Unequal Housing Conditions And Code Enforcement Contribute To Asthma Disparities In Boston, Massachusetts

Policy-induced air pollution health disparities: Statistical and data science considerations

Air pollution causes premature death and disease and disproportionately harms non-white and lower-income groups in the United States. Government policies are responsible for the racial disparity in air pollution exposure and related health outcomes. Investigating complex relationships between policies, air pollution, and health requires (i) harmonized data connecting policies, environmental exposures, socioeconomic characteristics, and health at the individual and area level; (ii) interpretable estimands accounting for the complex interplay between policies and disparities in exposures and health outcomes; and (iii) data science approaches that can elucidate direct and indirect policy effects on disparities to identify effective interventions. We review statistical considerations and new data science approaches needed to scrutinize the policy impacts on disparities in air pollution exposure and health outcomes.

Substandard housing and the risk of COVID-19 infection and disease severity: A retrospective cohort study

In this study we examine associations between substandard housing and the risk of COVID-19 infection and severity during the first year of the pandemic by linking individual-level housing and clinical datasets. Residents of Chelsea, Massachusetts who were tested for COVID-19 at any Mass General Brigham testing site and who lived at a property that had received a city housing inspection were included (N = 2873). Chelsea is a densely populated city with a high prevalence of substandard housing. Inspected properties with housing code violations were considered substandard; inspected properties without violations were considered adequate. COVID-19 infection was defined as any positive PCR test, and severe disease defined as hospitalization with COVID-19. We used a propensity score design to match individuals on variables including age, race, sex, and income. In the severity model, we also matched on ten comorbidities. We estimated the risk of COVID-19 infection and severity associated with substandard housing using Cox Proportional Hazards models for lockdown, the first phase of reopening, and the full study period. In our sample, 32% (919/2873) of individuals tested positive for COVID-19 and 5.9% (135/2297) had severe disease. During lockdown, substandard housing was associated with a 48% increased risk of COVID-19 infection (95%CI 1.1-2.0, p = 0.006). Through Phase 1 reopening, substandard housing was associated with a 39% increased infection risk (95%CI 1.1-1.8, p = 0.020). The difference in risk attenuated over the full study period. There was no difference in severe disease risk between the two groups. The increased risk, observed only during lockdown and early reopening - when residents were most exposed to their housing - strengthens claims that substandard housing conveys higher infection risk. The results demonstrate the value of combining cross-sector datasets. Existing city housing data can be leveraged 1) to identify and prioritize high-risk areas for future pandemic response, and 2) for longer-term housing solutions.

Toward a new model of childhood asthma care: community needs assessment in an underserved urban population

OBJECTIVES

The objective of this study was to utilize a community-engaged research approach to better understand gaps and opportunities for improving asthma care from the perspectives of patients, caregivers, community organization representatives, and healthcare providers in a predominantly minority community.

METHODS

Forty-one participants from four groups (patients, caregivers, community organization representatives, healthcare providers) participated in interviews or focus groups. A phenomenological approach to this qualitative research allowed the research team to better understand the lived experiences of families seeking asthma care in this community.

RESULTS

Five gaps and five corresponding opportunities were identified. The gaps identified were unequal healthcare resource distribution; underrepresentation of health professionals from diverse backgrounds; experiences of environmental racism; mistrust, bias, and discrimination in healthcare encounters; and systemic marginalization of communities. The opportunities identified include increasing healthcare infrastructure and accessibility; increasing racially, culturally, and linguistically congruent healthcare; implementing equitable improvements to the built environment; building relationships with communities and individuals; and acknowledging communities' strengths and resilience.

CONCLUSION

This study identified systemic gaps to asthma care that are of prominent concern to the community.

Environmental Health: A Position Paper From the American College of Physicians

Environmental health refers to the health effects associated with environmental factors, such as air pollution, water contamination, and climate change. Environmental hazards are associated with poor outcomes in common diseases, including diabetes and heart disease. In this position paper, the American College of Physicians (ACP) seeks to inform physicians about environmental health and offers policymakers recommendations to reduce the adverse health consequences of climate change, improve air and water quality, reduce exposure to toxic substances, and address environmental injustice. ACP affirms that all communities, including people of color, people with low income, and marginalized populations, deserve to live in a healthy environment.

Mapping emergency department asthma visits to identify poor-quality housing in New Haven, CT, USA: a retrospective cohort study

BACKGROUND

Housing conditions are a key driver of asthma incidence and severity. Previous studies have shown increased emergency department visits for asthma among residents living in poor-quality housing. Interventions to improve housing conditions have been shown to reduce emergency department visits for asthma, but identification and remediation of poor housing conditions is often delayed or does not occur. This study evaluates whether emergency department visits for asthma can be used to identify poor-quality housing to support proactive and early intervention.

METHODS

We conducted a retrospective cohort study of children and adults living in and around New Haven, CT, USA, who were seen for asthma in an urban, tertiary emergency department between March 1, 2013, and Aug 31, 2017. We geocoded and mapped patient addresses to city parcels, and calculated a composite estimate of the incidence of emergency department use for asthma for each parcel (N_v × N_p/log₂[P], where N_v is the estimated mean number of visits per patient, N_p is the number of patients, and P is the estimated population). To determine whether parcel-level emergency department use for asthma was associated with public housing inspection scores, we used regression analyses, adjusting for neighbourhood-level and individual-level factors contributing to emergency department use for asthma. Public housing complex inspection scores were obtained from standardised home inspections, which are conducted every 1-3 years for publicly funded housing. We used a sliding-window approach to estimate how far in advance of a failed inspection the model could identify elevated use of emergency departments for asthma, using the city-wide 90th percentile as a cutoff for elevated incidence.

FINDINGS

11 429 asthma-related emergency department visits from 6366 unique patients were included in the analysis. Mean patient age was 32·4 years (SD 12·8); 3836 (60·3%) patients were female, 2530 (39·7%) were male, 3461 (57·2%) were Medicaid-insured, and 2651 (41·6%) were Black. Incidence of emergency department use for asthma was strongly correlated with lower housing inspection scores (Pearson's r=-0·55 [95% CI -0·70 to -0·35], p=3·5 × 10^-6), and this correlation persisted after adjustment for patient-level and neighbourhood-level demographics using a linear regression model (r=-0·54 [-0·69 to -0·33], p=7·1 × 10^-6) and non-linear regression model (r=-0·44 [-0·62 to -0·21], p=3·8 × 10^-4). Elevated asthma incidence rates were typically detected around a year before a housing complex failed a housing inspection.

INTERPRETATION

Emergency department visits for asthma are an early indicator of failed housing inspections. This approach represents a novel method for the early identification of poor housing conditions and could help to reduce asthma-related morbidity and mortality.

FUNDING

Harvard-National Institute of Environmental Health Sciences (NIEHS) Center for Environmental Health.