043 individuals who were either immigrant (4,247; 9.4%) and non-immigrant (40,796; 90.6%). The independent variable was educational attainment, the dependent variable was SRH (measured with a single item), confounders were age, gender, race, employment and marital status, and moderator was immigration (nativity) status. Results: Higher educational attainment was associated with higher odds of good SRH (odds ratio OR = 2.08 for 12 years of education, OR = 2.81 for 13-15 years of education, OR = 4.38 for college graduation, and OR = 4.83 for graduate studies). However, we found significant statistical interaction between immigration status and college graduation on SRH, which was indicative of smaller association between college graduation and SRH for immigrant than non-immigrant US adults. Conclusions: In line with MDRs, the association between educational attainment and SRH was weaker for immigrant than non-immigrant. It is essential to implement two sets of policies to achieve health inequalities among immigrant populations: policies that increase educational attainment of immigrants and those that increase the health returns of educational attainment for immigrants.

Heart failure: a prevalence-based and model-based cost analysis.

Introduction: Heart failure (HF) imposes a heavy economic burden on patients, their families, and society as a whole. Therefore, it is crucial to quantify the impact and dimensions of the disease in order to prioritize and allocate resources effectively. Methods: This study utilized a prevalence-based, bottom-up, and incidence-based Markov model to assess the cost of illness. A total of 502 HF patients (classes I-IV) were recruited from Madani Hospital in Tabriz between May and October 2022. Patients were followed up every two months for a minimum of two and a maximum of six months using a person-month measurement approach. The perspective of the study was societal, and both direct and indirect costs were estimated. Indirect costs were calculated using the Human Capital (HC) method. A two-part regression model, consisting of the Generalized Linear Model (GLM) and Probit model, was used to analyze the relationship between HF costs and clinical and demographic variables. Results: The total cost per patient in one year was 261,409,854.9 Tomans (21,967.21 PPP). Of this amount, 207,147,805.8 Tomans (17,407.38 PPP) (79%) were indirect costs, while 54,262,049.09 Tomans (4,559.84 PPP) (21%) were direct costs. The mean lifetime cost was 2,173,961,178 Tomans. Premature death accounted for the highest share of lifetime costs (48%), while class III HF had the lowest share (2%). Gender, having basic insurance, and disease class significantly influenced the costs of HF, while comorbidity and age did not have a significant impact. The predicted amount closely matched the observed amount, indicating good predictive power. Conclusion: This study revealed that HF places a significant economic burden on patients in terms of both direct and indirect costs. The substantial contribution of indirect costs, which reflect the impact of the disease on other sectors of the economy, highlights the importance of unpaid work. Given the significant variation in HF costs among assessed variables, social and financial support systems should consider these variations to provide efficient and fair support to HF patients.

Financial burden of prostate cancer in the Iranian population: a cost of illness and financial risk protection analysis.

BACKGROUND: Prostate cancer is the second most common cancer in males worldwide and the third most common among Iran's male population. However, there is a lack of evidence regarding its direct and indirect costs in low and middle-income countries. This study intends to bridge the gap using a cost of illness approach, assessing the costs of prostate cancer from the perspectives of patients, society, and the insurance system. METHODS: Two hundred ninety seven patients were included in the study. Data for a 2-month period were obtained from patients registered at two hospitals (Tabriz, Tehran) in Iran in 2017. We applied a prevalence-based, bottom-up approach to assess the costs of the illness. We used the World Health Organization methods to measure the prevalence and investigate the determinants of catastrophic and impoverishing health expenditures. RESULTS: We determined the total costs of the disease for the patients to be IRR 68 million (PPP $ 5,244.44). Total costs of the disease from the perspective of the society amounted to IRR 700,000 million (PPP $ 54 million). Insurance companies expended IRR 20 million (PPP $ 1,558.80) per patient. Our findings show that 31% of the patients incurred catastrophic health expenditure due to the disease. Five point forty-four percent (5.44%) of the patients were impoverished due to the costs of this cancer. CONCLUSION: We found an alarmingly high prevalence of catastrophic health expenditures among prostate cancer patients. In addition, prostate cancer puts a substantial burden on both the patients and society.

