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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]

BACKGROUND: Fertility rates have started declining in India in the last few decades. The total fertility rate, which was 3.5 in 93-94 declined to 2.5 in 2005-6. Researchers attribute this fertility transition to concomitant socio-economic development. Decreasing ovarian reserve is an important contributor for age related infertility . OBJECTIVES: The objective of this study was to assess the association of ovarian reserve with socio-economic status (SES) with the available clinical ovarian reserve markers in reproductive age women. MATERIALS AND METHODS: A total of 160 married women in the age group of 20-35 years, belonging to all three socio-economic strata were assessed for ovarian reserve using the clinical ovarian reserve parameters Antimullerian hormone (AMH), Antral follicle count (AFC) and follicular stimulating hormone (FSH). Analysis of variance was used to see the association of ovarian reserve with SES. RESULTS: Both the ovarian parameters AMH and AFC have shown a significant association with SES (P = 0.000 for AMH and P = 0.023 for AFC). The association between FSH and SES was not significant (P = 0.147). CONCLUSIONS: Higher SES in this study was seen to be associated with better ovarian reserve as assessed by the available clinical ovarian reserve markers. [ABSTRACT FROM AUTHOR]