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Exposure to indoor air pollution (IAP) is a leading environmental risk for respiratory diseases. We investigated the relationship between respiratory symptoms and polluting indoor activities such as smoking, cooking and contact with pets among children in Ho Chi Minh City (HCMC), Vietnam. A cross-sectional survey applied a multistage sampling method in 24 randomly selected secondary schools across the city. Approximately 15,000 students completed self-administrated questionnaires on risk factors and respiratory health outcomes within the preceding 12 months. Data were analyzed using a multivariable logistic regression model with robust standard errors. Wheeze was the most common respiratory symptom (39.5 %) reported, followed by sneezing and runny nose (28.3 %). A small percentage of students self-reported asthma (8.6 %). Approximately 56 % of participants lived with family members who smoked. A positive association between exposure to indoor secondhand smoke and respiratory symptoms was observed, with adjusted odds ratios (aOR) of 1.41 (95 % CI: 1.25-1.60, p < 0.001) for wheezing and 1.64 (95 % CI: 1.43-1.87, p < 0.001) for sneezing and runny nose, respectively. Using an open stove fuelled by coal, wood, or kerosene for cooking was associated with wheeze (aOR: 1.36, CI 95 %: 1.10-1.68, p = 0.01) and sneezing and runny nose (aOR: 1.36, CI 95 %: 1.09-1.69, p = 0.01). In the present study, IAP was associated with adverse health outcomes, as evidenced by an increase in respiratory symptoms reported within the previous 12 months.
Subject(s)
Air Pollution, Indoor , Air Pollution , Tobacco Smoke Pollution , Child , Humans , Air Pollution, Indoor/adverse effects , Cross-Sectional Studies , Sneezing , Vietnam/epidemiology , Rhinorrhea , Cooking , Risk FactorsABSTRACT
INTRODUCTION: Influenza B viruses (IBV) cause a significant health and economic burden annually. Due to lower antigenic drift rate, less extensive antigenic diversity, and lack of animal reservoirs, the development of highly effective universal vaccines against IBV might be in reach. Current seasonal influenza vaccines are formulated to induce antibodies against the Hemagglutinin (HA) protein, but their effectiveness is reduced by mismatch between vaccine and circulating strains. AREAS COVERED: Given antibodies against the Neuraminidase (NA) have been associated with protection during influenza infection, there is considerable interest in the development of NA-based influenza vaccines. This review summarizes insights into the role of NA-based immunity against IBV and highlights knowledge gaps that should be addressed to inform the design of next-generation influenza B vaccines. We discuss how antibodies recognize broadly cross-reactive epitopes on the NA and the lack of understanding of IBV NA antigenic evolution which would benefit vaccine development in the future. EXPERT OPINION: Demonstrating NA antibodies as correlates of protection for IBV in humans would be paramount. Determining the extent of IBV NA antigenic evolution will be informative. Finally, it will be critical to determine optimal strategies for incorporating the appropriate NA antigens in existing clinically approved vaccine formulations.
Subject(s)
Influenza Vaccines , Influenza, Human , Orthomyxoviridae Infections , Animals , Humans , Influenza B virus , Neuraminidase , Antigens, Viral , Antibodies, Viral , Hemagglutinin Glycoproteins, Influenza Virus , Orthomyxoviridae Infections/prevention & controlABSTRACT
This study aims to investigate climate change's impact on health and adaptation in Vietnam through a systematic review and additional analyses of heat exposure, heat vulnerability, awareness and engagement, and projected health costs. Out of 127 reviewed studies, findings indicated the wider spread of infectious diseases, and increased mortality and hospitalisation risks associated with extreme heat, droughts, and floods. However, there are few studies addressing health cost, awareness, engagement, adaptation, and policy. Additional analyses showed rising heatwave exposure across Vietnam and global above-average vulnerability to heat. By 2050, climate change is projected to cost up to USD1-3B in healthcare costs, USD3-20B in premature deaths, and USD6-23B in work loss. Despite increased media focus on climate and health, a gap between public and government publications highlighted the need for more governmental engagement. Vietnam's climate policies have faced implementation challenges, including top-down approaches, lack of cooperation, low adaptive capacity, and limited resources.
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Electroluminescence efficiencies and stabilities of quasi-two-dimensional halide perovskites are restricted by the formation of multiple-quantum-well structures with broad and uncontrollable phase distributions. Here, we report a ligand design strategy to substantially suppress diffusion-limited phase disproportionation, thereby enabling better phase control. We demonstrate that extending the π-conjugation length and increasing the cross-sectional area of the ligand enables perovskite thin films with dramatically suppressed ion transport, narrowed phase distributions, reduced defect densities, and enhanced radiative recombination efficiencies. Consequently, we achieved efficient and stable deep-red light-emitting diodes with a peak external quantum efficiency of 26.3% (average 22.9% among 70 devices and cross-checked) and a half-life of ~220 and 2.8 h under a constant current density of 0.1 and 12 mA/cm2, respectively. Our devices also exhibit wide wavelength tunability and improved spectral and phase stability compared with existing perovskite light-emitting diodes. These discoveries provide critical insights into the molecular design and crystallization kinetics of low-dimensional perovskite semiconductors for light-emitting devices.
