| 研究課題/領域番号 |
21K17894
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| 研究種目 |
若手研究
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| 配分区分 | 基金 |
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| 審査区分 |
小区分63040:環境影響評価関連
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| 研究機関 | 筑波大学 |
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研究代表者 |
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| 研究期間 (年度) |
2021-04-01 – 2025-03-31
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| 研究課題ステータス |
交付 (2022年度)
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| 配分額 *注記 |
4,680千円 (直接経費: 3,600千円、間接経費: 1,080千円)
2023年度: 1,560千円 (直接経費: 1,200千円、間接経費: 360千円)
2022年度: 1,040千円 (直接経費: 800千円、間接経費: 240千円)
2021年度: 2,080千円 (直接経費: 1,600千円、間接経費: 480千円)
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| キーワード | air pollution / particulate matter / mortality / health risk / time series study |
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| 研究開始時の研究の概要 |
As the association varies across study locations, regional evidence is crucial to obtain accurate information and thereby better protect the population. This study focuses on such aspects of Japan using nationwide data covering all 47 prefectures with advanced flexible modeling strategies.
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| 研究実績の概要 |
During the second year of the project (FY2022), we developed analytical methods to estimate the short-term associations between PM2.5 and mortality in Japan. To quantify these associations, we conducted a two-stage analysis. In the first stage, the location-specific risks of PM2.5 were estimated by utilizing a time-series quasi-Poisson model. We applied a distributed lag non-linear model along with a flexible functional form of splines to evaluate the location-specific associations. We controlled various important covariates, including weather variables, day of the week, and seasonal and long-term time trends. Sensitivity analyses were carried out to determine the robustness of our findings. To assess and compare the shapes of the concentration-response (CR) relationship, all local CR functions were formulated using a unified statistical design. In the second stage, we used a random-effect meta-analysis to combine the regional and national overall estimates.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
The project is on track with statistical modeling advancements to quantify location-specific health risks. Moreover, data from 2010 to 2016 is being updated to 2019.
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| 今後の研究の推進方策 |
In the project's final year, we will conduct a regional risk assessment based on our FY2022 findings. Local estimations will be mapped to visualize the risks and the efficacy of the current AQG standards will be assessed using the CR functions obtained for each location in Japan. The geographical heterogeneity will be explained based on indicators of local characteristics. In addition, the susceptible population will be identified through stratified analyses.
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