Effect of long-term exposure to PM2.5 on the risk of type 2 diabetes and arthritis in type 2 diabetes patients: Evidence from a national cohort in China

Synergistic effects of air pollution and artificial light at night on diabetes risk: A prospective cohort study

Previous studies have indicated associations between air pollutants, outdoor artificial light at night (ALAN) exposure, and diabetes risk, but their interactive effects remain insufficiently validated. Based on data from two large Chinese cohorts (CHARLS and CFPS) with 28,903 participants followed for 3 years (2013-2018), we employed Cox proportional hazards regression models to evaluate the associations of pollutants and outdoor ALAN with diabetes incidence risk and their interactions, along with stratified analyses. Results demonstrated significant linear relationships between PM1 and PM2.5 concentrations and diabetes risk. Each 10 μg/m3 increase in PM1 and PM2.5 was associated with hazard ratios (HRs) of 1.065 (95 % CI: 1.061-1.069) and 1.036 (95 % CI: 1.034-1.038), respectively. Other pollutants (SO2, NO2, and CO) and outdoor ALAN exposure showed non-linear associations with diabetes risk, with each standard deviation increase in outdoor ALAN exposure associated with an HR of 1.004 (95 % CI: 1.001-1.007). Furthermore, co-exposure to PM1, PM2.5, PM10, and SO2 with outdoor ALAN demonstrated significant additive effects. Stratified analyses revealed significantly higher diabetes risks among individuals aged ≥65 years and unmarried populations. Regional differences showed higher pollutant susceptibility among northern residents, while southern residents demonstrated greater sensitivity to outdoor ALAN exposure. This study revealed for the first time significant synergistic effects between environmental pollutants and outdoor ALAN exposure on diabetes risk, highlighting the importance of environmental and light pollution in diabetes prevention and control, and providing theoretical basis for future policy development.

Associations between long-term exposure to ultrafine particles and type 2 diabetes: A large-scale, multicenter study in China

Few studies have examined the associations between long-term exposure to ultrafine particles (UFP) and type 2 diabetes (T2DM). This study aimed to investigate the impact of long-term UFP exposure on diabetes prevalence and stages, as well as glycemic markers, using data from a large multi-center cohort collected from 2017 to 2021. The health outcomes assessed included diabetes prevalence and stages (normoglycemia, prediabetes, and diabetes), as well as glycemic markers, i.e., fasting blood glucose (FPG) and glycated hemoglobin (HbA1c). The three-year average UFP concentration prior to baseline was used as the long-term UFP exposure level. This cross-sectional study included 93,990 participants, with a diabetes prevalence of 10.97 %. An interquartile range increase in UFP was significantly associated with diabetes prevalence and stages, with ORs of 1.20 (95 % CI: 1.14, 1.26) and 1.11 (95 % CI: 1.07, 1.44), respectively. Specifically, for comparison between normoglycemia and prediabetes, and between prediabetes and diabetes, the corresponding ORs were 1.01 (95 % CI: 0.96, 1.04) and 1.24 (95 % CI: 1.17, 1.31), respectively. UFP exposure was also significantly associated with elevated levels of FPG and HbA1c. These findings suggest that long-term UFP exposure may be a potential risk factor for diabetes with larger risks in the prediabetes population.

Causal association between PM2.5 and metabolic syndrome in the Chinese elderly population-insights from a cohort study of CHARLS

Existing evidence suggests that the components of metabolic syndrome (MS) are sensitive to PM2.5, especially in the elderly population, and related results targeting different regions and populations are inconsistent. This study aims to quantify the risk of association between PM2.5 and MS components in the elderly population, as well as the moderating effect of physical exercise (PE) for this association. Biochemical data, demographic data and health behavior data were obtained from CHARLS dataset in 2011 and 2015, and the individual information was matched to obtain the two-wave panel data. We match meteorological data by region to obtain population exposure indicators. Subsequently, the directed acyclic graphs was used to control confonding, then instrumental variable method and fixed effects model were employed to evaluate the causal relationship between PM2.5 and MS components and the moderating effect of PE. A total of 6125 individuals were included. The prevalence of MS was 34.5% and 32.9% in 2011 and 2015 respectively. The instrumental variable probit regression indicated that high concentration PM2.5 exposure (coefPM2.5 = 0.007, P < 0.001) may increase the risk of MS, and PM2.5 had a significant impact on the components of MS, with a positive impact on waist circumference (WC) (coef = 0.052, P < 0.001) and systolic blood pressure (SYS) (coef = 0.214, P < 0.001), and with a negative impact on high-density lipoprotein cholesterol (HDL-C) (coef = - 0.030, P = 0.021), Triglyceride (TG) (coef = - 0.275, P = 0.048) and diastolic blood pressure (DIA) (coef = - 0.030, P = 0.007). Specifically, for each 1 SD increase in PM2.5 exposure, HDL-C decreased by 0.57 mg/dL, TG decreased by 5.29 mg/dL, DIA decreased by 0.57 mmHg, waist circumference increased by 1.001 cm, and SYS increased by 4.11 mmHg. Additionally, low-intensity physical exercise may alleviate the effect of PM2.5 on WC and SYS, while the high intensity exercise may increase the effect of PM2.5 on WC. Exposure to PM2.5 is associated with the occurrence of MS in the elderly population, and has a significant impact on the components of MS in different directions. The moderating effect of physical activity on PM2.5 and MS varies by component. These results may provide scientific support for the prevention and treatment of MS in the elderly.

