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BACKGROUND: Estimates of influenza-associated mortality are important for national and international decision making on public health priorities. Previous estimates of 250â000-500â000 annual influenza deaths are outdated. We updated the estimated number of global annual influenza-associated respiratory deaths using country-specific influenza-associated excess respiratory mortality estimates from 1999-2015. METHODS: We estimated country-specific influenza-associated respiratory excess mortality rates (EMR) for 33 countries using time series log-linear regression models with vital death records and influenza surveillance data. To extrapolate estimates to countries without data, we divided countries into three analytic divisions for three age groups (<65 years, 65-74 years, and ≥75 years) using WHO Global Health Estimate (GHE) respiratory infection mortality rates. We calculated mortality rate ratios (MRR) to account for differences in risk of influenza death across countries by comparing GHE respiratory infection mortality rates from countries without EMR estimates with those with estimates. To calculate death estimates for individual countries within each age-specific analytic division, we multiplied randomly selected mean annual EMRs by the country's MRR and population. Global 95% credible interval (CrI) estimates were obtained from the posterior distribution of the sum of country-specific estimates to represent the range of possible influenza-associated deaths in a season or year. We calculated influenza-associated deaths for children younger than 5 years for 92 countries with high rates of mortality due to respiratory infection using the same methods. FINDINGS: EMR-contributing countries represented 57% of the global population. The estimated mean annual influenza-associated respiratory EMR ranged from 0·1 to 6·4 per 100â000 individuals for people younger than 65 years, 2·9 to 44·0 per 100â000 individuals for people aged between 65 and 74 years, and 17·9 to 223·5 per 100â000 for people older than 75 years. We estimated that 291â243-645â832 seasonal influenza-associated respiratory deaths (4·0-8·8 per 100â000 individuals) occur annually. The highest mortality rates were estimated in sub-Saharan Africa (2·8-16·5 per 100â000 individuals), southeast Asia (3·5-9·2 per 100â000 individuals), and among people aged 75 years or older (51·3-99·4 per 100â000 individuals). For 92 countries, we estimated that among children younger than 5 years, 9243-105â690 influenza-associated respiratory deaths occur annually. INTERPRETATION: These global influenza-associated respiratory mortality estimates are higher than previously reported, suggesting that previous estimates might have underestimated disease burden. The contribution of non-respiratory causes of death to global influenza-associated mortality should be investigated. FUNDING: None.
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Salud Global/estadística & datos numéricos , Gripe Humana/mortalidad , Estaciones del Año , Adolescente , Adulto , Anciano , Niño , Preescolar , Femenino , Humanos , Lactante , Recién Nacido , Gripe Humana/complicaciones , Modelos Lineales , Masculino , Persona de Mediana Edad , Factores Socioeconómicos , Adulto JovenRESUMEN
BACKGROUND: Despite substantial positive impacts of Thailand's tobacco control policies on reducing the prevalence of smoking, current trends suggest that further reductions are needed to ensure that WHO's 2025 voluntary global target of a 30% relative reduction in tobacco use is met. In order to confirm this hypothesis, we aim to estimate the effect of tobacco control policies in Thailand on the prevalence of smoking and attributed deaths and assess the possibilities of achieving WHO's 2025 global target. This paper addresses this knowledge gap which will contribute to policy control measures on tobacco control. Results of this study can help guide policy makers in implementing further interventions to reduce the prevalence of smoking in Thailand. METHOD: A Markov chain model was developed to examine the effect of tobacco control policies, such as accessibility restrictions for youths, increased tobacco taxes and promotion of smoking cessation programs, from 2015 to 2025. Outcomes included smoking prevalence and the number of smoking-attributable deaths. Due to the very low prevalence of female smokers in 2014, this study applied the model to estimate the smoking prevalence and attributable mortality among males only. RESULTS: Given that the baseline prevalence of smoking in 2010 was 41.7% in males, the target of a 30% relative reduction requires that the prevalence be reduced to 29.2% by 2025. Under a baseline scenario where smoking initiation and cessation rates among males are attained by 2015, smoking prevalence rates will reduce to 37.8% in 2025. The combined tobacco control policies would further reduce the prevalence to 33.7% in 2025 and 89,600 deaths would be averted. CONCLUSION: Current tobacco control policies will substantially reduce the smoking prevalence and smoking-attributable deaths. The combined interventions can reduce the smoking prevalence by 19% relative to the 2010 level. These projected reductions are insufficient to achieve the committed target of a 30% relative reduction in smoking by 2025. Increased efforts to control tobacco use will be essential for reducing the burden of non-communicable diseases in Thailand.
