Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India

Relationship between exposure to fine particulate matter and cardiovascular risk factors and the modifying effect of socioeconomic status: a cross-sectional study in Beijing, China

Accumulating research suggested that long-term exposure to fine particulate matter (PM2.5) is related to cardiovascular disease (CVD). However, evidence regarding the relationship between PM2.5 and CVD risk factors remains inconsistent. We hypothesized that this association may be partially modified by socioeconomic status (SES). To investigate the relationships and to test the modifying effect of SES, we included baseline data for 21,018 adults from September 2017 to May 2018. PM2.5 concentrations were determined by employing an amalgamation of linear measurements obtained from monitoring stations located near the participants' residential and workplace addresses. We assessed SES across several domains, including income, education, and occupation levels, as well as through a composite SES index. The results indicated that for every 10 μg/m3 increase in PM2.5 exposure, the risk of hypercholesterolemia, hyperbetalipoproteinemia, diabetes, and hyperhomocysteinemia (HHcy) increased by 7.7% [Odds ratio (OR) = 1.077, 95% Confidence Interval (CI) = 1.011, 1.146], 19.6% (OR = 1.196, 95% CI = 1.091, 1.312), 4.2% (OR = 1.042, 95% CI = 1.002, 1.084), and 17.1% (OR = 1.171, 95% CI = 1.133, 1.209), respectively. Compared to the high SES group, those with low SES are more prone to hypercholesterolemia, hyperbetalipoproteinemia, diabetes, and HHcy. Notably, the disparities in SES appear significant in the relationship between PM2.5 exposure and hypercholesterolemia as well as hyperbetalipoproteinemia. But for diabetes and HHcy, the modification effect of SES on PM2.5 shows an inconsistent pattern. In conclusion, the results confirm the association between PM2.5 and cardiovascular risk factors and low SES significantly amplified the adverse PM2.5 effect on dyslipidemia. It is crucial to emphasize a need to improve the socioeconomic inequality among adults in Beijing and contribute to the understanding of the urgency in protecting the health of vulnerable groups.

Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China

BACKGROUND

The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces.

METHODS

A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations.

RESULTS

Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups.

CONCLUSION

Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

Long-term exposure to air pollution and risk of insulin resistance: A systematic review and meta-analysis

OBJECTIVE

The effects of air pollution on metabolism have become a popular research topic, and a large number of studies had confirmed that air pollution exposure could induce insulin resistance (IR) to varying degrees, but the results were inconsistent, especially for the long-term exposures. The aim of the current study was to further investigate the potential effects of air pollution on IR.

METHODS

A systematic review and meta-analysis of four electronic databases, including PubMed, Embase, Web of Science and Cochrane were conducted, searching for relevant studies published before June 10, 2023, in order to explore the potential relationships between long-term exposure to air pollution and IR. A total of 10 studies were included for data analysis, including seven cohort studies and three cross-sectional studies. Four major components of air pollution, including PM2.5 (particulate matter with an aerodynamic diameter of 2.5 µm or less), PM10 (particulate matter with an aerodynamic diameter of 10 µm or less), NO2, and SO2 were selected, and each analyzed for the potential impacts on insulin resistance, in the form of adjusted percentage changes in the homeostasis assessment model of insulin resistance (HOMA-IR).

RESULTS

This systematic review and meta-analysis showed that for every 1 μg/m³ increase in the concentration of selected air pollutants, PM2.5 induced a 0.40% change in HOMA-IR (95%CI: -0.03, 0.84; I2 =67.4%, p = 0.009), while PM10 induced a 1.61% change (95%CI: 0.243, 2.968; I2 =49.1%, p = 0.001). Meanwhile, the change in HOMA-IR due to increased NO2 or SO2 exposure concentration was only 0.09% (95%CI: -0.01, 0.19; I2 =83.2%, p = 0.002) or 0.01% (95%CI: -0.04, 0.06; I2 =0.0%, p = 0.638), respectively.

CONCLUSIONS

Long-term exposures to PM2.5, PM10, NO2 or SO2 are indeed associated with the odds of IR. Among the analyzed pollutants, inhalable particulate matters appear to exert greater impacts on IR.

