Exploring the spatial association between the distribution of temperature and urban morphology with green view index.

Urban heat islands will occur if city neighborhoods contain insufficient green spaces to create a comfortable environment, and residents' health will be adversely affected. Current satellite imagery can only effectively identify large-scale green spaces and cannot capture street trees or potted plants within three-dimensional building spaces. In this study, we used a deep convolutional neural network semantic segmentation model on Google Street View to extract environmental features at the neighborhood level in Taipei City, Taiwan, including the green vegetation index (GVI), building view factor, and sky view factor. Monthly temperature data from 2018 to 2021 with a 0.01° spatial resolution were used. We applied a linear mixed-effects model and geographically weighted regression to explore the association between pedestrian-level green spaces and ambient temperature, controlling for seasons, land use information, and traffic volume. Their results indicated that a higher GVI was significantly associated with lower ambient temperatures and temperature differences. Locations with higher traffic flows or specific land uses, such as religious or governmental, are associated with higher ambient temperatures. In conclusion, the GVI from street-view imagery at the community level can improve the understanding of urban green spaces and evaluate their effects in association with other social and environmental indicators.

The impact of co-exposure to air and noise pollution on the incidence of metabolic syndrome from a health checkup cohort.

Previous studies have found associations between the incidence of metabolic syndrome (MetS) and exposure to air pollution or road traffic noise. However, investigations on environmental co-exposures are limited. This study aimed to investigate the association between co-exposure to air pollution and road traffic noise and MetS and its subcomponents. Participants living in Taipei City who underwent at least two health checkups between 2010 and 2016 were included in the study. Data were sourced from the MJ Health database, a longitudinal, large-scale cohort in Taiwan. The monthly traffic noise exposure (Lden and Lnight) was computed using a dynamic noise map. Monthly fine particulate data at one kilometer resolution were computed from satellite imagery data. Cox proportional hazards regression models with month as the underlying time scale were used to estimate hazard ratios (HRs) for the impact of PM2.5 and road traffic noise exposure on the risk of developing MetS or its subcomponents. Data from 10,773 participants were included. We found significant positive associations between incident MetS and PM2.5 (HR: 1.88; 95% CI 1.67, 2.12), Lden (HR: 1.10; 95% CI 1.06, 1.15), and Lnight (HR: 1.07; 95% CI 1.02, 1.13) in single exposure models. Results further showed significant associations with an elevated risk of incident MetS in co-exposure models, with HRs of 1.91 (95% CI 1.69, 2.16) and 1.11 (95% CI 1.06, 1.16) for co-exposure to PM2.5 and Lden, and 1.90 (95% CI 1.68, 2.14) and 1.08 (95% CI 1.02, 1.13) for co-exposure to PM2.5 and Lnight. The HRs for the co-exposure models were higher than those for models with only a single exposure. This study provides evidence that PM2.5 and noise exposure may elevate the risk of incident MetS and its components in both single and co-exposure models. Therefore, preventive approaches to mitigate the risk of MetS and its subcomponents should consider reducing exposure to PM2.5 and noise pollution.

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.

Effectiveness of controlling COVID-19 epidemic by implementing soft lockdown policy and extensive community screening in Taiwan.

Strict and repeated lockdowns have caused public fatigue regarding policy compliance and had a large impact on several countries' economies. We aimed to evaluate the effectiveness of a soft lockdown policy and the strategy of active community screening for controlling COVID-19 in Taiwan. We used village-based daily confirmed COVID-19 statistics in Taipei City and New Taipei City, between May 2, 2021, and July 17, 2021. The temporal Gi* statistic was used to compute the spatiotemporal hotspots. Simple linear regression was used to evaluate the trend of the epidemic, positivity rate from community screening, and mobility changes in COVID-19 cases and incidence before and after a level three alert in both cities. We used a Bayesian hierarchical zero-inflated Poisson model to estimate the daily infection risk. The cities accounted for 11,403 (81.17%) of 14,048 locally confirmed cases. The mean effective reproduction number (Re) surged before the level three alert and peaked on May 16, 2021, the day after the level three alert in Taipei City (Re = 3.66) and New Taipei City (Re = 3.37). Mobility reduction and a lower positive rate were positively associated with a lower number of cases and incidence. In the spatiotemporal view, seven major districts were identified with a radial spreading pattern from one hard-hit district. Villages with a higher inflow degree centrality among people aged ≥ 60 years, having confirmed cases, specific land-use types, and with a higher aging index had higher infection risks than other villages. Early soft lockdown policy and detection of infected patients showed an effective strategy to control COVID-19 in Taiwan.