When States Mandate Hospital Community Benefit Reports, Provision Increases.

GOAL: We examined the variation in community benefit and charity care reporting standards mandated by states to determine whether state-mandated community benefit and charity care reporting is associated with greater provision of these services. METHODS: We used 2011-2019 data from IRS Form 990 Schedule H for 1,423 nonprofit hospitals to create a sample of 12,807 total observations. Random effects regression models were used to examine the association between state reporting requirements and community benefit spending by nonprofit hospitals. Specific reporting requirements were analyzed to determine whether certain requirements were associated with increased spending on these services. PRINCIPAL FINDINGS: Nonprofit hospitals in states that required reports spent a higher percentage of total hospital expenditures on community benefits (9.1%, SD = 6.2%) compared to states without these requirements (7.2%, SD = 5.7%). A similar association between the percentage of charity care and total hospital expenditures (2.3% and 1.5%) was found. The greater number of reporting requirements was associated with lower levels of charity care provision, as hospitals allocated more resources to other community benefits. PRACTICAL APPLICATIONS: Mandating the reporting of specific services is associated with greater provision of certain specific services, but not all. A concern is that when many services must be reported, the provision of charity care might be reduced as hospitals choose to allocate their community benefit dollars to other categories. As a result, policymakers may want to focus their attention on the services they most want to prioritize.

Influence of Not-for-Profit Hospital Ownership Type on Community Benefit and Charity Care.

Non-profit hospitals are expected to provide charity care and other community benefits to adjust their tax exemption status. Using the Medicare Hospital Cost Report, American Hospital Association Annual Survey, and the American Community Survey datasets, we examined if church-affiliated hospitals spent more on charity care and community benefit. For this analysis, we defined five main categories of community benefits were measured: total community benefit; charity care; Medicaid shortfall; unreimbursed other means-tested services; and the total of unreimbursed education and unfunded research. Multiple regression was used to examine the effect of church ownership, controlling for other factors, on the level of community benefit in 2644 general acute care non-profit hospitals. Descriptive analyses and multiple regression were used to show the relationship between the provision of community benefits and church affiliation including Catholic (CH), other church-affiliated hospitals (OCAH), and non-church affiliated hospitals (NCAH). The non-profit hospital on average spent 6.5% of its total expenses on community benefits. NCAH spent 6.09%, CH spent 7.5%, and OCAH spent 9.4%. Non-profits spent 2.8% of their total expenses on charity care, with the highest charity care spending for OCAH (5.2%), followed by CH (3.9%), and NCAH (2.4%). Regression results showed that CH and OCAH, on average, spent 1.08% and 2.16% more on community benefits than NCAHs. In addition, CH and OCAH spent more on other categories of community benefits except for education and research. Church-affiliated hospitals spend more on community benefits and charity care than non-church affiliated nonprofit hospitals.

Association between non-profit hospital community benefit spending and health outcomes.

