Health and Economic Benefits of Air Pollution Reductions in Vietnam During 2020-2021.

Objectives: This paper explores the potential reduction in the number of deaths and the corresponding economic benefits in Vietnam that could have arisen from the decreased in concentrations of particulate matter with a diameter of 2.5 µm or less (PM2.5) and nitrogen dioxide (NO2). Methods: Using Global Exposure Mortality Models, we estimated the potential health and economic benefits on people aged 25 and above across Vietnam's 63 provinces. The counterfactual scenario assumed reducing PM2.5 and NO2 concentrations to levels observed during the two COVID-19 epidemic waves in 2021 with national lockdowns and activity restrictions. Results: In 2019, PM2.5 concentrations ranged from 12.8 to 40.8 µg/m3 while NO2 concentrations ranged between 2.9 and 36.98 µg/m3. The reduced levels of PM2.5 and NO2 resulted in 3,807 (95% CI: 2,845-4,730) and 2,451 (95% CI: 2,845-4,730) avoided deaths of adults aged 25 and above due to non-injury-related causes, respectively. Considering that every prevented death represents potential tangible and intangible cost savings, reduced levels of PM2.5 and NO2 concentrations during COVID-19 restrictions would have resulted in economic benefits of $793.0 million (95% CI: 592.7-985.4) and $510.6 million (95% CI: 381.3-634.9), respectively. Conclusion: The COVID-19 lockdown led to decreased PM2.5 and NO2 concentrations, benefiting health and economy in Vietnam. Our findings highlight the potential advantages of implementing air quality control policies in the country.

Effects of Heatwaves on Hospital Admissions for Cardiovascular and Respiratory Diseases, in Southern Vietnam, 2010-2018: Time Series Analysis.

This study investigated the associations between heatwaves and daily hospital admissions for cardiovascular and respiratory diseases in two provinces in Viet Nam known to be vulnerable to droughts during 2010-2018. This study applied a time series analysis with data extracted from the electronic database of provincial hospitals and meteorological stations from the corresponding province. To eliminate over-dispersion, this time series analysis used Quasi-Poisson regression. The models were controlled for the day of the week, holiday, time trend, and relative humidity. Heatwaves were defined as the maximum temperature exceeding P90th over the period from 2010 to 2018 during at least three consecutive days. Data from 31,191 hospital admissions for respiratory diseases and 29,056 hospitalizations for cardiovascular diseases were investigated in the two provinces. Associations between hospital admissions for respiratory diseases and heatwaves in Ninh Thuan were observed at lag 2, with excess risk (ER = 8.31%, 95% confidence interval: 0.64-16.55%). However, heatwaves were negatively associated with cardiovascular diseases in Ca Mau, which was determined amongst the elderly (age above 60), ER = -7.28%, 95%CI: -13.97--0.08%. Heatwaves can be a risk factor for hospital admission due to respiratory diseases in Vietnam. Further studies need to be conducted to assert the link between heat waves and cardiovascular diseases.

Mortality benefits of reduction fine particulate matter in Vietnam, 2019.

Introduction and objectives: Studies assessing the health benefits of air pollution reduction in Vietnam are scarce. This study quantified the annual mortality burden due to PM2.5 pollution in Vietnam above the World Health Organization recommendation for community health (AQG: 5 µg/m3) and the proposed National Technical Regulation on Ambient Air Quality (proposed QCVN: 15 µg/m3). Methodology: This study applied a health impact assessment methodology with the hazard risk function for non-communicable diseases (NCDs) and lower respiratory infections (LRIs) in the Global Exposure Mortality Model (GEMM) to calculate attributable deaths, Years of Life lost, and Loss of Life expectancy at birth due to air pollution in the Vietnamese population above 25 years of age in 11 provinces. We obtained annual average PM2.5 concentrations for Vietnam in 2019 at a 3x3 km grid modeled using Mixed Linear regression and multi-data sources. Population and baseline mortality data were obtained from administrative data system in Vietnam. We reported the findings at both the provincial and smaller district levels. Results: Annual PM2.5 concentrations in all studied provinces exceeded both the AQG and the proposed QCVN. The maximum annual number of attributable deaths in the studied provinces if they had complied with WHO air quality guidelines was in Ha Noi City, with 5,090 (95%CI: 4,253-5,888) attributable deaths. At the district level, the highest annual rate of attributable deaths if the WHO recommendation for community health had been met was 104.6 (95%CI: 87.0-121.5) attributable deaths per 100,000 population in Ly Nhan (Ha Nam province). Conclusion: A much larger number of premature deaths in Vietnam could potentially be avoided by lowering the recommended air quality standard. These results highlight the need for effective clean air action plans by local authorities to reduce air pollution and improve community health.