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Fumar/epidemiología , Fumar/mortalidad , Adolescente , Adulto , Anciano , Causas de Muerte , Femenino , Encuestas Epidemiológicas , Humanos , Masculino , Persona de Mediana Edad , Prevalencia , Política Pública , Prevención del Hábito de Fumar/estadística & datos numéricos , Tailandia/epidemiología , Adulto JovenRESUMEN
BACKGROUND: Despite achievement of universal health coverage in Thailand, socioeconomic inequality in health has been a major policy concern. This study examined mortality patterns across different socioeconomic strata in Thailand. METHODS: We conducted a cross-sectional analysis of the 2010 Population and Housing Census on area-level socioeconomic deprivation against the 2010 mortality from the vital registration database at the super-district level. We used principal components analysis to construct a socioeconomic deprivation index and K-mean cluster analysis to group socioeconomic status and cause-specific mortality. RESULTS: Excess mortality rates from all diseases, except colorectal cancer, were observed among super-districts with low socioeconomic status. Spatial clustering was evident in the distribution of socioeconomic status and mortality rates. Cluster analysis revealed that super-districts which were predominantly urban tended to have low all-cause standardize mortality ratio but a high colorectal cancer-specific mortality rate. Deaths due to liver cancer, diabetes, and renal diseases were common in the low socioeconomic super-districts which hosted one third of the total Thai population. CONCLUSION: Socially deprived areas have an excess of overall and cause specific deaths. Populations living in more affluent areas, despite low general mortality, still have many preventable deaths such as colorectal cancer. These findings warrant future epidemiological studies investigating various causes of excessive deaths in non-deprived areas and implementation of policies to reduce the mortality gap between rich and poor areas.
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Causas de Muerte , Disparidades en el Estado de Salud , Pobreza , Clase Social , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Censos , Análisis por Conglomerados , Estudios Transversales , Diabetes Mellitus/mortalidad , Femenino , Humanos , Enfermedades Renales/mortalidad , Masculino , Persona de Mediana Edad , Mortalidad , Neoplasias/mortalidad , Análisis de Componente Principal , Factores Socioeconómicos , Análisis Espacial , Tailandia/epidemiología , Cobertura Universal del Seguro de Salud , Adulto JovenRESUMEN
BACKGROUND: Thailand has achieved remarkable improvement in health status since the achievement of universal health coverage in 2002. Health equity has improved significantly. However, challenges on health inequity still remain.This study aimed to determine the trends of geographical inequalities in disease specific mortality in Thailand after the country achieved universal health coverage. METHODS: National vital registration data from 2001 to 2014 were used to calculate age-adjusted mortality rate and standardized mortality ratio (SMR). To minimize large variations in mortality across administrative districts, the adjacent districts were systematically grouped into "super-districts" by taking into account the population size and proximity. Geographical mortality inequality among super-districts was measured by the coefficient of variation. Mixed effects modeling was used to test the difference in trends between super-districts. RESULTS: The overall SMR steadily declined from 1.2 in 2001 to 0.9 in 2014. The upper north and upper northeast regions had higher SMR whereas Greater Bangkok achieved the lowest SMR. Decreases in SMR were mostly seen in Greater Bangkok and the upper northern region. Coefficient of variation of SMR rapidly decreased from 20.0 in 2001 to 12.5 in 2007 and remained close to this value until 2014. The mixed effects modelling revealed significant differences in trends of SMR across super-districts. Inequality in mortality declined among adults (≥15 years old) but increased in children (0-14 years old). A declining trend in inequality of mortality was seen in almost all regions except Greater Bangkok where the inequality in SMR remained high throughout the study period. CONCLUSIONS: A decline in the adult mortality inequality across almost all regions of Thailand followed universal health coverage. Inequalities in child mortality rates and among residents of Greater Bangkok need further exploration.
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Disparidades en el Estado de Salud , Mortalidad/tendencias , Características de la Residencia/estadística & datos numéricos , Cobertura Universal del Seguro de Salud/estadística & datos numéricos , Adolescente , Adulto , Anciano , Niño , Mortalidad del Niño/tendencias , Preescolar , Femenino , Humanos , Lactante , Recién Nacido , Masculino , Persona de Mediana Edad , Tailandia/epidemiología , Adulto JovenRESUMEN
OBJECTIVE: To assess economic burden attributable to smoking in Thailand in 2009. METHODS: A prevalence-based, disease-specific cost of illness approach was used to estimate the direct medical costs, indirect medical costs, productivity loss due to premature deaths and absenteeism caused by smoking-related diseases. Direct healthcare costs were obtained from the inpatient and outpatient charge database at the National Health Security Office and the Central Office for Healthcare Information. Indirect healthcare costs were obtained from the Health and Welfare Survey. The household Socioeconomic Survey provided data on income of the population. Costs were estimated for 7 disease groups, namely, lung cancer, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), upper aerodigestive tract cancer, other cancer, other respiratory diseases and other medical conditions. Smoking Attributable Fractions were derived from the 2009 Thai Burden of Disease study. RESULTS: Total economic burden of smoking amounted to 74.88 billion Thai Baht (THB) (95% CI 74.59 to 75.18) (US$2.18, 95% CI US$2.17 to US$2.19 billion). Of this, most of the burden resulted from productivity loss 62.24 billion THB (95% CI 62.05 to 62.44) (US$1.81, 95% CI US$1.81 to US$1.82 billion). Total medical cost was 12.64 billion THB (12.44 to 12.85) (US$0.37, 95% CI US$0.36 to US$0.37 billion). Excluding other medical conditions, the direct healthcare costs were highest for CVD, followed by COPD and other respiratory diseases, respectively. All together, the total cost of smoking accounted for 0.78% (95% CI 0.78% to 0.79%) of the national gross domestic product and about 18.19% (95% CI 18.12% to 18.27%) of total health expenditure. CONCLUSIONS: The total economic loss from smoking-related diseases highlights the significant loss to the society, health sector and the country's economy. Such information is crucial for informing national public health policy, particularly when a conflict arises between the economy and health.
