HiMIC-Monthly: A 1 km high-resolution atmospheric moisture index collection over China, 2003-2020

Near-surface atmospheric moisture is a key environmental and hydro-climatic variable that has significant implications for the natural and human systems. However, high-resolution moisture data are severely lacking for fine-scale studies. Here, we develop the first 1 km high spatial resolution dataset of monthly moisture index collection in China (HiMIC-Monthly) over a long period of 2003~2020. HiMIC-Monthly is generated by the light gradient boosting machine algorithm (LightGBM) based on observations at 2,419 weather stations and multiple covariates, including land surface temperature, vapor pressure, land cover, impervious surface proportion, population density, and topography. This collection includes six commonly used moisture indices, enabling fine-scale assessment of moisture conditions from different perspectives. Results show that the HiMIC-Monthly dataset has a good performance, with R2 values for all six moisture indices exceeding 0.96 and root mean square error and mean absolute error values within a reasonable range. The dataset exhibits high consistency with in situ observations over various spatial and temporal regimes, demonstrating broad applicability and strong reliability.

The Burden of Occupational Noise-Induced Hearing Loss From 1990 to 2019: An Analysis of Global Burden of Disease Data

OBJECTIVES

The relationship between long-term exposure to occupational noise and hearing loss has been extensively documented. We aimed to assess spatial and temporal changes in the burden of occupational noise-induced hearing loss (ONIHL) in 204 countries and territories with varying socio-demographic indexes (SDI) from 1990 to 2019.

DESIGN

Temporal and spatial trends in age-standardized disability-adjusted life year rates (ASDR) for ONIHL were estimated by sex, age, SDI level, country, and geographic region from 1990 to 2019. We used the Joinpoint model to calculate annual average percentage changes to assess such trends and projected trends in ASDR for ONIHL globally and across different income regions from 2020 to 2044 using an age-period-cohort model. We fitted the relationship between ASDR and SDI, ASDR and healthcare access and quality index, respectively.

RESULTS

Overall, the global burden of ONIHL has decreased since 1990, especially in middle and lower SDI regions. In 2019, the global ASDR for ONIHL was 84.23 (95% confidence interval: 57.46 to 120.52) per 100,000 population. From 1990 to 2019, the global ASDR for ONIHL decreased by 1.72% (annual average percentage change = -0.05, 95% confidence interval: -0.07 to -0.03). Our projections showed a decreasing trend in the global ONIHL burden until 2044. ASDR and SDI (R = -0.8, p < 0.05), ASDR and healthcare access and quality index (R = -0.75, p < 0.05) showed significant negative correlations.

CONCLUSIONS

The global ONIHL burden has decreased over the past three decades, especially in regions with middle and lower SDI levels. However, the global ONIHL burden still remained severe in 2019, notably among males, the middle-aged and elderly, and regions with lower SDI levels.

Association of residential greenness with obstructive sleep apnea among Chinese old adults and the mediation role of PM2.5 and leisure-time physical activity

Few studies have investigated the association of residential greenness with obstructive sleep apnea (OSA). This study was to comprehensively examine the association of residential greenness exposure with OSA and explore the mediating effect of leisure-time physical activity (LTPA) and PM2.5 on the association among Chinese old adults. A prospective cohort study that enrolled 2027 adults aged ≥65 was conducted between 1st July 2015 and 30th September 2019 in Southern China. OSA was ascertained by Berlin Questionnaire. Greenness exposure was measured by contemporaneous and cumulative average normalized difference vegetation index (NDVI) in the 1000 m radius around each participant's residential address. Hazard ratios (HRs) with 95 % confidence intervals (CIs) were calculated by Cox proportional hazards model to assess the impact of greenness exposure on the incidence of OSA after adjusting for confounders. LTPA and PM2.5 were examined as potential mediators in the aforementioned models. A total of 293, nearly 14.5 %, participants developed OSA within 59,251 person-months of follow-up. When comparing the highest with lowest tertiles, both contemporaneous NDVI (>0.351 vs. ≤0.325: HR = 0.20, 95 % CI = 0.13-0.31) and cumulative NDVI (> 0.346 vs. ≤ 0.317: HR = 0.32, 95 % CI = 0.21-0.47) were associated with a reduced risk of OSA after adjusting for confounders. LTPA and PM2.5 significantly mediated the association between greenness and OSA. In conclusion, this study indicated that exposure to higher residential greenness could decrease OSA risk, and this benefit may be achieved by promoting physical activity and decreasing PM2.5 concentration. The findings suggest to formulate targeted interventional strategies by expanding residential greenness to prevent OSA and reduce disease burden.

Impact of heat on emergency hospital admissions related to kidney diseases in Texas: Uncovering racial disparities

BACKGROUND AND OBJECTIVE

While impact of heat exposure on human health is well-documented, limited research exists on its effect on kidney disease hospital admissions especially in Texas, a state with diverse demographics and a high heat-related death rate. We aimed to explore the link between high temperatures and emergency kidney disease hospital admissions across 12 Texas Metropolitan Statistical Areas (MSAs) from 2004 to 2013, considering causes, age groups, and ethnic populations.

METHODS

To investigate the correlation between high temperatures and emergency hospital admissions, we utilized MSA-level hospital admission and weather data. We employed a Generalized Additive Model to calculate the association specific to each MSA, and then performed a random effects meta-analysis to estimate the overall correlation. Analyses were stratified by age groups, admission causes, and racial/ethnic disparities. Sensitivity analysis involved lag modifications and ozone inclusion in the model.