Exposure to PM2.5 and its five constituents is associated with the incidence of type 2 diabetes mellitus: a prospective cohort study in northwest China

Studies have demonstrated that fine particulate matter (PM2.5) is an underlying risk factor for type 2 diabetes mellitus (T2DM), but evidence exploring the relationship between PM2.5 chemical components and T2DM was extremely limited, to investigate the effects of long-term exposure to PM2.5 and its five constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+]), organic matter [OM] and black carbon [BC]) on incidence of T2DM. Based on the "Jinchang Cohort" platform, a total of 19,884 participants were selected for analysis. Daily average concentrations of pollutants were gained from Tracking Air Pollution in China (TAP). Cox proportional hazards regression models were utilized to estimate the hazard ratios (HR) and 95% confidence interval (CI) in single-pollutant models, restricted cubic splines functions were used to examine the dose-response relationships, and quantile g-computation (QgC) was applied to evaluate the combined effect of PM2.5 compositions on T2DM. Stratification analysis was also considered. A total of 791 developed new cases of T2DM were observed during a follow-up period of 45254.16 person-years. The concentrations of PM2.5, NO3-, NH4+, OM and BC were significantly associated with incidence of T2DM (P-trend < 0.05), with the HRs in the highest quartiles of 2.16 (95% CI 1.79, 2.62), 1.43 (95% CI 1.16, 1.75), 1.75 (95% CI 1.45, 2.11), 1.31 (95% CI 1.08, 1.59) and 1.79 (95% CI 1.46, 2.21), respectively. Findings of QgC model showed a noticeably positive joint effect of one quartile increase in PM2.5 constituents on increased T2DM morbidity (HR 1.27, 95% CI 1.09, 1.49), and BC (32.7%) contributed the most to the overall effect. The drinkers, workers and subjects with hypertension, obesity, higher physical activity, and lower education and income were generally more susceptible to PM2.5 components hazards. Long-term exposure to PM2.5 and its components (i.e., NO3-, NH4+, OM, BC) was positively correlated with T2DM incidence. Moreover, BC may be the most responsible for the association between PM2.5 constituents and T2DM. In the future, more epidemiological and experimental studies are needed to identify the link and potential biological mechanisms.

PM2.5 exposure, glycemic markers and incidence of type 2 diabetes in two large Indian cities

INTRODUCTION

Exposure to fine particulate matter has been associated with several cardiovascular and cardiometabolic diseases. However, such evidence mostly originates from low-pollution settings or cross-sectional studies, thus necessitating evidence from regions with high air pollution levels, such as India, where the burden of non-communicable diseases is high.

RESEARCH DESIGN AND METHODS

We studied the associations between ambient PM2.5 levels and fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c) and incident type 2 diabetes mellitus (T2DM) among 12 064 participants in an adult cohort from urban Chennai and Delhi, India. A meta-analytic approach was used to combine estimates, obtained from mixed-effects models and proportional hazards models, from the two cities.

RESULTS

We observed that 10 μg/m3 differences in monthly average exposure to PM2.5 was associated with a 0.40 mg/dL increase in FPG (95% CI 0.22 to 0.58) and 0.021 unit increase in HbA1c (95% CI 0.009 to 0.032). Further, 10 μg/m3 differences in annual average PM2.5 was associated with 1.22 (95% CI 1.09 to 1.36) times increased risk of incident T2DM, with non-linear exposure response.

CONCLUSIONS

We observed evidence of temporal association between PM2.5 exposure, and higher FPG and incident T2DM in two urban environments in India, thus highlighting the potential for population-based mitigation policies to reduce the growing burden of diabetes.

The Association Between PM2.5 Exposure and Diabetes Mellitus Among Thai Army Personnel

OBJECTIVES

This study investigated the association between baseline exposures to particulate matter with a diameter < 2.5 microns (PM2.5) and subsequent temporal changes in PM2.5 exposure with the incidence of type 2 diabetes among Royal Thai Army personnel.