Deep learning models for forecasting dengue fever based on climate data in Vietnam.

BACKGROUND: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. OBJECTIVE: This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change. METHODS: Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997-2013 were used to train models, which were then evaluated using data from 2014-2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). RESULTS AND DISCUSSION: LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features. CONCLUSION: This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years.

Vietnam Climate Change and Health Vulnerability and Adaptation Assessment, 2018.

BACKGROUND: The Global Climate Risk Index 2020 ranked Vietnam as the sixth country in the world most affected by climate variability and extreme weather events over the period 1999-2018. Sea level rise and extreme weather events are projected to be more severe in coming decades, which, without additional action, will increase the number of people at risk of climate-sensitive diseases, challenging the health system. This article summaries the results of a health vulnerability and adaptation (V&A) assessment conducted in Vietnam as evidences for development of the National Climate Change Health Adaptation Plan to 2030. METHODS: The assessment followed the first 4 steps outlined in the World Health Organization's Guidelines in conducting "Vulnerability and Adaptation Assessments." A framework and list of indicators were developed for semi-quantitative assessment for the period 2013 to 2017. Three sets of indicators were selected to assess the level of (1) exposure to climate change and extreme weather events, (2) health sensitivity, and (3) adaptation capacity. The indicators were rated and analyzed using a scoring system from 1 to 5. RESULTS: The results showed that climate-sensitive diseases were common, including dengue fever, diarrheal, influenza, etc, with large burdens of disease that are projected to increase. From 2013 to 2017, the level of "exposure" to climate change-related hazards of the health sector was "high" to "very high," with an average score from 3.5 to 4.4 (out of 5.0). For "health sensitivity," the scores decreased from 3.8 in 2013 to 3.5 in 2017, making the overall rating as "high." For "adaptive capacity," the scores were from 4.0 to 4.1, which meant adaptive capacity was "very low." The overall V&A rating in 2013 was "very high risk" (score 4.1) and "high risk" with scores of 3.8 in 2014 and 3.7 in 2015 to 2017. CONCLUSIONS: Adaptation actions of the health sector are urgently needed to reduce the vulnerability to climate change in coming decades. Eight adaptation solutions, among recommendations of V&A assessment, were adopted in the National Health Climate Change Adaptation Plan.

Exposure to air pollution and risk of hospitalization for cardiovascular diseases amongst Vietnamese adults: Case-crossover study.

BACKGROUND: Associations between hospital admissions and ambient air pollutants in the Vietnamese population have been reported in previous studies. However, most studies were conducted in Hanoi or Hochiminh city. We used hospital records of seven hospitals in Northern Vietnam to investigate short-term associations between ambient air pollutants and hospital admissions due to cardiovascular conditions. METHODS: We used 135'101 hospital records of residents (age ≥15) living in three provinces (Hanoi, Quang Ninh, and Phu Tho) and daily ambient air pollutant concentrations to estimate percentage changes and 95% confidence intervals for hospital admissions due to seven cardiovascular conditions per interquartile range (IQR) increases in daily ambient air pollutants. We used a time-stratified case-crossover analysis adjusting for meteorological factors, indicators of holidays and influenza epidemics. We also investigated modification of effects by age groups (<65 and ≥65), seasons (cold and hot) and hospital levels (national and province level). RESULTS: Particulate matter concentrations were positively associated with daily hospital admissions due to most cardiovascular conditions. For example, an increment in the two-day average (lag1-2) level of PM2.5 by one IQR (34.4 µg/m3) was associated with a 6.3% (95%CI: 3.0%-9.8%) increase in the daily count of admissions for ischemic heart disease in Hanoi and with 23.2% (95%CI: 11.1%-36.5%) for cardiac failure in Quang Ninh. Moreover, hospitalisations for stroke in Hanoi and cardiac failure in Phu Tho showed strong positive associations with SO2. The findings also show that estimates varied by age groups, seasons and hospital levels. CONCLUSION: Ambient air pollutants were associated with daily cardiovascular admissions in Northern Vietnam. The findings underline the important role of ambient air pollutants as a trigger of cardiovascular conditions.