RESULTS

Our analysis found that each 1 °C increase in temperature was associated with a 1.73 % (95 % CI [1.43, 2.03]) increase in hospital admissions related to all types of kidney diseases. Besides, the effect estimates varied across different age groups and specific types of kidney diseases. We observed statistically significant associations between high temperatures and emergency hospital admissions for Acute Kidney Injury (AKI) (3.34 % (95 % CI [2.86, 3.82])), Kidney Stone (1.76 % (95 % CI [0.94, 2.60])), and Urinary Tract Infections (UTI) (1.06 % (95 % CI [0.61, 1.51])). Our research findings indicate disparities in certain Metropolitan Statistical Areas (MSAs). In Austin, Houston, San Antonio, and Dallas metropolitan areas, the estimated effects are more pronounced for African Americans when compared to the White population. Additionally, in Dallas, Houston, El Paso, and San Antonio, the estimated effects are greater for the Hispanic group compared to the Non-Hispanic group.

CONCLUSIONS

This study finds a strong link between higher temperatures and kidney disease-related hospital admissions in Texas, especially for AKI. Public health actions are necessary to address these temperature-related health risks, including targeted kidney health initiatives. More research is needed to understand the mechanisms and address health disparities among racial/ethnic groups.

Protocol for a pragmatic cluster randomised controlled trial to evaluate the effectiveness of digital health interventions in improving non-communicable disease management during the pandemic in rural Pakistan

BACKGROUND

The COVID-19 pandemic has revealed gaps in global health systems, especially in the low- and middle-income countries (LMICs). Evidence shows that patients with non-communicable diseases (NCDs) are at higher risk of contracting COVID-19 and suffering direct and indirect health consequences. Considering the future challenges such as environmental disasters and pandemics to the LMICs health systems, digital health interventions (DHI) are well poised to strengthen health care resilience. This study aims to implement and evaluate a comprehensive package of DHIs of integrated COVID-NCD care to manage NCDs in primary care facilities in rural Pakistan.

METHODS

The study is designed as a pragmatic, parallel two-arm, multi-centre, mix-methods cluster randomised controlled trial. We will randomise 30 primary care facilities in three districts of Punjab, where basic hypertension and diabetes diagnosis and treatment are provided, with a ratio of 1:1 between intervention and control. In each facility, we will recruit 50 patients who have uncontrolled hypertension. The intervention arm will receive training on an integrated COVID-NCD guideline, and will use a smartphone app-based telemedicine platform where patients can communicate with health providers and peer-supporters, along with a remote training and supervision system. Usual care will be provided in the control arm. Patients will be followed up for 10 months. Our primary indicator is systolic blood pressure measured at 10 months. A process evaluation guided by implementation science frameworks will be conducted to explore implementation questions. A cost-effectiveness evaluation will be conducted to inform future scale up in Pakistan and other LMICs.

DISCUSSION

Our study is one of the first randomised controlled trials to evaluate the effectiveness of DHIs to manage NCDs to strengthen health system resilience in LMICs. We will also evaluate the implementation process and cost-effectiveness to inform future scale-up in similar resource constrained settings.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier-NCT05699369.

Migraine and air pollution: A systematic review

OBJECTIVE

To systematically synthesize evidence from a broad range of studies on the association between air pollution and migraine.

BACKGROUND

Air pollution is a ubiquitous exposure that may trigger migraine attacks. There has been no systematic review of this possible association.

METHODS

We searched for empirical studies assessing outdoor air pollution and any quantified migraine outcomes. We included short- and long-term studies with quantified air pollution exposures. We excluded studies of indoor air pollution, perfume, or tobacco smoke. We assessed the risk of bias with the World Health Organization's bias assessment instrument for air quality guidelines.

RESULTS

The final review included 12 studies with over 4,000,000 participants. Designs included case-crossover, case-control, time series, and non-randomized pre-post intervention. Outcomes included migraine-related diagnoses, diary records, medical visits, and prescriptions. Rather than pooling the wide variety of exposures and outcomes into a meta-analysis, we tabulated the results. Point estimates above 1.00 reflected associations of increased risk. In single-pollutant models, the percent of point estimates above 1.00 were carbon monoxide 5/5 (100%), nitrogen dioxide 10/13 (78%), ozone 7/8 (88%), PM2.5 13/15 (87%), PM10 2/2 (100%), black carbon 0/1 (0%), methane 4/6 (75%), sulfur dioxide 3/5 (60%), industrial toxic waste 1/1 (100%), and proximity to oil and gas wells 6/13 (46%). In two-pollutant models, 16/17 (94%) of associations with nitrogen dioxide were above 1.00; however, more than 75% of the confidence intervals included the null value. Most studies had low to moderate risks of bias. Where differences were observed, stronger quality articles generally reported weaker associations.

CONCLUSIONS

Balancing the generally strong methodologies with the small number of studies, point estimates were mainly above 1.00 for associations of carbon monoxide, nitrogen dioxide, ozone, and particulate matter with migraine. These results were most consistent for nitrogen dioxide.

A daily high-resolution (1 km) human thermal index collection over the North China Plain from 2003 to 2020

Human-perceived temperature (HPT) describes the joint effects of multiple climatic factors such as temperature and humidity. Extreme HPT events may reduce labor capacity and cause thermal discomfort and even mortality. These events are becoming more frequent and more intense under global warming, posing severe threats to human and natural systems worldwide, particularly in populated areas with intensive human activities, e.g., the North China Plain (NCP). Therefore, a fine-scale HPT dataset in both spatial and temporal dimensions is urgently needed. Here we construct a daily high-resolution (~1 km) human thermal index collection over NCP from 2003 to 2020 (HiTIC-NCP). This dataset contains 12 HPT indices and has high accuracy with averaged determination coefficient, mean absolute error, and root mean squared error of 0.987, 0.970 °C, and 1.292 °C, respectively. Moreover, it exhibits high spatiotemporal consistency with ground-level observations. The dataset provides a reference for human thermal environment and could facilitate studies such as natural hazards, regional climate change, and urban planning.