OBJECTIVE: To determine if greater non-profit hospital spending for community benefits is associated with better health outcomes in the county where they are located. DATA SOURCES AND STUDY SETTING: Community benefit data from IRS Form 990/Schedule H was linked to health outcome data from Area Health Resource Files, Map the Meal Gap, and Medicare claims from the Center for Medicare and Medicaid Services at the county level. Counties with at least one non-profit hospital in the United States from 2015 to 2019 (N = 5469 across the 5 years) were included. STUDY DESIGN: We ran multiple regressions on community benefit expenditures linked with the number of health professionals, food insecurity, and adherence to diabetes and hypertension medication for each county. DATA COLLECTION: The three outcomes were chosen based on prior studies of community benefit and a recent survey sent to 12 health care executives across four regions of the U.S. Data on community benefit expenditures and health outcomes were aggregated at the county level. PRINCIPAL FINDINGS: Average hospital community benefit spending in 2019 was $63.6 million per county ($255 per capita). Multivariable regression results did not demonstrate significant associations of total community benefit spending with food insecurity or medication adherence for diabetes. Statistically significant associations with the number of health professionals per 1000 (coefficient, 12.10; SE, 0.32; p < 0.001) and medication adherence for hypertension (marginal effect, 0.27; SE, 0.09; p = 0.003) were identified, but both would require very large increases in community benefit spending to meaningfully improve outcomes. CONCLUSIONS: Despite varying levels of non-profit hospital community benefit investment across counties, higher community benefit expenditures are not associated with an improvement in the selected health outcomes at the county level. Hospitals can use this information to reassess community benefit strategies, while federal, state, and local governments can use these findings to redefine the measures of community benefit they use to monitor and grant tax exemption.

Social Determinants of Mental, Physical, and Oral Health of Middle-Aged and Older African Americans in South Los Angeles.

BACKGROUND: A growing body of research suggests that financial difficulties could weaken the protective effects of socioeconomic status (SES) indicators, including education and income, on the health status of marginalized communities, such as African Americans. AIM: We investigated the separate and joint effects of education, income, and financial difficulties on mental, physical, and oral self-rated health (SRH) outcomes in African American middle-aged and older adults. METHODS: This cross-sectional study enrolled 150 middle-aged and older African Americans residing in South Los Angeles. Data on demographic factors (age and gender), socioeconomic characteristics (education, income, and financial difficulties), and self-rated health (mental, physical, and oral health) were collected. Three linear regression models were used to analyze the data. RESULTS: Higher education and income were associated with a lower level of financial strain in a bivariate analysis. However, according to multivariable models, only financial difficulties were associated with poor mental, physical, and oral health. As similar patterns emerged for all three health outcomes, the risk associated with financial difficulties seems robust. CONCLUSIONS: According to our multivariable models, financial strain is a more salient social determinant of health within African American communities than education and income in economically constrained urban environments such as South Los Angeles. While education and income lose some protective effects, financial strain continues to deteriorate the health of African American communities across domains.

Income Inequality, Race/Ethnicity, and Obesity in U.S. Men 20 Years and Older: 1999 to 2016.

Obesity is a significant public health problem globally and within the United States. It varies by multiple factors, including but not limited to income. The literature indicates little evidence of the association between income and obesity. We examined the association between income and obesity in U.S. adult men ages 20 years and older and tested racial and ethnic differences. We used data from the 1999 to 2016 National Health and Nutrition Examination Surveys for analyses. Obesity was determined using body mass index ≥30 kg/m2. We used poverty income ratio (PIR) as a proxy for income and calculated the Gini coefficient (GC) to measure income inequality. We then categorized low-, medium-, and high PIR to examine the relationship between income inequality and obesity. We used Modified Poisson regression in a sample of 17,238 adult men, including 9,511 White Non-Hispanic White (NHW), 4,166 Non-Hispanic Black (NHB), and 3,561 Mexican Americans (MA). We controlled the models for age category, racial and ethnic groups, marital status, education, health behaviors, health insurance coverage, self-reported health, comorbidity, and household structure. Results of our adjusted models suggested a positive and significant association between PIR and obesity among NHWs and NHBs in medium and high PIR; this association was not significant in MAs. Results of our analyses using GC in obese men indicate that compared with NHWs (GC: 0.306, SE: 0.004), MAs (GC: 0.368, SE: 0.005), and NHBs (GC: 0.328, SE: 0.005) had experienced higher-income inequality. In treating obesity, policymakers should consider race/ethnicity strategies to reduce inequality in income.

Analysis of trends in nurse practitioner billing for emergency medical services: 2015-2018.

