Association between residential greenness and overweight/obesity among rural adults in northwestern China

Associations between residential greenness and obesity phenotypes among adults in Southwest China

BACKGROUND

Although exposure to greenness has generally benefited human metabolic health, the association between greenness exposure and metabolic obesity remains poorly studied. We aimed to investigate the associations between residential greenness and obesity phenotypes and the mediation effects of air pollutants and physical activity (PA) level on the associations.

METHODS

We used the baseline of the China Multi-Ethnic Cohort (CMEC) study, which enrolled 87,613 adults. Obesity phenotypes were defined based on obesity and metabolic status, including metabolically unhealthy obesity (MUO), non-obesity (MUNO), metabolically healthy obesity (MHO), and non-obesity (MHNO). Greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 500-m buffer zones around the participants' residence. Multivariable logistic regression was used to estimate the associations between greenness and obesity phenotypes. Stratified analyses by age, sex, educational level, and urbanicity were performed to identify how the effect varies across different subgroups. Causal mediation analysis was used to examine the mediation effects of air pollutants and PA level.

RESULTS

Compared with MHNO, each interquartile range (IQR) increase in greenness exposure was associated with reduced risks of MHO (ORNDVI [95% CI] = 0.87 [0.81, 0.93]; OREVI = 0.91 [0.86, 0.97]), MUO (ORNDVI = 0.83 [0.78, 0.88]; OREVI = 0.86 [0.81, 0.91]), and MUNO (ORNDVI = 0.88 [0.84, 0.91]; OREVI = 0.89 [0.86, 0.92]). For each IQR increase in both NDVI and EVI, the risks of MHO, MUO, and MUNO were reduced more in men, participants over 60 years, those with a higher level of education, and those living in urban areas, compared to their counterparts. Concentrations of particulate matter (PM) and PA level partially mediated the associations between greenness exposure and obesity phenotypes.

CONCLUSIONS

Exposure to residential greenness was associated with decreased risks of MHO, MUO, and MUNO, which was mediated by concentrations of PM and PA level, and modified by sex, age, educational level, and urbanicity.

Associations of the neighbourhood built and natural environment with cardiometabolic health indicators: A cross-sectional analysis of environmental moderators and behavioural mediators

BACKGROUND

Most studies examining the effects of neighbourhood urban design on cardiometabolic health focused solely on the built or natural environment. Also, they did not consider the roles of neighbourhood socio-economic status (SES) and ambient air pollution in the observed associations, and the extent to which these associations were mediated by physical activity and sedentary behaviours.

METHODS

We used data from the AusDiab3 study (N = 4141), a national cohort study of Australian adults to address the above-mentioned knowledge gaps. Spatial data were used to compute indices of neighbourhood walkability (population density, intersection density, non-commercial land use mix, commercial land use), natural environment (parkland and blue spaces) and air pollution (annual average concentrations of nitrogen dioxide (NO2) and fine particulate matter <2.5 μm in diameter (PM2.5)). Census indices were used to define neighbourhood SES. Clinical assessments collected data on adiposity, blood pressure, blood glucose and blood lipids. Generalised additive mixed models were used to estimate associations.

RESULTS

Neighbourhood walkability showed indirect beneficial associations with most indicators of cardiometabolic health via resistance training, walking and sitting for different purposes; indirect detrimental associations with the same indicators via vigorous gardening; and direct detrimental associations with blood pressure. The neighbourhood natural environment had beneficial indirect associations with most cardiometabolic health indicators via resistance training and leisure-time sitting, and beneficial direct associations with adiposity and blood lipids. Neighbourhood SES and air pollution moderated only a few associations of the neighbourhood environment with physical activity, blood lipids and blood pressure.

CONCLUSIONS

Within a low-density and low-pollution context, denser, walkable neighbourhoods with good access to nature may benefit residents' cardiometabolic health by facilitating the adoption of an active lifestyle. Possible disadvantages of living in denser neighbourhoods for older populations are having limited opportunities for gardening, higher levels of noise and less healthy dietary patterns associated with eating out.

