A simple physical-activity-based model for managing children's activities against exposure to air pollutants

Meng, Huicui; Zhang, Xiaoyu; Xiao, Jinqiu; Zhang, Yilan; Lin, Weiwei; Li, Zijian

doi:10.1016/j.jenvman.2020.111823

Cited by 11 publications

(6 citation statements)

References 25 publications

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“…These associations during the summer season could be explained by total outdoor time spent, which is heavily influenced by weather conditions. 41,42 Meng et al 43 reported that children are more vulnerable to total air pollutant exposure during non-winter days than winter. In this study, there were lower criteria pollutant concentrations and null values for aeroallergen counts for the majority of the winter days.…”

Section: Discussionmentioning

confidence: 99%

Joint association between ambient air pollutant mixture and pediatric asthma exacerbations

Puvvula

Poole

González

et al. 2022

Environmental Epidemiology

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Background: Exposure to air pollutants is known to exacerbate asthma, with prior studies focused on associations between single pollutant exposure and asthma exacerbations. As air pollutants often exist as a complex mixture, there is a gap in understanding the association between complex air pollutant mixtures and asthma exacerbations. We evaluated the association between the air pollutant mixture (52 pollutants) and pediatric asthma exacerbations. Method: This study focused on children (age ≤ 19 years) who lived in Douglas County, Nebraska, during 2016-2019. A seasonal-scale joint association between the outdoor air pollutant mixture adjusting for potential confounders (temperature, precipitation, wind speed, and wind direction) in relation to pediatric asthma exacerbation-related emergency department (ED) visits was evaluated using the generalized weighted quantile sum (qWQS) regression with repeated holdout validation. Results: We observed associations between air pollutant mixture and pediatric asthma exacerbations during spring (lagged by 5 days), summer (lag 0-5 days), and fall (lag 1-3 days) seasons. The estimate of the joint outdoor air pollutant mixture effect was higher during the summer season (adjusted-β WQS = 1.11, 95% confidence interval [CI]: 0.66, 1.55), followed by spring (adjusted-β WQS = 0.40, 95% CI: 0.16, 0.62) and fall (adjusted-β WQS = 0.20, 95% CI: 0.06, 0.33) seasons. Among the air pollutants, PM 2.5 , pollen, and mold contributed higher weight to the air pollutant mixture. Conclusion: There were associations between outdoor air pollutant mixture and pediatric asthma exacerbations during the spring, summer, and fall seasons. Among the 52 outdoor air pollutant metrics investigated, PM 2.5 , pollen (sycamore, grass, cedar), and mold (Helminthosporium, Peronospora, and Erysiphe) contributed the highest weight to the air pollutant mixture.

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Section: Discussionmentioning

confidence: 99%

Joint association between ambient air pollutant mixture and pediatric asthma exacerbations

Puvvula

Poole

González

et al. 2022

Environmental Epidemiology

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“…RPGen may also be applied to models of inhalation, as descriptions of the household can be used as the basis for agent-based models. For example, exposure models that measure exposure outcomes between time indoors and time outdoors may be influenced by the presence of a vehicle, the structure of the household, number of windows, and number of rooms [51]. When combined with downstream exposure models, this approach can then effectively simulate the population with a high level of resolution.…”

Section: Other Exposure Modelsmentioning

confidence: 99%

The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk

East

Dawson

Glen

et al. 2021

Toxics

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Exposure to chemicals is influenced by associations between the individual’s location and activities as well as demographic and physiological characteristics. Currently, many exposure models simulate individuals by drawing distributions from population-level data or use exposure factors for single individuals. The Residential Population Generator (RPGen) binds US surveys of individuals and households and combines the population with physiological characteristics to create a synthetic population. In general, the model must be supported by internal consistency; i.e., values that could have come from a single individual. In addition, intraindividual variation must be representative of the variation present in the modeled population. This is performed by linking individuals and similar households across income, location, family type, and house type. Physiological data are generated by linking census data to National Health and Nutrition Examination Survey data with a model of interindividual variation of parameters used in toxicokinetic modeling. The final modeled population data parameters include characteristics of the individual’s community (region, state, urban or rural), residence (size of property, size of home, number of rooms), demographics (age, ethnicity, income, gender), and physiology (body weight, skin surface area, breathing rate, cardiac output, blood volume, and volumes for body compartments and organs). RPGen output is used to support user-developed chemical exposure models that estimate intraindividual exposure in a desired population. By creating profiles and characteristics that determine exposure, synthetic populations produced by RPGen increases the ability of modelers to identify subgroups potentially vulnerable to chemical exposures. To demonstrate application, RPGen is used to estimate exposure to Toluene in an exposure modeling case example.

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“…Toddlers, who are over 1 year old and under 3 years old, are susceptible and vulnerable to air pollution 4 . Toddlers, due to their immature organ structure and function, as well as their active physical activity and rapid breathing rate, are at a higher risk of inhaling air pollutants [5][6][7][8] . Furthermore, their developing organs are particularly sensitive to the damage caused by air pollution [5][6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Development and validation of the air pollution exposure protective behavior scale for toddlers

Wang,

Shen,

et al. 2024

Interdisciplinary Nursing Research

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Objectives: This study aimed to develop the Air Pollution Exposure Protective Behavior Scale for Toddlers (APP-T) and test its psychometric properties, to provide a tool for the assessment of air pollution exposure protective behaviors for toddlers. Methods: A draft scale containing 39 items was constructed based on an evidence summary, an interview and literature review. The scale was revised according to the comments from 16 experts in public health, environmental science and nursing through a modified Delphi method, and the results of a pilot test of air pollution exposure protective behaviors for toddlers (n=57). A formal survey was conducted using the revised scale (n=876). Factor structure and model fit of the scale were examined using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). An expert consultation was conducted to assess the content validity. Known-groups validity, internal consistency, test-retest reliability, and split-half reliability of the scale were also calculated. Results: A five-point Likert scale of four dimensions, consisting of 25 main items, two additional items and four validation items, was developed in this study, to assess the air pollution exposure protective behaviors for toddlers. In the formal survey, the four factors of the scale explained 63.0% of the variance, with a good model fit and acceptable convergence. The scale Cronbach’s α was 0.93. The test-retest correlation coefficients for all four dimensions and the whole scale scores were above 0.70 and statistically significant, with a Spearman-Brown coefficient of 0.85. Conclusion: This study developed and validated an assessment scale, the Air Pollution Exposure Protective Behavior Scale for Toddlers (APP-T), with good reliability and validity. This scale can provide a basis for clarifying the current situation of air pollution exposure protective behaviors for toddlers and for implementing precision nursing on respiratory symptoms and diseases for toddlers.

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A simple physical-activity-based model for managing children's activities against exposure to air pollutants

Cited by 11 publications

References 25 publications

Joint association between ambient air pollutant mixture and pediatric asthma exacerbations

Joint association between ambient air pollutant mixture and pediatric asthma exacerbations

The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk

Development and validation of the air pollution exposure protective behavior scale for toddlers

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