Impact of heat on emergency hospital admission in Texas: geographic and racial/ethnic disparities

BACKGROUND

Studies exploring the racial/ethnicity disparity of the impact of heat on hospital admission are notably limited, especially in Texas, a state with a diverse population and consistently ranking among the top ten U.S. states for heat-related deaths per capita from 2018 to 2020.

OBJECTIVE

Our objective is to determine the correlation between elevated temperatures and emergency hospital admissions for various causes and age groups across 12 Metropolitan Statistical Areas(MSAs) in Texas. Additionally, we aim to investigate health inequalities in the five largest MSAs in Texas between 2004 and 2013.

METHODS

We used MSA-level hospital admission and weather data to estimate the relationship between heat and emergency hospital admissions. We applied a Generalized Additive Model and random effects meta-analysis to calculate MSA-specific associations and overall correlation, repeating the analysis for age groups and specific causes of admission. We also investigated health disparities across racial and ethnic groups and performed a sensitivity analysis.

RESULTS

The results showed that a 1 °C increase in temperature was associated with a 0.50% (95% CI [0.38%, 0.63%]) increase in all-cause emergency hospital admissions. Heat's impact on hospital admissions varied among age groups and causes, with children under 6 years showing the highest effect estimate (0.64% (95% CI [0.32%,0.96%])). Statistically significant associations were found for Cardiovascular Diseases (0.27% (95% CI [0.07%,0.47%])), Ischemic Heart Diseases (0.53% (95% CI [0.15%,0.92%])), Pneumonia (0.70% (95% CI [0.25%,1.16%])), and Respiratory Diseases (0.67% (95% CI [0.18%,1.17%])). Health disparities were found among racial and ethnic groups in the five largest MSAs.

IMPACT STATEMENT

Studies exploring the impact of heat on hospital admission in Texas are notably limited. Our research provided a comprehensive examination of the connection between heat and emergency hospital admissions throughout Texas. Furthermore, we are the first to examine racial/ethnic disparities, identifying African American and Hispanic groups as disproportionately affected. These insights provide valuable insights for policymakers to allocate resources and implement strategies to mitigate the negative consequences of rising temperatures.

Effects of long-term ambient air pollution exposure on township-level pulmonary tuberculosis notification rates during 2005-2017 in Ningxia, China

Studies examining long-term effects of ambient air pollution exposure, measured as annual averages, on pulmonary tuberculosis (TB) incidence are scarce, particularly in endemic, rural settings. We performed a small-area study in Ningxia Hui Autonomous Region (NHAR), a high TB-burden area in rural China, using township-level (n = 358 non-overlapping townships) annual TB notification data (2005-2017). We aimed to determine if annual average concentrations of ambient air pollution (particulate matter <2·5 μm [PM_2·5], nitrogen dioxide [NO₂] ozone [O₃]) were associated with TB notification rates (as a proxy for incidence). Air pollution effects on TB notification rates at township-level were estimated as incidence rate ratios (IRR), fitted using a generalised estimating equation (GEE) adjusted for covariates (age, sex, occupation, education, ethnicity, remoteness [urban or rural], household crowding and solid fuel use). A total of 38,942 TB notifications were reported in NHAR between 2005 and 2017. The mean annual TB notification rate was 67 (standard deviation [SD]; 7) per 100,000 people. Median concentrations of PM_2·5, NO₂, and O₃ were 42 μg/m³ (interquartile range [IQR]; 38-48 μg/m³), 15 ppb (IQR; 12-16 ppb), and 56 ppb (IQR; 56-57 ppb), respectively. In single pollutant models, adjusted for covariates, an interquartile range (IQR) increase (10 μg/m³) in PM_2·5 was significantly associated with higher TB notification rates (IRR: 1∙35; 95% CI: 1·25-1·48). Comparable effects on notifications of TB were observed for increases in NO₂ exposure (IRR: 1·20 per IQR (4 ppb) increase; 95% CI: 1·08-1·31). Ground-level ozone was not associated with TB notification rate in any models. The observed effects were consistent over time, in multi-pollutant models, and appeared robust to additional adjustment for indicators of household crowding, solid fuel use and remoteness. More rigorous study designs are needed to understand if improving air quality has population-level benefits on TB disease incidence in endemic settings.

Development and Validation of a Sub-National, Satellite-Based Land-Use Regression Model for Annual Nitrogen Dioxide Concentrations in North-Western China

Existing national- or continental-scale models of nitrogen dioxide (NO₂) exposure have a limited capacity to capture subnational spatial variability in sparsely-populated parts of the world where NO₂ sources may vary. To test and validate our approach, we developed a land-use regression (LUR) model for NO₂ for Ningxia Hui Autonomous Region (NHAR) and surrounding areas, a small rural province in north-western China. Using hourly NO₂ measurements from 105 continuous monitoring sites in 2019, a supervised, forward addition, linear regression approach was adopted to develop the model, assessing 270 potential predictor variables, including tropospheric NO₂, optically measured by the Aura satellite. The final model was cross-validated (5-fold cross validation), and its historical performance (back to 2014) assessed using 41 independent monitoring sites not used for model development. The final model captured 63% of annual NO₂ in NHAR (RMSE: 6 ppb (21% of the mean of all monitoring sites)) and contiguous parts of Inner Mongolia, Gansu, and Shaanxi Provinces. Cross-validation and independent evaluation against historical data yielded adjusted R² values that were 1% and 10% lower than the model development values, respectively, with comparable RMSE. The findings suggest that a parsimonious, satellite-based LUR model is robust and can be used to capture spatial contrasts in annual NO₂ in the relatively sparsely-populated areas in NHAR and neighbouring provinces.

