Associations between community green view index and fine particulate matter from Airboxes.

Urban greenery can help to improve air quality, reduce health risks and create healthy livable urban communities. This study aimed to explore the role of urban greenery in reducing air pollution at the community level in Tainan City, Taiwan, using air quality sensors and street-view imagery. We also collected the number of road trees around each air quality sensor site and identified the species that were best at absorbing PM2.5. Three greenness metrics were used to assess community greenery in this study: two Normalized Difference Vegetation Indices (NDVI) from different satellites and the Green View Index (GVI) from Google Street View (GSV) images. Land-use Regression (LUR) was used for statistical analysis. The results showed that a higher GVI within a 500 m buffer was significantly associated with decreased PM2.5. Neither NDVI metrics within a 500 m circular buffer were significantly associated with decreased PM2.5. Evergreen trees were significantly associated with lower ambient PM2.5, compared with deciduous and semi-deciduous trees. Because localized changes in air quality profoundly affect public health and environmental equity, our findings provide evidence for future urban community greenspace planning and its beneficial impacts on reducing air pollution.

Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study.

Background: Uncontrolled asthma in adults leads to poor clinical outcome, while the clinical heterogeneity of phenotypes interferes the applicable genetic determinants. This study aimed to identify phenotypes and genetic impact on poorly-controlled asthma to optimize individualized treatment strategies. Methods: This propensity score-matched case-control study included 340 and 1020 asthmatics with poorly-controlled asthma and well-controlled asthma, respectively. Data were obtained from the 2008-2015 Taiwan Biobank Database and linked to the National Health Insurance Research Database. All asthmatics were aged ≥30 years, without cancer history, and each completed a questionnaire, physical examination, and genome-wide single nucleotide polymorphisms (SNPs). Multivariate adjusted odds ratios (ORs) for genetic risk scores were calculated using conditional logistic regression, stratified by age and sex. A model integrating obesity- and asthma-associated phenotypes and genotypes was applied for poorly-controlled asthma risk prediction. Results: General obesity with body mass index (BMI) ≥27 kg/m2 (OR:1.49, 95% confidence interval (CI) 1.09-2.03), central obesity with waist-to-height ratio (WHtR) ≥0.5 (OR:1.62, 95% CI 1.22-2.15), and parental history of asthma (OR:1.65, and 1.68; for BMI model and WHtR model, respectively) were significantly associated with poorly-controlled asthma in adults, and the combination effect of both obesity phenotypes was 1.66 (95% CI 1.17-2.35). A total of 16 obesity-associated SNPs and 9 asthma-associated SNPs were converted into genetic scores, and the aforementioned phenotypes were incorporated into the risk prediction model for poorly-controlled asthma, with an area under curve 0.72 in the receiver operating characteristic curve. The potential biological functions of genes are involved in immunity pathways. Conclusion: The prediction model integrating obesity-asthma phenotypes and genotypes for poorly-controlled asthma can facilitate the prediction of high-risk asthma and provide potential targets for novel treatment.

Relationships among green space, ambient fine particulate matter, and cancer incidence in Taiwan: A 16-year retrospective cohort study.