Long-term exposure to particulate air pollution associated with the progression of type 2 diabetes mellitus in China: effect size and urban-rural disparities

BACKGROUND

Recent Western studies link long-term particulate matter (PM) exposure to type 2 diabetes mellitus (T2DM) progression, but little is known for low- and middle-income countries. This study aimed to estimate the relationship between PM exposure and T2DM progression in China, and also assess urban-rural disparities.

METHODS

Using 7-year cohort data of 1.3 million Chinese over 40, a multistate model estimated the associations of PM exposure with T2DM progression. Covariates included demographics, socioeconomic status, health behaviors, medication, and meteorological factors. Sub-sample analyses were done for rural and urban areas.

RESULTS

For participants exposed to high levels of PM 2.5 , the 5-year absolute risks of developing T2DM and its complications were 4.31% (95% CI: 4.22-4.40) and 31.04% (95% CI: 29.97-32.08), respectively. In the low- PM 2.5 -exposure group, these risks were 3.82% (95% CI: 3.74-3.91) and 30.55% (95% CI: 29.43-31.65). For each 10 µg/m3 increase in PM 2.5 exposure, the HRs (95% CI) for the progression from no T2DM diagnosis to a T2DM diagnosis were 1.13 (1.13-1.14), and for the progression from T2DM to the development of T2DM complications were 1.04 (1.03-1.06). Moreover, the HRs (95% CI) for mortality risk were 1.09 (1.08-1.09) for participants without T2DM, 1.06 (1.00-1.14) for those with T2DM, and 1.10 (1.05-1.16) for those with T2DM complications. Similar associations were observed for other PM-related metrics. In rural areas, PM exposure was more strongly associated with the progression from T2DM and its complications to death. Conversely, in urban areas, PM exposure had a stronger association with the progression from a non-T2DM state to a formal T2DM diagnosis. Urban residents are exposed to higher levels of toxic components like heavy metals, potentially increasing T2DM risk, yet urban healthcare infrastructure offers protection against T2DM-related mortality.

CONCLUSIONS

PM exposure is significantly associated with T2DM progression. Urban areas should focus on primary prevention, while rural areas need to improve secondary and tertiary prevention like healthcare services.

Associations of prenatal exposure to fine particulate matter and its constituents with small for gestational age risk: A twin study in China

This study aimed to examine the impact of PM2.5 and its constituents on small for gestational age (SGA). We collected records of 8082 twin pairs and their mothers from 21 hospitals across China. Concentrations of PM2.5 and its constituents were from the Tracking Air Pollution dataset. Generalized linear models were utilized in this observational study to explore the relationship between SGA and PM2.5. An increase in PM2.5 by one interquartile range during pregnancy was linked to a 17 % increased SGA risk (OR = 1.17, 95 % CI: 1.05-1.31), with a population attributable fraction of 18.97 % (95 %CI: 5.65 %, 30.93 %). Additionally, higher risk of SGA was associated with exposure to ammonium (OR=1.17, 95 %CI: 1.03-1.34), sulfate (OR=1.10, 95 %CI: 1.01-1.21), nitrate (OR=1.16, 95 %CI: 1.02-1.33), black carbon (OR=1.09, 95 %CI: 1.00-1.19), and organic matter (OR=1.11, 95 %CI: 1.00-1.23) during pregnancy. Similar associations were observed for SGA with PM2.5 and its constituents in late pregnancy (all P < 0.05). Furthermore, individuals conceived via assisted reproduction (OR = 1.22, 95 % CI: 1.03-1.43), with pregnancy complications (OR = 1.23, 95 % CI: 1.07-1.41), and residing in colder areas (OR = 1.20, 95 % CI: 1.02-1.40) shown more susceptible to PM2.5. Our findings provide evidence that maternal PM2.5 exposure increased SGA risk, especially during the late pregnancy.

