Residential Green and Blue Spaces and Type 2 Diabetes Mellitus: A Population-Based Health Study in China

Residential environment and risk of chronic diseases: A prospective study

The impact of green-blue spaces on human health remains inconclusive, and the current understanding of disease spectrum associated with these spaces is still incomplete. We aimed to comprehensively investigate the relationship between residential environment and chronic diseases, while also examining the potential mediating role of air pollutants in these relationships. Using data from the UK Biobank, we created a residential environment score (RES) based on four types of green-blue spaces: natural environment, green space, domestic garden, and water area, with scores assigned according to the percentage of each space within a 300 m buffer. We also calculated an air pollution score derived from concentrations of NO2, NOx, PM2.5, PM2.5-10, and PM10. Employing logistic regression and Cox regression models, we analyzed the associations between RES and multisystem health outcomes among 502,490 participants at baseline. Our assessment identified 41 chronic diseases across 12 categories significantly related to RES increases (false-discovery-rate adjusted P-values < 0.01). Cox regression indicated that higher RES was associated with reduced risks for 18 diseases, excluding melanoma and bladder cancer. For the 21 unreported outcomes such as iron deficiency anemia and purpura, we observed hazard ratios (95 %CI) indicating lower risks for various conditions in the highest quartile of RES compared to the lowest. Furthermore, air pollution significantly mediated the relationship between RES and over 90 % of these chronic diseases. Residential environment with abundant green-blue spaces is linked to lower risks of most chronic diseases, which is partially mediated by diminished air pollutants and largely underestimated.

Associations of green and blue spaces with visual acuity in youths from Shandong Province, China: A large population-based study

While growing evidence highlights the benefits of green and blue spaces for physical and mental health, their combined effects on youth visual acuity remain unclear. This study aimed to evaluate the associations of green and blue spaces with visual acuity in youths. We analyzed data from the 2023 Common Disease and Health Risk Factors Surveillance and Intervention Program among students in Shandong Province, China. Generalized linear mixed-effects models were employed to investigate the independent associations of green and blue spaces with visual acuity in youths. To explore potential interactions, an interaction term for green and blue spaces was incorporated. Quantile g-computation (Qgcomp) models were applied to evaluate their combined effects. Compared to the lowest quartile, higher quartiles (Q2, Q3, and Q4) of the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized difference water index (NDWI), and modified normalized difference water index (MNDWI) were significantly associated with improved visual acuity in both eyes. Additionally, each 0.1 unit increase in NDVI500, EVI500, NDWI500, and MNDWI500 was associated with 0.008 (95 % confidence interval [CI]: 0.007, 0.010), 0.003 (0.002, 0.004), 0.054 (0.028, 0.080), and 0.010 (0.002, 0.018) improvements in right-eye visual acuity, with similar findings for the left eye. A significant interaction was observed between NDVI and NDWI (all P for interaction < 0.001), and combined exposure to green and blue spaces was positively associated with visual acuity (all P < 0.001). Furthermore, demographic and lifestyle factors modified the associations of blue and green spaces with visual acuity levels in youths. Greater exposure to green and blue spaces may benefit visual health in youths, with potential interactive and combined effects. Implementing policies to enhance the availability of green and blue spaces around schools may offer opportunities to alleviate visual impairment in youths.

Physical urban environment and cardiometabolic diseases in the five largest Bulgarian cities