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From the aerial parts of Eupatorium fortunei, four thymol derivatives (1-4) were isolated and structurally elucidated by NMR and mass spectroscopic methods. Of which, a new dimeric thymol derivative (1) was characterized and its absolute configuration was established by electronic circular dichroism quantum method. In addition, the 1D and 2D NMR as well as HR-ESI mass spectral data of 2 were provided for the first time. Compounds 2-4 were evaluated for their inhibitory activity against α-glucosidase and acetylcholinesterase enzymes. All tested compounds showed weak inhibition at the concentration range of 1-256 µg/mL in both enzymatic assays.
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OBJECTIVE: Lack of recognition of asthma in childhood results in unmet asthma treatment needs and leads to the risk of sub-optimal respiratory health. The present study assessed the prevalence of asthmatic under-recognition in middle school children in Vietnam. METHODS: We conducted a school-based survey among 15,112 Vietnamese children. Most of them are aged from 13 to 14. Schools and students were recruited using multi-stage sampling. Respiratory symptoms were collected via self-report using a standardized tool from the International Study of Asthma and Allergies in Childhood. Under-recognition of asthma was defined as a presence of at least one asthma-like symptom but a negative response to having ever asthma. Associations were investigated using logistic regression. RESULTS: Prevalence of asthma-like symptoms was 27.3% and prevalence of physician-diagnosed asthma was 8.5%. Over 80% of symptomatic children were not diagnosed with asthma. Under-recognition of asthma was found more in girls (adjusted odds ratio; aOR = 1.75; 95%CI: 1.54 to 1.98). CONCLUSIONS: Asthma is significantly under-recognized in Vietnamese middle-school children. Urgent action is required to improve the recognition of asthma in Vietnam.
Subject(s)
Asthma , Child , Female , Humans , Male , Asthma/diagnosis , Asthma/epidemiology , Prevalence , Southeast Asian People , Students , Surveys and Questionnaires , Vietnam/epidemiology , AdolescentABSTRACT
Various adverse health outcomes caused by particulate matter (PM) exposure has been documented, while the evidence for the adverse effects of PM exposure on mental and behavioral disorders (MBDs) is limited. To date, few epidemiological studies, especially in developing countries, have focused on these adverse effects. In the past decade, air pollution sources in Vietnam have noticeably increased, resulting to the elevated concentrations of ambient air pollutants particularly fine PM or PM with an aerodynamic diameter ≤2.5 µm (PM2.5). Hence, investigating the short-term association between PM2.5 and MBDs is worthwhile. In this study, a quasi-Poisson time-series regression analysis was used to investigate the association between PM2.5 exposure and daily hospitalizations for MBDs to the Ho Chi Minh City Mental Health Hospital during 2017-2020. A natural cubic spline smooth function for time was used to screen out long-term and seasonality trends. Stratified analyses were also performed by sex, age, and season. During study period, 9,986 hospitalizations for MBDs were recorded and included in the analysis. Results suggested that a 10 µg/m3 daily increase in PM2.5 concentration was associated with a statistically significant 2.96% (95% confidence interval: 0.23%-5.76%) increase in hospitalizations for MBDs. The effects of PM2.5 exposure on hospital admissions were more pronounced in female patients and the middle-age group (35-59 years). This finding could increase awareness regarding prevention and minimization of MBDs on the public.
Subject(s)
Air Pollutants , Air Pollution , Adult , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/adverse effects , Air Pollution/analysis , China , Environmental Exposure/analysis , Female , Hospitalization , Humans , Middle Aged , Particulate Matter/analysis , Vietnam/epidemiologyABSTRACT
Vietnam is highly vulnerable to climate change-related extreme weather events such as heatwaves. This study assesses the association between heatwaves and hospitalizations due to mental and behavioral disorders (MBDs) in Ho Chi Minh City (HCMC). We collected daily MBD hospital admissions data at the HCMC Mental Health Hospital from 2017 to 2019. Heatwaves effects were characterized into the main effect (i.e., the intensity of temperature during heatwaves) and the added effect (i.e., the duration of heatwaves). Time series Poisson regression coupled with a distributed lag linear model (DLM) was used to quantify the 14-day lags effect of heatwaves. Confounders including long-term trend, seasonality, days of the week, holidays, and relative humidity were included in the model. Heatwaves increased all-cause MBD hospitalization by 62% (95%Cl, 36-93%) for the main effect and by 8% (95% Cl, - 3% to 19%) for the added effect. Noticeably, the group aged 18-60 years old was affected by the main effect of the heatwave, while the group aged 61 years and older was affected by the added effect of the heatwave. The effects of heatwaves differed among groups of MBD hospitalizations. The mental and behavioral disorder group due to psychoactive substance use was significantly affected by the main effect of heatwaves (RR:2.21; 95%Cl:1.55-3.15). The group of schizophrenia, schizotypal and delusional disorders were highly vulnerable towards both the main and the added effect of heatwaves with RR = 1.50 (95%CI, 1.20-1.86) and RR = 1.14 (95%CI, 1.01-1.30), respectively.