METHODS

A retrospective cohort study was conducted using nationwide health check-up data from 21 325 Thai Army personnel between 2018 and 2021. Multilevel mixed-effects parametric survival statistics were utilized to analyze the relationship between baseline (i.e., PM2.5-baseline) and subsequent changes (i.e., PM2.5-change) in PM2.5 exposure and the occurrence of type 2 diabetes. Hazard ratios (HRs) and 95% confidence intervals (CIs) were employed to assess this association while considering covariates.

RESULTS

There was a significant association between both PM2.5 baseline and PM2.5-change and the incidence of type 2 diabetes in a dose-response manner. Compared to quartile 1, the HRs for quartiles 2 to 4 of PM2.5-baseline were 1.11 (95% CI, 0.74 to 1.65), 1.51 (95% CI, 1.00 to 2.28), and 1.77 (95% CI, 1.07 to 2.93), respectively. Similarly, the HRs for quartiles 2 to 4 of PM2.5-change were 1.41 (95% CI, 1.14 to 1.75), 1.43 (95% CI, 1.13 to 1.81) and 2.40 (95% CI, 1.84 to 3.14), respectively.

CONCLUSIONS

Our findings contribute to existing evidence regarding the association between short-term and long-term exposure to PM2.5 and the incidence of diabetes among personnel in the Royal Thai Army.

KCNQ1 rs2237892 polymorphism modify the association between short-term ambient particulate matter exposure and fasting blood glucose: A family-based study

BACKGROUND

The association between particulate matter and fasting blood glucose (FBG) has shown conflicting results. Genome-wide association studies have shown that KCNQ1 rs2237892 polymorphism is associated with the risk of diabetes. Whether KCNQ1 rs2237892 polymorphism might modify the association between particulate matter and FBG is still uncertain.

METHODS

Data collected from a family-based cohort study in Northern China, were used to perform the analysis. A generalized additive Gaussian model was used to examine the short-term effects of air pollutants on FBG. We further conducted interaction analyses by including a cross-product term of air pollutants by rs2237892 within KCNQ1 gene.

RESULTS

A total of 4418 participants were included in the study. In the single pollutant model, the FBG level increased 0.0031 mmol/L with per 10 μg/m³ elevation in fine particular matter (PM_2.5) for lag 0 day. After additional adjustments for nitrogen dioxide (NO₂) and sulfur dioxide (SO₂), similar results were observed for lag 0-2 days. As for particulate matter with particle size below 10 μm (PM₁₀), the significant association between the daily average concentration of the pollutant and FBG level was observed for lag 0-3 days. Additionally, rs2237892 in KCNQ1 gene modified the association between PM and FBG level. The higher risk of FBG levels associated with elevations in PM₁₀ and PM_2.5 were more evident as the number of risk allele C increased. Individuals with a CC genotype had the highest risk of elevation in FBG levels.

CONCLUSION

Short-term exposures to PM_2.5 and PM₁₀ were associated with higher FBG levels. Additionally, rs2237892 in KCNQ1 gene might modify the association between the air pollutants and FBG levels.

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.

Association of urinary and ambient black carbon, and other ambient air pollutants with risk of prediabetes and metabolic syndrome in children and adolescents

The effects of exposure to black carbon (BC) on various diseases remains unclear, one reason being potential exposure misclassification following modelling of ambient air pollution levels. Urinary BC particles may be a more precise measure to analyze the health effects of BC. We aimed to assess the risk of prediabetes and metabolic syndrome (MetS) in relation to urinary BC particles and ambient BC and to compare their associations in 5453 children from IDEFICS/I. Family cohort. We determined the amount of BC particles in urine using label-free white-light generation under femtosecond pulsed laser illumination. We assessed annual exposure to ambient air pollutants (BC, PM_2.5 and NO₂) at the place of residence using land use regression models for Europe, and we calculated the residential distance to major roads (≤250 m vs. more). We analyzed the cross-sectional relationships between urinary BC and air pollutants (BC, PM_2.5 and NO₂) and distance to roads, and the associations of all these variables to the risk of prediabetes and MetS, using logistic and linear regression models. Though we did not observe associations between urinary and ambient BC in overall analysis, we observed a positive association between urinary and ambient BC levels in boys and in children living ≤250 m to a major road compared to those living >250 m away from a major road. We observed a positive association between log-transformed urinary BC particles and MetS (OR_{per unit increase} = 1.72, 95% CI = 1.21; 2.45). An association between ambient BC and MetS was only observed in children living closer to a major road. Our findings suggest that exposure to BC (ambient and biomarker) may contribute to the risk of MetS in children. By measuring the internal dose, the BC particles in urine may have additionally captured non-residential sources and reduced exposure misclassification. Larger studies, with longitudinal design including measurement of urinary BC at multiple time-points are warranted to confirm our findings.