This study investigated the associations between residential environmental characteristics and the prevalence of cardiometabolic diseases in the five largest Bulgarian cities. Representative cross-sectional survey data (N = 4640 adults) was collected in Sofia, Plovdiv, Varna, Burgas, and Ruse. Participants self-reported diagnosis or medication intake for hypertension, ischemic heart disease (IHD), stroke, and diabetes mellitus, as well as domestic burning of solid fuel and having a domestic garden. Residential addresses were linked to greenspace (overall vegetation level, tree cover, urban greenspace), bluespace, walkability, air pollution (NO2), and traffic noise (Lden). In the 300 m buffer, bluespace presence was inversely associated with hypertension (odds ratio [OR] = 0.67; 95% CI: 0.45, 1.00), IHD (OR = 0.45; 95% CI: 0.21, 0.99), and diabetes (OR = 0.51; 95% CI: 0.25, 1.04). Higher walkability and tree cover were inversely associated with hypertension (OR per 2 units = 0.85; 95% CI: 0.75, 0.96) and diabetes (OR per 10% = 0.77; 95% CI: 0.62, 0.97), respectively. These associations were stronger in larger buffers. Solid fuel burning was associated with IHD (OR = 1.63; 95% CI: 1.07, 2.50). There was an indication of a positive association between aircraft Lden and both stroke and IHD. The direction of the associations for domestic gardens, NO2, road traffic and railway Lden was counterintuitive. We detected some nonlinear associations. In conclusion, people living in urban neighborhoods that were more walkable, closer to bluespace, and greener had lower prevalence of cardiometabolic diseases, while solid fuel burning was associated with higher odds of cardiovascular diseases. Unexpected associations with some exposures may be due to unaccounted for urban fabric characteristics. This study is among the first assessing an understudied region in Southeastern Europe. Its findings have the potential to inform public discourse and provide evidence to support the implementation of urban design conducive to cardiometabolic health.

Simulating the impact of greenspace exposure on metabolic biomarkers in a diverse population living in San Diego, California: A g-computation application

Introduction

Growing evidence exists that greenspace exposure can reduce metabolic syndrome risk, a growing public health concern with well-documented inequities across population subgroups. We capitalize on the use of g-computation to simulate the influence of multiple possible interventions on residential greenspace on nine metabolic biomarkers and metabolic syndrome in adults (N = 555) from the 2014-2017 Community of Mine Study living in San Diego County, California.

Methods

Normalized difference vegetation index (NDVI) exposure from 2017 was averaged across a 400-m buffer around the participants' residential addresses. Participants' fasting plasma glucose, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglyceride concentrations, systolic and diastolic blood pressure, hemoglobin A1c (%), waist circumference, and metabolic syndrome were assessed as outcomes of interest. Using parametric g-computation, we calculated risk differences for participants being exposed to each decile of the participant NDVI distribution compared to minimum NDVI. Differential health impacts from NDVI exposure by sex, ethnicity, income, and age were examined.

Results

We found that a hypothetical increase in NDVI exposure led to a decrease in hemoglobin A1c (%), glucose, and high-density lipoprotein cholesterol concentrations, an increase in fasting total cholesterol, low-density lipoprotein cholesterol, and triglyceride concentrations, and minimal changes to systolic and diastolic blood pressure, waist circumference, and metabolic syndrome. The impact of NDVI changes was greater in women, Hispanic individuals, and those under 65 years old.

Conclusions

G-computation helps to simulate the potential health benefits of differential NDVI exposure and identifies which subpopulations can benefit most from targeted interventions aimed at minimizing health disparities.

Association of greenspaces exposure with cardiometabolic risk factors: a systematic review and meta-analysis

BACKGROUND

Cardiometabolic conditions are major contributors to the global burden of disease. An emerging body of evidence has associated access to and surrounding public open spaces (POS) and greenspace with cardiometabolic risk factors, including obesity, body mass index (BMI), hypertension (HTN), blood glucose (BG), and lipid profiles. This systematic review aimed to synthesize this evidence.

METHODS

This systematic review was conducted based on the PRISMA guidelines. Four electronic databases including Web of Science, PubMed, Scopus, and Google Scholar were searched for eligible articles published until July 2023. All observational studies which assessed the association of greenspace and POS with cardiometabolic risk factors including obesity, BMI, HTN, BG, and lipid profiles were included and reviewed by two authors independently. Heterogeneity between studies was assessed using the I2 index and Cochrane's Q test. Random/fixed effect meta-analyses were used to combine the association between greenspace exposure with cardiometabolic risk factors.

RESULTS

Overall, 118 relevant articles were included in our review. The majority of the articles were conducted in North America or Europe. In qualitative synthesis, access or proximity to greenspaces or POS impacts BMI and blood pressure or HTN, BG, and lipid profiles via various mechanisms. According to the random effect meta-analysis, more access to greenspace was significantly associated with lower odds of HTN (odds ratio (OR): 0.81, 95% confidence intervals (CIs): 0.61-0.99), obesity (OR: 0.83, 95% CIs: 0.77-0.90), and diabetes (OR:0.79, 95% CI: 0.67,0.90).