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Costo de Enfermedad , Costos de la Atención en Salud/estadística & datos numéricos , Gastos en Salud/estadística & datos numéricos , Fumar/efectos adversos , Absentismo , Adolescente , Adulto , Eficiencia , Femenino , Humanos , Renta , Masculino , Persona de Mediana Edad , Prevalencia , Fumar/economía , Fumar/epidemiología , Encuestas y Cuestionarios , Tailandia/epidemiología , Adulto JovenRESUMEN
To better define infectious diseases of concern in Thailand, trends in the mortality rate during 1958-2009 were analyzed by using data from public health statistics reports. From 1958 to the mid-1990s, the rate of infectious disease-associated deaths declined 5-fold (from 163.4 deaths/100,000 population in 1958 to 29.5/100,000 in 1997). This average annual reduction of 3.2 deaths/100,000 population was largely attributed to declines in deaths related to malaria, tuberculosis, pneumonia, and gastrointestinal infections. However, during 1998-2003, the mortality rate increased (peak of 70.0 deaths/100,000 population in 2003), coinciding with increases in mortality rate from AIDS, tuberculosis, and pneumonia. During 2004-2009, the rate declined to 41.0 deaths/100,000 population, coinciding with a decrease in AIDS-related deaths. The emergence of AIDS and the increase in tuberculosis- and pneumonia-related deaths in the late twentieth century emphasize the need to direct resources and efforts to the control of emerging and re-emerging infectious diseases.
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Enfermedades Transmisibles/mortalidad , Enfermedades Transmisibles/epidemiología , Enfermedades Transmisibles/historia , Historia del Siglo XX , Historia del Siglo XXI , Humanos , Vigilancia de la Población , Tailandia/epidemiologíaRESUMEN
BACKGROUND: Influenza-associated mortality in subtropical or tropical regions, particularly in developing countries, remains poorly quantified and often underestimated. We analyzed data in Thailand, a middle-income tropical country with good vital statistics and influenza surveillance data. METHODS: We obtained weekly mortality data for all-cause and three underlying causes of death (circulatory and respiratory diseases, and pneumonia and influenza), and weekly influenza virus data, from 2006 to 2011. A negative binomial regression model was used to estimate deaths attributable to influenza in two age groups (<65 and ≥65 years) by incorporating influenza viral data as covariates in the model. RESULTS: From 2006 to 2011, the average annual influenza-associated mortality per 100 000 persons was 4·0 (95% CI: -18 to 26). Eighty-three percent of influenza-associated deaths occurred among persons aged > 65 years. The average annual rate of influenza-associated deaths was 0·7 (95% CI: -8·2 to 10) per 100 000 population for person aged <65 years and 42 (95% CI: -137 to 216) for person aged ≥ 65 years. DISCUSSION: In Thailand, estimated excess mortality associated with influenza was considerable even during non-pandemic years. These data provide support for Thailand's seasonal influenza vaccination campaign. Continued monitoring of mortality data is important to assess impact.
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BACKGROUND: The World Health Organization (WHO) initiative to estimate the global burden of foodborne diseases established the Foodborne Diseases Burden Epidemiology Reference Group (FERG) in 2007. In addition to global and regional estimates, the initiative sought to promote actions at a national level. This involved capacity building through national foodborne disease burden studies, and encouragement of the use of burden information in setting evidence-informed policies. To address these objectives a FERG Country Studies Task Force was established and has developed a suite of tools and resources to facilitate national burden of foodborne disease studies. This paper describes the process and lessons learned during the conduct of pilot country studies under the WHO FERG initiative. FINDINGS: Pilot country studies were initiated in Albania, Japan and Thailand in 2011 and in Uganda in 2012. A brief description of each study is provided. The major scientific issue is a lack of data, particularly in relation to disease etiology, and attribution of disease burden to foodborne transmission. Situation analysis, knowledge translation, and risk communication to achieve evidence-informed policies require specialist expertise and resources. CONCLUSIONS: The FERG global and regional burden estimates will greatly enhance the ability of individual countries to fill data gaps and generate national estimates to support efforts to reduce the burden of foodborne disease.