School and childcare facility air quality decision-makers' perspectives on using low-cost sensors for wildfire smoke response.

BACKGROUND: During wildfire smoke episodes, school and childcare facility staff and those who support them rely upon air quality data to inform activity decisions. Where ambient regulatory monitor data is sparse, low-cost sensors can help inform local outdoor activity decisions, and provide indoor air quality data. However, there is no established protocol for air quality decision-makers to use sensor data for schools and childcare facilities. To develop practical, effective toolkits to guide the use of sensors in school and childcare settings, it is essential to understand the perspectives of the potential end-users of such toolkit materials. METHODS: We conducted 15 semi-structured interviews with school, childcare, local health jurisdiction, air quality, and school district personnel regarding sensor use for wildfire smoke response. Interviews included sharing PM2.5 data collected at schools during wildfire smoke. Interviews were transcribed and transcripts were coded using a codebook developed both a priori and amended as additional themes emerged. RESULTS: Three major themes were identified by organizing complementary codes together: (1) Low-cost sensors are useful despite data quality limitations, (2) Low-cost sensor data can inform decision-making to protect children in school and childcare settings, and (3) There are feasibility and public perception-related barriers to using low-cost sensors. CONCLUSIONS: Interview responses provided practical implications for toolkit development, including demonstrating a need for toolkits that allow a variety of sensor preferences. In addition, participants expected to have a wide range of available time for monitoring, budget for sensors, and decision-making types. Finally, interview responses revealed a need for toolkits to address sensor uses outside of activity decisions, especially assessment of ventilation and filtration.

Data for Equity: Creating an Antiracist, Intersectional Approach to Data in a Local Health Department.

OBJECTIVE: To develop recommendations to embed equity into data work at a local health department and a framework for antiracist data praxis. DESIGN: A working group comprised staff from across the agency whose positions involved data collection, analysis, interpretation, or communication met during April-July 2018 to identify and discuss successes and challenges experienced by staff and to generate recommendations for achieving equitable data practices. SETTING: Local health department in New York City. RESULTS: The recommendations encompassed 6 themes: strengthening analytic skills, communication and interpretation, data collection and aggregation, community engagement, infrastructure and capacity building, and leadership and innovation. Specific projects are underway or have been completed. CONCLUSIONS: Improving equity in data requires changes to data processes and commitment to racial and intersectional justice and process change at all levels of the organization and across job functions. We developed a collaborative model for how a local health department can reform data work to embed an equity lens. This framework serves as a model for jurisdictions to build upon in their own efforts to promote equitable health outcomes and become antiracist organizations.

Randomized trial of a portable HEPA air cleaner intervention to reduce asthma morbidity among Latino children in an agricultural community.

BACKGROUND: Data on pediatric asthma morbidity and effective environmental interventions in U.S. agricultural settings are few. We evaluated the effectiveness of HEPA air cleaners on asthma morbidity among a cohort of rural Latino children. METHODS: Seventy-five children with poorly controlled asthma and living in non-smoking homes were randomly assigned to asthma education alone or along with HEPA air cleaners placed in their sleeping area and home living room. The Asthma Control Test (ACT) score, asthma symptoms in prior 2 weeks, unplanned clinical utilization, creatinine-adjusted urinary leukotriene E4 (uLTE4 [ng/mg]), and additional secondary outcomes were evaluated at baseline, six, and 12 months. Group differences were assessed using multivariable-adjusted generalized estimating equations. Incident rate ratios of ever experiencing the metrics of poorer asthma health during follow-up (suboptimal asthma management) were estimated using Poisson regression models in secondary analysis. RESULTS: Mean child age was 9.2 and 8.6 years in intervention and control groups, respectively, and two-thirds of participants were male. Primary analysis of repeated measures of ACT score did not differ between groups (HEPA group mean change compared to controls 10% [95% CI: - 12-39%]). A suggestion of greater decrease in uLTE4 (ng/mg creatinine) was observed (- 10% [95% CI: - 20 -1%]). Secondary analysis showed children with HEPAs were less likely to have an ACT score meeting a clinically defined cutoff for poorly controlled asthma using repeated measures (IRR: 0.45 [95% CI: 0.21-0.97]). In Poisson models, intervention participants had reduced risk of ever meeting this cutoff (IRR: 0.43 [95% CI: 0.21-0.89]), ever having symptoms in the past 2 weeks (IRR: 0.71 [95% CI: 0.52-0.98]), and lower risk of any unplanned clinical utilization (IRR: 0.35 [95% CI: 0.13-0.94]) compared to control participants. DISCUSSION: The HAPI study showed generally improved outcomes among children in the HEPA air cleaner group. However, primary analyses did not meet statistical significance and many outcomes were subjective (self-report) in this unblinded study, so findings must be interpreted cautiously. HEPA air cleaners may provide additional benefit for child asthma health where traditional asthmagens (traffic, tobacco smoke) are not prominent factors, but larger studies with more statistical power and blinded designs are needed. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04919915 . Date of retrospective registration: May 19, 2021.

