Government social assistance programmes are failing to protect the health of low-income populations: evidence from the USA and Canada (2003–2014)

Reciprocal relations between financial hardship, sense of societal belonging and mental health for social assistance recipients

This study assesses the extent to which reciprocal relations exist between financial hardship, sense of societal belonging and mental health for social assistance recipients. This provides crucial information on how a desired change in these outcomes may be realized, and which factors to target to improve recipients' disadvantaged situation most. In order to answer our research question, we drew on three-wave panel data (N = 348) from a social experiment in the municipality of Nijmegen, the Netherlands, which ran from December 2017 to January 2020. The data were analyzed using cross-lagged panel models. Our findings show that financial hardship and sense of societal belonging did not predict change in recipients' mental health. A better mental health at baseline, in contrast, predicted an increase in sense of societal belonging one and two years later. In addition, both a better mental health and a stronger sense of societal belonging at baseline predicted a decrease in financial hardship one year later, but this relation was not found between other waves. These findings emphasize that improving recipients' mental health may be a promising policy strategy to improve their situation.

Are Neighborhood Characteristics Associated With Outcomes After THA and TKA? Findings From a Large Healthcare System Database

BACKGROUND

Non-White patients have higher rates of discharge to an extended care facility, hospital readmission, and emergency department use after primary THA and TKA. The reasons for this are unknown. Place of residence, which can vary by race, has been linked to poorer healthcare outcomes for people with many health conditions. However, the potential relationship between place of residence and disparities in these joint arthroplasty outcomes is unclear.

QUESTIONS/PURPOSES

(1) Are neighborhood-level characteristics, including racial composition, marital proportions, residential vacancy, educational attainment, employment proportions, overall deprivation, access to medical care, and rurality associated with an increased risk of discharge to a facility, readmission, and emergency department use after elective THA and TKA? (2) Are the associations between neighborhood-level characteristics and discharge to a facility, readmission, and emergency department use the same among White and Black patients undergoing elective THA and TKA?

METHODS

Between 2007 and 2018, 34,008 records of elective primary THA or TKA for osteoarthritis, rheumatoid arthritis, or avascular necrosis in a regional healthcare system were identified. After exclusions for unicompartmental arthroplasty, bilateral surgery, concomitant procedures, inability to geocode a residential address, duplicate records, and deaths, 21,689 patients remained. Ninety-seven percent of patients in this cohort self-identified as either White or Black, so the remaining 659 patients were excluded due to small sample size. This left 21,030 total patients for analysis. Discharge destination, readmissions within 90 days of surgery, and emergency department visits within 90 days were identified. Each patient's street address was linked to neighborhood characteristics from the American Community Survey and Area Deprivation Index. A multilevel, multivariable logistic regression analysis was used to model each outcome of interest, controlling for clinical and individual sociodemographic factors and allowing for clustering at the neighborhood level. The models were then duplicated with the addition of neighborhood characteristics to determine the association between neighborhood-level factors and each outcome. The linear predictors from each of these models were used to determine the predicted risk of each outcome, with and without neighborhood characteristics, and divided into tenths. The change in predicted risk tenths based on the model containing neighborhood characteristics was compared to that without neighborhood characteristics.The change in predicted risk tenth for each outcome was stratified by race.