Approaching precision public health by automated syndromic surveillance in communities.

BACKGROUND: Sentinel physician surveillance in communities has played an important role in detecting early signs of epidemics. The traditional approach is to let the primary care physician voluntarily and actively report diseases to the health department on a weekly basis. However, this is labor-intensive work, and the spatio-temporal resolution of the surveillance data is not precise at all. In this study, we built up a clinic-based enhanced sentinel surveillance system named "Sentinel plus" which was designed for sentinel clinics and community hospitals to monitor 23 kinds of syndromic groups in Taipei City, Taiwan. The definitions of those syndromic groups were based on ICD-10 diagnoses from physicians. METHODS: Daily ICD-10 counts of two syndromic groups including ILI and EV-like syndromes in Taipei City were extracted from Sentinel plus. A negative binomial regression model was used to couple with lag structure functions to examine the short-term association between ICD counts and meteorological variables. After fitting the negative binomial regression model, residuals were further rescaled to Pearson residuals. We then monitored these daily standardized Pearson residuals for any aberrations from July 2018 to October 2019. RESULTS: The results showed that daily average temperature was significantly negatively associated with numbers of ILI syndromes. The ozone and PM2.5 concentrations were significantly positively associated with ILI syndromes. In addition, daily minimum temperature, and the ozone and PM2.5 concentrations were significantly negatively associated with the EV-like syndromes. The aberrational signals detected from clinics for ILI and EV-like syndromes were earlier than the epidemic period based on outpatient surveillance defined by the Taiwan CDC. CONCLUSIONS: This system not only provides warning signals to the local health department for managing the risks but also reminds medical practitioners to be vigilant toward susceptible patients. The near real-time surveillance can help decision makers evaluate their policy on a timely basis.

The metabolic syndrome is associated with the risk of urothelial carcinoma from a health examination database.

PURPOSE: The metabolic syndrome was associated with bladder cancer in the previous studies. However, there have no large-scale cohort studies to elucidate the relationship between metabolic syndromes and urothelial carcinoma including urinary bladder urothelial carcinoma (UBUC) and upper tract urothelial carcinoma (UTUC). METHODS: We analyze a population-based cohort study by using physical examination data and diagnosis of UC from the Taiwan Cancer Registry Database. Differences in demographic and clinical characteristics among UTUC and non-UTUC groups, UBUC and non-UBUC groups were compared. Odds ratios (ORs) for determining risk factors were estimated through the multiple logistic regression model. RESULTS: A total of 557,063 records for 211,319 participants which consisted of 31 UTUC and 309 UBUC met the eligibility criteria in this study. Our results showed that female are more likely to develop UTUC than male. As opposed to UTUC, male are more likely to develop UBUC than female. It also showed that participants smoked or chewed betel quid daily are more likely to develop UBUC. Age and estimated glomerular filtration rate (eGFR) are significantly increased the risk of developing UTUC. The association between the eGFR and risk of UTUC is stronger (P < 0.001) for eGFR < 45 (vs. eGFR ≥ 75, OR = 6.795; 95% CI 2.901-15.917). Metabolic syndrome is related to higher risk of UBUC incidence [OR was 1.373 (95% CI 1.104-1.707)]. CONCLUSIONS: There was a significant relationship between the incidence of UBUC and metabolic syndrome. Renal function impairment presents higher risk in both UBUC and UTUC development.

Detecting spatio-temporal hotspots of scarlet fever in Taiwan with spatio-temporal Gi* statistic.

A resurgence of scarlet fever has caused many pediatric infections in East Asia and the United Kingdom. Although scarlet fever in Taiwan has not been a notifiable infectious disease since 2007, the comprehensive national health insurance data can still track its trend. Here, we used data from the open data portal of the Taiwan Centers for Disease Control. The scarlet fever trend was measured by outpatient and hospitalization rates from 2009 to 2017. In order to elucidate the spatio-temporal hotspots, we developed a new method named the spatio-temporal Gi* statistic, and applied Joinpoint regression to compute the annual percentage change (APC). The overall APCs in outpatient and hospitalization were 15.1% (95% CI: 10.3%-20.2%) and 7.7% (95%CI: 4.5% -10.9%). The major two infected groups were children aged 5-9 (outpatient: 0.138 scarlet fever diagnoses per 1,000 visits; inpatient: 2.579 per 1,000 visits) and aged 3-4 (outpatient: 0.084 per 1,000 visits; inpatient: 1.469 per 1,000 visits). We found the counties in eastern Taiwan and offshore counties had the most hotspots in the outpatient setting. In terms of hospitalization, the hotspots mostly occurred in offshore counties close to China. With the help of the spatio-temporal statistic, health workers can set up enhanced laboratory surveillance in those hotspots.