Effectiveness of portable HEPA air cleaners on reducing indoor PM2.5 and NH3 in an agricultural cohort of children with asthma: A randomized intervention trial.

We conducted a randomized trial of portable HEPA air cleaners with pre-filters designed to also reduce NH3 in non-smoking homes of children age 6-12 with asthma in Yakima Valley (Washington, USA). Participants were recruited through the Yakima Valley Farm Workers Clinic asthma education program. All participants received education on home triggers while intervention families additionally received two HEPA cleaners (child's sleeping area, main living area). Fourteen-day integrated samples of PM2.5 and NH3 were measured at baseline and one-year follow-up. We fit ANCOVA models to compare follow-up concentrations in HEPA vs control homes, adjusting for baseline concentrations. Seventy-one households (36 HEPA, 35 control) completed the study. Most were single-family homes, with electric heat and stove, A/C, dogs/cats, and mean (SD) 5.3 (1.8) occupants. In the sleeping area, baseline geometric mean (GSD) PM2.5 was 10.7 (2.3) µg/m3 (HEPA) vs 11.2 (1.9) µg/m3 (control); in the living area, it was 12.5 (2.3) µg/m3 (HEPA) vs 13.6 (1.9) µg/m3 (control). Baseline sleeping area NH3 was 62.4 (1.6) µg/m3 (HEPA) vs 65.2 (1.8) µg/m3 (control). At follow-up, HEPA families had 60% (95% CI, 41%-72%; p < .0001) and 42% (19%-58%; p = .002) lower sleeping and living area PM2.5 , respectively, consistent with prior studies. NH3 reductions were not observed.

Effectiveness of portable HEPA air cleaners on reducing indoor endotoxin, PM10, and coarse particulate matter in an agricultural cohort of children with asthma: A randomized intervention trial.

We conducted a randomized trial of portable HEPA air cleaners in the homes of children age 6-12 years with asthma in the Yakima Valley, Washington. All families received asthma education while intervention families also received two HEPA cleaners (child's bedroom, living room). We collected 14-day integrated samples of endotoxin in settled dust and PM10 and PM10-2.5 in the air of the children's bedrooms at baseline and one-year follow-up, and used linear regression to compare follow-up levels, adjusting for baseline. Seventy-one families (36 HEPA, 35 control) completed the study. Baseline geometric mean (GSD) endotoxin loadings were 1565 (6.3) EU/m2 and 2110 (4.9) EU/m2 , respectively, in HEPA vs. control homes while PM10 and PM10-2.5 were 22.5 (1.9) µg/m3 and 9.5 (2.9) µg/m3 , respectively, in HEPA homes, and 19.8 (1.8) µg/m3 and 7.7 (2.0) µg/m3 , respectively, in control homes. At follow-up, HEPA families had 46% lower (95% CI, 31%-57%) PM10 on average than control families, consistent with prior studies. In the best-fit heterogeneous slopes model, HEPA families had 49% (95% CI, 6%-110%) and 89% lower (95% CI, 28%-177%) PM10-2.5 at follow-up, respectively, at 50th and 75th percentile baseline concentrations. Endotoxin loadings did not differ significantly at follow-up (4% lower, HEPA homes; 95% CI, -87% to 50%).

Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study.

Background: Artificial intelligence (AI) has repeatedly been shown to encode historical inequities in healthcare. We aimed to develop a framework to quantitatively assess the performance equity of health AI technologies and to illustrate its utility via a case study. Methods: Here, we propose a methodology to assess whether health AI technologies prioritise performance for patient populations experiencing worse outcomes, that is complementary to existing fairness metrics. We developed the Health Equity Assessment of machine Learning performance (HEAL) framework designed to quantitatively assess the performance equity of health AI technologies via a four-step interdisciplinary process to understand and quantify domain-specific criteria, and the resulting HEAL metric. As an illustrative case study (analysis conducted between October 2022 and January 2023), we applied the HEAL framework to a dermatology AI model. A set of 5420 teledermatology cases (store-and-forward cases from patients of 20 years or older, submitted from primary care providers in the USA and skin cancer clinics in Australia), enriched for diversity in age, sex and race/ethnicity, was used to retrospectively evaluate the AI model's HEAL metric, defined as the likelihood that the AI model performs better for subpopulations with worse average health outcomes as compared to others. The likelihood that AI performance was anticorrelated to pre-existing health outcomes was estimated using bootstrap methods as the probability that the negated Spearman's rank correlation coefficient (i.e., "R") was greater than zero. Positive values of R suggest that subpopulations with poorer health outcomes have better AI model performance. Thus, the HEAL metric, defined as p (R >0), measures how likely the AI technology is to prioritise performance for subpopulations with worse average health outcomes as compared to others (presented as a percentage below). Health outcomes were quantified as disability-adjusted life years (DALYs) when grouping by sex and age, and years of life lost (YLLs) when grouping by race/ethnicity. AI performance was measured as top-3 agreement with the reference diagnosis from a panel of 3 dermatologists per case. Findings: Across all dermatologic conditions, the HEAL metric was 80.5% for prioritizing AI performance of racial/ethnic subpopulations based on YLLs, and 92.1% and 0.0% respectively for prioritizing AI performance of sex and age subpopulations based on DALYs. Certain dermatologic conditions were significantly associated with greater AI model performance compared to a reference category of less common conditions. For skin cancer conditions, the HEAL metric was 73.8% for prioritizing AI performance of age subpopulations based on DALYs. Interpretation: Analysis using the proposed HEAL framework showed that the dermatology AI model prioritised performance for race/ethnicity, sex (all conditions) and age (cancer conditions) subpopulations with respect to pre-existing health disparities. More work is needed to investigate ways of promoting equitable AI performance across age for non-cancer conditions and to better understand how AI models can contribute towards improving equity in health outcomes. Funding: Google LLC.

Cumulative Impacts and COVID-19: Implications for Low-Income, Minoritized, and Health-Compromised Communities in King County, WA.

Few studies have assessed how the intersection of social determinants of health and environmental hazards contributes to racial disparities in COVID-19. The aim of our study was to compare COVID-19 disparities in testing and positivity to cumulative environmental health impacts, and to assess how unique social and environmental determinants of health relate to COVID-19 positivity in Seattle, King County, WA, at the census tract level. Publicly available data (n = 397 census tracts) were obtained from Public Health-Seattle & King County, 2018 ACS 5-year estimates, and the Washington Tracking Network. COVID-19 testing and positive case rates as of July 12, 2020, were mapped and compared to Washington State Environmental Health Disparities (EHD) Map cumulative impact rankings. We calculated odds ratios from a series of univariable and multivariable logistic regression analyses using cumulative impact rankings, and community-level socioeconomic, health, and environmental factors as predictors and having ≥ 10% or < 10% census tract positivity as the binary outcome variable. We found a remarkable overlap between Washington EHD cumulative impact rankings and COVID-19 positivity in King County. Census tracts with ≥ 10 % COVID-19 positivity had significantly lower COVID-19 testing rates and higher proportions of people of color and faced a combination of low socioeconomic status-related outcomes, poor community health outcomes, and significantly higher concentrations of fine particulate matter (PM2.5). King County communities experiencing high rates of COVID-19 face a disproportionate cumulative burden of environmental and social inequities. Cumulative environmental health impacts should therefore systematically be considered when assessing for risk of exposure to and health complications resulting from COVID-19.