CONCLUSIONS

Findings of this systematic review and meta-analysis suggested that greenspace accessibility is associated with some cardiometabolic risk factors. Improving greenspace accessibility could be considered as one of the main strategies to reduce cardiometabolic risk factors at population level.

Unveiling causal connections: Long-term particulate matter exposure and type 2 diabetes mellitus mortality in Southern China

Evidence of the potential causal links between long-term exposure to particulate matters (PM, i.e., PM1, PM2.5, and PM1-2.5) and T2DM mortality based on large cohorts is limited. In contrast, the existing evidence usually suffers from inherent bias with the traditional association assessment. A prospective cohort of 580,757 participants in the southern region of China were recruited during 2009 and 2015 and followed up through December 2020. PM exposure at each residential address was estimated by linking to the well-established high-resolution simulation dataset. Hazard ratios (HRs) were calculated using time-varying marginal structural Cox models, an established causal inference approach, after adjusting for potential confounders. During follow-up, a total of 717 subjects died from T2DM. For every 1 μg/m3 increase in PM2.5, the adjusted HRs and 95% confidence interval (CI) for T2DM mortality was 1.036 (1.019-1.053). Similarly, for every 1 μg/m3 increase in PM1 and PM1-2.5, the adjusted HRs and 95% CIs were 1.032 (1.003-1.062) and 1.085 (1.054-1.116), respectively. Additionally, we observed a generally more pronounced impact among individuals with lower levels of education or lower residential greenness which as measured by the Normalized Difference Vegetation Index (NDVI). We identified substantial interactions between NDVI and PM1 (P-interaction = 0.003), NDVI and PM2.5 (P-interaction = 0.019), as well as education levels and PM1 (P-interaction = 0.049). The study emphasizes the need to consider environmental and socio-economic factors in strategies to reduce T2DM mortality. We found that PM1, PM2.5, and PM1-2.5 heighten the peril of T2DM mortality, with education and green space exposure roles in modifying it.

Lower regional urbanicity and socioeconomic status attenuate associations of green spaces with hypertension and diabetes mellitus: a national representative cross-sectional study in China

BACKGROUND

High blood pressure (HBP) and diabetes mellitus (DM) are two of the most prevalent cardiometabolic disorders globally, especially among individuals with lower socio-economic status (SES). Studies have linked residential greenness to decreased risks of HBP and DM. However, there has been limited evidence on whether SES may modify the associations of residential greenness with HBP and DM.

METHODS

Based on a national representative cross-sectional study among 44,876 adults, we generated the normalized difference vegetation index (NDVI) at 1 km spatial resolution to characterize individuals' residential greenness level. Administrative classification (urban/rural), nighttime light index (NLI), individual income, and educational levels were used to characterize regional urbanicity and individual SES levels.

RESULTS

We observed weaker inverse associations of NDVI with HBP and DM in rural regions compared to urban regions. For instance, along with per interquartile range (IQR, 0.26) increment in residential NDVI at 0∼5 year moving averages, the ORs of HBP were 1.04 (95%CI: 0.94, 1.15) in rural regions and 0.85 (95%CI: 0.79, 0.93) in urban regions (P = 0.003). Along with the decrease in NLI levels, there were continuously decreasing inverse associations of NDVI with DM prevalence (P for interaction <0.001). In addition, weaker inverse associations of residential NDVI with HBP and DM prevalence were found among individuals with lower income and lower education levels compared to their counterparts.

CONCLUSIONS

Lower regional urbanicity and individual SES could attenuate the associations of residential greenness with odds of HBP and DM prevalence.

Beneficial associations between outdoor visible greenness at the workplace and metabolic syndrome in Chinese adults

BACKGROUND

Greenness surrounding residential places has been found to significantly reduce the risk of diseases such as hypertension, obesity, and metabolic syndrome (MetS). However, it is unclear whether visible greenness exposure at the workplace has any impact on the risk of MetS.

METHODS

Visible greenness exposure was assessed using a Green View Index (GVI) based on street view images through a convolutional neural network model. We utilized logistic regression to examine the cross-sectional association between GVI and MetS as well as its components among 51,552 adults aged 18-60 in the city of Hangzhou, China, from January 2018 to December 2021. Stratified analyses were conducted by age and sex groups. Furthermore, a scenario analysis was conducted to investigate the risks of having MetS among adults in different GVI scenarios.

