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Air pollution, residential greenness and medical expenditure in older adults

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Abstract Background: Environmental factors have been thought of as potential determinants for human health and would plausibly affect health expenditures. However, little is known about the association between air pollution, greenness, and their combined effect on medical expenditures, let alone, related evidence in older adults is rarely. Method: We used data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Medical expenditures were defined as out-of-pocket medical expenditures in the 12 months preceding the survey. A two-year average of PM2.5 concentrations prior to medical expenditures was collected as PM2.5 exposures. Greenness exposure was contemporaneous with PM2.5 and evaluated by residential units’ NDVI value in 250 m buffer. The two-part models were performed to assess the independent influences of PM2.5, greenness, and its combined influence. The first model was a logistic regression model based on the whole sample, called the participation models. Then a log-transformed linear regression model was fitted using samples with nonzero medical expenditures, named intensity models. Result: We found that each 10-µg/m3 increment in PM2.5 increased the odds of incurring any costs (coefficient=0.80, P <0.001) according to the participation models. PM2.5 was associated with an increase in expenditure based on intensity models (coefficient=0.08, P <0.001). Each 0.1-unit increase in greenness decreased the odds of incurring any costs in the participation models (coefficient=-0.77, P <0.05). The risk of increasing medical expenditures attributed to PM2.5was higher in areas with a low level of greenness (coefficient=0.16, P <0.001). While greenness did not present a protective effect for increasing costs in the low level of PM2.5 (coefficient=0.21, P <0.05), increasing greenness could reduce costs in the high and medium level of PM2.5. Uneducated participants and others without pensions were vulnerable to the combined effect. Conclusion: Air pollution is a potential source of medical expenditures; in comparison, expanding greenspace is associated with these societal costs saved. Suppose the combined impact of greenness and PM2.5 was to be replicated in a future study, which would improve the utility of current evidence.
Title: Air pollution, residential greenness and medical expenditure in older adults
Description:
Abstract Background: Environmental factors have been thought of as potential determinants for human health and would plausibly affect health expenditures.
However, little is known about the association between air pollution, greenness, and their combined effect on medical expenditures, let alone, related evidence in older adults is rarely.
Method: We used data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS).
Medical expenditures were defined as out-of-pocket medical expenditures in the 12 months preceding the survey.
A two-year average of PM2.
5 concentrations prior to medical expenditures was collected as PM2.
5 exposures.
Greenness exposure was contemporaneous with PM2.
5 and evaluated by residential units’ NDVI value in 250 m buffer.
The two-part models were performed to assess the independent influences of PM2.
5, greenness, and its combined influence.
The first model was a logistic regression model based on the whole sample, called the participation models.
Then a log-transformed linear regression model was fitted using samples with nonzero medical expenditures, named intensity models.
Result: We found that each 10-µg/m3 increment in PM2.
5 increased the odds of incurring any costs (coefficient=0.
80, P <0.
001) according to the participation models.
PM2.
5 was associated with an increase in expenditure based on intensity models (coefficient=0.
08, P <0.
001).
Each 0.
1-unit increase in greenness decreased the odds of incurring any costs in the participation models (coefficient=-0.
77, P <0.
05).
The risk of increasing medical expenditures attributed to PM2.
5was higher in areas with a low level of greenness (coefficient=0.
16, P <0.
001).
While greenness did not present a protective effect for increasing costs in the low level of PM2.
5 (coefficient=0.
21, P <0.
05), increasing greenness could reduce costs in the high and medium level of PM2.
5.
Uneducated participants and others without pensions were vulnerable to the combined effect.
Conclusion: Air pollution is a potential source of medical expenditures; in comparison, expanding greenspace is associated with these societal costs saved.
Suppose the combined impact of greenness and PM2.
5 was to be replicated in a future study, which would improve the utility of current evidence.

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