Health workers' perspectives of a mobile health tool to improve diagnosis and management of paediatric acute respiratory illnesses in Uganda: a qualitative study.

OBJECTIVES: Mobile health tools have potential to improve the diagnosis and management of acute lower respiratory illnesses (ALRI), a leading cause of paediatric mortality worldwide. The objectives were to evaluate health workers' perceptions of acceptability, usability and feasibility of Acute Lower Respiratory Illness Treatment and Evaluation (ALRITE), a novel mobile health tool to help frontline health workers diagnose, treat and provide education about ALRI in children <5 years. DESIGN: A qualitative study including semistructured interviews with health facility administrators and focus groups with primary care health workers. SETTING: Two federally funded Ugandan primary care health facilities, one peri-urban and one rural. PARTICIPANTS: We enrolled 3 health administrators and 28 health workers (clinical officers and nurses). INTERVENTION: The ALRITE smartphone application was developed to help frontline health workers adhere to ALRI guidelines and differentiate wheezing illnesses from pneumonia in children under 5 years of age. ALRITE contains a simple decision tree, a partially automated respiratory rate counter, educational videos and an adapted respiratory assessment score to determine bronchodilator responsiveness. We performed a demonstration of ALRITE for participants at the beginning of interviews and focus groups. No participant had used ALRITE prior. RESULTS: Themes impacting the potential implementation of ALRITE were organised using individual-level, clinic-level and health-system level determinants. Individual-level determinants were acceptability and perceived benefit, usability, provider needs and provider-patient relationship. Clinic-level determinants were limited resources and integration within the health centre. Systems-level determinants included medication shortages and stakeholder engagement. CONCLUSIONS: Incorporation of these themes will ready ALRITE for field testing. Early engagement of end users provides insights critical to the development of tailored mHealth decision support tools.

Quantifying the Distribution of Environmental Health Threats and Hazards in Washington State Using a Cumulative Environmental Inequality Index.

Background: Environmental racism, community stressors, and age-related susceptibility play a significant role in environmental inequality. The goal of this article was to use an inequality index (II) to assess the level of equality in environmental threats and hazards based on race, poverty, and age in Washington State. Methods: Using the Washington Environmental Health Disparities Map, we quantified the level of disproportionate burdens on communities with greater populations of people of color, people in poverty, children younger than 5, and people older than 65 using 3 cumulative environmental indices and 10 individual environmental indicators. Results: Census tracts with a higher proportion of people of color and those with people living below 185% federal poverty levels were found to be disproportionately burdened by environmental threats (II = -0.175 and II = -0.167, respectively, p < 0.001). Individual environmental indicators were found to disproportionately burden communities of color and low-income communities. Children younger than 5 were also disproportionately burdened by cumulative environmental indices (II = -0.076, p < 0.001) and individual indicators. Our analysis did not show disproportionate burden of environmental health threats based on the proportion of people older than 65 (II = 0.124, p < 0.001). Discussion: The disproportionate burden of the cumulative environmental threats on communities of color and low-income communities in this study corroborates similar analyses. These findings can be applied in policy and regulatory actions to correct the distributive environmental disparities. Conclusion: We found much higher burdens among historically marginalized communities and children who are more susceptible to environmental threats and hazards.

Community-Level Factors Associated with COVID-19 Cases and Testing Equity in King County, Washington.