The combined effects of exposure to multiple PM2.5 components on overweight and obesity in middle-aged and older adults: a nationwide cohort study from 125 cities in China

The prevalence of overweight or obesity increased rapidly over the past decades in most countries, including China. However, little evidence exists about the effects of long-term exposure to PM2.5 components on overweight or obesity, particularly in developing countries. We measured different weight stages according to body mass index (BMI), and investigated the effects of exposure to PM2.5 components (ammonium [[Formula: see text]], sulfate [[Formula: see text]], nitrate [[Formula: see text]], black carbon and organic matter) on different BMI levels in middle-aged and elderly people of China. Our study explored the effects of single and multiple air pollution exposures on overweight and obesity by using the Generalized Linear Model and Quantile g-Computation model (QgC). This study found a significantly positive association between five PM2.5 components and overweight/obesity. In the QgC model, there was still a positive association between multiple exposure to PM2.5 components and overweight when all PM2.5 components were considered as a whole. In addition, males, the elderly, and urban residents were also more sensitive to five PM2.5 components.

A short history from Karelia study to biodiversity and public health interventions

Contact with natural environments enriches the human microbiome, promotes immune balance and protects against allergies and inflammatory disorders. In Finland, the allergy &amp; asthma epidemic became slowly visible in mid 1960s. After the World War II, Karelia was split into Finnish and Soviet Union (now Russia) territories. This led to more marked environmental and lifestyle changes in the Finnish compared with Russian Karelia. The Karelia Allergy Study 2002–2022 showed that allergic conditions were much more common on the Finnish side. The Russians had richer gene-microbe network and interaction than the Finns, which associated with better balanced immune regulatory circuits and lower allergy prevalence. In the Finnish adolescents, a biodiverse natural environment around the homes associated with lower occurrence of allergies. Overall, the plausible explanation of the allergy disparity was the prominent change in environment and lifestyle in the Finnish Karelia from 1940s to 1980s. The nationwide Finnish Allergy Programme 2008–2018 implemented the biodiversity hypothesis into practice by endorsing immune tolerance, nature contacts, and allergy health with favorable results. A regional health and environment programme, Nature Step to Health 2022–2032, has been initiated in the City of Lahti, EU Green Capital 2021. The programme integrates prevention of chronic diseases (asthma, diabetes, obesity, depression), nature loss, and climate crisis in the spirit of Planetary Health. Allergic diseases exemplify inappropriate immunological responses to natural environment. Successful management of the epidemics of allergy and other non-communicable diseases may pave the way to improve human and environmental health.

Residential greenness and air pollution concerning excessive gestational weight gain during pregnancy: A cross-sectional study in Wuhan, China

BACKGROUND

Previous studies have indicated that exposure to residential greenness may benefit the health status of pregnant women, and air pollution may exert a mediating effect. Gestational weight gain (GWG) is an important indicator of pregnant women and fetuses' health and nutrition status. However, evidence concerning the impact of residential greenness on excessive gestational weight gain (EGWG) is scarce, and to what extent air pollution in urban settings mediates this relationship remains unclear.

OBJECTIVE

This study aims to explore the association of residential greenness with EGWG, consider the mediating effect of air pollution, and estimate the combined impact of residential greenness and air pollution exposures on EGWG.

METHOD

This population-based cross-sectional study involved 51,507 pregnant women with individual-level data on residential addresses in the Wuhan Maternal and Child Health Management Information System. Two spectral indexes, the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI), were used to proxy residential greenness. The air pollution data included six indicators (PM_2.5, PM₁₀, SO₂, CO, NO₂, O₃) and used the Ordinary Kriging interpolation method to estimate overall pregnancy exposure to air pollutants. Generalized linear mixed regression models were utilized to explore the relationship between residential greenness and EGWG. Restricted cubic spline (RCS) models were developed to examine the dose-response relationships. Mediation analyses explored the potential mediating role of air pollution in the residential greenness-EGWG associations. Finally, the weighted-quantile-sum (WQS) regression model was used to investigate the association between residential greenness-air pollutants co-exposure and EGWG.

RESULT

Among all participants, 26,442 had EGWG. In the adjusted model, the negative association was found significant for NDVI_100-m, NDVI_200-m, and NDVI_500-m with EGWG. For example, each IQR increase in NDVI_100-m was associated with 2.8% (95% CI: 0.6-5.0) lower odds for EGWG. The result of WQS regression showed that, when considering the six air pollutants and NDVI_-100m together, both positive and negative WQS indices were significantly associated with EGWG, PM₁₀, PM_2.5, with SO₂ having significant weights in the positive effect direction and CO, O₃, NO₂, and NDVI_100-m having a negative effect. Our results also suggested that SO₂, NO₂, PM₁₀, PM_2.5, and CO significantly mediated the association between NDVI_-100m and EGWG, and our estimates were generally robust in the sensitivity analysis.

