Dataset Information

Building Vulnerability in a Changing Climate: Indoor Temperature Exposures and Health Outcomes in Older Adults Living in Public Housing during an Extreme Heat Event in Cambridge, MA.

ABSTRACT: In the Northeastern U.S., future heatwaves will increase in frequency, duration, and intensity due to climate change. A great deal of the research about the health impacts from extreme heat has used ambient meteorological measurements, which can result in exposure misclassification because buildings alter indoor temperatures and ambient temperatures are not uniform across cities. To characterize indoor temperature exposures during an extreme heat event in buildings with and without central air conditioning (AC), personal monitoring was conducted with 51 (central AC, n = 24; non-central AC, n = 27) low-income senior residents of public housing in Cambridge, Massachusetts in 2015, to comprehensively assess indoor temperatures, sleep, and physiological outcomes of galvanic skin response (GSR) and heart rate (HR), along with daily surveys of adaptive behaviors and health symptoms. As expected, non-central AC units (T_mean = 25.6 °C) were significantly warmer than those with central AC (T_mean = 23.2 °C, p < 0.001). With higher indoor temperatures, sleep was more disrupted and GSR and HR both increased (p < 0.001). However, there were no changes in hydration behaviors between residents of different buildings over time and few moderate/several health symptoms were reported. This suggests both a lack of behavioral adaptation and thermal decompensation beginning, highlighting the need to improve building cooling strategies and heat education to low-income senior residents, especially in historically cooler climates.

SUBMITTER: Williams AA

PROVIDER: S-EPMC6651653 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Building Vulnerability in a Changing Climate: Indoor Temperature Exposures and Health Outcomes in Older Adults Living in Public Housing during an Extreme Heat Event in Cambridge, MA.

Williams Augusta A AA Spengler John D JD Catalano Paul P Allen Joseph G JG Cedeno-Laurent Jose G JG

International journal of environmental research and public health 20190704 13

In the Northeastern U.S., future heatwaves will increase in frequency, duration, and intensity due to climate change. A great deal of the research about the health impacts from extreme heat has used ambient meteorological measurements, which can result in exposure misclassification because buildings alter indoor temperatures and ambient temperatures are not uniform across cities. To characterize indoor temperature exposures during an extreme heat event in buildings with and without central air c ...[more]

PMID: 31277359

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Project description:BackgroundIn the United States, asthma is the most common chronic disease of childhood across all socioeconomic classes and is the most frequent cause of hospitalization among children. Asthma exacerbations have been associated with exposure to residential indoor environmental stressors such as allergens and air pollutants as well as numerous additional factors. Simulation modeling is a valuable tool that can be used to evaluate interventions for complex multifactorial diseases such as asthma but in spite of its flexibility and applicability, modeling applications in either environmental exposures or asthma have been limited to date.MethodsWe designed a discrete event simulation model to study the effect of environmental factors on asthma exacerbations in school-age children living in low-income multi-family housing. Model outcomes include asthma symptoms, medication use, hospitalizations, and emergency room visits. Environmental factors were linked to percent predicted forced expiratory volume in 1 second (FEV1%), which in turn was linked to risk equations for each outcome. Exposures affecting FEV1% included indoor and outdoor sources of NO2 and PM2.5, cockroach allergen, and dampness as a proxy for mold.ResultsModel design parameters and equations are described in detail. We evaluated the model by simulating 50,000 children over 10 years and showed that pollutant concentrations and health outcome rates are comparable to values reported in the literature. In an application example, we simulated what would happen if the kitchen and bathroom exhaust fans were improved for the entire cohort, and showed reductions in pollutant concentrations and healthcare utilization rates.ConclusionsWe describe the design and evaluation of a discrete event simulation model of pediatric asthma for children living in low-income multi-family housing. Our model simulates the effect of environmental factors (combustion pollutants and allergens), medication compliance, seasonality, and medical history on asthma outcomes (symptom-days, medication use, hospitalizations, and emergency room visits). The model can be used to evaluate building interventions and green building construction practices on pollutant concentrations, energy savings, and asthma healthcare utilization costs, and demonstrates the value of a simulation approach for studying complex diseases such as asthma.

Project description:Estimates of population air pollution exposure typically rely on the outdoor component only, and rarely account for populations spending the majority of their time indoors. Housing is an important modifier of air pollution exposure due to outdoor pollution infiltrating indoors, and the removal of indoor-sourced pollution through active or passive ventilation. Here, we describe the application of an indoor air pollution modelling tool to a spatially distributed housing stock model for England and Wales, developed from Energy Performance Certificate (EPC) data and containing information for approximately 11.5 million dwellings. First, we estimate indoor/outdoor (I/O) ratios and total indoor concentrations of outdoor air pollution for PM2.5 and NO2 for all EPC dwellings in London. The potential to estimate concentration from both indoor and outdoor sources is then demonstrated by modelling indoor background CO levels for England and Wales pre- and post-energy efficient adaptation, including heating, cooking, and smoking as internal sources. In London, we predict a median I/O ratio of 0.60 (99% CIs; 0.53-0.73) for outdoor PM2.5 and 0.41 (99%CIs; 0.34-0.59) for outdoor NO2; Pearson correlation analysis indicates a greater spatial modification of PM2.5 exposure by housing (??=?0.81) than NO2 (??=?0.88). For the demonstrative CO model, concentrations ranged from 0.4-9.9?ppm (99%CIs)(median?=?3.0?ppm) in kitchens and 0.3-25.6?ppm (median?=?6.4?ppm) in living rooms. Clusters of elevated indoor concentration are found in urban areas due to higher outdoor concentrations and smaller dwellings with reduced ventilation potential, with an estimated 17.6% increase in the number of living rooms and 63% increase in the number of kitchens exceeding recommended exposure levels following retrofit without additional ventilation. The model has the potential to rapidly calculate indoor pollution exposure across large housing stocks and estimate changes to exposure under different pollution or housing policy scenarios.

Dataset Information

Building Vulnerability in a Changing Climate: Indoor Temperature Exposures and Health Outcomes in Older Adults Living in Public Housing during an Extreme Heat Event in Cambridge, MA.

Publications

Building Vulnerability in a Changing Climate: Indoor Temperature Exposures and Health Outcomes in Older Adults Living in Public Housing during an Extreme Heat Event in Cambridge, MA.

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