Effect modification of greenness on PM2.5 associated all-cause mortality in a multidrug-resistant tuberculosis cohort

RATIONALE

Evidence for the association between fine particulate matter (PM_2.5) and mortality among patients with tuberculosis (TB) is limited. Whether greenness protects air pollution-related mortality among patients with multidrug-resistant tuberculosis (MDR-TB) is completely unknown.

METHODS

2305 patients reported in Zhejiang and Ningxia were followed up from MDR-TB diagnosis until death, loss to follow-up or end of the study (31 December 2019), with an average follow-up of 1724 days per patient. 16-day averages of contemporaneous Normalised Difference Vegetation Index (NDVI) in the 500 m buffer of patient's residence, annual average PM_2.5 and estimated oxidant capacity O_x were assigned to patients regarding their geocoded home addresses. Cox proportional hazards regression models were used to estimate HRs per 10 μg/m³ exposure to PM_2.5 and all-cause mortality among the cohort and individuals across the three tertiles, adjusting for potential covariates.

RESULTS

HRs of 1.702 (95% CI 1.680 to 1.725) and 1.169 (1.162 to 1.175) were observed for PM_2.5 associated with mortality for the full cohort and individuals with the greatest tertile of NDVI. Exposures to PM_2.5 were stronger in association with mortality for younger patients (HR 2.434 (2.432 to 2.435)), female (2.209 (1.874 to 2.845)), patients in rural (1.780 (1.731 to 1.829)) and from Ningxia (1.221 (1.078 to 1.385)). Cumulative exposures increased the HRs of PM_2.5-related mortality, while greater greenness flattened the risk with HRs reduced in 0.188-0.194 on average.

CONCLUSIONS

Individuals with MDR-TB could benefit from greenness by having attenuated associations between PM_2.5 and mortality. Improving greener space and air quality may contribute to lower the risk of mortality from TB/MDR-TB and other diseases.

Association of pre-existing comorbidities with mortality and disease severity among 167,500 individuals with COVID-19 in Canada: A population-based cohort study

Background

The novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada.

Methods and findings

We conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35–3.34; p<0.001), and the risk substantially was elevated from 2.14 (95%CI 1.76–2.60) to 4.81 (95%CI 3.95–5.85) times as the number of comorbidities increased from one to five or more. Significant predictors for mortality included comorbidities such as solid organ transplant (HR = 3.06, 95%CI 2.03–4.63; p<0.001), dementia (HR = 1.46, 95%CI 1.35–1.58; p<0.001), chronic kidney disease (HR = 1.45, 95%CI 1.34–1.57; p<0.001), severe mental illness (HR = 1.42, 95%CI%, 1.12–1.80; p<0.001), cardiovascular disease (CVD) (HR = 1.22, 95%CI, 1.15–1.30), diabetes (HR = 1.19, 95%, 1.12–1.26; p<0.001), chronic obstructive pulmonary disease (COPD) (HR = 1.19, 95%CI 1.12–1.26; p<0.001), cancer (HR = 1.17, 95%CI, 1.09–1.27; p<0.001), hypertension (HR = 1.16, 95%CI, 1.07–1.26; p<0.001). Compared to their effect in older age groups, comorbidities were associated with higher risk of mortality and severity in individuals under 50 years old. Individuals with five or more comorbidities in the below 50 years age group had 395.44 (95%CI, 57.93–2699.44, p<0.001) times higher risk of mortality compared to those without. Limitations include that data were collected during 2020 when the new variants of concern were not predominant, and that the ICES databases do not contain detailed individual-level socioeconomic and racial variables.

Conclusion

We found that solid organ transplant, dementia, chronic kidney disease, severe mental illness, CVD, hypertension, COPD, cancer, diabetes, rheumatoid arthritis, HIV, and asthma were associated with mortality or severity. Our study highlights that the number of comorbidities was a strong risk factor for deaths and severe outcomes among younger individuals with COVID-19. Our findings suggest that in addition of prioritizing by age, vaccination priority groups should also include younger population with multiple comorbidities.

Effects of high-frequency temperature variabilities on the morbidity of chronic obstructive pulmonary disease: Evidence in 21 cities of Guangdong, South China

BACKGROUND

While temperature changes have been confirmed as one of the contributory factors affecting human health, the association between high-frequency temperature variability (HFTV, i.e., temperature variation at short time scales such as 1, 2, and 5 days) and the hospitalization of chronic obstructive pulmonary disease (COPD) was rarely reported.

OBJECTIVES

To evaluate the associations between high-frequency temperature variabilities (i.e., at 1, 2, and 5-day scales) and daily COPD hospitalization.

METHODS

We collected daily records of COPD hospitalization and meteorological variables from 2013 to 2017 in 21 cities of Guangdong Province, South China. A quasi-Poisson regression with a distributed lag nonlinear model was first employed to quantify the effects of two HFTV measures, i.e., the day-to-day (DTD) temperature change and the intraday-interday temperature variability (IITV), on COPD morbidity for each city. Second, we used multivariate meta-analysis to pool the city-specific estimates, and stratified analyses were performed by age and sex to identify vulnerable groups. Then, the meta-regression with city-level characteristics was employed to detect the potential sources of the differences among 21 cities.

RESULTS

A monotonic increasing curve of the overall exposure-response association was observed, suggesting that positive HFTV (i.e., increased DTD and IITV) will significantly increase the risk of COPD admission. Negative DTD was associated with reduced COPD morbidity while positive DTD elevated the COPD risk. An interquartile range (IQR) increase in DTD was associated with a 24% (95% CI: 12-38%) increase in COPD admissions. An IQR increase in IITV_0-1 was associated with 18% (95% CI: 7-27%) increase in COPD admissions. Males and people aged 0-64 years appeared to be more vulnerable to the DTD effect than others. Potential sources of the disparity among different cities include urbanization level, sex structure, industry structure, gross domestic product (GDP), health care services, and air quality.

