Greenness-air pollution-physical activity-hypertension association among middle-aged and older adults: Evidence from urban and rural China

Huang, Biao; Xiao, Tong; Grekousis, George; Zhao, Hongsheng; He, Jiarui; Dong, Guang‐Hui; Liu, Ye

doi:10.1016/j.envres.2021.110836

Cited by 57 publications

(30 citation statements)

References 38 publications

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“…Limited physical activity or, even worst, no physical activity could dramatically increase the risk of many severe health disorders (i.e., diabetes, cancer, and cardiovascular disease), thus increasing the severity of potential COVID-19 infection ( Lippi et al, 2020 ). Furthermore, reduced or no leisure-time physical activity has been linked to experiencing unpleasant emotions such as sadness, anger, or frustration and, in general, to mental health and mental wellbeing ( Huang et al, 2021 ; Liu et al, 2019 ). In combination with prolonged quarantines, physical activity's absence triggers post-traumatic stress and depression ( Brooks et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Ranking the importance of demographic, socioeconomic, and underlying health factors on US COVID-19 deaths: A geographical random forest approach

Grekousis¹,

Feng²,

Marakakis³

et al. 2022

Health & Place

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A growing number of studies show that the uneven spatial distribution of COVID-19 deaths is related to demographic and socioeconomic disparities across space. However, most studies fail to assess the relative importance of each factor to COVID-19 death rate and, more importantly, how this importance varies spatially. Here, we assess the variables that are more important locally using Geographical Random Forest (GRF), a local non-linear regression method. Through GRF, we estimated the non-linear relationships between the COVID-19 death rate and 29 socioeconomic and health-related factors during the first year of the pandemic in the USA (county level). GRF outputs are compared to global (Random Forest and OLS) and local (Geographically Weighted Regression) models. Results show that GRF outperforms all models and that the importance of variables highly varies by location. For example, lack of health insurance is the most important factor in one-third (34.86%) of the US counties. Most of these counties are (concentrated mainly in the Midwest region and South region). On the other hand, no leisure-time physical activity is the most important primary factor for 19.86% of the US counties. These counties are found in California, Oregon, Washington, and parts of the South region. Understanding the location-based characteristics and spatial patterns of socioeconomic and health factors linked to COVID-19 deaths is paramount for policy designing and decision making. In this way, interventions can be designed and implemented based on the most important factors locally, avoiding thus general guidelines addressed for the entire nation.

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Section: Discussionmentioning

confidence: 99%

Ranking the importance of demographic, socioeconomic, and underlying health factors on US COVID-19 deaths: A geographical random forest approach

Grekousis¹,

Feng²,

Marakakis³

et al. 2022

Health & Place

Self Cite

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“…For example, we showed that neighborhood greenness levels seem to affect the social landscape of neighborhoods. In this sense, designing city expansions should prioritize high levels of greenery, something that is also linked to physical and mental health [11]. We also showed that areas with a low land-use mix have different socio-economic characteristics than high land-use mix areas.…”

Section: Discussionmentioning

confidence: 70%

Do Neighborhoods with Highly Diverse Built Environment Exhibit Different Socio-Economic Profiles as Well? Evidence from Shanghai

2021

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The link between the built environment and residential segregation has long been of interest to the discussion for sustainable and socially resilient cities. However, direct assessments on how extensively diverse built environments affect the social landscapes of cities at the neighborhood level are rare. Here, we investigate whether neighborhoods with a diverse built environment also exhibit different socio-economic profiles. Through a geodemographic approach, we scrutinize the socio-economic composition of Shanghai’s neighborhoods. We statistically compare the top 10% (very high values) to the bottom 10% (very low values) of the following built environment variables: density, land use mix, land use balance, and greenness. We show that high-density areas have three times the percentage of divorced residents than low-density areas. Neighborhoods with a high level of greenness have median values of 30% more residents aged between 25–44 years old and five times the percentage of houses between 60 to 119 m2 than low-greenness areas. In high land-use mix areas, the share of people that live on a pension is 30% more than the low land-use mix areas. The findings of this study can be used to improve the designs of modern, sustainable cities at the neighborhood level, significantly improving quality of life.

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“…We found a noticeable protective effect of greenery on PD in provinces than in metropolitan cities. Aside from Parkinson’s disease, for which no previous research has been done, various studies have looked into the relationship between urbanity and cancer mortality [ 37 ], general health [ 38 ], hypertension [ 39 ], and cardiovascular mortality [ 40 ]. Research on cancer mortality [ 37 ] and general health [ 38 ] indicated a stronger effect of residential greenness in urban areas than in rural regions, whereas studies on hypertension [ 39 ] and cardiovascular mortality [ 40 ] found a stronger effect of residential greenness in rural areas.…”

Section: Discussionmentioning

confidence: 99%

“…Aside from Parkinson’s disease, for which no previous research has been done, various studies have looked into the relationship between urbanity and cancer mortality [ 37 ], general health [ 38 ], hypertension [ 39 ], and cardiovascular mortality [ 40 ]. Research on cancer mortality [ 37 ] and general health [ 38 ] indicated a stronger effect of residential greenness in urban areas than in rural regions, whereas studies on hypertension [ 39 ] and cardiovascular mortality [ 40 ] found a stronger effect of residential greenness in rural areas. The possible urban–rural differences can be explained by several factors, including the amount of residential greenness [ 41 ], accessibility to green space [ 42 ], types of vegetation, and structure of green space [ 43 ], which need to be validated in further research.…”

Section: Discussionmentioning

confidence: 99%

Association between Residential Greenness and Incidence of Parkinson’s Disease: A Population-Based Cohort Study in South Korea

Jung

Park

Myung

et al. 2022

IJERPH

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It is widely known that exposure to residential greenness is beneficial for health. However, few studies have analyzed the association between greenery and Parkinson’s disease (PD). We selected 313,355 participants who matched the inclusion criteria from the National Health Insurance Service-National Sample Cohort, followed up from 2007 to 2015. Residential greenness, represented by the normalized difference vegetation index (NDVI), was obtained from satellite measurements. We estimated hazard ratios of PD associated with a 0.1-unit increase in long-term greenness exposure at the district level for the previous 1 year of each year until a censoring/event occurred, using time-varying Cox proportional hazard models, adjusted for individual- and area-level characteristics. During the 2,745,389 person-years of follow-up, 2621(0.8%) participants developed PD. Exposure to higher levels of residential greenness was found to be associated with a decreased risk of PD incidence (21% per 0.1-unit increase, 95% confidence interval (CI): 0.74–0.84). In subgroup analyses, stronger protective effects were observed in participants aged over 50 years, females, overweight/obese participants, non-urban residents, non-smokers, alcoholics, and those with comorbidities. Long-term exposure to greenness was beneficial to incident PD, and our findings could aid in the development of public-health strategies.

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Greenness-air pollution-physical activity-hypertension association among middle-aged and older adults: Evidence from urban and rural China

Cited by 57 publications

References 38 publications

Ranking the importance of demographic, socioeconomic, and underlying health factors on US COVID-19 deaths: A geographical random forest approach

Ranking the importance of demographic, socioeconomic, and underlying health factors on US COVID-19 deaths: A geographical random forest approach

Do Neighborhoods with Highly Diverse Built Environment Exhibit Different Socio-Economic Profiles as Well? Evidence from Shanghai

Association between Residential Greenness and Incidence of Parkinson’s Disease: A Population-Based Cohort Study in South Korea

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