Association of long-term air pollution exposure with the risk of prediabetes and diabetes: Systematic perspective from inflammatory mechanisms, glucose homeostasis pathway to preventive strategies

BACKGROUND

Limited evidence suggests the association of air pollutants with a series of diabetic cascades including inflammatory pathways, glucose homeostasis disorder, and prediabetes and diabetes. Subclinical strategies for preventing such pollutants-induced effects remain unknown.

METHODS

We conducted a cross-sectional study in two typically air-polluted Chinese cities in 2018-2020. One-year average PM₁, PM_2.5, PM₁₀, SO₂, NO₂, and O₃ were calculated according to participants' residence. GAM multinomial logistic regression was performed to investigate the association of air pollutants with diabetes status. GAM and quantile g-computation were respectively performed to investigate individual and joint effects of air pollutants on glucose homeostasis markers (glucose, insulin, HbA1c, HOMA-IR, HOMA-B and HOMA-S). Complement C3 and hsCRP were analyzed as potential mediators. The ABCS criteria and hemoglobin glycation index (HGI) were examined for their potential in preventive strategy.

RESULTS

Long-term air pollutants exposure was associated with the risk of prediabetes [Prevalence ratio for O₃ (PR_O₃) = 1.96 (95% CI: 1.24, 3.03)] and diabetes [PR_PM₁ = 1.18 (95% CI: 1.05, 1.32); PR_PM_2.5 = 1.08 (95% CI: 1.00, 1.16); PR_O₃ = 1.35 (95% CI: 1.03, 1.74)]. PM₁, PM₁₀, SO₂ or O₃ exposure was associated with glucose-homeostasis disorder. For example, O₃ exposure was associated with increased levels of glucose [7.67% (95% CI: 1.75, 13.92)], insulin [19.98% (95% CI: 4.53, 37.72)], HOMA-IR [34.88% (95% CI: 13.81, 59.84)], and decreased levels of HOMA-S [-25.88% (95% CI: -37.46, -12.16)]. Complement C3 and hsCRP played mediating roles in these relationships with proportion mediated ranging from 6.95% to 60.64%. Participants with HGI ≤ -0.53 were protected from the adverse effects of air pollutants.

CONCLUSION

Our study provides comprehensive insights into air pollutant-associated diabetic cascade and suggests subclinical preventive strategies.

Long-term exposure to PM2.5 constituents in relation to glucose levels and diabetes in middle-aged and older Chinese

BACKGROUND

Previous studies have indicated the associations between fine particulate matter (PM_2.5) exposure and diabetes or glucose levels. However, evidence linking PM_2.5 constituents and diabetes or glucose levels was extensively scarce, particularly in developing countries. This study aimed to investigate the associations of exposure to PM_2.5 and its five constituents (black carbon [BC], organic matter [OM], nitrate [NO₃^-], sulfate [SO₄^2-], and ammonium [NH₄⁺]) with diabetes and glucose levels among the middle-aged and elderly Chinese populations.

