Dataset Information

Prediction of personal exposure to PM_2.5 in mother-child pairs in rural Ghana.

ABSTRACT:

Background

Air pollution epidemiological studies usually rely on estimates of long-term exposure to air pollutants, which are difficult to ascertain. This problem is accentuated in settings where sources of personal exposure differ from those of ambient concentrations, including household air pollution environments where cooking is an important source.

Objective

The objective of this study was to assess the feasibility of estimating usual exposure to PM_2.5 based on short-term measurements.

Methods

We leveraged three types of short-term measurements from a cohort of mother-child pairs in 26 communities in rural Ghana: (A) personal exposure to PM_2.5 in mothers and age four children, ambient PM_2.5 concentrations (B) at the community level, and (C) at a central site. Baseline models were linear mixed models with a random intercept for community or for participant. Lowest root-mean-square-error (RMSE) was used to select the best-performing model.

Results

We analyzed 240 community-days and 251 participant-days of PM_2.5. Medians (IQR) of PM_2.5 were 19.5 (36.5) μg/m³ for the central site, 28.7 (41.5) μg/m³ for the communities, 70.6 (56.9) μg/m³ for mothers, and 80.9 (74.1) μg/m³ for children. The ICCs (95% CI) for community ambient and personal exposure were 0.30 (0.17, 0.47) and 0.74 (0.65, 0.81) respectively. The sources of variability differed during the Harmattan season. Children's daily exposure was best predicted by models that used community ambient compared to mother's exposure as a predictor (log-scale RMSE: 0.165 vs 0.325).

Conclusion

Our results support the feasibility of predicting usual personal exposure to PM_2.5 using short-term measurements in settings where household air pollution is an important source of exposure. Our results also suggest that mother's exposure may not be the best proxy for child's exposure at age four.

SUBMITTER: Daouda M

PROVIDER: S-EPMC9355911 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

Prediction of personal exposure to PM<sub>2.5</sub> in mother-child pairs in rural Ghana.

Daouda Misbath M Mujtaba Mohammed Nuhu MN Yang Qiang Q Seyram Kaali K Lee Alison G AG Tawiah Theresa T Ae-Ngibise Kenneth A KA Chillrud Steve N SN Jack Darby D Asante Kwaku Poku KP

Journal of exposure science & environmental epidemiology 20220317 4

<h4>Background</h4>Air pollution epidemiological studies usually rely on estimates of long-term exposure to air pollutants, which are difficult to ascertain. This problem is accentuated in settings where sources of personal exposure differ from those of ambient concentrations, including household air pollution environments where cooking is an important source.<h4>Objective</h4>The objective of this study was to assess the feasibility of estimating usual exposure to PM<sub>2.5</sub> based on shor ...[more]

PMID: 35301434

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Project description:BackgroundCooking and heating in households contribute importantly to air pollution exposure worldwide. However, there is insufficient investigation of measured fine particulate matter (PM2.5) exposure levels, variability, seasonality, and inter-spatial dynamics associated with these behaviours.MethodsWe undertook parallel measurements of personal, household (kitchen and living room), and community PM2.5 in summer (May-September 2017) and winter (November 2017-Janauary 2018) in 477 participants from one urban and two rural communities in China. After stringent data cleaning, there were 67,326-80,980 person-hours (ntotal = 441; nsummer = 384; nwinter = 364; 307 had repeated PM2.5 data in both seasons) of processed data per microenvironment. Age- and sex-adjusted geometric means of PM2.5 were calculated by key participant characteristics, overall and by season. Spearman correlation coefficients between PM2.5 levels across different microenvironments were computed.FindingsOverall, 26.4 % reported use of solid fuel for both cooking and heating. Solid fuel users had 92 % higher personal and kitchen 24-h average PM2.5 exposure than clean fuel users. Similarly, they also had a greater increase (83 % vs 26 %) in personal and household PM2.5 from summer to winter, whereas community levels of PM2.5 were 2-4 times higher in winter across different fuel categories. Compared with clean fuel users, solid fuel users had markedly higher weighted annual average PM2.5 exposure at personal (78.2 [95 % CI 71.6-85.3] μg/m3 vs 41.6 [37.3-46.5] μg/m3), kitchen (102.4 [90.4-116.0] μg/m3 vs 52.3 [44.8-61.2] μg/m3) and living room (62.1 [57.3-67.3] μg/m3 vs 41.0 [37.1-45.3] μg/m3) microenvironments. There was a remarkable diurnal variability in PM2.5 exposure among the participants, with 5-min moving average from 10 μg/m3 to 700-1200 μg/m3 across different microenvironments. Personal PM2.5 was moderately correlated with living room (Spearman r: 0.64-0.66) and kitchen (0.52-0.59) levels, but only weakly correlated with community levels, especially in summer (0.15-0.34) and among solid fuel users (0.11-0.31).ConclusionSolid fuel use for cooking and heating was associated with substantially higher personal and household PM2.5 exposure than clean fuel users. Household PM2.5 appeared a better proxy of personal exposure than community PM2.5.