Subject(s)
Hot Temperature , Mental Disorders , Adolescent , Adult , Cities , Hospitalization , Humans , Mental Disorders/epidemiology , Middle Aged , Vietnam/epidemiology , Young AdultABSTRACT
BACKGROUND: Diabetes-related distress (DRD) refers to the condition of negative emotion as a result of living with diabetes and the burden of self-care. This study aims to evaluate the prevalence and associated factors of DRD among people with type 2 diabetes. METHODS: A cross-sectional study was carried out on people with Type 2 Diabetes at three hospitals in Ho Chi Minh City, between April and November 2020. The study used the Vietnamese version of the Diabetes Distress Scale (DDS) which includes 17 items. The mean total distress score was calculated on the average of the 17 items. A mean score of equal to 2.0 or higher was classified as moderate to severe distress. Descriptive statistics were performed by frequency and percentage, and the multivariate Logistic Regression Analysis was used to assess information where p-value <0.05 was considered statistically significant. RESULTS: A total of 517 participants, who were mainly over 60 years old (56.8%) with females being 65.0%, participated in the study. Results showed that 23.6% and 5.8% of them, respectively, were found as being moderately or highly distressed. Some factors that correlated with the total distress results included age, timescale of diabetes, and glycemic control level (HbA1c). The rate of total distress in those who were over 60 years old and had a HbA1c <7 were less prevalent than those who were under 60, and had a HbA1c ≥7 (OR 0.5 95% CI 0.3-0.7; OR 0.5 95% CI: 0.3-0.9, respectively, all p<0.05), whilst the timescale of diabetes between 5 and 10 years was significantly more prevalent than those who had a timescale less 5 years (OR 1.8 95% CI 1.1-2.9, p<0.05). CONCLUSION: A high rate of distress exists in people with diabetes. Therefore, combining the evaluation of distress as part of the regular diagnostic procedures of diabetes care, and recommending physicians apply a comprehensive approach to diabetes management, is necessary.
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BACKGROUND: The novel coronavirus disease (COVID-19) has become a major threat to human life around the world. This study aims to assess the knowledge, attitude, and practices regarding COVID-19 among people with chronic diseases at the outpatient departments in Ho Chi Minh City. METHODS: A cross-sectional study was carried out between February and March 2020 using a convenience sampling strategy in three hospitals in Ho Chi Minh City (HCMC) via the use of a structured self-administered questionnaire. Factors relating to practices, prevalence ratio (PR), and 95% confidence interval were estimated by using the Poisson regression with robust options. P-value <0.05 was considered as statistically different. RESULTS: A total of 522 participants had a mean age of 51.5 ± 10.6 years. Most of them reported seeing information regarding the COVID-19 pandemic (93.7%) via television and social media (72.8% and 62.1%, respectively). Just over two-thirds of the participants (68.4%) answered with sufficient knowledge of COVID-19. Most respondents had a positive attitude toward COVID-19 (90.8%), although some misconceptions existed. Almost over three-fourths of them (77.2%) maintained good practices for prevention. The rate of good practices in those who had sufficient knowledge was 1.24 times greater than that among those who had insufficient knowledge (PR 1.24, 95% CI: 1.10-1.41, P<0.05). Also, the rate of good practices in males was lower than that of females (PR: 0.91, 95% CI: 0.83-0.99, P<0.05). CONCLUSION: There still exists an amount of insufficient knowledge and negative attitude regarding COVID-19, which may be barriers to good prevention practices among chronic illness patients. Education programs need to continue via television and social media and emphasize that people with chronic diseases are more likely to experience severe symptoms, including death from COVID-19. Additionally, management authorities should prolong specific policies to protect the more vulnerable in our community.
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BACKGROUND: Advances in earth observation and machine learning techniques have created new options for forest monitoring, primarily because of the various possibilities that they provide for classifying forest cover and estimating aboveground biomass (AGB). METHODS: This study aimed to introduce a novel model that incorporates the atom search algorithm (ASO) and adaptive neuro-fuzzy inference system (ANFIS) into mangrove forest classification and AGB estimation. The Ca Mau coastal area was selected as a case study since it has been considered the most preserved mangrove forest area in Vietnam and is being investigated for the impacts of land-use change on forest quality. The model was trained and validated with a set of Sentinel-1A imagery with VH and VV polarizations, and multispectral information from the SPOT image. In addition, feature selection was also carried out to choose the optimal combination of predictor variables. The model performance was benchmarked against conventional methods, such as support vector regression, multilayer perceptron, random subspace, and random forest, by using statistical indicators, namely, root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). RESULTS: The results showed that all three indicators of the proposed model were statistically better than those from the benchmarked methods. Specifically, the hybrid model ended up at RMSE = 70.882, MAE = 55.458, R2 = 0.577 for AGB estimation. CONCLUSION: From the experiments, such hybrid integration can be recommended for use as an alternative solution for biomass estimation. In a broader context, the fast growth of metaheuristic search algorithms has created new scientifically sound solutions for better analysis of forest cover.