INTRODUCTION: Green space and air pollution have been recognized as vital health determinants. There is a paucity of studies examining the interplay between green space, fine particulate matter (PM2.5), and the incidence of specific cancers. OBJECTIVE: We aimed to explore the contributions of green space and ambient PM2.5 to the risk of specific cancers in terms of the most common cancers based on incidence or mortality rate in Taiwan and to ascertain the interaction between green space and PM2.5 and their role in cancer risk. MATERIALS AND METHODS: This retrospective longitudinal cohort study included 407,415 participants. Data were obtained from the 2000-2015 Mei Jau Health Examination Database linked to the Taiwan Cancer Registry and Causes of Death datasets. All participants were aged ≥20 years and had no history of cancer. The environmental exposure were the normalized difference vegetation index (NDVI) and the 2-year average PM2.5 at baseline. Multivariate adjusted hazard ratios (HRs) were calculated using Cox proportional hazards models. We adjusted for covariates including demographics, anthropometrics, comorbidities, health behaviors, biochemical data, and environmental factors. RESULTS: During a median follow-up of 10.37 years, 11,576 cancer cases were reported. PM2.5 exposure increased the risk of all cancers (HR: 1.11, [95% CI: 1.06-1.15]), stomach cancer (HR: 1.27, [1.02-1.58]), endocrine gland cancer (HR: 2.13, [1.39-3.26]), breast cancer (HR: 1.12, [1.03-1.22]), and lung cancer (HR: 1.12, [1.01-1.24]). An increase in NDVI reduced the risk of prostate cancer (HR: 0.93, [0.88-0.99]) and lung cancer (HR: 0.95, [0.91-0.99]). NDVI influenced the incidence of prostate and all cancers by reducing PM2.5 concentrations. CONCLUSION: Long-term PM2.5 exposure is associated with an increased risk of some types of cancers. In contrast, an increase in environmental green space exposure is associated with lowering of the risk of prostate and lung cancer.

Relationship among genetic variants, obesity traits and asthma in the Taiwan Biobank.

BACKGROUND AND OBJECTIVE: Obesity and asthma impose a heavy health and economic burden on millions of people around the world. The complex interaction between genetic traits and phenotypes caused the mechanism between obesity and asthma is still vague. This study investigates the relationship among obesity-related polygenic risk score (PRS), obesity phenotypes and the risk of having asthma. METHODS: This is a matched case-control study, with 4 controls (8288 non-asthmatic) for each case (2072 asthmatic). Data were obtained from the 2008-2015 Taiwan Biobank Database and linked to the 2000-2016 National Health Insurance Research Database. All participants were ≥30 years old with no history of cancer and had a complete questionnaire, as well as physical examination, genome-wide single nucleotide polymorphisms and clinical diagnosis data. Environmental exposure, PM2.5, was also considered. Multivariate adjusted ORs and 95% CIs were calculated using conditional logistic regression stratified by age and sex. Mediation analysis was also assessed, using a generalised linear model. RESULTS: We found that the obese phenotype was associated with significantly increased odds of asthma by approximately 26%. Four obesity-related PRS, including body mass index (OR=1.07 (1.01-1.13)), waist circumference (OR=1.10 (1.04-1.17)), central obesity as defined by waist-to-height ratio (OR=1.09 (1.03-1.15)) and general-central obesity (OR=1.06 (1.00-1.12)), were associated with increased odds of asthma. Additional independent risk factors for asthma included lower educational level, family history of asthma, certain chronic diseases and increased PM2.5 exposure. Obesity-related PRS is an indirect risk factor for asthma, the link being fully mediated by the trait of obesity. CONCLUSIONS: Obese phenotypes and obesity-related PRS are independent risk factors for having asthma in adults in the Taiwan Biobank. Overall, genetic risk for obesity increases the risk of asthma by affecting the obese phenotype.

Association between renal function and cardiovascular mortality: a retrospective cohort study of elderly from health check-up.

OBJECTIVES: This study aimed to investigate the relationship between cardiovascular mortality in elderly Asians and decline in renal function. DESIGN: A retrospective cohort study. SETTING: Community-based health examination database from Taipei city. PARTICIPANTS: At the beginning, the database included 315 045 health check-up visits of 97 803 elderly persons aged ≥65 years old from 2005 to 2012. After excluding missing values and outliers, there were 64 732 elderly persons with at least two visits retained for further analyses. PRIMARY OUTCOME MEASURES: Kidney function indicators include estimated glomerular filtration rate (eGFR) and urine protein, and rapid decline in eGFR was defined as slope ≤ -5 mL/min/1.73 m2 per year. The endpoint outcome was defined as the cardiovascular deaths registered in the death registry encoded by the International Classification of Diseases. We applied a Cox proportional hazards model to analyse the association between renal function and cardiovascular mortality. RESULTS: In this study, we found 1264 elderly persons died from cardiovascular diseases, for whom the data included 4055 previous health check-up visits. We observed significant and independent associations of eGFR <60 mL/min/1.73 m2 (HR (95% CI) of 60>eGFR≥45 and eGFR<45 in males: 2.85 (1.33 to 6.09) and 3.98 (1.84 to 8.61); in females: 3.66 (1.32 to 10.15) and 6.77 (2.41 to 18.99)), positive proteinuria (HR (95% CI) of +/-, +,++ and +++, ++++ in males: 1.51 (1.29 to 1.78) and 2.31 (1.51 to 3.53); in females: 1.93 (1.54 to 2.42) and 4.23 (2.34 to 7.65)) and rapid decline in eGFR (HR (95% CI) in males: 3.24 (2.73 to 3.85); in females: 2.83 (2.20 to 3.64) with higher risk of cardiovascular mortality. The joint effect of increased concentration of urine protein and reduced eGFR was associated with a higher risk of cardiovascular mortality. CONCLUSIONS: Renal function and rapid decline in renal function are independent risk factors for cardiovascular mortality in the elderly.