METHODS

A national cross-sectional sample of participants aged 45+ years was enrolled from 28 provinces across China's mainland. Health examination and questionnaire survey for each respondent were performed during 2011-2012. Diabetes was determined by alternative definitions, and the main definition (MD) was self-report diabetes or antidiabetic medicine use or HbA_1c ≥6.5 or fasting glucose ≥7 mmol/L or random glucose ≥11.1 mmol/L. Monthly exposure to PM_2.5 mass and its five constituents (BC, OM, NO₃^-, SO₄^2-, and NH₄⁺) for each participant at residence were estimated using satellite-based spatiotemporal prediction models. Generalized linear models and linear mixed-effects models were used to assess the effects of exposure to PM_2.5 and its constituents on diabetes or glucose levels, respectively. Stratification analyses were done by sex and age.

RESULTS

We included a total of 17,326 adults over 45 years in this study. The 3-year mean (interquartile range [IQR]) concentrations of PM_2.5, BC, OM, NO₃^-, SO₄^2-, and NH₄⁺ were 47.9 (27.4) µg/m³, 2.9 (2.2) µg/m³, 9.2 (6.6) µg/m³, 10.2 (9.4) µg/m³, 11.0 (5.2) µg/m³, and 7.1 (4.4) µg/m³, respectively. Per IQR rise in exposure to PM_2.5 was significantly associated with an increase of 0.133 mmol/L (95% confidence interval, 0.048-0.219) in glucose concentrations. Similar positive associations were observed for BC (0.097 mmol/L [0.012-0.181]), OM (0.160 mmol/L [0.065-0.256]), NO₃^- (0.145 mmol/L [0.039-0.251]), SO₄^2- (0.111 mmol/L [0.026-0.196]), and NH₄⁺ (0.135 mmol/L [0.041-0.230]). Under different diabetes definitions, PM_2.5 mass and selected constituents with the exception of SO₄^2- were all associated with a higher risk of prevalent diabetes. In MD-based analysis, similar positive associations were observed for four constituents, with corresponding odds ratios of 1.180 (1.097-1.270) for PM_2.5, 1.154 (1.079-1.235) for BC, 1.170 (1.079-1.270) for OM, 1.200 (1.098-1.312) for NO₃^-, and 1.123 (1.037-1.215) for NH₄⁺. Stratified analyses showed a significantly higher risk of diabetes in males (1.225 [1.064-1.411]) than females (1.024 [0.923-1.136]) when exposed to PM_2.5. Participants under 65 years were generally more vulnerable to diabetes hazards related to PM_2.5 constituents exposure.

CONCLUSIONS

Exposures to PM_2.5 and its constituents (i.e., BC, OM, NO₃^-, and NH₄⁺) were positively associated with increased risks of prevalent diabetes and elevated glucose levels in middle-aged and older adults.

A review and analysis of personal and ambient PM2.5 measurements: Implications for epidemiology studies

BACKGROUND

In epidemiology studies, ambient measurements of PM_2.5 are often used as surrogates for personal exposures. However, it is unclear the degree to which ambient PM_2.5 reflects personal exposures.

OBJECTIVE

In order to examine potential sources of bias in epidemiology studies, we conducted a review and meta-analysis of studies to determine the extent to which short-term measurements of ambient PM_2.5 levels are related to short-term measurements of personal PM_2.5 levels.

METHODS

We conducted a literature search of studies reporting both personal and ambient measurements of PM_2.5 published in the last 10 years (2009-2019) and incorporated studies published prior to 2009 from reviews.

RESULTS

Seventy-one studies were identified. Based on 17 studies reporting slopes, a meta-analysis revealed an overall slope of 0.56 μg/m³ (95% CI: [0.39, 0.73]) personal PM_2.5 per μg/m³ increase in ambient PM_2.5. Slopes for summer months were higher (slope = 0.73, 95% CI: [0.64, 0.81]) than for winter (slope = 0.46, 95% CI: [0.36, 0.57]). Based on 44 studies reporting correlations, we calculated an overall personal-ambient PM_2.5 correlation of 0.63 (95% CI: [0.55, 0.71]). Correlations were stronger in studies conducted in Canada (r = 0.86, 95% CI: [0.67, 0.94]) compared to the USA (r = 0.60, 95% CI: [0.49, 0.70]) and China (r = 0.60, 95% CI: [0.46, 0.71]). Correlations also were stronger in urban areas (r = 0.53, 95% CI: [0.43, 0.62]) vs. suburban areas (r = 0.36, 95% CI: [0.21, 0.49]).