Preexisting multimorbidity predicts greater mortality risks related to long-term PM2.5 exposure

Long-term health risk assessments related to ambient fine particulate matter (PM2.5) exposure have been more limited to general population but not towards individuals suffering from multimorbidity. While both multimorbidity and PM2.5 are independently linked to elevated mortality risk, their combined effects and interactions remain practically unexplored. A cross-cohort analysis was undertaken on data from 3 prospective cohorts, initially enrolling 869038 adults aged ≥18 years followed up during 2005-2022. Multimorbidity was identified at baseline surveys through a list of nine common chronic conditions. Cox proportional hazards models were utilized to quantify the associations of long-term PM2.5 exposure with all-cause, cardiovascular, and respiratory mortality among individuals with and without multimorbidity. Joint effects and interactions between baseline multimorbidity and PM2.5 level on the additive and multiplicative scales were examined. Risk differences of PM2.5-induced mortality were analyzed stratified by number of chronic conditions and multimorbidity patterns. Subgroup and sensitivity analyses were carried out to evaluate the consistency of the findings. Among 713119 eligible participants for primary analysis, 65490 prevalent cases of multimorbidity were identified at baseline over a median follow-up of 12.2 years. Compared to individuals without multimorbidity, associations of PM2.5 exposure with all-cause and cardiovascular mortality were more prominent among multimorbidity individuals (P <0.05 for heterogeneity). Our analysis unveiled a significant additive interaction between PM2.5 level and preexisting multimorbidity status, yielding estimated attributable proportions of 11.7%-17.8% and excess risks of 31.1%-72.6% for different mortality outcomes. Sex subgroup and sensitivity analyses consistently produced similar results. This large-scale multicohort analysis demonstrated markedly stronger associations between PM2.5 levels and risks of all-cause and cardiovascular mortality in multimorbidity populations compared to those without multimorbidity. PM2.5 exposure and preexisting multimorbidity showed synergistic effects in triggering mortality events, wherein the joint risks were intensified with elevated PM2.5 levels and an increased number of chronic conditions.

Size-fractionated carbonaceous and iron-rich particulate matter in urban environments of France and Senegal

Road traffic is one of the main sources of particulate matter in the urban environment, emitting particulate organic and elemental carbon compounds and metal-rich particles through combustion and brakes and tires wear. In Western Africa, the carbon and metal composition of airborne particles is also influenced by additional sources linked to biomass combustion and recent industrialization. Here, we investigated the impact of combustion-related and non-combustion-related emissions on the distribution of carbonaceous fractions and iron-rich particles in two urban environments in France and Senegal. The supermicron fraction (D a > 1 µm) showed a significantly higher isothermal remanent magnetization (SIRM) than finer fractions, accounting for 79% in France and 81% in Senegal of the total SIRM. In the submicron fraction (D a < 1 µm), we noted significantly higher concentrations of total carbon (TC) and elemental carbon (EC) than for other fractions, both accounting for 71% in France and 68% and 75% in Senegal of the total and elemental particulate carbon concentration, respectively. Electron microscope observations revealed the presence of iron-rich particles forD a < 0.2 µm, however, associated with a weak SIRM. Such iron particles may be produced by combustion or abrasion while we suspect that emissions by the abrasion process produce larger particles.

Inverse association between uric acid levels and muscle quality index in adults: a cross-sectional analysis of NHANES 2011-2014

OBJECTIVE

The objective of this study was to delineate the association between serum uric acid (UA) levels and Muscle Quality Index (MQI), assessing muscle strength relative to mass, in adults aged 20 to 59 years.

METHODS

Utilizing data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014, this study examined the association between UA levels and MQI-a ratio of muscle strength to mass. Weighted linear models, adjusted for potential confounders, assessed the relationship, with a generalized additive model (GAM) probing for non-linear patterns. Subgroup analyses and interaction effects were conducted using weighted linear regression across diverse demographic and clinical groups to ensure the robustness and reliability of our findings.