Individual-level Coronavirus Disease 2019 (COVID-19) case data suggest that certain populations may be more impacted by the pandemic. However, few studies have considered the communities from which positive cases are prevalent, and the variations in testing rates between communities. In this study, we assessed community factors that were associated with COVID-19 testing and test positivity at the census tract level for the Seattle, King County, Washington region at the summer peak of infection in July 2020. Multivariate Poisson regression was used to estimate confirmed case counts, adjusted for testing numbers, which were associated with socioeconomic status (SES) indicators such as poverty, educational attainment, transportation cost, as well as with communities with high proportions of people of color. Multivariate models were also used to examine factors associated with testing rates, and found disparities in testing for communities of color and communities with transportation cost barriers. These results demonstrate the ability to identify tract-level indicators of COVID-19 risk and specific communities that are most vulnerable to COVID-19 infection, as well as highlight the ongoing need to ensure access to disease control resources, including information and education, testing, and future vaccination programs in low-SES and highly diverse communities.

Housing stability and diabetes among people living in New York city public housing.

Public housing provides affordable housing and, potentially, housing stability for low-income families. Housing stability may be associated with lower incidence or prevalence and better management of a range of health conditions through many mechanisms. We aimed to test the hypotheses that public housing residency is associated with both housing stability and reduced risk of diabetes incidence, and the relationship between public housing and diabetes risk varies by levels of housing stability. Using 2004-16 World Trade Center Health Registry data, we compared outcomes (housing stability measured by sequence analysis of addresses, self-reported diabetes diagnoses) between 730 New York City public housing residents without prevalent diabetes at baseline and 730 propensity score-matched non-public housing residents. Sequence analysis found 3 mobility patterns among all 1460 enrollees, including stable housing (65%), limited mobility (27%), and unstable housing patterns (8%). Public housing residency was associated with stable housing over 12 years. Diabetes risk was not associated with public housing residency; however, among those experiencing housing instability, a higher risk of diabetes was found among public housing versus non-public housing residents. Of those stably housed, the association remained insignificant. These findings provide important evidence for a health benefit of public housing via housing stability among people living in public housing.

The home air in agriculture pediatric intervention (HAPI) trial: Rationale and methods.

BACKGROUND: Data addressing air quality effects on children with asthma in rural U.S. communities are rare. Our community engaged research partnership previously demonstrated associations between neighborhood NH3 and ambient PM2.5 and asthma in the agricultural lower Yakima Valley of Washington. As a next step, the partnership desired an intervention approach to address concerns about pediatric asthma in this largely Latino immigrant, farm worker community. OBJECTIVE: The Home Air in Agriculture Pediatric Intervention (HAPI) sought to examine the effectiveness of enrichment of an existing asthma education program with portable high-efficiency particulate air (HEPA) cleaners designed to reduce PM2.5 and NH3. We investigated the effect of this enriched approach on these exposures and asthma health measures. DESIGN: We randomized children with poorly controlled asthma to a control arm (current asthma education program) or an intervention arm (current asthma education program + placement of two indoor air cleaners in the family's home). Outcomes included (1) 14-day integrated samples of indoor air contaminants (PM2.5 and NH3) at baseline and one-year follow-up and (2) child asthma health metrics at baseline, midpoint (4-6 months) and one-year follow-up. These included the Asthma Control Test, symptoms days, clinical utilization, oral corticosteroid use, pulmonary function, fractional exhaled nitric oxide, and urinary leukotriene E4 concentration. DISCUSSION: To our knowledge, this is the first randomized HEPA cleaner intervention designed to assess NH3 as well as PM2.5 and to evaluate health outcomes of children with asthma in an agricultural region.

Pesticide exposure and occupational safety training of indigenous farmworkers in Oregon.

This follow-up study assessed indigenous and Latino farmworkers' occupational health and safety needs and measured variables related to pesticide exposure and pesticide safety training among this population. Results yielded differences between indigenous workers and Latino workers related to language barriers, experiences of workplace discrimination, preferred modes of information dissemination, pesticide exposures, and sufficiency of pesticide training. Employing more people who speak indigenous languages as interpreters, community and organizational leaders, and health workers may remove some of the linguistic and cultural barriers to occupational safety training.