SIGNIFICANCE

Our results suggest a large degree of variability in the personal-ambient PM_2.5 association and the potential for exposure misclassification and measurement error in PM_2.5 epidemiology studies.

The Association between Exposure to Residential Indoor Volatile Organic Compounds and Measures of Central Arterial Stiffness in Healthy Middle-Aged Men and Women

It is well reported that individuals spend up to 90% of their daily time indoors, with between 60% to 90% of this time being spent in the home. Using a cross-sectional study design in a population of 111 healthy adults (mean age: 52.3 ± 9.9 years; 65% women), we investigated the association between exposure to total volatile organic compounds (VOCs) in indoor residential environments and measures of central arterial stiffness, known to be related to cardiovascular risk. Indoor VOC concentrations were measured along with ambulatory measures of pulse pressure (cPP), augmentation index (cAIx) and cAIx normalized for heart rate (cAIx₇₅), over a continuous 24-h period. Pulse wave velocity (cfPWV) was determined during clinical assessment. Multiple regression analysis was performed to examine the relationship between measures of arterial stiffness and VOCs after adjusting for covariates. Higher 24-h, daytime and night-time cAIx was associated with an interquartile range increase in VOCs. Similar effects were shown with cAIx₇₅. No significant effects were observed between exposure to VOCs and cPP or cfPWV. After stratifying for sex and age (≤50 years; >50 years), effect estimates were observed to be greater and significant for 24-h and daytime cAIx in men, when compared to women. No significant effect differences were seen between age groups with any measure of arterial stiffness. In this study, we demonstrated that residential indoor VOCs exposure was adversely associated with some measures of central arterial stiffness, and effects were different between men and women. Although mechanistic pathways remain unclear, these findings provide a possible link between domestic VOCs exposure and unfavourable impacts on individual-level cardiovascular disease risk.

Longitudinal relationship of particulate matter and metabolic control and severe hypoglycaemia in children and adolescents with type 1 diabetes

BACKGROUND

Evidence for the metabolic impact of long-term exposure to air pollution on diabetes is lacking. We investigated the association of particulate matter <10 μm (PM₁₀) and <2.5 μm (PM_2.5) with yearly averages of HbA1c, daily insulin dose (IU/kg) and rates of severe hypoglycaemia in type 1 diabetes (T1D).

METHODS

We studied data of 44,383 individuals with T1D < 21 years which were documented in 377 German centres within the diabetes prospective follow-up registry (DPV) between 2009 and 2018. Outcomes were aggregated by year and by patient. PM₁₀-and PM_2.5-yearly averages prior to the respective treatment year were linked to individuals via the five-digit postcode areas of residency. Repeated measures linear and negative binomial regression were used to study the association between PM-quartiles (Q1 lowest, Q4 highest concentration) and yearly averages of HbA1c, daily insulin dose and rates of severe hypoglycaemia (confounders: sex, time-dependent age, age at diabetes onset, time-dependent type of treatment, migratory background, degree of urbanisation and socioeconomic index of deprivation).

RESULTS

Adjusted mean HbA1c increased with PM₁₀ (Q1: 7.96% [95%-CI: 7.95-7.98], Q4: 8.03% [8.02-8.05], p-value<0.001) and with PM_2.5 (Q1: 7.97% [7.95-7.99], Q4: 8.02% [8.01-8.04], p < 0.001). Changes in daily insulin dose were inversely related to PM (PM₁₀ and PM_2.5: Q1 0.85 IU/kg [0.84-0.85], Q4: 0.83 IU/kg [0.82-0.83], p < 0.001). Adjusted rates of severe hypoglycaemia increased with PM-quartile groups (PM₁₀ Q1:11.2 events/100 PY [10.9-11.5], PM₁₀ Q4: 15.3 [14.9-15.7], p < 0.001; PM_2.5 Q1: 9.9 events/100 PY [9.6-10.2], PM_2.5 Q4: 14.2 [13.9-14.6], p < 0.001).