Project description:In-utero exposure to fine particulate matter (PM2.5) and specific sources and components of PM2.5 have been linked with lower birthweight. However, previous results have been mixed, likely due to heterogeneity in sources impacting PM2.5 and due to measurement error from using ambient data. Therefore, we investigated the effect of PM2.5 sources and their high-loading components on birthweight using data from 198 women in the 3rd trimester from the MADRES cohort 48-h personal PM2.5 exposure monitoring sub-study. The mass contributions of six major sources of personal PM2.5 exposure were estimated for 198 pregnant women in the 3rd trimester using the EPA Positive Matrix Factorization v5.0 model, along with their 17 high-loading chemical components using optical carbon and X-ray fluorescence approaches. Single- and multi-pollutant linear regressions evaluated the association between personal PM2.5 sources/components and birthweight, adjusting for gestational age, maternal age, race, infant sex, parity, diabetes status, temperature, maternal education, and smoking history. Participants were predominately Hispanic (81%), with a mean (SD) gestational age of 39.1 (1.5) weeks and age of 28.2 (6.0) years. Mean birthweight was 3295.8 g (484.1) and mean PM2.5 exposure was 21.3 (14.4) µg/m3. A 1 SD increase in the mass contribution of the fresh sea salt source was associated with a 99.2 g decrease in birthweight (95% CI - 197.7, - 0.6), and aged sea salt was associated with a 70.1 g decrease in birthweight (95% CI - 141.7, 1.4). Magnesium, sodium, and chlorine were associated with lower birthweight, which remained after adjusting for PM2.5 mass. This study found evidence that major sources of personal PM2.5 including fresh and aged sea salt were negatively associated with birthweight, with the strongest effect on birthweight from Na and Mg. The effect of crustal and fuel oil sources differed by infant sex with negative associations seen in boys compared to positive associations in girls.

Project description:Many portable monitors for quantifying mass concentrations of particulate matter air pollution rely on aerosol light scattering as the measurement method; however, the relationship between scattered light (what is measured) and aerosol mass concentration (the metric of interest) is a complex function of the refractive index, size distribution, and shape of the particles. In this study, we compared 33-h personal PM2.5 concentrations measured simultaneously using nephelometry (personal DataRAM pDR-1200) and gravimetric filter sampling for working adults (44 participants, 249 samples). Nephelometer- and filter-derived 33-h average PM2.5 concentrations were correlated (Spearman's ρ = 0.77); however, the nephelometer-derived concentration was within 20% of the filter-derived concentration for only 13% of samples. The nephelometer/filter ratio, which is used to correct light-scattering measurements to a gravimetric sample, had a median value of 0.52 and varied by over a factor of three (10th percentile = 0.35, 90th percentile = 1.1). When 33-h samples with >50% of 10-s average nephelometer readings below the nephelometer limit of detection were removed from the dataset during sensitivity analyses, the fraction of nephelometer-derived concentrations that were within 20% of the filter-derived concentration increased to 25%. We also evaluated how much the accuracy of nephelometer-derived concentrations improved after applying: (1) a median correction factor derived from a subset of 44 gravimetric samples, (2) participant-specific correction factors derived from one same from each subject, and (3) correction factors predicted using linear models based on other variables recorded during the study. Each approach independently increased the fraction of nephelometer-derived concentrations that were within 20% of the filter-derived concentration to approximately 45%. These results illustrate the challenges with using light scattering (without correction to a concurrent gravimetric sample) to estimate personal exposure to PM2.5 mass among mobile adults exposed to low daily average concentrations (median = 8 μg m-3 in this study).

Project description:BackgroundPersonal exposure to fine particulate matter (PM2.5) is impacted by different sources each with different chemical composition. Determining these sources is important for reducing personal exposure and its health risks especially during pregnancy.ObjectiveIdentify main sources and their contributions to the personal PM2.5 exposure in 213 women in the 3rd trimester of pregnancy in Los Angeles, CA.MethodsWe measured 48-hr integrated personal PM2.5 exposure and analyzed filters for PM2.5 mass, elemental composition, and optical carbon fractions. We used the EPA Positive Matrix Factorization (PMF) model to resolve and quantify the major sources of personal PM2.5 exposure. We then investigated bivariate relationships between sources, time-activity patterns, and environmental exposures in activity spaces and residential neighborhoods to further understand sources.ResultsMean personal PM2.5 mass concentration was 22.3 (SD = 16.6) μg/m3. Twenty-five species and PM2.5 mass were used in PMF with a final R2 of 0.48. We identified six sources (with major species in profiles and % contribution to PM2.5 mass) as follows: secondhand smoking (SHS) (brown carbon, environmental tobacco smoke; 65.3%), fuel oil (nickel, vanadium; 11.7%), crustal (aluminum, calcium, silicon; 11.5%), fresh sea salt (sodium, chlorine; 4.7%), aged sea salt (sodium, magnesium, sulfur; 4.3%), and traffic (black carbon, zinc; 2.6%). SHS was significantly greater in apartments compared to houses. Crustal source was correlated with more occupants in the household. Aged sea salt increased with temperature and outdoor ozone, while fresh sea salt was highest on days with westerly winds from the Pacific Ocean. Traffic was positively correlated with ambient NO2 and traffic-related NOx at residence. Overall, 76.8% of personal PM2.5 mass came from indoor or personal compared to outdoor sources.ImpactWe conducted source apportionment of personal PM2.5 samples in pregnancy in Los Angeles, CA. Among identified sources, secondhand smoking contributed the most to the personal exposure. In addition, traffic, crustal, fuel oil, fresh and aged sea salt sources were also identified as main sources. Traffic sources contained markers of combustion and non-exhaust wear emissions. Crustal source was correlated with more occupants in the household. Aged sea salt source increased with temperature and outdoor ozone and fresh sea salt source was highest on days with westerly winds from the Pacific Ocean.

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Dataset Information

Prediction of personal exposure to PM_2.5 in mother-child pairs in rural Ghana.

Background

Objective

Methods

Results

Conclusion

Publications

Prediction of personal exposure to PM<sub>2.5</sub> in mother-child pairs in rural Ghana.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Prediction of personal exposure to PM2.5 in mother-child pairs in rural Ghana.

Background

Objective

Methods

Results

Conclusion

Publications

Prediction of personal exposure to PM<sub>2.5</sub> in mother-child pairs in rural Ghana.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Prediction of personal exposure to PM_2.5 in mother-child pairs in rural Ghana.