Association of ambient air pollution with lengths of hospital stay for hanoi children with acute lower-respiratory infection, 2007-2016.

INTRODUCTION: The association between ambient air pollution and length of hospital stay (LOS) for children with lower-respiratory infection is unclear. MATERIALS AND METHODS: The association was examined using admission data for 75,432 children in Hanoi, aged 0-5 years, hospitalized with acute lower-respiratory infection (ALRI) and daily air pollutant levels in Hanoi between 2007 and 2016. We estimated the odds ratio of being discharged for an interquartile range (IQR) increment (IQR) of ambient pollutants during one to four days prior to admission date. We used pooled logistic regression models including a B-spline function of calendar time and terms describing the baseline odds, adjusting for meteorological factors, age, gender, residential location, week-day of admission, discharge on weekends or holidays, and number of respiratory hospitalizations one day prior to the discharge date. RESULTS: An IQR increase in O3 concentrations (85.8 µg/m3) was associated with a 5% (95%CI: 2%-8%) decrease in the odds of discharge from hospital among children with ALRI. Results were similar for PM10, but only for children aged 2-5 years. For the other pollutants, corresponding associations were close to null or in the opposite direction. For example, increase in CO was associated with shorter LOS. CONCLUSIONS: Our study provides the first investigation of the associations between lengths of hospital stays and air pollutant levels prior to hospitalization in Asian children. Increased levels of O3 prior to admission predicted prolonged hospitalizations. The inconsistencies in the findings for other pollutants call for further investigations.

Acute effects of ambient air pollution on lower respiratory infections in Hanoi children: An eight-year time series study.

BACKGROUND: Lower respiratory diseases are the most frequent causes of hospital admission in children worldwide, particularly in developing countries. Daily levels of air pollution are associated with lower respiratory diseases, as documented in many time-series studies. However, investigations in low-and-middle-income countries, such as Vietnam, remain sparse. OBJECTIVE: This study investigated the short-term association of ambient air pollution with daily counts of hospital admissions due to pneumonia, bronchitis and asthma among children aged 0-17 in Hanoi, Vietnam. We explored the impact of age, gender and season on these associations. METHODS: Daily ambient air pollution concentrations and hospital admission counts were extracted from electronic databases received from authorities in Hanoi for the years 2007-2014. The associations between outdoor air pollution levels and hospital admissions were estimated for time lags of zero up to seven days using Quasi-Poisson regression models, adjusted for seasonal variations, meteorological variables, holidays, influenza epidemics and day of week. RESULTS: All ambient air pollutants were positively associated with pneumonia hospitalizations. Significant associations were found for most pollutants except for ozone and sulfur dioxide in children aged 0-17. Increments of an interquartile range (21.9µg/m3) in the 7-day-average level of NO2 were associated with a 6.1% (95%CI 2.5% to 9.8%) increase in pneumonia hospitalizations. These associations remained stable in two-pollutant models. All pollutants other than CO were positively associated with hospitalizations for bronchitis and asthma. Associations were weaker in infants than in children aged 1-5. CONCLUSION: Strong associations between hospital admissions for lower respiratory infections and daily levels of air pollution confirm the need to adopt sustainable clean air policies in Vietnam to protect children's health.