DISCUSSION

Air pollution was associated with higher HbA1c levels and increased risk of severe hypoglycaemia in people with T1D, consequently indicating a higher risk of diabetes complications. Further studies are needed to explore causal pathways of the observed associations.

Short-term effects of real-time individual fine particulate matter exposure on lung function: a panel study in Zhuhai, China

Fine particulate matter (PM_2.5) is still the primary air pollutant in most Chinese cities and its adverse effects on lung function have been widely reported. However, short-term effects of individual exposure to PM_2.5 on pulmonary expiration flow indices remain largely unknown. In this study, we examined the short-term effects of real-time individual exposure to PM_2.5 on lung function in a panel of 115 healthy adults. We measured individual real-time PM_2.5 exposure and lung function. Environmental PM_2.5 concentrations in the same period were collected from the nearest monitoring station. Generalized linear model was used to assess the effects of individual PM_2.5 exposure on lung function after adjusting for potential confounders. Individual PM_2.5 exposure ranged from 18.5 to 42.4 μg/m³ with fluctuations over time and ambient PM_2.5 concentrations presented a moderate trend of fluctuation at the same day. Except forced expiratory volume in 1 s (FEV₁) decline related to 2-h moving average PM_2.5 exposure, no significant associations between individual PM_2.5 exposure and other volume indices including forced vital capacity (FVC) and FEV₁/FVC ratio were observed. The adverse effects of individual PM_2.5 exposure on pulmonary expiration flow indices including peak expiratory flow (PEF), maximal mid-expiratory flow (MMF) and forced expiratory flow at 50%, and 75% of vital capacity (FEF_50% and FEF_75%) were observed to be strongest at 2 moving average hours and could last for 24 h. Stratified analysis showed greater and longer effects among participants who were aged over 40 years, males, or smokers. These findings suggested that individual PM_2.5 exposure was significantly associated with altered lung function, especially with pulmonary expiration flow indices decline, which was strongest at 2 moving average hours and could last for 24 h.

PM2.5 and Diabetes in the Japanese Population

Growing evidence suggests that PM_2.5 is associated with diabetes mellitus (DM). Although DM is a major public health concern, there has not yet been a study of this association in Japan. We used health examination data from 66,885 individuals in Tokyo, Japan 2005–2019. Cox proportional hazards models were used to evaluate an association between annual exposure to PM_2.5 and glycated hemoglobin A_1c (HbA_1c), or fasting plasma glucose (FPG). An increase of 1 μg/m³ in the annual average of PM_2.5 concentration was associated (HR = 1.029; 95% CI = 1.004–1.055) with an increase in diabetes (incident + prevalent). For incident DM, a greater PM_2.5 level was associated with more DM (HR = 1.029; 95% CI, 1.003–1.055). Compared to HbA_1c, FPG showed a stronger association with the annual exposure to PM_2.5 (HR = 1.065; 95% CI, 1.040–1.091). We found that greater exposure to PM_2.5 in the long-term was associated with an increased risk of diabetes, and that the magnitude of association became stronger as the exposure duration increased. Omorogieva Ojo

The Impact of Air Pollution on Neurodegenerative Diseases

BACKGROUND

With the development of industrialization in human society, ambient pollutants are becoming more harmful to human health. Epidemiological and toxicological studies indicate that a close relationship exists between particulate matter with a diameter ≤2.5 µm (PM2.5) and neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). To further confirm the relationship, we focus on possible relevant mechanisms of oxidative stress and neuroinflammation underlying the association between PM2.5 and neurodegenerative diseases in the review.

METHODS

A literature search was performed on the studies about PM2.5 and neurodegenerative diseases via PubMed. A total of 113 articles published were selected, and 31 studies were included.

RESULTS

PM2.5 can enter the central nervous system through 2 main pathways, the blood-brain barrier and olfactory neurons. The inflammatory response and oxidative stress are 2 primary mechanisms via which PM2.5 leads to toxicity in the brain. PM2.5 abnormally activates microglia, inducing the neuroinflammatory process. Inflammatory markers such as IL-1β play an essential role in neurodegenerative diseases such as AD and PD. Moreover, the association between lipid mechanism disorders related to PM2.5 and neurodegenerative diseases has been gaining momentum.