RESULTS

Among 5,277 participants, a significant inverse association was observed between UA levels and MQI, with a 0.08 decrease in MQI per 1 mg/dL increase in UA (95% CI: -0.11 to -0.06, p < 0.001). The negative trend was dose-dependent across UA quartiles, which was most pronounced in the highest quartile (Q4: -0.28, 95% CI: -0.36 to -0.19, p < 0.001). Curve-fitting analysis revealed a consistent inverse relationship without evidence of non-linearity. Stratified analyses reinforced the core findings across all examined subgroups, highlighting the universal relevance of the observed association.

CONCLUSION

Our findings demonstrate a significant inverse association between elevated serum UA levels and MQI, highlighting the potential importance of uric acid management in enhancing muscle quality among young and middle-aged adults. The consistency of this relationship across different subgroups underscores the need for targeted strategies and interventions to manage UA levels. Future research should explore longitudinal impacts and intervention outcomes to further elucidate the potential benefits of uric acid management on muscle health.

Extreme temperature events, functional dependency, and cardiometabolic multimorbidity: Insights from a national cohort study in China

BACKGROUND

Extreme temperature events (ETEs), including heatwaves and cold spells, are attracting increasing attention because of their impacts on human health. However, the association between ETEs and cardiometabolic multimorbidity (CMM) and the role of functional dependency in this relationship remain unclear.

METHODS

A prospective cohort study was conducted using data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, considering 12 definitions each for heatwaves and cold spells, and three levels of functional dependency. Mixed Cox models with time-varying variables were used to comprehensively assess the independent and combined effects of ETEs and functional dependency on CMM. Additionally, subgroup analyses were conducted to investigate whether the relationship between ETEs and CMM was modified by the baseline characteristics.

RESULTS

Heatwave and cold spell exposures were associated with an increased risk of CMM (HR range: 1.028-1.102 and 1.046-1.187, respectively). Compared to participants with normal functional abilities, the risk of CMM increased with higher levels of functional dependency (HR range: 1.938-2.185). ETEs exposure and functional dependency are jointly associated with CMM risk. Participants with high-intensity ETEs exposure and high functional dependency had the greatest risk of developing CMM. Participants aged 60 and above were more susceptible to the effects of ETEs on CMM. Additionally, urban residents and those in northern regions were more vulnerable to heatwaves.

CONCLUSION

Both ETEs exposure and functional dependency increase the risk of developing CMM. Participants with functional dependency exposed to high-intensity ETEs faced the highest risk of developing CMM. These findings highlight the significant impact of ETEs on CMM and the importance of protecting vulnerable populations during periods of extreme temperature.

Particulate matter 2.5 accelerates aging: Exploring cellular senescence and age-related diseases

Exposure to Particulate matter 2.5 (PM2.5) accelerates aging, causing declines in tissue and organ function, and leading to diseases such as cardiovascular, neurodegenerative, and musculoskeletal disorders. PM2.5 is a major environmental pollutant and an exogenous pathogen in air pollution that is now recognized as an accelerator of human aging and a predisposing factor for several age-related diseases. In this paper, we seek to elucidate the mechanisms by which PM2.5 induces cellular senescence, such as genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, and mitochondrial dysfunction, and age-related diseases. Our goal is to increase awareness among researchers within the field of the toxicity of environmental pollutants and to advocate for personal and public health initiatives to curb their production and enhance population protection. Through these endeavors, we aim to promote longevity and health in older adults.

Association of Blood Selenium Levels with Diabetes and Heart Failure in American General Adults: a Cross-sectional Study of NHANES 2011-2020 pre

Selenium is an essential trace element closely related to human health; however, the relationship between blood selenium levels, diabetes, and heart failure remains inconclusive. Therefore, this study aimed to explore the relationship between blood selenium levels and the prevalence of diabetes as well as heart failure in American general adults aged 20 years or older. This study utilized data from four survey cycles from NHANES 2011-2020 pre. Blood selenium levels were considered as both a continuous variable and quartiles, and logistic regression was employed to investigate the associations between blood selenium levels with diabetes and heart failure. Nonlinear relationships were examined by restricted cubic spline regression. The analysis included a total of 16311 participants aged 20 years or older. After adjustment for all potential confounder, we found when the blood selenium levels increased by 10 ug/L, the average risk of diabetes increased by 4.2% (95% CI: 1.5%, 7.0%), and the average risk of heart failure decreased by 5.0% (95% CI: 0.1%, 9.8%). In addition, compared with the lowest reference group, blood selenium levels were significantly positively associated with risk of diabetes in participants in the fourth quartile (OR=1.458, 95% CI: 1.173, 1.812), while significantly negatively associated with the risk of heart failure in participants in the second, third and fourth quartiles (Q2, OR=0.677, 95% CI: 0.471, 0.974) (Q3, OR=0.609, 95% CI: 0.426, 0.870) (Q4, OR=0.653, 95% CI: 0.443, 0.961). There was a nonlinear and reverse L-shaped association between blood selenium and diabetes, while a negative dose-response association between blood selenium and heart failure. Furthermore, the association between blood selenium levels and heart failure was more pronounced in participants with poor glycemic control, rather than diabetic patients. High blood selenium levels may be positively related to diabetes, while low blood selenium levels may be associated to heart failure. Appropriate blood selenium levels may help prevent diabetes and heart failure.