Association between health behaviors and mood disorders among the elderly: a community-based cohort study.

BACKGROUND: According to a WHO report, nearly 15% of adults aged 60 and over suffer from a mental disorder, constituting 6.6% of the total disability for this age group. Taipei City faces rapid transformation towards an aging society, with the proportion of elderly in the total population rising from 12% in 2008 to 16% in 2016. The aim of this study is to identify the prevalence of mental disorders among the elderly in Taipei City and to elucidate risk factors contributing to mental disorders. METHODS: The elderly health examination database was obtained from the Department of Health, Taipei City government, from 2005 to 2012. A total of 86,061 people underwent publicly funded health examinations, with 348,067 visits. Each year, there are around 43,000 elderly persons in Taipei City using this service. We used a mental health questionnaire including five questions to estimated relative risks among potential risk factors with the generalized estimating equations (GEE) model to measure the mental health status of the elderly. Mood disorders were measured with the Brief Symptom Rating Scale (BSRS-5) questionnaire. Age, education level, gender, marital status, living alone, drinking milk, eating vegetables and fruits, long-term medication, smoking status, frequency of alcohol consumption, frequency of physical activity, BMI, and number of chronic diseases were included as covariates. RESULTS: The results show that being male (odds ratio (OR) 0.57; 95% CI = 0.56, 0.59), higher education (OR 0.88; 95% CI = 0.82, 0.95), no long-term medication (OR 0.57; 95% CI = 0.56, 0.58), and exercising three or more times per week (OR 0.94; 95% CI = 0.91, 0.98) were all positively correlated with better emotional status. However, being divorced (OR = 1.22, 95% CI = 1.09, 1.36), not drinking milk (OR = 1.12, 95% CI = 1.09, 1.14), not eating enough vegetables and fruits every day (OR = 1.78, 95% CI = 1.73, 1.83), daily smoking (OR = 1.15, 95% CI = 1.01, 1.32), and having more chronic diseases (OR = 1.02, 95% CI = 1.01, 1.03) were all correlated with poor mental status among the elderly. CONCLUSIONS: The findings of this research can both estimate the prevalence of mood disorders at the community level, and identify risk factors of mood disorders at the personal level.

A flow-based statistical model integrating spatial and nonspatial dimensions to measure healthcare access.

Assessing access to healthcare for an entire healthcare system involves accounting for demand, supply, and geographic variation. In order to capture the interaction between healthcare services and populations, various measures of healthcare access have been utilized, including the popular two-step floating catchment area (2SFCA) method. However, despite the many advantages of 2SFCA, the problems, such as inappropriate assumption of healthcare demand and failure to capture cascading effects across the system have not been satisfactorily addressed. In this paper, a statistical model for evaluating flows of individuals was added to the 2SFCA method (hereafter we refer to it as F2SFCA) in order to overcome limitations associated with its current restriction. The proposed F2SFCA model can incorporate both spatial and nonspatial dimensions and thus synthesizes them into one framework. Moreover, the proposed F2SFCA model can be easily adapted to measure access for different types of individuals, over different service provider types, or with capacity constraints in a healthcare system. We implemented the proposed model in a case study assessing access to healthcare for the elderly in Taipei City, Taiwan, and compared the weaknesses and strengths to the 2SFCA method and its variations.

Analyzing Personal Happiness from Global Survey and Weather Data: A Geospatial Approach.