The Effects of Asthma on the Association Between Pulmonary Function and Obesity: A 16-Year Longitudinal Study.

BACKGROUND: Asthma and obesity are important public health issues around the world. Obesity is considered a risk factor associated with the severity and incidence of asthma. We investigated the relationships between poor pulmonary function (defined by forced vital capacity (FVC) and percentage of predicted FVC (FVC%)) and obesity. METHODS: This is a retrospective longitudinal study using the MJ health examination database in Taiwan from 2000 to 2015. There were 160,609 participants aged ≥20 years with complete obesity indicators and lung function data, and having at least two visits. A generalized estimation equation (GEE) model was applied to estimate the association between lung function and obesity. RESULTS: BMI was the best indicator to predict poor pulmonary function for our participants. Results of BMI are presented as an example: Obesity (body mass index (BMI) ≥27.0 kg/m2) is significantly associated with lower FVC [adjusted coefficients (ß) for asthmatics: -0.11 L (95% CI: -0.14, -0.08); adjusted ß for non-asthmatics: -0.08 L (-0.09, -0.08)] and FVC% [adjusted ß for asthmatics: -1.91% (95% CI: -2.64, -1.19); adjusted ß for non-asthmatics: 1.48% (-1.63, -1.33)]. Annual change of BMI (ΔBMI/year) is an independent risk factor for decreased FVC [adjusted ß for asthmatics: -0.030 L (-0.048, -0.013); adjusted ß for non-asthmatics: -0.019 L (-0.022, -0.016)] and FVC% [adjusted ß for non-asthmatics: -0.603% (-1.063, -0.142); adjusted ß for non-asthmatics: -0.304% (-0.393, -0.214)], and is significantly associated with accelerated FVC decline [adjusted ß of ΔFVC/year and ΔFVC %/year for asthmatics: -0.038 L (-0.054, -0.022) and -0.873% (-1.312, -0.435); adjusted ß of ΔFVC/year and ΔFVC %/year for non-asthmatics: -0.033 L (-0.042, -0.024) and -0.889% (-1.326, -0.452)]. CONCLUSION: Obesity is significantly associated with decreased lung function, and asthmatics had a higher risk than non-asthmatics.

The Association between Noise Exposure and Metabolic Syndrome: A Longitudinal Cohort Study in Taiwan.

Metabolic syndrome is becoming more common worldwide. Studies suggest environmental pollution, including traffic noise, might be linked with metabolic syndrome. This study sought to evaluate how noise exposure is linked to the development of metabolic syndrome and its components in Taiwan. Using data from a cohort of 42,509 participants and Cox proportional hazards regression models, the effects of noise exposure on metabolic syndrome and its components were quantified. After adjustment for covariates (age, gender, body mass index, and physical activity), the hazard ratio for metabolic syndrome was 1.13 (95% CI: 1.04-1.22) for medium noise exposure and 1.24 (95% CI: 1.13-1.36) for high noise exposure. Noise exposure was also positively associated with all of metabolic syndrome's components. This finding suggests noise exposure might contribute to metabolic syndrome and its components. Policies aiming to reduce noise pollution might reduce the risks of metabolic syndrome and its components.