Changes in PM2.5-related diabetes risk under the implementation of the clean air act in Shanghai

OBJECTIVES

We examined the associations between PM2.5 exposure and Type 2 diabetes mellitus risk under the implementation of the Clean Air Act (CAA) among high-risk population for diabetes in Shanghai.

METHODS

A total of 10,499 subjects from the Shanghai High-Risk Diabetic Screen (SHiDS) project between 2002 and 2018, linked with remotely sensed PM2.5 concentrations, were enrolled in this study. Ordinary least squares and logistic regression were applied to explore associations between PM2.5 and diabetes risk in various exposure periods.

RESULTS

In year 2002-2013 (before CAA), the diabetes risk increased 7.5 % (95 % CI: 1.018-1.137), 8.0 % (95 % CI: 1.022-1.142) and 7.9 % (95 % CI: 1.021-1.141) under each 10 μg/m3 increase of long-term (1, 2 and 3 years) PM2.5 exposure, respectively. Elevated PM2.5 exposure were also associated with a significant increase in glycemic parameters before CAA implementation. However, in the year 2014-2018 (after CAA), the associations between PM2.5 exposure and diabetes risk were not significant after controlling for potential confounders.

CONCLUSION

Our findings suggest that long-term and high-level exposure to PM2.5 was associated with increased prevalence of diabetes. Moreover, the implementation of CAA might ameliorate PM2.5-related diabetes risk.

Household air pollution and urinary incontinence symptoms among older adults in LASI: a large-scale population-based study

BACKGROUND

The effects of household air pollution on urinary incontinence (UI) symptoms and stress urinary incontinence (SUI) symptoms have not been studied. This study seeks to investigate the correlation between household air pollution and UI/SUI symptoms among middle-aged and elderly adults in India.

METHODS

We employed data derived from individuals aged 45 years and older who participated in the inaugural wave (2017-2018) of the Longitudinal Aging Study in India (LASI). The assessment of household air pollution exposure and the occurrence of UI/SUI symptoms relied on self-reported data. The analytical approach adopted was cross-sectional in nature and encompassed a cohort of 64,398 participants. To explore relationships, we utilized multivariate logistic regression analysis, incorporating subgroup analysis and interaction tests.

RESULTS

1,671 (2.59%) participants reported UI symptoms and 4,862 (7.55%) participants reported SUI symptoms. Also, the prevalence of UI/SUI symptoms is much higher among middle-aged and elderly adults who use solid polluting fuels (UI: 51.23% vs. 48.77%; SUI: 54.50% vs. 45.50%). The results revealed a noteworthy correlation between household air pollution and the probability of experiencing UI/SUI symptoms, persisting even after adjusting for all conceivable confounding variables (UI: OR = 1.552, 95% CI: 1.377-1.749, p < 0.00001; SUI: OR: 1.459, 95% CI: 1.357-1.568, p < 0.00001). Moreover, significant interaction effects were discerned for age, education level, tobacco consumption, alcohol consumption, and physical activity (p for interaction < 0.05).

CONCLUSIONS

The results of our study indicate that the utilization of solid fuels in the home increases the likelihood of developing urinary incontinence and stress urinary incontinence. As a result, we argue that there is an immediate need to reform the composition of cooking fuel and raise public awareness about the adverse effects of air pollution in the home.