STUDY OBJECTIVE: Despite projections of an oversupply of residency-trained emergency medicine physicians by 2030 and amidst intensifying national debate over Nurse Practitioner (NP) qualifications to practice independently and unsupervised, NPs are increasingly staffing Emergency Departments (EDs) as hospitals seek to contain costs while simultaneously expanding services. We sought to characterize NP practice in the ED by examining NP independent billing by level of severity of illness, and relationship to practice authority, State Medicaid expansion status, and rurality. METHODS: Medicare provider utilization and payment data between 2015-2018 was used to explore NP billing as compared to five other clinician provider types for common emergency services acuity codes (CPT codes 99281-99285) to determine services billed for levels of severity of illness and trends over time. Number of services billed by clinician provider type related to state policies on NP practice authority, location, and population characteristics was explored. RESULTS: NPs who independently billed for ED CPT codes (99282-99285), increased during this time and decreased for acuity code 99281 (minor and self-limiting). Overall, NPs saw a greater increase than all other providers in both the highest severity CPT codes of 99284 and 99285. The analysis revealed that type of clinician, state practice authority policy, number of NPs, and percent of population 65 years and older (by zipcode) and population size are positive predictors for services billed. The negative predictors were rurality, states which accepted the Medicaid expansion, having a higher number of non-English speaking residents, and non-emergency medicine clinicians. CONCLUSION: As a proportion of the providers independently billing in the ED, NPs are increasingly managing higher acuity patients as evidenced by billing percentage of the highest acuity CPT codes (99284 and 99285). During the same time period, ED MDs decreased their billing in the same categories. Current employment of NPs in the ED may not be fulfilling its original vision to care for the lower acuity patients in order to allow MDs to care for the more acutely and critically ill patients, and to increase the services for underserved populations in rural areas, those over age 65, and those with limited English language proficiency. Future research should investigate ED policies resulting in NPs as opposed to MDs seeing patients with greater severity codes.

How Income Inequality and Race Concentrate Depression in Low-Income Women in the US; 2005-2016.

Aim: To estimate the association between income and depressive symptoms in adult women, ages 20 years and older. Methods: Data for this study came from the 2005-2016 National Health and Nutrition Examination Survey (NHANES). We measured the presence of depressive symptoms by using a 9-item PHQ (Public Health Questionnaire, PHQ-9) and the Poverty to Income Ratio (PIR) as a proxy for income. We employed Negative Binomial Regression (NBRG) and logistic regression models in a sample of 11,420 women. We adjusted models by age, racial/ethnic groups, marital status, education, health insurance, comorbidity, and utilization of mental health professionals. We calculated the Gini Coefficient (GC) as a measure of income inequality, using PIR. Results: Between 2005 and 2016, 20.1% of low-PIR women suffered from depression (PHQ ≥10) compared with 12.0% of women in medium-PIR and 5.0% in high-PIR. The highest probabilities of being depressed were in Black Non-Hispanics (BNH) and Hispanics (12.0%), and then in White NH (WNH; 9.1%). The results of NBRG have shown that women in medium-PIR (0.90 [CI: 0.84-0.97]) and high-PIR 0.76 (CI: 0.70-0.82) had a lower incidence-rate ratio than women in low-PIR. The logistic regression results showed that income is protective in High-PIR groups (OR = 0.56, CI [0.43-0.73]). Conclusion: Policies to treat depression should prioritize the needs of low-income women of all racial groups and women.

How place and race drive the numbers of fatal police shootings in the US: 2015-2020.