CONCLUSIONS

The increases of DTD and IITV have significant adverse impacts on COPD hospitalization. As climate change intensifies, precautions need to be taken to mitigate the impacts of high-frequency temperature changes.

Greenness exposure and all-cause mortality during multi-drug resistant tuberculosis treatment: A population-based cohort study

BACKGROUND

Living closer to greenness were thought to benefit various health outcomes. We aimed to assess the association between residential greenness and mortality among patients undergoing multidrug resistant tuberculosis (MDR-TB) treatment.

METHODS

We enrolled all local MDR-TB patients reported in Zhejiang, China from 2009 to 2017 and followed them throughout the treatment. We calculated the contemporaneous normalized difference vegetation index (NDVI) in the 250 and 500 m radius around patient's residence. Cox proportional hazards regression models with time-varying NDVI were used to assess the impact of greenness exposure on all-cause mortality during MDR-TB treatment, adjusting for potential individual and contextual covariates.

RESULTS

We ascertained 1,621 active MDR-TB cases, which contributed 3036 person-years at risk with an average follow-up of 684 days (s.d. 149 days) per patient. Among them, there were 163 deaths during follow-up, representing a crude mortality rate of 537 deaths per 10,000 person-years. Patients exposed to the second quintile (Q2) of greenness within the 500 m buffer had around 64% reduced mortality risk over the lowest quintile of greenness with hazard ratio (HR) = 0.364 (95% CI: 0.109-1.22). In lower nighttime light (NTL) areas, the hazard ratios (HR) per quintile increase in NDVI within the 500 m buffer were Q2: 0.35 (95% CI: 0.10-1.18), Q3: 0.24 (95% CI: 0.09-0.66), Q4: 0.26 (95% CI: 0.10-0.69), and Q5: 0.26 (95% CI: 0.10-0.71) relevant to the lowest quintile Q1, with a trend of p-value ≤0.01. Patients who were female, younger (<60 years), resided in urban areas, or had high PM_2.5 (i.e. particles with diagram ≤2.5 μm) exposure were more likely to benefit from greenness exposure. Associations were neither observed with NDVI in the 250 m buffer nor for patients living in higher NTL areas. There was a non-linear exposure-response relationship between greenness and deaths with p-value ≤0.05.

CONCLUSION

Increasing greenness exposure along with medical treatment reduces all-cause mortality among patients living in lower NTL areas.

Geographical disparities in access to hospital care in Ontario, Canada: a spatial coverage modelling approach

OBJECTIVES

Previous studies on geographical disparities in healthcare access have been limited by not accounting for the healthcare provider's capacity, a key determinant of supply and demand relationships.

DESIGN

This study proposed a spatial coverage modelling approach to evaluate disparities in hospital care access using Canadian Institute for Health Information data in 2007.

SETTING

This study focusses on accessibility of inpatient and emergency cares at both levels of individual hospital and the administrative regions of Local Health Integration Network (LHIN) levels.

MEASURES

We integrated a set of traffic and geographical data to precisely estimate travel time as a measure of the level of accessibility to the nearest hospital by three scenarios: walking, driving and a combination of the both. We estimated population coverage rates, using hospital capacities and population in the catchments, as a measure of the level of the healthcare availability. Hospital capacities were calculated based on numbers of medical staff and beds, occupation rates and annual working hours of healthcare providers.

RESULTS

We observed significant disparities in hospital capacity, travel time and population coverage rate across the LHINs. This study included 25 teaching and 148 community hospitals. The teaching hospitals had stronger capacities with 489 209 inpatient and 130 773 emergency patients served in the year, while the population served in community hospitals were 2.64 times higher. Compared with north Ontario, more locations in the south could reach to hospitals within 30 min irrespective of the travel mode. Additionally, Northern Ontario has higher population coverage rates, for example, with 42.6~46.9% for inpatient and 15.7~44% for emergency cares, compared with 2.4~34.7% and 0.35~14.6% in Southern Ontario, within a 30 min catchment by driving.

CONCLUSION

Creating a comprehensive, flexible and integrated healthcare system should be considered as an effective approach to improve equity in access to care.

Contribution of urbanization to the changes in extreme climate events in urban agglomerations across China

Unprecedented urbanization in China facilitates the rapid development of urban agglomerations (UAs) and may exert prominent effects on regional climate and environment change. By analyzing a set of 27 extreme temperature and precipitation indices, this study examines the changes in extreme climate events in 20 UAs in China and evaluates the urbanization effects using a dynamic classification of urban and rural stations by time-varying land use/cover maps. The regional differences of the urbanization effects on extreme climate events are also investigated by a k-means clustering. It is found that, for both temperature and precipitation extremes, the urban and rural areas exhibit remarkably distinct changes and demonstrate significant urbanization effect, which also varies across different climate backgrounds. Urbanization profoundly contributes to increasing hot extremes and reducing cold extremes in most UAs, while it seems to pose the opposite effects in several UAs of arid and high-latitude regions. On average, the urbanization effect accounts for around 30% of the total change in extreme temperature events over the urban core areas of 20 UAs. On the other hand, the urbanization effects on extreme precipitation indices display stronger regional discrepancies than temperature extremes. Urbanization tends to have weakening effects on extreme precipitation events in UAs over coastal regions and intensifying influences on those in central/west China. It causes more (less) frequent and more (less) intense precipitation in UAs of inland central/west (coastal) areas. Our findings provide a systematic understanding of the urbanization effects on extreme climate and may have important implications for the mitigation of urban disasters.