Dynamic changes in ambient PM2.5 and body mass index among old adults: a nationwide cohort study

Outdoor air pollution has been considered as a severe environmental health issue that almost affecting everyone in the world, and intensive actions were launched. However, little is known about the association between dynamic changes in ambient fine particulate matter (PM2.5) exposure and body mass index (BMI) among old adults. To investigate the dynamic changes in ambient PM2.5 and body mass index among the elderly, we included a total of 7204 participants from 28 provinces of China during 2011-2015 in the China Health and Retirement Longitudinal Study (CHARLS). Ambient fine particle matter (PM2.5) was estimated using a well-validated space-time extremely randomized trees model. Change in PM2.5 and BMI (ΔPM2.5 and ΔBMI) were calculated as the value at a follow-up visit minus value at baseline. Linear mixed-effects models were applied to quantify the associations, controlling for sociodemographic factors. We found that per 1 μg/m3 increase in PM2.5 exposure was associated with a 0.031-0.044 kg/m2 increase in BMI among the elderly. We observed an approximate linear concentration-response relationship of PM2.5 and BMI in each visit. Each 1 μg/m3 increase in ΔPM2.5 exposure was associated with an increase in ΔBMI (β = 0.040, 95% CI 0.030, 0.049), while per 1 μg/m3 decrease in the ΔPM2.5 exposure level was associated with a decrease in ΔBMI (β = -0.016, 95% CI -0.027, -0.004). Our findings suggest that dynamic changes in ambient PM2.5 was positively associated with changes in BMI among old Chinese population.

Association between living environmental quality and risk of arthritis in middle-aged and older adults: a national study in China

Background

The association between combined environmental factors and the risk of arthritis is still scarcely studied. The present study performed cross-sectional and cohort studies to explore the association between risk score of living environment quality and the risk of arthritis in middle-aged and older adults in China.

Methods

The study was based on China Health and Retirement Longitudinal Study (CHARLS), and it recruited 17,218 participants in the cross-sectional study and 11,242 participants in the seven-year follow-up study. The living environment quality was measured by household fuel types, household water sources, room temperature, residence types, and ambient concentration of PM2.5. Logistic regression and Cox proportional hazard regression models were utilized to examine the association between the living environment quality and the risk of arthritis. Competing risk models and stratified analyses were applied to further verify our results.

Results

Compared with individuals in the suitable environment group, people who lived in moderate (OR:1.28, 95%CI: 1.14-1.43) and unfavorable environments (OR:1.49, 95%CI:1.31-1.70) showed higher risks of arthritis when considering the multiple living environmental factors (P for trend <0.001) in the cross-sectional analysis. In the follow-up study, similar results (P for trend = 0.021), moderate environment group (HR:1.26, 95%CI:1.01-1.56) and unfavorable environment group (HR: 1.36, 95%CI: 1.07-1.74), were founded.

Conclusion

Inferior living environment might promote the development of arthritis. It is necessary for the public, especially old people, to improve the living environment, which may be the key to the primary prevention of arthritis.

Associations of the built environment with type 2 diabetes in Asia: a systematic review

OBJECTIVES

Our study aimed to systematically review the literature and synthesise findings on potential associations of built environment characteristics with type 2 diabetes (T2D) in Asia.

DESIGN

Systematic review of the literature.

DATA SOURCES

Online databases Medline, Embase and Global Health were used to identify peer-reviewed journal articles published from inception to 23 January 2023.

ELIGIBILITY CRITERIA

Eligible studies included cohort, cross-sectional and case-control studies that explored associations of built environment characteristics with T2D among adults 18 years and older in Asia.

DATA EXTRACTION AND SYNTHESIS

Covidence online was used to remove duplicates and perform title, abstract and full-text screening. Data extraction was carried out by two independent reviewers using the OVID database and data were imported into MS Excel. Out of 5208 identified studies, 28 studies were included in this systematic review. Due to heterogeneity in study design, built environment and outcome definitions, a semiqualitative analysis was conducted, which synthesised results using weighted z-scores.

RESULTS

Five broad categories of built environment characteristics were associated with T2D in Asia. These included urban green space, walkability, food environment, availability and accessibility of services such as recreational and healthcare facilities and air pollution. We found very strong evidence of a positive association of particulate matter (PM_2.5, PM₁₀), nitrogen dioxide and sulfur dioxide (p<0.001) with T2D risk.

CONCLUSION

Several built environment attributes were significantly related to T2D in Asia. When compared with Western countries, very few studies have been conducted in Asia. Further research is, therefore, warranted to establish the importance of the built environment on T2D. Such evidence is essential for public health and planning policies to (re)design neighbourhoods and help improve public health across Asian countries.

PROSPERO REGISTRATION NUMBER

CRD42020214852.