Place and race are two important predictors of fatal police shootings. We used Mapping Police Violence Data and the Washington Post Fatal Force Data to determine whether a county's deprivation status within communities influences the association between the number of fatal police shootings, and how the number of fatal police shootings differs by race and ethnicity. We categorized counties based on the Social Vulnerability Index (SVI) to three categories: low-, medium-, and high-SVI. The analytical sample included 3136 US counties between 2015 and 2020; during this time, 5525 individuals were fatally shot by police. Our findings show that place strongly impacts the number of fatal police shootings. Among all fatal shootings, 713 occurred in low-SVI counties, 1660 in middle-SVI, and 3152 in high-SVI counties. Race played a significant role; fatal shooting deaths increased by 2.3 times among White individuals, 9.6 times among Black individuals, and 15 times among Hispanic individuals between low- and high-SVI counties. The results of negative binomial regressions show a strong association between fatal police shootings and the counties' characteristics. In comparison with low-SVI counties, residents in counties with moderate and high-SVI are more likely to be fatally shot by police by 4.9 and 5.8 percentage points. In addressing violence and fatal police shootings, the vulnerability of counties and the population's racial composition play significant roles and need specific attention in addressing systemic racial disparities in the criminal justice system.

Investigating Racial Differences in Allostatic Load by Educational Attainment among Non-Hispanic Black and White Men.

Education continues to be a key factor contributing to increased access to critical life-improving opportunities and has been found to be protective against Allostatic Load (AL). The purpose of this study was to assess AL among Non-Hispanic (NH) White and NH Black men with the same level of education. We used 1999-2016 National Health and Nutrition Examination Surveys (NHANES) data with an analytical sample of 6472 men (1842 NH Black and 4630 NH White), and nine biomarkers to measure AL, controlling for various demographic and health-related factors. NH Black men had a higher AL score than NH White men (39.1%, 842 vs. 37.7%, 1,975). Racial disparities in AL between NH Black and NH White men who have a college degree or above (PR: 1.49, CI: [1.24-1.80]) were observed. Models posited similar AL differences at every other level of education, although these were not statistically significant. The findings reveal that socioeconomic returns to education and the societal protective mechanisms associated with education vary greatly between White and Black men.

How Income and Income Inequality Drive Depressive Symptoms in U.S. Adults, Does Sex Matter: 2005-2016.

IMPORTANCE: Depression is one of the leading causes of disability in the United States. Depression prevalence varies by income and sex, but more evidence is needed on the role income inequality may play in these associations. OBJECTIVE: To examine the association between the Poverty to Income Ratio (PIR)-as a proxy for income-and depressive symptoms in adults ages 20 years and older, and to test how depression was concentrated among PIR. DESIGN: Using the 2005-2016 National Health and Nutrition Examination Survey (NHANES), we employed Negative Binomial Regression (NBRG) in a sample of 24,166 adults. We used a 9-item PHQ (Public Health Questionnaire, PHQ-9) to measure the presence of depressive symptoms as an outcome variable. Additionally, we plotted a concentration curve to explain how depression is distributed among PIR. RESULTS: In comparison with high-income, the low-income population in the study suffered more from greater than or equal to ten on the PHQ-9 by 4.5 and 3.5 times, respectively. The results of NBRG have shown that people with low-PIR (IRR: 1.30, 95% CI: 1.23-1.37) and medium-PIR (IRR: 1.55, 95% CI: 1.46-1.65) have experienced a higher relative risk ratio of having depressive symptoms. Women have a higher IRR (IRR: 1.29, 95% CI: 1.24-1.34) than men. We observed that depression was concentrated among low-PIR men and women, with a higher concentration among women. CONCLUSION AND RELEVANCE: Addressing depression should target low-income populations and populations with higher income inequality.

Factors Associated with Compliance to the Hospital Price Transparency Final Rule: a National Landscape Study.