RESULTS

The mean age of the participants was 40.1, and 38.5% were women. We found a statistically significant association between GVI and having MetS. Compared to the lowest quartile of GVI, participants in the highest quartile of GVI had a 17% (95% CI: 11-23%) lower odds of having MetS. The protective association was stronger in the males, but we did not observe such differences in different age groups. Furthermore, we found inverse associations between GVI and the odds of hypertension, low high-density lipoprotein cholesterol, obesity, and high levels of FPG.

CONCLUSIONS

Higher exposure to outdoor visible greenness in the workplace environment might have a protective effect against MetS.

Association of land urbanization and type 2 diabetes mellitus prevalence and mediation of greenness and physical activity in Chinese adults

The prevalence of type 2 diabetes (T2D) is higher in urban than in rural areas. Limited information is available on the association between T2D and Land urbanization (LU) while LU influences not only greenness and Particulate Matter 2.5 (PM2.5) but also inhabitant behavior. We aimed to explore the association between the LU level and T2D prevalence, as well as whether greenness, PM2.5, or conscious physical activity mediated any of the observed associations. This study encompassed 27,633 adult participants from Shandong Province who completed the sixth National Health Service Survey in 2018. Ambient LU exposure was estimated by spatial characteristics, including the existing impervious surface area (ISA), road density (RD), and annual night light (NL). Exposures were estimated using satellite images and OpenStreetMap, with 1000 m used as the main analysis buffer. Two-level logistic regression models were used to investigate the association between the LU metrics and T2D. Additionally, we explored potential mechanisms of the association through mediation analysis. The prevalence of T2D among participants was 5.14%, with average exposures to ISA_1000m of 1.441 km2, RD_1000m of 3.856 km/km2, and NL_1000m of 9.821 nW/cm2/sr. Higher levels of LU exposure were associated with higher T2D ORs [for each interquartile of ISA_1000m, RD_1000m, and NL_1000m, the adjusted OR (95% CI) for the T2D prevalence were 1.29 (1.19-1.4), 1.25 (1.15-1.36), and 1.25 (1.15-1.36), respectively]. This relationship persisted in several sensitivity analyses including use of different buffer sizes. We observed stronger associations among participants younger than 65 years or in men. Greenness mediated a 20.78%-65.36% of the estimated associations, conscious physical activity mediated a 10.35%-15.85%, while PM2.5 mediated insignificantly. These results suggest a deleterious association between higher levels of LU and T2D among adult residents in a developing country. Greenness and conscious physical activity mediate the association.

The neighbourhood environment and profiles of the metabolic syndrome

BACKGROUND

There is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components.

METHODS

We used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO₂ and PM_2.5 were estimated using satellite-based land-use regression models. Latent class analysis (LCA) identified homogenous groups (latent classes) of participants based on MetS components data. Participants were then classified into five metabolic profiles according to their MetS-components latent class and MetS status. Generalised additive mixed models were used to estimate relationships of environmental attributes with MetS status and metabolic profiles.

RESULTS

LCA yielded three latent classes, one including only participants without MetS ("Lower probability of MetS components" profile). The other two classes/profiles, consisting of participants with and without MetS, were "Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure" and "Higher probability of MetS components". Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO₂ were associated with the odds of membership to healthier metabolic profiles without MetS, while annual average concentration of PM_2.5 was associated with unhealthier metabolic profiles with MetS.

CONCLUSIONS

This study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components.

Using an Exposome-Wide Approach to Explore the Impact of Urban Environments on Blood Pressure among Adults in Beijing-Tianjin-Hebei and Surrounding Areas of China

