Effect of apparent temperature on hospitalization from a spectrum of cardiovascular diseases in rural residents in Fujian, China.

Cardiovascular disease (CVD) is a leading threat to global public health. Although associations between temperature and CVD hospitalization have been suggested for developed countries, limited evidence is available for developing countries or rural residents. Moreover, the effect of apparent temperature (AT) on the spectrum of cause-specific CVDs remains unknown. Based on 2,024,147 CVD hospitalizations for rural residents from eight regions in Fujian Province, China, during 2010-2016, a quasi-Poisson regression with distributed lag non-linear model was fitted to estimate the AT effect on daily CVD hospitalization for each region, and then pooled in a meta-regression that included regional indicators related to rural residents. Stratified analyses were performed according to the cause of hospitalization, sex and age groups. Finally, we calculated the fraction of CVD hospitalizations attributable to AT, as a reflection of the burden associated with AT. The heat effect appeared at lag 0-1 days, with 19% (95% CI, 11-26%) increased risk of CVD hospitalization, which was worse for ischemic heart disease, heart failure, arrhythmias and ischemic stroke. The decreased AT was associated with increase of hemorrhagic stroke at lag 0-28 days. People aged 65 and above suffered more from the heat effect on cardiovascular and cerebrovascular diseases. Regions with a lower gross value of agricultural production, rural residents' per capita net income, number of air conditioners and water heaters were more susceptible. A large number of hospitalizations were attributable to heat for most subcategories. High AT level increased CVD hospitalization, and the subcategories had different susceptibilities. The effects were modified by individual and regional characteristics. These findings have important implications for the development of targeted interventions and for hospital service planning.

Application of a combined model with seasonal autoregressive integrated moving average and support vector regression in forecasting hand-foot-mouth disease incidence in Wuhan, China.

Hand-foot-mouth disease (HFMD) is a serious public health problem with increasing cases and substantial financial burden in China, especially in Wuhan city. Hence, there is an urgent need to construct a model to predict the incidence of HFMD that could make the prevention and control of this disease more effective.The incidence data of HFMD of Wuhan city from January 2009 to December 2016 were used to fit a combined model with seasonal autoregressive integrated moving average (SARIMA) model and support vector regression (SVR) model. Then, the SARIMA-SVR hybrid model was constructed. Subsequently, the fitted SARIMA-SVR hybrid model was applied to obtain the fitted HFMD incidence from 2009 to 2016. Finally, the fitted SARIMA-SVR hybrid model was used to forecast the incidence of HFMD of the year 2017. To assess the validity of the model, the mean square error (MSE) and mean absolute percentage error (MAPE) between the actual values and predicted values of HFMD incidence (2017) were calculated.From 2009 to 2017, a total of 107636 HFMD cases were reported in Wuhan City, Hubei Province, and the male-to-female ratio is 1.60:1. The age group of 0 to 5 years old accounts for 95.06% of all reported cases and scattered children made up the large proportion (accounted for 56.65%). There were 2 epidemic peaks, from April to July and September to December, respectively, with an emphasis on the former. High-prevalence areas mainly emerge in Dongxihu District, Jiangxia District, and Hongshan District. SARIMA (1,0,1)(0,0,2)[12] is the optimal model given with a minimum Akaike information criterion (AIC) (700.71), then SVR model was constructed by using the optimum parameter (C = 100000, =0.00001, =0.01). The forecasted incidences of single SARIMA model and SARIMA-SVR hybrid model from January to December 2017 match the actual data well. The single SARIMA model shows poor performance with large MSE and MAPE values in comparison to SARIMA-SVR hybrid model.The SARIMA-SVR hybrid model in this study showed that accurate forecasting of the HFMD incidence is possible. It is a potential decision supportive tool for controlling HFMD in Wuhan, China.

Ischemic heart disease deaths, disability-adjusted life years and risk factors in Fujian, China during 1990-2013: Data from the Global Burden of Disease Study 2013.

OBJECTIVES: Ischemic heart disease (IHD) is a large public health problem and is associated with a number of modifiable risk factors. The aim of this study was to estimate the IHD burden and attributable to risk factors in Fujian, China during 1990 to 2013. METHODS: IHD deaths, disability-adjusted life years (DALYs) and attributable to risk factors were estimated as part of the Global Burden of Disease (GBD) 2013 Study. Statistical models were employed to produce comprehensive results of IHD deaths, DALYs and attributable to risk. Means and 95% uncertainty intervals (UIs) were calculated for mortality and DALYs. The median of the percent change and 95% UI were determined for the period between 1990 and 2013. RESULTS: The age-standardized IHD deaths rate increased by 15.3% from 1990 [74.7 (95% UI 62.9-99.1) per 100,000] to 2013 [82.7 (56.5-95.5) per 100,000]. The age-standardized IHD DALYs has slightly decreased 8.8% from 1990 to 2013[from 1356.2 (1134.3-1732.1) to 1202.7 (879.6-1404.6) per 100,000]. All risks combined account for 94.7% (92.9%- 96.0%) of IHD DALYs for all ages in 2013. The five leading risk factors for all ages IHD DALYs were high systolic blood pressure, high total cholesterol, smoking, diet high in sodium, and high fasting plasma glucose. CONCLUSION: Despite decreased age-standardized IHD deaths and DALY rate since 1990, population growth and aging led to a higher global burden of IHD in 2013. Behavioral, environmental, and metabolic risks can explain most of the IHD DALYs providing many opportunities for prevention.