RESULTS

After controlling for age, sex, insurance type, surgery type, and comorbidities, we found that an increase of one SD of neighborhood unemployment (odds ratio 1.26 [95% confidence interval 1.17 to 1.36]; p < 0.001) was associated with an increased likelihood of discharge to a facility, whereas an increase of one SD in proportions of residents receiving public assistance (OR 0.92 [95% CI 0.86 to 0.98]; p = 0.008), living below the poverty level (OR 0.82 [95% CI 0.74 to 0.91]; p < 0.001), and being married (OR 0.80 [95% CI 0.71 to 0.89]; p < 0.001) was associated with a decreased likelihood of discharge to a facility. Residence in areas one SD above mean neighborhood unemployment (OR 1.12 [95% CI [1.04 to 1.21]; p = 0.002) was associated with increased rates of readmission. An increase of one SD in residents receiving food stamps (OR 0.83 [95% CI 0.75 to 093]; p = 0.001), being married (OR 0.89 [95% CI 0.80 to 0.99]; p = 0.03), and being older than 65 years (OR 0.93 [95% CI 0.88 to 0.98]; p = 0.01) was associated with a decreased likelihood of readmission. A one SD increase in the percentage of Black residents (OR 1.11 [95% CI 1.00 to 1.22]; p = 0.04) and unemployed residents (OR 1.15 [95% CI 1.05 to 1.26]; p = 0.003) was associated with a higher likelihood of emergency department use. Living in a medically underserved area (OR 0.82 [95% CI 0.68 to 0.97]; p = 0.02), a neighborhood one SD above the mean of individuals using food stamps (OR 0.81 [95% CI 0.70 to 0.93]; p = 0.004), and a neighborhood with an increasing percentage of individuals older than 65 years (OR 0.90 [95% CI 0.83 to 0.96]; p = 0.002) were associated with a lower likelihood of emergency department use. With the addition of neighborhood characteristics, the risk prediction tenths of the overall cohort remained the same in more than 50% of patients for all three outcomes of interest. When stratified by race, neighborhood characteristics increased the predicted risk for 55% of Black patients for readmission compared with 17% of White patients (p < 0.001). The predicted risk tenth increased for 60% of Black patients for emergency department use compared with 21% for White patients (p < 0.001).

CONCLUSION

These results can be used to identify high-risk patients who might benefit from preemptive interventions to avoid these particular outcomes and to create more realistic, comprehensive risk adjustment models for value-based care programs. Additionally, this study demonstrates that neighborhood characteristics are associated with greater risk for these outcomes among Black patients compared with White patients. Further studies should consider that race/ethnicity and neighborhood characteristics may not function independently from each other. Understanding this link between race and place of residence is essential for future racial disparities research.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Effects of social assistance on self-rated health

Based on the China Health and Retirement Longitudinal Study (CHARLS) data in 2018, medical assistance and life assistance have significant negative influences on self-rated health, found via an empirical analysis based on the Oprobit model. Such negative influences are robust based on the substitution of explained variables and propensity score matching. It can be found from a heterogeneity analysis that the negative influences of medical assistance on self-rated health are more significant in urban residents and residents in Central China and East China. Meanwhile, negative influences of life assistance on self-rated health are more significant in urban residents, and residents in Central China, East China, and Northeast China. This study provides empirical evidence to improve the health of residents by using medical assistance and life assistance accurately and offers important policy enlightenments to formulate appropriate social assistance policies.

Unemployment Insurance and Mortality Among the Long-Term Unemployed: A Population-Based Matched-Cohort Study

Unemployment insurance is hypothesized to play an important role in mitigating the adverse health consequences of job loss. In this prospective cohort study, we examined whether receiving unemployment benefits is associated with lower mortality among the long-term unemployed. Census records from the 2006 Canadian Census Health and Environment Cohort (n = 2,105,595) were linked to mortality data from 2006-2016. Flexible parametric survival analysis and propensity score matching were used to model time-varying relationships between long-term unemployment (≥20 weeks), unemployment-benefit recipiency, and all-cause mortality. Mortality was consistently lower among unemployed individuals who reported receiving unemployment benefits, relative to matched nonrecipients. For example, mortality at 2 years of follow-up was 18% lower (95% confidence interval (CI): 9, 26) among men receiving benefits and 30% lower (95% CI: 18, 40) among women receiving benefits. After 10 years of follow-up, unemployment-benefit recipiency was associated with 890 (95% CI: 560, 1,230) fewer deaths per 100,000 men and 1,070 (95% CI: 810, 1,320) fewer deaths per 100,000 women. Our findings indicate that receiving unemployment benefits is associated with lower mortality among the long-term unemployed. Expanding access to unemployment insurance may improve population health and reduce health inequalities associated with job loss.