CONCLUSION

Exposure to a higher level of residential greenness is associated with a reduced risk of EGWG, in which air pollution may exert a mediating effect. Pregnant women might benefit more in gaining healthy gestational weight when greenness levels increase from low to medium than from medium to high. Given the current cross-sectional study design, large-sale prospective cohort studies are needed to confirm our findings further.

The role of residential greenness levels, green land cover types and diversity in overweight/obesity among older adults: A cohort study

BACKGROUND

Few studies have investigated the effects of greenness exposure, green land cover types and diversity and their interaction with particulate matter (PM) to adiposity.

METHOD

Cohort data were collected from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Baseline data on greenness levels, green land cover types and diversity were assessed by the Normalized Difference Vegetation Index (NDVI), three greenery types (trees, shrublands and grassland) and Shannon's diversity index, respectively. Body mass index (BMI) and waist circumference (WC) were separately used as dependent variables and represented for peripheral overweight/obesity and central obesity, respectively. The mixed Cox model with random intercept was used to estimate the effects of greenness levels, types and diversity on overweight/obesity using single and multiple exposure models. We also examined the interaction of PM and the aforementioned indicators on overweight/obesity on both additive and multiplicative scales.

RESULTS

Single exposure models showed that higher levels of residential greenness, tree coverage and ratio of trees to shrublands/grassland were inversely associated with peripheral overweight/obesity and central obesity. An increase in shrublands, grassland and diversity of green was related to lower odds of peripheral overweight/obesity. Multiple exposure models confirmed the association between greenness levels and peripheral overweight/obesity. Males, educated participants and elderly who lived in southern regions and areas with cleaner air environments acquired more benefits from greenspace exposure. Single and multiple exposure models indicated that an antagonistic effect of increasing PM and decreasing greenness levels on peripheral overweight/obesity and central obesity. Single exposure models showed the potential interaction of tree coverage, ratio of trees to grassland and PM_2.5 exposures on the risk of peripheral overweight/obesity.

CONCLUSION

Increasing residential greenness and diversity of green were associated with healthy weight status. The relationship between greenery and overweight/obesity varied, and the effects of greenspace exposure on overweight/obesity were associated with air pollution.

Air pollution, greenness and risk of overweight among middle-aged and older adults: A cohort study in China

BACKGROUND

Exposure to air pollution may increase the risk of obesity, but living in greener space may reduce this risk. Epidemiological evidence, however, is inconsistent.

METHODS

Using data from the China Health and Retirement Longitudinal Study (2011-2015), we conducted a nationwide cohort study of 7424 adults. We measured overweight/obesity according to body mass index. We used annual average ground-level air pollutants, including ozone (O₃), nitrogen dioxide (NO2), and particulate matter with aerodynamic diameters ≤2.5 μm (PM_2.5), to demonstrate air pollution levels. We used the Normalized difference vegetation index (NDVI) to measure greenness exposure. We used time-varying Cox proportional hazard regression models to analyze the connections among air pollution, greenness, and the development of overweight/obesity in middle-aged and older adults in China. We also conducted mediation analyses to examine the mediating effects of air pollution.

RESULTS

We found that lower risk of overweight/obesity was associated with more greenness exposure and lower levels of air pollution. We identified that an interquartile increment in NDVI was correlated with a lower hazard ratio (HR) of becoming overweight or obese (HR = 0.806, 95% confidence interval [CI]: 0.754-0.862). Although a 10 μg/m³ increase in PM_2.5 and NO₂ was correlated with higher risks (HR = 1.049, 95% CI = 1.022-1.075, HR = 1.376, 95% CI = 1.264-1.499). Effects of PM_2.5 on being overweight or obese were stronger in men than in women. According to the mediation analysis, PM_2.5 and NO₂ mediated 8.85% and 19.22% of the association between greenness and being overweight or obese.

CONCLUSIONS

An increased risk of being overweight or obese in middle-aged and older adults in China was associated with long-term exposure to higher levels of PM_2.5 and NO₂. This risk was reduced through NDVI exposure, and the associations were partially mediated by air pollutants. To verify these findings, fine-scale studies are needed.

Association of decreases in PM2.5 levels due to the implementation of environmental protection policies with the incidence of obesity in adolescents: A prospective cohort study

AIMS

To explore the association between decreased levels of particulate matter (≤2.5 µm; PM_2.5) due to the implementation of environmental protection policies and the incidence of obesity in adolescents in Chongqing, China through a prospective cohort study.