CONCLUSIONS

In conclusion, PM2.5 could significantly increase the risk of neurological disorders, such as AD and PD. Furthermore, any policy aimed at reducing air-polluting emissions and increasing air quality would be protective in human beings.

Long-term exposure to PM2.5 and fasting plasma glucose in non-diabetic adolescents in Yogyakarta, Indonesia

BACKGROUND

Indonesia is facing serious air pollution. However, very few studies have been conducted to examine the health risks of air pollution in Indonesia, particularly for adolescents.

OBJECTIVE

To assess the association between long-term exposure to ambient particles with a diameter of <2.5 μm (PM_2.5) and fasting plasma glucose (FPG) in adolescents.

METHODS

A cross-sectional study was conducted in 482 adolescents aged 14-18 years in Yogyakarta, Indonesia in 2016. We finally included 469 (97.30%) participants who had no missing data for data analysis. We collected individual data on socio-demographics, behavioral habits, and health information through standardized questionnaires. Satellite-based PM_2.5 concentrations from 2013 to 2016 were assigned based on participants' residential addresses. The association between PM_2.5 and FPG was examined using a generalized linear regression model while FPG was modeled as a continuous variable. An ordered logistic regression model was used to assess the relationship between PM_2.5 and FPG categories.

RESULTS

Every 1 μg/m³ increase in PM_2.5 was associated with a 0.34 mg/dL [95 confidence interval (95% CI): 0.08 mg/dL, 0.59 mg/dL] increase in FPG levels. Comparing with the low FPG level (under 86 mg/dL), every 1 μg/m³ increase in PM_2.5 was associated with a 10.20% (95% CI: 1.60%, 19.80%) increase in the odds of impaired fasting glucose (IFG) (100-125 mg/dL). Stratified analyses indicated greater effects on participants with hypertension [odds ratio (OR) = 1.30, 95% CI: 1.09, 1.57] and those had higher physical activities (OR = 1.36, 95% CI: 1.09, 1.57). Adolescents' sex, obesity status and different cutoff points of FPG did not modify the association between the exposure to PM_2.5 and FPG levels.

CONCLUSION

Long-term exposure to PM_2.5 was associated with increased FPG levels in Indonesian non-diabetic adolescents.

Effect of air pollution on hospitalization for acute exacerbation of chronic obstructive pulmonary disease, stroke, and myocardial infarction

This study aims to analyze the acute effects of PM_2.5, PM₁₀, SO₂, NO₂, and O₃ on hospitalizations for acute exacerbation of chronic obstructive pulmonary disease (AECOPD), stroke, and myocardial infarction (MI) from 2014 to 2017 in Shenyang, China. Hospitalization records for AECOPD (17,655), stroke (276,736) and MI (26,235) and air pollutions concentration data (PM_2.5, PM₁₀, SO₂, NO₂, and O₃) were collected. A generalized additive model (GAM) was utilized to determine the impact of air pollutants on the relative risk (RR) of hospitalization for AECOPD, stroke, and MI. Stratified analysis for AECOPD was based on gender and age. It was based on gender, age, hypertension, and diabetes for stroke, and for MI it was based on gender, age, and coronary atherosclerosis. The lag effect for AECOPD in terms of gender analysis occurred at lag3-lag5. The hospitalization risk for stroke with hypertension due to SO₂ and NO₂ was greater than that of stroke without hypertension. The risk of hospitalization for stroke with hypertension as a comorbidity due to O₃ was lower than without hypertension. The risk of hospitalization for MI combined with coronary atherosclerosis due to PM_2.5, PM₁₀, or NO₂ was higher than that of hospitalizations for MI without coronary atherosclerosis. Air pollution increased the rate of hospitalization for AECOPD. SO₂ and O₃ appeared protective for stroke patients with coronary atherosclerosis. PM_2.5, PM₁₀, and NO₂ had no influence on total hospitalization for myocardial infarction.