Objective To predict the burden caused by fatal road traffic injuries from 2015 to 2030. Methods We searched the websites of United Nations Population Division,United States Department of Agriculture,World Health Organization,China Energy Research Foundation and other agencies to obtain the predictive values of gross domestic product(GDP)per capita,urbanization, motorization and education from 2015 to 2030 in China. Predicted values were then applied to log-linear models to estimate the numbers and years of life lost due to road traffic injuries from 2015 to 2030. Results The mortality rate caused by road traffic injury decreased slightly,from 13.7/100 000 in 2015 to 11.8/100 000 in 2030. 191,189,183,169 thousand persons were estimated to die from road traffic crashes in 2015,2020,2025 and 2030,respectively,showing a declining trend. Years of Life Lost(YLLs)caused by road traffic deaths were predicted to be 6 918,6 634,6 189,5 513 thousand years in 2015,2020,2025 and 2030,respectively,also showing a gradual downward trend. But the YLLs displayed an increase among people at 55 years of age or older,between 2015 and 2030. Results from the sensitivity analysis showed a stable forecasting result. Conclusion Mortality, number of deaths and YLLs from road traffic crashes were predicted to decrease slightly,between 2015 and 2030 but the number of deaths and YLLs due to road traffic injuries will continue to increase from 2015 to 2030.

OBJECTIVE: To determine the prevalence and incidence of illness of two-week duration, and the factors influencing these, among residents 15 years and older in four counties of Hunan Province. METHODS: Data were sampled from four counties of Hunan Province for the Fourth National Health Service Survey. Incidence and two-week prevalence of disease were used to assess the health service needs of residents. A non-conditional, stepwise logistic regression was employed to explore the influencing factors. RESULTS: The two-week prevalence and incidence were 11.5% and 3.9%, respectively, in four counties of Hunan. The three leading diseases of two-week prevalence were: respiratory diseases, digestive diseases, and musculoskeletal diseases. Non-conditional stepwise logistic regression showed that urban residents had 0.64 times the risk of two-week illness compared with the rural residents (P< 0.05); residents in the 45-59 year age group and the 60+ year age group had 1.69 and 2.62 times the risk of two-week illness compared with residents in the 15-44 year age group, respectively (P<0.05). The widowed had 1.91 times the risk of prevalence of two-week illness contrasted to singles (P<0.05); the students had 0.29 times the risk of two-week illness contrasted to the workers (P<0.05); urban residents had 0.63 times the risk of two-week illness compared with the rural (P<0.05); the widowed had 2.37 times the risk of incidence of two-week illness compared with singles (P<0.05). CONCLUSION The majority of health service needs of residents of four counties is generated by three diseases: respiratory diseases, digestive diseases, and musculoskeletal diseases. Relatively, rural residents, the elderly, employed persons and the widowed have higher health service needs than others and deserve specific attention.
Adolescent ; Adult ; Aged ; China ; epidemiology ; Community Health Services ; statistics & numerical data ; Digestive System Diseases ; epidemiology ; Female ; Humans ; Incidence ; Male ; Middle Aged ; Musculoskeletal Diseases ; epidemiology ; Respiratory Tract Diseases ; epidemiology ; Sampling Studies ; Surveys and Questionnaires ; Young Adult

OBJECTIVES: To assess the accuracy and influential factors for hypertension prevalence based on questionnaire interview by on-site measurement. METHODS: Data were from the baseline surveys for chronic diseases among residents ages ≥18 years old in 4 districts/counties of Changsha between 2013 and 2014. All surveys adopted multi-stage random sampling to select samples. The Bootstrap resampling method was used to randomly select 1 000 repeated samples with replacement to obtain robust estimate of subgroup prevalence rates. Hypertension prevalence was calculated by using the data from both questionnaire interview and on-site measurement. Using the results of on-site measurement as the golden standard, the accuracy of questionnaire interview and 95% uncertainty interval were estimated. Multivariate logistic regression was used to investigate the influential factors for the underestimated hypotension prevalence based on questionnaire interview. RESULTS: The hypertension prevalence from on-site measurement among the residents in the 4 districts/counties of Changsha was significantly higher than that from questionnaire interview (prevalence ratio: 1.26-2.31). Taking the results of on-site measurement as the golden standard, the sensitivity of questionnaire interview on hypotension prevalence range from 41.76% to 74.83% among the 4 districts/counties, and the specificity fell between 98.51% and 99.46%. The underestimation in questionnaire interview was more likely to occur in the youngest age group (18-34 years old), males, and residents were at lower levels of education in all 4 districts/counties. CONCLUSIONS Compared with the on-site measurement, questionnaire interview significantly under-estimate the hypertension prevalence, suggesting that the on-site measurement method should be firstly considered in epidemiological surveys for hypertension prevalence. If only the questionnaire method can be used to collect data due to conditions, it is necessary to make corresponding corrections to the questionnaire results with reference to relevant research evidence.
Adolescent ; Adult ; China ; Humans ; Hypertension ; epidemiology ; Logistic Models ; Male ; Prevalence ; Risk Factors ; Surveys and Questionnaires ; Young Adult