METHODS

A total of 2105 children (52.02% male; aged 7.33 ± 0.60 years at baseline) were enrolled from the Chongqing Children's Health Cohort. A mixed linear regression model was used to analyse the relationships of PM_2.5 levels with obesity indicators after adjusting for covariates. Additionally, a Poisson regression model was used to determine the relationship between PM_2.5 exposure and the incidence of overweight/obesity.

RESULTS

The average PM_2.5 exposure levels from participant conception to 2014, from 2015 to 2017, and from 2018 to 2019 were 66.64 ± 5.33 μg/m³, 55.49 ± 3.78 μg/m³, and 42.50 ± 1.87 μg/m³, respectively; these levels significantly decreased over time (P < 0.001). Throughout the entire follow-up period, the incidence of overweight/obesity after a ≥ 25 μg/m³ decrease in the PM_2.5 level was 4.57% among females; this incidence was the lowest among females who experienced remarkable decreases in PM_2.5 exposure. A 1-µg/m³ decrease in the PM_2.5 level significantly decreased the body mass index (BMI), BMI z score (BMI_z), and weight of adolescents (all P < 0.001). Compared with a < 20-μg/m³ decrease in the PM_2.5 level, a ≥ 25-μg/m³ decrease protected against increased BMI (net difference= -0.93; 95% confidence interval [CI]: (-1.23,-0.63) kg/m²), BMI_z (-0.28 (-0.39, -0.17)), weight (-1.59 (-2.44, -0.74) kg), and incidence of overweight/obesity (0.48 (0.37, 0.62), P < 0.001). Moreover, compared with a < 20-μg/m³ decrease in the PM_2.5 level, a ≥ 25-μg/m³ decrease resulted in significant absolute differences in BMI (-1.26 (-1.56, -0.96) kg/m²), BMI_z (-0.53 (-0.65, -0.40)) and weight (-3.01 (-3.8, -2.19) kg) (all P < 0.001).

CONCLUSIONS

This study showed the etiological relevance of declining PM_2.5 concentrations for the incidence of obesity in children and adolescents, suggesting that controlling ambient air pollutants may prevent the development of obesity in this age group. Continuous implementation of environmental protection policies in China has led to substantial health benefits.

Living near greenness is associated with higher bone strength: A large cross-sectional epidemiological study in China

BACKGROUND

Living near green spaces may benefit various health outcomes. However, no studies have investigated the greenness-bone linkage in the general population. Moreover, to which extent ambient air pollution (AAP), physical activity (PA), and body mass index (BMI) mediate this relationship remains unclear. We aimed to explore the association between greenness and bone strength and the potential mediating roles of AAP, PA, and BMI in Chinese adults.

METHODS

This cross-sectional analysis enrolled 66,053 adults from the China Multi-Ethnic Cohort in 2018-2019. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were employed to define residential greenness. The calcaneus quantitative ultrasound index (QUI) was used to indicate bone strength. Multiple linear regression models and mediation analyses were used to estimate the residential greenness-bone strength association and potential pathways operating through AAP (represented by PM_2.5 [particulate matter <2.5 μm in diameter]), PA, and BMI. Stratification analyses were performed to identify susceptible populations.

RESULTS

Higher residential exposure to greenness was significantly associated with an increase in QUI, with changes (95% confidence interval) of 3.28 (3.05, 3.50), 3.57 (3.34, 3.80), 2.68 (2.46, 2.90), and 2.93 (2.71, 3.15) for every interquartile range increase in NDVI_500m, NDVI_1000m, EVI_500m, and EVI_1000m, respectively. Sex, urbanicity, annual family income, smoking, and drinking significantly modified the association of greenness-bone strength, with more remarkable associations in males, urban residents, subjects from wealthier families, smokers, and drinkers. For the NDVI_500m/EVI_500m-QUI relationship, the positive mediating roles of PM_2.5 and PA were 6.70%/8.50 and 2.43%/2.69%, respectively, whereas those negative for BMI and PA-BMI were 0.88%/1.06% and 0.05%/0.05%, respectively.

CONCLUSION

Living in a greener area may predict higher bone strength, particularly among males, urban residents, wealthier people, smokers, and drinkers. AAP, PA, BMI, and other factors may partially mediate the positive association. Our findings underscore the importance of optimizing greenness planning and management policies.