Effects of urbanization on winter wind chill conditions over China

Human-perceived wind chill describes the combined effects of wind velocity and low temperature, strongly related to human health and natural environment. Although long-term trends in the air or ambient temperature over China under global warming have been well studied in the literature, the changes in human-perceived wind chill conditions, especially under possible urbanization effects, are still not completely known. This paper investigates the changes of wind chill over China and quantifies the associated urbanization effect by examining nearly 2000 meteorological stations during 1961-2014 using the generalized additive model (GAM). Results show that the winter wind chill temperature (WCT) in China exhibits more prominent raising trends than the air temperature, i.e., 0.623 and 0.349 °C per decade, respectively. The wind speed (V) and wind chill days (WCD) decreased by 0.149 m/s and 1.970 days per decade, respectively. These trends become more substantial in densely populated and highly urbanized areas such as the North China Plain. The expansion of urban built-up area induces additional warming (reducing) to the increase (decrease) in WCT (WCD). On average, an increase from 0% to 100% in the urban fraction induced 0.290 ± 0.067 °C higher WCT (± denotes the 95% confidence interval), along with a reduction in V and WCD by 0.052 ± 0.014 m/s and 3.513 ± 0.387 days, respectively; whereas, the presence of the grassland and forest significantly diminishes the WCT and increases the WCD and surface V. It is expected that wind chill over China tends to be weakened under glocal warming and local urbanization in the near future. Our results have important implications for climate change mitigation, urban planning, landscape design, and air pollution abatement.

Transmission of multidrug-resistant tuberculosis in Shanghai: roles of residential status

SETTING

Shanghai is a mega city where 39% of the population comprises internal migrants.

OBJECTIVE

To examine the different roles played by migrants and permanent residents in the transmission of multidrug-resistant tuberculosis (MDR-TB).

DESIGN

We conducted a population-based cohort study to assess MDR-TB transmission in Shanghai between 1 January 2009 and 31 December 2012 using genotyping and geospatial analyses.

RESULTS

A total of 367 MDR-TB cases formed the study cohort. Significant differences between MDR-TB cases who were internal migrants and those who were permanent residents were found with regard to age, sex, region, genetic characteristics and treatment outcomes. Permanent residents had a higher transmission rate than internal migrants (OR 3.36, 95%CI 1.86-6.09). Permanent residents and genotypic clustering cases had similar clusters in central downtown and some parts of suburban areas. Most of the clusters of internal migrants were found in rural areas bordering suburban areas. Clusters of genotypic non-clustering cases showed patterns that closely matched those of internal migrants, suggesting acquired drug resistance in migrants.

CONCLUSION

In Shanghai, permanent residents were significantly associated with recent transmission of MDR-TB in central downtown areas. Clustered cases of internal migrants in rural areas were most likely to have contracted MDR-TB through acquired resistance.

A systematic literature review and critical appraisal of epidemiological studies on outdoor air pollution and tuberculosis outcomes

Ambient air pollution is the leading environmental risk factor for disease globally. Air pollutants can increase the risk of some respiratory infections, but their effects on tuberculosis (TB) are unclear. In this systematic literature review, we aimed to assess epidemiological studies on the association between outdoor air pollutants and TB incidence, hospital admissions and death (collectively referred to here as 'TB outcomes'). We sought to consolidate available evidence on this topic and propose recommendations for future studies. Following PRISMA guidelines, we searched PubMed, Web of Science, Google Scholar, and Scopus with no restrictions imposed on year of publication. A total of 11 epidemiological studies, performed in Asia, Europe and North America, met our inclusion criteria (combined sample size: 215,337 people). We extracted key study characteristics from each eligible publication, including design, exposure assessment, analytical approaches and effect estimates. The studies were assessed for overall quality and risk of bias using standard criteria. The pollutant most frequently associated with statistically significant effects on TB outcomes was fine particulate matter ( < 2.5 µm; PM_2.5); 6/11 studies assessed PM_2.5, of which 4/6 demonstrated a significant association). There was some evidence of significant associations between PM₁₀ ( < 10 µm), nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) and TB outcomes, but these associations were inconsistent. The existing epidemiological evidence is limited and shows mixed results. However, it is plausible that exposure to air pollutants, particularly PM_2.5, may suppress important immune defence mechanisms, increasing an individual's susceptibility to development of active TB and TB-related mortality. Considering the small number of studies relative to the demonstrably large global health burdens of air pollution and TB, further research is required to corroborate the findings in the current literature. Based on a critical assessment of existing evidence, we conclude with methodological suggestions for future studies.

Mild weather changes over China during 1971-2014: Climatology, trends, and interannual variability

While previous studies largely focus on extreme events, little is known about the behaviors of mild weather, a positive and pleasant condition occurring frequently, directly associated with outdoor activities, and highly relatable to the public. Here we examine the climatological characteristics and long-term trends of mild weather over China during 1971–2014, as well as the possible linkage with the El Niño−Southern Oscillation. It is found that, on average, China experiences 94.5 days (25.4% of all days) of mild weather in a year, and the annual number of mild days increased by 1.02% per decade (3.73 days per decade) during 1971–2014, especially in summer (1.54% per decade), spring (1.49% per decade), and autumn (1.03% per decade). We also find that most parts of China have been experiencing increasing mild weather in 1971–1998 but decreasing in 1998–2014. Clustering analysis reveals six subregions that exhibit distinct mild weather behaviors. In particular, harsh seasons (i.e., summer of southern China and winter of northern China) are becoming even less pleasant. Besides these secular trends, it is also noticed that El Niño event in the preceding winter is followed by less pleasant spring and summer and more pleasant autumn and winter in most areas of China. The results reported here have significant implications for urban planners and governmental policymakers.