Occupational conditions and well-being of indigenous farmworkers.

Increasing numbers of indigenous farmworkers from Mexico and Guatemala have been arriving in the Pacific Northwest (indigenous people are not of Hispanic or Latino descent and migrate from regions with unique cultural and linguistic traditions). Multilingual project outreach workers administered surveys to 150 farmworkers in Oregon to assess health, occupational safety, and general living conditions. This study confirms the increasing presence of indigenous peoples in Oregon and characterizes differences between indigenous and Latino farmworkers' occupational and health needs.

Neighborhood design and active aging.

This qualitative analysis of focus groups describes how neighborhood design encourages active aging. Nine focus groups were conducted in 2002 and 2003 with residents (N=60) aged 55 and over living in Portland, OR, USA. Content analysis revealed that local shopping and services, traffic and pedestrian infrastructure, neighborhood attractiveness, and public transportation influence activity among older adults. This information will be useful for making policy recommendations relating to land use planning and transportation, to assist in senior-friendly developments and neighborhood improvements, and to design effective senior health interventions with an emphasis on neighborhood design influences.

Application of qualitative methods in program planning for health promotion interventions.

The use of qualitative methods can provide an in-depth understanding of the issues and barriers related to community health and can help to inform the planning of health promotion programs and interventions. Although there are many examples in the literature that describe the application of quantitative data to program planning, few articles explicitly describe the application of qualitative data, such as data gathered using focus groups, in-depth interviews, and windshield tours, in program planning. Using the East Side Village Health Worker Partnership in Detroit, Michigan, as a case study example, this article explains the methods of incorporating qualitative data into each stage of program planning and development, including community assessment, development of goals and objectives, implementation of activities, and program evaluation.

Developing a reliable Senior Walking Environmental Assessment Tool.

BACKGROUND: Research of the effects of the built environment on physical activity often excludes certain segments of the population. The senior population, one segment perhaps most influenced by the physical features of an environment, has been understudied. Developing reliable measures of the environment is important to increase our understanding of the environmental effects on physical activity among seniors. METHODS: A review of urban planning and health literature helped identify important concepts and theories that were used to inform the development of the Senior Walking Environmental Assessment Tool (SWEAT). Urban planning and health research professionals were consulted and provided feedback on the tool. A total of 355 neighborhood segments were assessed using SWEAT. Thirty-six neighborhood segments were assessed for inter-rater reliability. RESULTS: Overall, raters exhibited good-to-excellent agreement on most items included in SWEAT. Items assessing buildings and destinations were less reliable than other categories. CONCLUSIONS: The development of a reliable senior-specific environmental measurement of detailed street level environmental features that may influence walking among seniors is important to advance this research and engage communities to consider simple environmental changes that encourage walking among seniors.

Pulmonary anatomy and physiology and the effects of COPD.

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States, yet it has received relatively little attention in the literature compared with other leading killers such as cancer and heart disease. To identify, assess, intervene, and care for patients with COPD in the home, a comprehensive understanding of this disease and its effects is imperative. This article discusses the epidemiology of COPD, reviews normal pulmonary anatomy and physiology, and explains the physiological changes to the pulmonary system caused by COPD.

The relationship between social support, stress, and health among women on Detroit's East Side.

A conceptual model of the stress process has been useful in examining relationships between numerous social determinants (e.g., chronic stress), protective factors (e.g., social support), and health status. In this article, the authors examine multiple sources of chronic stress, instrumental and emotional support, and health outcomes among a random sample (N = 679) of predominantly low-income African American women who reside on Detroit's east side. The findings suggest that a number of chronic stressors have an impact on depressive symptoms and general health and that even though instrumental and emotional support each have a significant effect over and above the effects of the stressors, when both are included in the model, instrumental support, and not emotional support, remains as a significant predictor of health outcomes. These findings suggest the need for health education interventions and policy strategies that strengthen social support and aim at macro-level changes necessary to reduce chronic stressful conditions.