Past studies have shown that personal subjective happiness is associated with various macro- and micro-level background factors, including environmental conditions, such as weather and the economic situation, and personal health behaviors, such as smoking and exercise. We contribute to this literature of happiness studies by using a geospatial approach to examine both macro and micro links to personal happiness. Our geospatial approach incorporates two major global datasets: representative national survey data from the International Social Survey Program (ISSP) and corresponding world weather data from the National Oceanic and Atmospheric Administration (NOAA). After processing and filtering 55,081 records of ISSP 2011 survey data from 32 countries, we extracted 5,420 records from China and 25,441 records from 28 other countries. Sensitivity analyses of different intervals for average weather variables showed that macro-level conditions, including temperature, wind speed, elevation, and GDP, are positively correlated with happiness. To distinguish the effects of weather conditions on happiness in different seasons, we also adopted climate zone and seasonal variables. The micro-level analysis indicated that better health status and eating more vegetables or fruits are highly associated with happiness. Never engaging in physical activity appears to make people less happy. The findings suggest that weather conditions, economic situations, and personal health behaviors are all correlated with levels of happiness.

Latitude-based approach for detecting aberrations of hand, foot, and mouth disease epidemics.

BACKGROUND: Epidemics of hand, foot and mouth disease (HFMD) among children in East Asia have been a serious annual public health problem. Previous studies in China and island-type territories in East Asia showed that the onset of HFMD epidemics evolved with increased latitude. Based on the natural characteristics of the epidemics, we developed regression models for issuing aberration alerts and predictions. METHODS: HFMD sentinel surveillance data from 2008 to 2014 in Japan are used in this study, covering 365 weeks and 47 prefectures between 24 and 46° of north latitude. Average HFMD cases per sentinel are standardized as Z rates. We fit weekly Z rate differences between prefectures located in the south and north of a designated prefecture with linear regression models to detect the surging trend of the epidemic for the prefecture. We propose a rule for issuing an aberration alert determined by the strength of the upward trend of south-north Z rate differences in the previous few weeks. In addition to the warning, we predict a Z rate for the next week with a 95% confidence interval. RESULTS: We selected Tokyo and Kyoto for evaluating the proposed approach to aberration detection. Overall, the peaks of epidemics in Tokyo mostly occurred in weeks 28-31, later than in Kyoto, where the disease peaked in weeks 26-31. Positive south-north Z rate differences in both prefectures were clearly observed ahead of the HFMD epidemic cycles. Aberrations in the major epidemics of 2011 and 2013 were successfully detected weeks earlier. The prediction also provided accurate estimates of the epidemic's trends. CONCLUSIONS: We have used only the latitude, one geographical feature affecting the spatiotemporal distribution of HFMD, to develop rules for early aberration detection and prediction. We have also demonstrated that the proposed rules performed well using real data in terms of accuracy and timeliness. Although our approach may provide helpful information for controlling epidemics and minimizing the impact of diseases, the performance could be further improved by including other influential meteorological factors in the proposed latitude-based approach, which is worth further investigation.

Effect of Meteorological and Geographical Factors on the Epidemics of Hand, Foot, and Mouth Disease in Island-Type Territory, East Asia.

Hand, foot, and mouth disease (HFMD) has threatened East Asia for more than three decades and has become an important public health issue owing to its severe sequelae and mortality among children. The lack of effective treatment and vaccine for HFMD highlights the urgent need for efficiently integrated early warning surveillance systems in the region. In this study, we try to integrate the available surveillance and weather data in East Asia to elucidate possible spatiotemporal correlations and weather conditions among different areas from low to high latitude. The general additive model (GAM) was applied to understand the association between HFMD and latitude, as well as meteorological factors for islands in East Asia, namely, Japan, Taiwan, Hong Kong, and Singapore, from 2012 to 2014. The results revealed that latitude was the most important explanatory factor associated with the timing and amplitude of HFMD epidemics (P < 0.0001). Meteorological factors including higher dew point, lower visibility, and lower wind speed were significantly associated with the rise of epidemics (P < 0.01). In summary, weather conditions and geographic location could play some role in affecting HFMD epidemics. Regional integrated surveillance of HFMD in East Asia is needed for mitigating the disease risk.

[Correlation of Fms-like tyrosine kinase 3 (FLT3) gene expression to FLT3/internal tandem duplication mutation in peripheral blood of acute myeloid leukemia.].