Plant metabolites are important for plant development and human health. Plants of celery (Apiumgraveolens L.) with different-colored petioles have been formed in the course of long-term evolution. However, the composition, content distribution, and mechanisms of accumulation of metabolites in different-colored petioles remain elusive. Using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), 1159 metabolites, including 100 lipids, 72 organic acids and derivatives, 83 phenylpropanoids and polyketides, and several alkaloids and terpenoids, were quantified in four celery cultivars, each with a different petiole color. There were significant differences in the types and contents of metabolites in celery with different-colored petioles, with the most striking difference between green celery and purple celery, followed by white celery and green celery. Annotated analysis of metabolic pathways showed that the metabolites of the different-colored petioles were significantly enriched in biosynthetic pathways such as anthocyanin, flavonoid, and chlorophyll pathways, suggesting that these metabolic pathways may play a key role in determining petiole color in celery. The content of chlorophyll in green celery was significantly higher than that in other celery cultivars, yellow celery was rich in carotenoids, and the content of anthocyanin in purple celery was significantly higher than that in the other celery cultivars. The color of the celery petioles was significantly correlated with the content of related metabolites. Among the four celery cultivars, the metabolites of the anthocyanin biosynthesis pathway were enriched in purple celery. The results of quantitative real-time polymerase chain reaction (qRT-PCR) suggested that the differential expression of the chalcone synthase (CHS) gene in the anthocyanin biosynthesis pathway might affect the biosynthesis of anthocyanin in celery. In addition, HPLC analysis revealed that cyanidin is the main pigment in purple celery. This study explored the differences in the types and contents of metabolites in celery cultivars with different-colored petioles and identified key substances for color formation. The results provide a theoretical basis and technical support for genetic improvement of celery petiole color.
Anthocyanins ; Apium/metabolism* ; Chlorophyll/metabolism* ; Color ; Gene Expression Regulation, Plant ; Humans ; Metabolomics ; Plant Proteins/genetics* ; Tandem Mass Spectrometry

OBJECTIVETo predict the burden caused by fatal road traffic injuries from 2015 to 2030.

METHODSWe searched the websites of United Nations Population Division,United States Department of Agriculture, World Health Organization, China Energy Research Foundation and other agencies to obtain the predictive values of gross domestic product (GDP) per capita, urbanization, motorization and education from 2015 to 2030 in China. Predicted values were then applied to log-linear models to estimate the numbers and years of life lost due to road traffic injuries from 2015 to 2030.

RESULTSThe mortality rate caused by road traffic injury decreased slightly, from 13.7/100 000 in 2015 to 11.8/100 000 in 2030. 191, 189, 183, 169 thousand persons were estimated to die from road traffic crashes in 2015, 2020, 2025 and 2030, respectively, showing a declining trend. Years of Life Lost (YLLs) caused by road traffic deaths were predicted to be 6 918, 6 634, 6 189, 5 513 thousand years in 2015, 2020, 2025 and 2030, respectively, also showing a gradual downward trend. But the YLLs displayed an increase among people at 55 years of age or older, between 2015 and 2030. Results from the sensitivity analysis showed a stable forecasting result.

CONCLUSIONMortality, number of deaths and YLLs from road traffic crashes were predicted to decrease slightly, between 2015 and 2030 but the number of deaths and YLLs due to road traffic injuries will continue to increase from 2015 to 2030.

Accidents, Traffic ; mortality ; Adolescent ; Adult ; Aged ; Child ; Child, Preschool ; China ; epidemiology ; Cost of Illness ; Female ; Humans ; Infant ; Infant, Newborn ; Male ; Middle Aged ; Young Adult

OBJECTIVETo develop the forecasting models for fatal road traffic injuries and to provide evidence for predicting the future trends on road traffic injuries.

METHODSData on the mortality of road traffic injury including factors as gender and age in different countries, were obtained from the World Health Organization Mortality Database. Other information on GDP per capita, urbanization, motorization and education were collected from online resources of World Bank, WHO, the United Nations Population Division and other agencies. We fitted logarithmic models of road traffic injury mortality by gender and age group, including predictors of GDP per capita, urbanization, motorization and education. Sex- and age-specific forecasting models developed by WHO that including GDP per capita, education and time etc. were also fitted. Coefficient of determination(R(2)) was used to compare the performance between our modes and WHO models.

RESULTS2 626 sets of data were collected from 153 countries/regions for both genders, between 1965 and 2010. The forecasting models of road traffic injury mortality based on GDP per capita, motorization, urbanization and education appeared to be statistically significant(P < 0.001), and the coefficients of determination for males at the age groups of 0-4, 5-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65+ were 22.7% , 31.1%, 51.8%, 52.3%, 44.9%, 41.8%, 40.1%, 25.5%, respectively while the coefficients for these age groups in women were 22.9%, 32.6%, 51.1%, 49.3%, 41.3%, 35.9%, 30.7%, 20.1%, respectively. The WHO models that were based on the GDP per capita, education and time variables were statistically significant (P < 0.001)and the coefficients of determination were 14.9% , 22.0%, 31.5%, 33.1% , 30.7%, 28.5%, 27.7% and 17.8% for males, but 14.1%, 20.6%, 30.4%, 31.8%, 26.7%, 24.3%, 17.3% and 8.8% for females, respectively.

CONCLUSIONThe forecasting models that we developed seemed to be better than those developed by WHO.

Accidents, Traffic ; mortality ; prevention & control ; trends ; Adolescent ; Adult ; Aged ; Child ; Child, Preschool ; Female ; Forecasting ; Humans ; Infant ; Infant, Newborn ; Male ; Middle Aged ; Models, Statistical