Traffic-related air pollution induces non-allergic eosinophilic airway inflammation and cough hypersensitivity in guinea-pigs

BACKGROUND

The pathogenesis and pathophysiology of eosinophilia-related chronic cough such as non-asthmatic eosinophilic bronchitis and cough variant asthma are still not clear.

OBJECTIVE

This study is to examine the potential role of traffic-related air pollution (TRAP) in eosinophilic inflammation and cough responses.

METHODS

Non-sensitized guinea-pigs were exposed to TRAP in an urban traffic tunnel or kept in a filtered air environment for 7 or 14 days. Reflexive cough was measured using citric acid and allyl isothiocyanate (AITC) challenges, respectively. Spontaneous cough counting was determined using audio recording and a waveform analysis. Airway inflammation was evaluated using differential cells in bronchoalveolar lavage fluid (BALF) and lung histopathology. To further elucidate the relationship between airway inflammation and cough hypersensitivity, a subgroup of those exposed for 14 days received a dexamethasone treatment.

RESULTS

Compared to reflexive cough count (mean (95% confidence interval) in 10 minutes) provoked by the AITC challenge for the unexposed animals (3.1 (1.7-4.5)), those were increased significantly following both the 7-day (12.0 (6.8-17.2), P < 0.01) and the 14-day (12.0 (6.4-17.6), P < 0.01) TRAP exposure. The effect provoked by the citric acid challenge was more profound following the 14-day exposure (26.0 (19.5-32.5) vs 3.8 (1.5-6.0) for the control, P < 0.001). TRAP exposures enhanced spontaneous cough events, caused a significant increase of eosinophils and neutrophils in BALF and resulted in a dramatic eosinophilic infiltration in submucosal layer of trachea and bronchus, which can be inhibited significantly by dexamethasone treatment.

CONCLUSIONS & CLINICAL RELEVANCE

TRAP exposures induced cough hypersensitivity and non-allergic eosinophilic inflammation of airways in guinea-pigs. This study highlights the potential mechanisms of eosinophilia-related chronic cough that can be induced by traffic-related air pollution.

Differential effects of size-specific particulate matter on emergency department visits for respiratory and cardiovascular diseases in Guangzhou, China

BACKGROUND

Studies differentiating the cardiorespiratory morbidity effects of PM_2.5, PM₁₀, and PM_2.5∼10 (i.e. coarse PM or PMc) are still limited and inconsistent.

OBJECTIVE

To estimate the acute, cumulative, and harvesting effects of exposure to the three size-specific PM on cardiorespiratory morbidity, and their concentration-response relations.

METHODS

A total of 6,727,439 emergency department (ED) visits were collected from 16 public teaching hospitals in Guangzhou, from January 1st 2012 to December 31st 2015, among which over 2.1 million were asthma, COPD, pneumonia, respiratory tract infection (RTI), hypertension, stroke, and coronary heart disease (CHD). Distributed lag non-linear models (DLNM) was used to estimate the associations between the three size-specific PM and ED visits for the cardiovascular diseases. Long-term trends, seasonality, influenza epidemics, meteorological factors, and other gas pollutants, including SO2, NO₂, and O₃, were adjusted. We stratified the analyses by gender and age.

RESULTS

Elevated PM_2.5 and PM₁₀ were significantly associated with increased ED visits for pneumonia, RTI, and CHD at both lag₀ and lag_0-3. A 10 μg/m³ increment of PMc (at lag_0-14) was estimated to increase ED visits for pneumonia by 6.32% (95% CI, 4.19, 8.49) and for RTI by 4.72% (95% CI, 3.81, 5.63), respectively. PMc showed stronger cumulative effects on asthma in children than elderly. We observed significant harvesting effects (i.e. morbidity displacements) of the three size-specific PM on respiratory but very little on cardiovascular ED visits. The concentration-response curves suggested non-linear relations between exposures to the three different sizes of PM and respiratory morbidity.

CONCLUSIONS

Overall, the three size-specific PM demonstrated distinct acute and cumulative effects on the cardiorespiratory diseases. PM_2.5 and PMc would have significant effects on pneumonia and RTI. Strategies should be considered to further reduce levels of ambient PM_2.5 and PMc.

Ambient sulfur dioxide levels associated with reduced risk of initial outpatient visits for tuberculosis: A population based time series analysis

BACKGROUND

Recent biochemical studies suggest that exogenous sulfur dioxide (SO₂) at low concentrations may have been beneficial in inhibiting mycobacteria tuberculosis (TB) growth. However, there is a dearth of population-based studies.

OBJECTIVES

To examine the association of ambient SO₂ levels and initial TB outpatient visits.

METHODS

In Ningbo, China, we collected all daily initial outpatient visits for TB and routinely air pollution monitoring data between January 2009 and December 2013. A time-series study was conducted by using generalized additive regression (GAM) with log-linear Poisson models to estimate the associations between daily initial TB outpatient visits and daily average concentration of SO_2. Other traffic-related co-pollutants were adjusted. Sensitivity analyses were conducted to examine the relationship when 1% extreme SO₂ concentrations excluded or if related to the early onsets of TB symptoms.

RESULTS

SO₂ concentrations in Ningbo were low with a daily average of 25 μg/m³ (i.e. 0.0089 ppm). Negative associations were identified between ambient SO₂ concentrations and daily initial TB outpatient visits. A 10 μg/m³ increase in SO₂ at lag₃ and lag_0-3 days were associated with -2.0% (95%CI, -3.2, -0.8) and -4.6% (95%CI, -6.8, -2.4) changes, respectively, in initial TB outpatient visits according to single-pollutant models. The negative association became stronger when nitrogen dioxide (NO₂) or particulate matter with aerodynamic diameter less than 10 μm (PM₁₀) was adjusted in two-pollutant models. This association was higher in males vs. females and in middle-aged adults vs. the elderly. We found a stronger negative association between SO₂ concentration and the initial symptom occurrence.