BACKGROUND AND OBJECTIVE: Fms-like tyrosine kinase 3 internal tandem duplication (FLT3/ITD) is associated with an unfavorable prognosis in acute myeloid leukemia (AML). However, the role of FLT3 expression as well as its correlation to FLT3/ITD has not sufficiently studied. This study was to evaluate the relationship between FLT3 gene expression and FLT3/ITD mutation in patients with de novo AML. METHODS: FLT3 gene expression was determined by real-time quantitative polymerase chain reaction (RQ-PCR). FLT3/ITD mutation was detected by PCR in 79 de novo AML patients. RESULTS: FLT3/ITD mutations were found in 22.8% (18/79) patients. FLT3 gene expression (range: 0-7320, median: 312) was detected in 92.4% (73/79) patients, but not in normal controls. Compared to AML patients with low FLT3 expressers and without FLT3/ITD mutation, patients with high FLT3 expressers and FLT3/ITD mutation had a significantly higher white blood count as well as a higher ratio of bone marrow blasts. The positive rate of FLT3/ITD mutation was not correlated to the level of FLT3 expression, and no statistical difference of FLT3 expression was found between AML patients with and without FLT3/ITD mutation. The complete remission (CR) rate of AML patients with FLT3/ITD mutation (58.8%) was significance lower than that of those without FLT3/ITD mutation (82.1%). In AML patients without FLT3/ITD mutation, the CR rate was significantly lower in patients with high FLT3 expressers (69.2%) than in those with low FLT3 expressers (93.3%). CONCLUSION: The FLT3 expression is not associated with FLT3/ITD mutation. High-FLT3 expression may be a poor prognostic factor for AML patients without FLT3/ITD mutation.

[The significance of quantification of MDR1 and WT1 gene expression in acute myeloid leukemia].

OBJECTIVE: To study the quantification of MDR1 and WT1 gene expression in patients with de novo acute myeloid leukemia (AML) and to explore the role of these two genes in clinical drug resistance and their correlation with risk stratification. METHODS: A real time quantitative reverse transcriptase polymerase chain reaction method was established for detecting MDR1 and WT1 gene expression levels in 63 de novo AML patients. RESULTS: The expression of WT1 and MDR1 was significantly higher in de novo AML patients than in normal controls (P < 0.001). WT1 levels were significantly correlated with corresponding levels of MDR1 gene in de novo AML patients (P = 0.004). Expression levels of WT1 and MDR1 gene were not associated with FAB subtype and risk stratification (P > 0.05). AML patients with FLT3-ITD mutations had a significantly higher WT1 expression level as compared to with those without (P < 0.05), on the contrary MDR1 expression was not associated with FLT3-ITD mutations (P > 0.05). Patients with co-expression of high levels of WT1 and MDR1 had a significantly lower complete remission rate after induction therapy than those with low levels (P < 0.05). CONCLUSION: There is a positive correlation between MDR1 gene expression and WT1 gene expression in AML. Quantification of the two gene expression together is more effective for judgement of prognosis in AML.

Detection of FLT3 gene and FLT3/ITD mutation by polymerase chain reaction-single-strand conformation polymorphism in patients with acute lymphoblastic leukemia.

OBJECTIVE: To analyze Fms-like tyrosine kinase 3 (FLT3) gene and FLT3 internal tandem duplication (ITD) mutation in acute lymphoblastic leukemia (ALL) patients of different immunological subtypes. METHODS: Polymerase chain reaction-single-strand conformation polymorphism (PCR-SSCP) was used to detect FLT3 gene and FLT3/ITD mutation in 63 ALL cases. RESULTS: Among the 63 ALL cases, FLT3 gene was detected in 41 (61.5%) cases. The positivity rate of FLT3 gene in pre-pre B-lineage ALL, pre-B-ALL, B-lineage ALL and T-lineage ALL cases were 93.3% (14/15), 77.8% (14/18), 41.7% (5/12) and 28.6% (4/14), respectively. The positivity rate of FLT3 gene was significantly higher in pre-pre B-ALL/pre B-ALL subtypes (84.8%) than in B-ALL subtypes (41.7%, P<0.005), and the rate was significantly higher in B-ALL subtypes (73.3%) than in T-ALL subtypes (28.6%, P<0.001). Two cases (3.2%) were found to have FLT3/ITD mutation, which were also positive for myeloid antigen expression and diagnosed as acute mixed-lineage leukemia, showing leukocytosis and high percentage of bone marrow blast cells with poor prognosis. CONCLUSIONS: FLT3 gene can be detected in both B-and T-lineage ALL patients, but more frequently in the former. In B-lineage ALL patients, FLT3 gene is more frequent in cases with undifferentiated than those with differentiated blast cells. FLT3/ITD is rarely detected in ALL patients and FLT3/ITD mutation detection might be helpful to identify the genotypes and evaluate the prognosis of acute leukemia.