BACKGROUND: The Hospital Price Transparency Final Rule, effective January 1, 2021, requires hospitals to post online a machine-readable file that includes payer-specific negotiated commercial prices for all services. The regulation aims to improve the affordability of hospital care by promoting price competition. However, a low compliance level among hospitals would compromise the operational effectiveness of this regulation. Understanding hospitals' compliance status to the regulation has important implications for its enforcement effort and effectiveness assessment. OBJECTIVE: To analyze nationwide hospitals' compliance status to the Hospital Price Transparency Rule. DESIGN: Cross-sectional observational study. PARTICIPANTS: A total of 3558 Medicare-certified general acute-care hospitals were examined. MAIN MEASURES: A binary compliance rating was generated by using data collected by Turquoise Health. "Noncompliance" means that no machine-readable file was posted or the posted file contains no commercial negotiated prices. "Compliance" means that a machine-readable file was posted with commercial negotiated prices for at least one insurance plan. KEY RESULTS: As of June 1, 2021, 55% of the 3558 Medicare-certified general acute-care hospitals we examined had not posted a machine-readable file containing commercial negotiated prices. Wide variations of compliance existed across states and hospital referral regions. A hospital's compliance status is strongly associated with the average compliance status of peer hospitals in the same market. Hospitals with greater IT preparedness, for-profit hospitals, system-affiliated hospitals, large hospitals, and non-urban hospitals had greater compliance. More concentrated hospital markets had greater average compliance. CONCLUSIONS: Hospitals take into consideration the behavior of their peers in the same market when making price disclosure decisions. Compliant hospitals are likely to have better IT preparedness, more financial resources and personnel expertise to mitigate the cost required for the implementation of the Price Transparency Rule. The compliance cost, therefore, might be a barrier for some hospitals.

Comparing the value of community benefit and Tax-Exemption in non-profit hospitals.

OBJECTIVE: We examined the characteristics of non-profit hospitals providing more community benefits and charity care than value of their tax exemptions and how this relationship changed between 2011 and 2018. DATA SOURCES: Primary dataset was schedule H Form IRS 990 data. This data was merged with the American Hospital Association, Medicare Hospital Cost Report, and the America Community Survey. STUDY DESIGN: We measured six categories of tax benefits and 17 types of community benefits. Subtracting the average value of community benefits provided by for-profit hospitals, we computed incremental community benefit and charity care provided by each non-profit hospital. EXTRACTION METHODS: A nationally representative sample was created of 11 776 non-profit hospital-year observations from 1472 unique hospitals over the 2011 to 2018 period was created. Descriptive analyses and random effect logistic regression were used to show associations between hospital characteristics and difference between incremental net community benefits and the value of tax-exemption. PRINCIPAL FINDINGS: After adjusting for community benefits provided by for-profits hospitals, on average, non-profit hospitals spent 5.9% (CI: 5.8%-6.0%) of their total expenses on community benefits; 1.3% (CI: 1.2%-1.3%) on charity care; and received 4.3% (CI: 4.2%-4.4%) of total expenses in tax exemptions. A total of 38.5% of non-profit hospitals did not provide more community benefit and 86% did not provide more charity care than the value of their tax exemption. Hospitals with fewer beds, providing residency education and located in high poverty communities were more likely to provide more incremental community benefits and charity care than the value of their tax exemption, while system affiliation had a negative association. CONCLUSION: The amount of community benefits and charity care provided by non-profits varied substantially across non-profit hospitals. Establishing minimum requirements for non-profit hospitals or publicly ranking hospitals based on their community benefit or charity care contributions, could encourage greater community benefits and charity care.

Comparison of Trends in Nonprofit Hospitals' Charity Care Eligibility Policies Between Medicaid Expansion States and Medicaid Nonexpansion States.

Nonprofit hospitals provide charity care to financially disadvantaged patients according to their self-designed eligibility policies. The Affordable Care Act may have prompted nonprofit hospitals to adopt more generous eligibility policies, but no prior research has examined the longitudinal trend. The expansion of Medicaid coverage in many states has been found to reduce charity care provision, but it is unclear whether the change in charity care eligibility policies differed between Medicaid expansion and nonexpansion states. Using mandatory tax filings, we found that both hospitals in Medicaid expansion states and hospital in nonexpansion states adopted more generous eligibility policies in 2018 than in 2010, but the change was greater in the former for discounted charity care; while the former provided less charity care regardless of their policy changes, the latter provided more when their policies became more generous. This study has implications for policy discussions on the justification of nonprofit hospitals' tax-exempt status.