CONCLUSION

Short-term exposure to ambient SO₂ was associated with reduced risk of initial TB outpatient visits, suggesting acute protective effects of low-level ambient SO₂ exposure on bacteria-induced pulmonary infections.

Estimating Risks of Inapparent Avian Exposure for Human Infection: Avian Influenza Virus A (H7N9) in Zhejiang Province, China

Inapparent avian exposure was suspected for the sporadic infection of avian influenza A(H7N9) occurring in China. This type of exposure is usually unnoticed and difficult to model and measure. Infected poultry with avian influenza H7N9 virus typically remains asymptomatic, which may facilitate infection through inapparent poultry/bird exposure, especially in a country with widespread practice of backyard poultry. The present study proposed a novel approach that integrated ecological and case-control methods to quantify the risk of inapparent avian exposure on human H7N9 infection. Significant associations of the infection with chicken and goose densities, but not with duck density, were identified after adjusting for spatial clustering effects of the H7N9 cases across multiple geographic scales of neighborhood, community, district and city levels. These exposure risks varied geographically in association with proximity to rivers and lakes that were also proxies for inapparent exposure to avian-related environment. Males, elderly people, and farmers were high-risk subgroups for the virus infection. These findings enable health officials to target educational programs and awareness training in specific locations to reduce the risks of inapparent exposure.

Spatial and temporal analysis of tuberculosis in Zhejiang Province, China, 2009-2012

BACKGROUND

Tuberculosis (TB) is an infectious disease of major public health concern. The disease has demonstrated large space-time variations. This study aims to explore the space-time dynamics of TB cases in an economically and geographically dynamic province in China with specific references of TB control for policy makers.

METHODS

Data on all reported TB cases from 2009 to 2012 were collected from the TB program at the Zhejiang Provincial Center for Disease Control and Prevention. We employed time series and exploratory spatial data analyses, including Moran's I, Local Getis's G i (*) , and Kulldorff's space-time scan statistics, to identify the temporal trends and spatial patterns of TB at a county level.

RESULTS

A total of 147,941 TB cases were reported during 2009-2012 in Zhejiang. A higher proportion of TB cases were younger, male, and registered permanent residents among all TB cases notified in the province. TB cases were reported most frequently in April with small peaks in June, July, and October. This disease was spatially clustering with Moran's I values ranged from 0.29 to 0.32 (p < 0.001). A most likely cluster and ten secondary clusters were identified, mainly concentrated in the southeast and west counties of the province.

CONCLUSIONS

This study identified seasonal patterns and significant space-time clusters of TB cases in Zhejiang, China. Poverty, migration, and seasonal effects may play important roles in potential clusters.

Ambient carbon monoxide associated with reduced risk of hospital admissions for respiratory tract infections

RATIONALE

Recent experimental and clinical studies suggest that exogenous carbon monoxide (CO) at lower concentrations may have beneficial effects under certain circumstances, whereas population-based epidemiologic studies of environmentally relevant CO exposure generated mixed findings.

OBJECTIVES

To examine the acute effects of ambient CO on respiratory tract infection (RTI) hospitalizations.

METHODS

A time series study was conducted. Daily emergency hospital admission and air pollution data in Hong Kong were collected from January 2001 to December 2007. Log-linear Poisson models were used to estimate the associations between daily hospital admissions for RTI and daily average concentrations of CO across three background air monitoring stations and three roadside stations, respectively, controlling for other traffic-related copollutants.

MEASUREMENTS AND MAIN RESULTS

CO concentrations were low during the study period with a daily average of 0.6 ppm in background stations and 1.0 ppm in roadside stations. Negative associations were found between ambient CO concentrations and daily hospital admissions for RTI. One ppm increase in background CO at lag 0-2 days was associated with -5.7% (95% confidence interval, -9.2 to -2.1) change in RTI admissions from the whole population according to single-pollutant model; the negative association became stronger when nitrogen dioxide or particulate matter with aerodynamic diameter less than 10 μm was adjusted for in two-pollutant models. The negative association seemed to be stronger in the adults than in the children and elderly.

CONCLUSIONS

Short-term exposure to ambient CO was associated with decreased risk of hospital admissions for RTI, suggesting some acute protective effects of low ambient CO exposure on respiratory infection.

Using knowledge fusion to analyze avian influenza H5N1 in East and Southeast Asia

Highly pathogenic avian influenza (HPAI) H5N1, a disease associated with high rates of mortality in infected human populations, poses a serious threat to public health in many parts of the world. This article reports findings from a study aimed at improving our understanding of the spatial pattern of the highly pathogenic avian influenza, H5N1, risk in East-Southeast Asia where the disease is both persistent and devastating. Though many disciplines have made important contributions to our understanding of H5N1, it remains a challenge to integrate knowledge from different disciplines. This study applies genetic analysis that identifies the evolution of the H5N1 virus in space and time, epidemiological analysis that determines socio-ecological factors associated with H5N1 occurrence, and statistical analysis that identifies outbreak clusters, and then applies a methodology to formally integrate the findings of the three sets of methodologies. The present study is novel in two respects. First it makes the initiative attempt to use genetic sequences and space-time data to create a space-time phylogenetic tree to estimate and map the virus' ability to spread. Second, by integrating the results we are able to generate insights into the space-time occurrence and spread of H5N1 that we believe have a higher level of corroboration than is possible when analysis is based on only one methodology. Our research identifies links between the occurrence of H5N1 by area and a set of socio-ecological factors including altitude, population density, poultry density, and the shortest path distances to inland water, coastlines, migrating routes, railways, and roads. This study seeks to lay a solid foundation for the interdisciplinary study of this and other influenza outbreaks. It will provide substantive information for containing H5N1 outbreaks.