Short-term association between ambient air pollution and pneumonia in children: A systematic review and meta-analysis of time-series and case-crossover studies.

Ambient air pollution has been associated with respiratory diseases in children. However, its effects on pediatric pneumonia have not been meta-analyzed. We conducted a systematic review and meta-analysis of the short-term association between ambient air pollution and hospitalization of children due to pneumonia. We searched the Web of Science and PubMed for indexed publications up to January 2017. Pollutant-specific excess risk percentage (ER%) and confidence intervals (CI) were estimated using random effect models for particulate matter (PM) with diameter ≤ 10 (PM10) and ≤2.5 µm (PM2.5), sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). Results were further stratified by subgroups (children under five, emergency visits versus hospital admissions, income level of study location, and exposure period). Seventeen studies were included in the meta-analysis. The ER% per 10 µg/m3 increase of pollutants was 1.5% (95% CI: 0.6%-2.4%) for PM10 and 1.8% (95% CI: 0.5%-3.1%) for PM2.5. The corresponding values per 10 ppb increment of gaseous pollutants were 2.9% (95% CI: 0.4%-5.3%) for SO2, 1.7% (95% CI: 0.5%-2.8%) for O3, and 1.4% (95% CI: 0.4%-2.4%) for NO2. ER% per 1000 ppb increment of CO was 0.9% (95% CI: 0.0%-1.9%). Associations were not substantially different between subgroups. This meta-analysis shows a positive association between daily levels of ambient air pollution markers and hospitalization of children due to pneumonia. However, lack of studies from low-and middle-income countries limits the quantitative generalizability given that susceptibilities to the adverse effects of air pollution may be different in those populations. The meta-regression in our analysis further demonstrated a strong effect of country income level on heterogeneity.

Estimation of Vietnam national burden of disease 2008.

Burden of disease has been used to assess population health status. This article presents the first estimations of burden of disease in Vietnam in 2008 using disability-adjusted life years (DALYs). DALYs were calculated using the Global Burden of Disease (GBD) methods. Incidence, prevalence of diseases, and causes of death was extracted from Vietnam data. Disability weights were borrowed from GBD and Dutch research. In 2008, the total burden of disease in Vietnam was 12.3 million DALYs. Noncommunicable diseases dominated the total burden of diseases in Vietnam, accounting for 71% of the total burden, and cardiovascular disease was the leading cause group of premature death. While pneumonia was an important cause of burden in Vietnamese children, stroke and depression were the main causes of disease burden among adults. The study provides a snapshot of Vietnamese health status and offers guidance for health policymaking in Vietnam.

Risk factors for chronic disease in Viet Nam: a review of the literature.

INTRODUCTION: Chronic diseases account for most of the disease burden in low- and middle-income countries, particularly those in Asia. We reviewed literature on chronic disease risk factors in Viet Nam to identify patterns and data gaps. METHODS: All population-based studies published from 2000 to 2012 that reported chronic disease risk factors were considered. We used standard chronic disease terminology to search PubMed and assessed titles, abstracts, and articles for eligibility for inclusion. We summarized relevant study information in tables listing available studies, risk factors measured, and the prevalence of these risk factors. RESULTS: We identified 23 studies conducted before 2010. The most common age range studied was 25 to 64 years. Sample sizes varied, and sample frames were national in 5 studies. A combination of behavioral, physical, and biological risk factors was studied. Being overweight or obese was the most common risk factor studied (n = 14), followed by high blood pressure (n = 11) and tobacco use (n = 10). Tobacco and alcohol use were high among men, and tobacco use may be increasing among Vietnamese women. High blood pressure is common; however, people's knowledge that they have high blood pressure may be low. A high proportion of diets do not meet international criteria for fruit and vegetable consumption. Prevalence of overweight and obesity is increasing. None of the studies evaluated measured dietary patterns or total caloric intake, and only 1 study measured dietary salt intake. CONCLUSION: Risk factors for chronic diseases are common in Viet Nam; however, more recent and context-specific information is required for planning and monitoring interventions to reduce risk factors and chronic disease in this country.