Existing studies mostly explored the association between urban environmental exposures and blood pressure (BP) in isolation, ignoring correlations across exposures. This study aimed to systematically evaluate the impact of a wide range of urban exposures on BP using an exposome-wide approach. A multicenter cross-sectional study was conducted in ten cities of China. For each enrolled participant, we estimated their urban exposures, including air pollution, built environment, surrounding natural space, and road traffic indicator. On the whole, this study comprised three statistical analysis steps, that is, single exposure analysis, multiple exposure analysis and a cluster analysis. We also used deletion-substitution-addition algorithm to conduct variable selection. After considering multiple exposures, for hypertension risk, most significant associations in single exposure model disappeared, with only neighborhood walkability remaining negatively statistically significant. Besides, it was observed that SBP (systolic BP) raised gradually with the increase in PM_2.5, but such rising pattern slowed down when PM_2.5 concentration reached a relatively high level. For surrounding natural spaces, significant protective associations between green and blue spaces with BP were found. This study also found that high population density and public transport accessibility have beneficially significant association with BP. Additionally, with the increase in the distance to the nearest major road, DBP (diastolic BP) decreased rapidly. When the distance was beyond around 200 m, however, there was no obvious change to DBP anymore. By cluster analysis, six clusters of urban exposures were identified. These findings reinforce the importance of improving urban design, which help promote healthy urban environments to optimize human BP health.

Residential greenness is associated with disease severity among COVID-19 patients aged over 45 years in Wuhan, China

Evidence regarding environmental factors associated with disease severity of COVID-19 remained scarce. This study aimed to investigate the association of residential greenness exposure with COVID-19 severity applying a retrospective cross-sectional study in Wuhan, China. We included 30,253 COVID-19 cases aged over 45 years from January 1 to February 27, 2020. Residential greenness was quantitatively assessed using normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). A multilevel generalized linear model using Poisson regression was implemented to analyze the association between greenness exposure and disease severity of COVID-19, after adjusting for potential covariates. A linear exposure-response relationship was found between greenness and COVID-19 severity. In the adjusted model, one 0.1 unit increase of NDVI and EVI in the 1000-m buffer radius was significantly associated with a 7.6% (95% confidence interval (CI): 4.0%, 11.1%) and 10.0% (95% CI: 5.1%, 14.7%) reduction of the prevalence of COVID-19 severity, respectively. The effect of residential greenness seemed to be more pronounced among participants with lower population density and economic levels. Air pollutants mediated 0.82~12.08% of the greenness and COVID-19 severity association, particularly to nitrogen dioxide. Sensitivity analyses suggested the robustness of the results. Our findings suggested that residential greenness exposure was beneficial to reduce the prevalence of COVID-19 severity.

A negative association between prevalence of diabetes and urban residential area greenness detected in nationwide assessment of urban Bangladesh

Residential area greenness may influence diabetes, but limited studies have explored this relationship in developing countries. This study assessed the association between residential area greenness and diabetes among urban adults in Bangladesh. The mediation effect of the body mass index (BMI) was also assessed. A total of 2367 adults aged ≥ 35 years were extracted from a nationally representative survey. Diabetes was characterised as fasting plasma glucose level be ≥ 7.0 mmol/L or taking prescribed medications to reduce blood sugar level. Residential area greenness was estimated by enhanced vegetation index. Binary logistic regression models were employed to estimate the association between residential area greenness and diabetes adjusting for sociodemographic factors. Mediation analysis was performed to assess whether BMI mediated the association between greenness and diabetes. Greater area greenness was associated with lower odds of diabetes (adjusted odds ratio 0.805, 95% confidence interval 0.693–0.935, p = 0.0052). BMI significantly mediated 36.4% of the estimated association between greenness and diabetes. Presence of areas of greenness adjacent to living area tends to be associated with lower diabetes prevalence. Findings emphasised the importance of preserving the local environment to tackle the growing diabetes prevalence in Bangladesh.

Microbiota and epigenetics: promising therapeutic approaches?

The direct/indirect responsibility of the gut microbiome in disease induction in and outside the digestive tract is well studied. These results are usually from the overpopulation of certain species on the cost of others, interaction with beneficial microflora, interference with normal epigenetic control mechanisms, or suppression of the immune system. Consequently, it is theoretically possible to cure such disorders by rebalancing the microbiome inside our bodies. This can be achieved by changing the lifestyle pattern and diet or by supplementation with beneficial bacteria or their metabolites. Various approaches have been explored to manipulate the normal microbial inhabitants, including nutraceutical, supplementations with prebiotics, probiotics, postbiotics, synbiotics, and antibiotics, or through microbiome transplantation (fecal, skin, or vaginal microbiome transplantation). In the present review, the interaction between the microbiome and epigenetics and their role in disease induction is discussed. Possible future therapeutic approaches via the reestablishment of equilibrium in our internal micro-ecosystem are also highlighted.