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The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0–14), the middle-aged (aged 15–64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam’s trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively “young”. Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development. [ABSTRACT FROM AUTHOR]

To balance the supply and demand in China's beef market, beef consumption must be scientifically and effectively forecasted. Beef consumption is affected by many factors and is characterized by gray uncertainty. Therefore, gray theory can be used to forecast the beef consumption, In this paper, the structural defects and unreasonable parameter design of the traditional gray model are analyzed. Then, a new gray model termed, EGM(1,1,r), is built, and the modeling conditions and error checking methods of EGM(1,1,r) are studied. Then, EGM(1,1,r) is used to simulate and forecast China’s beef consumption. The results show that both the simulation and prediction precisions of the new model are better than those of other gray models. Finally, the new model is used to forecast China’s beef consumption for the period from 2019–2025. The findings will serve as an important reference for the Chinese government in formulating policies to ensure the balance between the supply and demand for Chinese beef. [ABSTRACT FROM AUTHOR]

Background: Around the world, regulatory bodies have taken the lead in determining the competencies required to become a physician. As a first step in addressing this project, it was decided to develop a set of core competencies that were unique to China and that might serve as a basis for medical education. The purpose of this paper was to construct a competency model for clinical physicians in China. Methods: Data was collected using a cross-sectional survey of 6247 clinicians from seven administrative regions (31 provinces, autonomous regions and municipalities directly under the central government) in China. The total sample was randomly divided into two sub-samples, an initial sample (Sample 1) and a replication sample (Sample 2). Independent exploratory factor analysis was conducted in each sample and the results were compared to determine the stability. After that the confirmatory factor analysis was used to ascertain the competency model for physicians. The reliability, convergent and discriminant validity of competency-based instrument were also examined. Results: 76 items with 8 dimensions were identified, accounting for 68.41% of the construct’s total variance in the initial sample and 67.47% in the replication sample. For the two samples, the overall scale reliability (Cronbach’s alpha) was both 0.985 with dimensions from 0.905 to 0.954 for the initial sample and from 0.902 to 0.955 for the replication sample after deleting the items. In confirmatory factor analysis, the result showed that all items had acceptable goodness of fit index. RMSEA and SRMR were less than 0.08 (RMSEA = 0.046, SRMR = 0.040), while GFI, NFI, IFI, and CFI were higher than 0.9 (GFI = 0.905, NFI = 0.903, IFI = 0.909, CFI = 0.909), leading to acceptable construct validity. All construct reliability values of the factors were higher than 0.70, and all average variance extracted values exceeded 0.50. Thus, we considered the reliability and validity of the 8 dimensions were acceptable. Conclusions: The instrument was shown to be both valid and reliable for measuring clinical physicians’ competency in China. The results of the competency-based instrument can be used by ministry of health and administrators of hospitals to assess physicians’ competencies, encourage and guide them to modify their behaviors according to the evaluation criteria, and also cultivate physicians with strong clinical practice, innovation and independent scientific research ability. Through these measurements and understandings, the overall level of clinical physicians will be increased in China. [ABSTRACT FROM AUTHOR]

Background: Postpartum Family Visits (PFVs) have been advocated as a way to improve health outcomes for puerperal women and their newborns. This study aimed to identify individual factors associated with the utilization of PFVs in rural Jiangsu Province, China. Methods: We employed responses of the household survey in Jiangsu province, part of the National Health Service Survey (NHSS), a nationally representative survey in China. The data analysis framework was designed based on Andersen’s behavioral model. The outcome variables included nonuse and deficient use of PFVs, and the explanatory variables were organized into three hierarchical levels: predisposing, enabling and need factors. Univariate analysis and multivariate logistic regression analysis were conducted to examine the impact of the three hierarchical levels on PFVs utilization. Results: A total of 884 rural women who had a childbearing history in the prior five years answered PFVs questions. About 23.4% of them had never received any PFVs, and 40.4% received <3 visits. In the results of multivariate logistic regression, educational level (OR = 0.43, 95% CI: 0.24–0.77), income (OR = 0.62, 95% CI: 0.43–0.88), the distance from the nearest hospital (OR = 1.49, 95% CI: 1.07–2.07) and parity (OR = 2.17, 95% CI: 1.54–3.05) had significant relationship with nonuse. Factors significantly associated with deficient use of PFVs included employment (OR = 0.62, 95% CI: 0.39–0.98), the distance from the nearest hospital (OR = 1.73, 95% CI: 1.26–2.36), level of delivery institution (OR = 1.57, 95% CI: 1.14–2.17), and parity (OR = 1.45, 95% CI: 1.03–2.05). Conclusion: The study found lower Social Economic Status (SES), long distance with primary health institutions, and the increased need for services stemming from multi-parity reduced the likelihood of nonuse or deficient use of PFVs in rural areas. Multiparous, low SES women and those living far away from primary health institutions should be paid more attention to assure the coverage of postpartum care. [ABSTRACT FROM AUTHOR]

Background: Intimate partner violence (IPV) is the most common form of violence against women worldwide. IPV during pregnancy is an important risk factor for adverse health outcomes for women and their offspring. However, the prevalence of IPV during pregnancy is not well understood in China. The objective of this study was to estimate the pooled prevalence of IPV during pregnancy in China using a systematic review and meta-analysis. Methods: Systematic literature searches were conducted in PubMed, Web of Science, CNKI, Wanfang, Weipu and CBM databases to identify relevant articles published from the inception of each database to January 31, 2016 that reported data on the prevalence of IPV during pregnancy in China. The Risk of Bias Tool for prevalence studies was used to assess the risk of bias in individual studies. Owing to significant between-study heterogeneity, a random-effects model was used to calculate the pooled prevalence and corresponding 95% confidence interval, and then univariate meta-regression analyses were performed to investigate the sources of heterogeneity. Subgroup analysis was conducted to explore the risk factors associated with IPV during pregnancy. Results: Thirteen studies with a total of 30,665 individuals were included in this study. The overall pooled prevalence of IPV during pregnancy was 7.7% (95% CI: 5.6–10.1%) with significant heterogeneity (I2 = 97.8%, p < 0.001). The results of the univariate meta-regression analyses showed that only the variable “sample source” explained part of the heterogeneity in this study (p < 0.05). The characteristics “number of children” and “unplanned pregnancy” were determined as risk factors for experiencing violence during pregnancy. Conclusions: The prevalence of IPV during pregnancy in China is considerable and one of the highest reported in Asia, which suggests that issues of violence against women during pregnancy should be included in efforts to improve the health of pregnant women and their offspring. In addition, a nationwide epidemiological study is needed to confirm the prevalence estimates and identify more risk factors for IPV during pregnancy. [ABSTRACT FROM AUTHOR]