To expand the evidence base to inform future public policy aimed at accident prevention, we investigated the impact of different categories of injury on average life expectancy in China. We used data from the National...To expand the evidence base to inform future public policy aimed at accident prevention, we investigated the impact of different categories of injury on average life expectancy in China. We used data from the National Death Cause Registration Information System and National Maternity and Children Health Surveillance databases, as well as 2010 population data from the National Bureau of Statistics. We then calculated the average life expectancy of the Chinese population, in addition to life expectancy after eliminating injury-related mortality. The average life expectancy of the Chinese population in 2010 was 74.93 years. After eliminating deaths due to injuries, the fourth leading cause of mortality in China, average life expectancy increased by 1.36 years. When this was broken down by population sub-groups, these gains were 1.76 and 0.79 years in men and women, 0.94 and 1.56 years in urban and rural residents, and 1.11, 1.30, and 1.67 years for residents in the Eastern, Central and Western regions respectively. After eliminating all categories of injury, the average life expectancy of the Chinese population was found to increase by 1.36 years. This figure was higher for males and residents of rural areas and Western China.展开更多
The fertility occupies a central position in the study of population growth.The growth of the population depends entirely on human fertility,including birth,death rates and life expectancy.Growth of the fertility is o...The fertility occupies a central position in the study of population growth.The growth of the population depends entirely on human fertility,including birth,death rates and life expectancy.Growth of the fertility is one of the key determinants of the Population Growth.This paper focused on the determinant factors of population growth in Rwanda.From the findings,there is a statistically significance of fertility trends at 0.05 percent because the t-statistic in table-4 is greater than its critical value(1.96)at 0.05 percent.The results provides evidence of Fertility,birth,death and life expectancy as factors which boost population to grow in Rwanda.The results founded,indicate the existence of high fertility rates even decreasing,lead to increase population due to its positive values over time.This means that Fertility rates in Rwanda has a positive impact on the country's population growth,especially in the youth who realizes around 48 percent of entire Rwandan’s Population.The relationship between fertility rate and the time describe a decreasing function,which interesting for us showing that fertility has been reduced over time.In other words,as well as the years increased,the fertility decreased.The coefficient of Time is(-0.117035)which implies that a unit change in time will change Total Fertility Rate(TFR)by(-0.117035),table-1.The model of fertility represents a decreasing function while the time function still increasing,as shows in the figure-2.The fertility variable has positive relationships with the population dependent variable even the fertility coefficient is negative,the probability p-value is significant at 0.05 significance level on one hand and the absolute t-statistic is great than the critical value at 0.05 level of significance,which confirm the statistically significance of t-statistic.The coefficients on the death rate and Life expectancy are respectively positive and significant at all confidence level,table-5.展开更多
Backgrounds::Cardiovascular disease(CVD)remains the leading cause of deaths nationwide.However,little is understood about its temporal trend and corresponding influence on longevity improvements.We aimed to describe t...Backgrounds::Cardiovascular disease(CVD)remains the leading cause of deaths nationwide.However,little is understood about its temporal trend and corresponding influence on longevity improvements.We aimed to describe the updated tendency in CVD mortality and to quantify its impact on life expectancy(LE)increase in China.Methods::All-cause mortality rates were calculated with population sizes from the National Bureau of Statistics and death counts from the National Health Commission.We estimated CVD mortality rates by allocating age-and sex-based mortality envelopes to each CVD subtype based on its proportion derived from the Disease Surveillance Points system.The probability of CVD premature deaths and LE were calculated with life tables and we adopted Arriaga’s method to quantitate age-and cause-specific contributions to LE gains.Results::During 2013 to 2018,the age-standardized mortality rate of CVD decreased from 289.69(95%confidence interval[CI]:289.03,290.35)/100,000 to 272.37(95%CI:271.81,272.94)/100,000,along with a decline in probability of CVD premature deaths from 9.05%(95%CI:9.02%,9.09%)to 8.13%(95%CI:8.10%,8.16%).The gap in CVD mortality across sexes expanded with more remarkable declines in females,especially for those aged 15 to 64 years.Among major subtypes,the probability of premature deaths from hemorrhage stroke declined fastest,while improvements of ischemic stroke and ischemic heart disease were limited,and there was an increase in stroke sequelae.LE in China reached 77.04(95%CI:76.96,77.12)years in 2018 with an increase of 1.38 years from 2013.Of the total LE gains,21.15%(0.29 years)were attributed to reductions of CVD mortality in the overall population,mostly driven by those aged>65 years.Conclusions::The general process in reducing CVD mortality has contributed to longevity improvements in China.More attention should be paid to prevention and control of atherosclerotic CVD and stroke sequelae,especially for the elderly.Working-age males also deserve additional attention due to inadequate improvements.展开更多
基金supported by the US Centers for Disease Control and Prevention, Atlanta, Georgia,USAThinkTank Research Center for Health Development, Beijing, China
文摘To expand the evidence base to inform future public policy aimed at accident prevention, we investigated the impact of different categories of injury on average life expectancy in China. We used data from the National Death Cause Registration Information System and National Maternity and Children Health Surveillance databases, as well as 2010 population data from the National Bureau of Statistics. We then calculated the average life expectancy of the Chinese population, in addition to life expectancy after eliminating injury-related mortality. The average life expectancy of the Chinese population in 2010 was 74.93 years. After eliminating deaths due to injuries, the fourth leading cause of mortality in China, average life expectancy increased by 1.36 years. When this was broken down by population sub-groups, these gains were 1.76 and 0.79 years in men and women, 0.94 and 1.56 years in urban and rural residents, and 1.11, 1.30, and 1.67 years for residents in the Eastern, Central and Western regions respectively. After eliminating all categories of injury, the average life expectancy of the Chinese population was found to increase by 1.36 years. This figure was higher for males and residents of rural areas and Western China.
文摘The fertility occupies a central position in the study of population growth.The growth of the population depends entirely on human fertility,including birth,death rates and life expectancy.Growth of the fertility is one of the key determinants of the Population Growth.This paper focused on the determinant factors of population growth in Rwanda.From the findings,there is a statistically significance of fertility trends at 0.05 percent because the t-statistic in table-4 is greater than its critical value(1.96)at 0.05 percent.The results provides evidence of Fertility,birth,death and life expectancy as factors which boost population to grow in Rwanda.The results founded,indicate the existence of high fertility rates even decreasing,lead to increase population due to its positive values over time.This means that Fertility rates in Rwanda has a positive impact on the country's population growth,especially in the youth who realizes around 48 percent of entire Rwandan’s Population.The relationship between fertility rate and the time describe a decreasing function,which interesting for us showing that fertility has been reduced over time.In other words,as well as the years increased,the fertility decreased.The coefficient of Time is(-0.117035)which implies that a unit change in time will change Total Fertility Rate(TFR)by(-0.117035),table-1.The model of fertility represents a decreasing function while the time function still increasing,as shows in the figure-2.The fertility variable has positive relationships with the population dependent variable even the fertility coefficient is negative,the probability p-value is significant at 0.05 significance level on one hand and the absolute t-statistic is great than the critical value at 0.05 level of significance,which confirm the statistically significance of t-statistic.The coefficients on the death rate and Life expectancy are respectively positive and significant at all confidence level,table-5.
基金This study was supported by grants from the Chinese Academyof MedicalSciences(CAMS)Innovation Fund for Medical Sciences(No.2021-I2M-1-010,No.2017-I2M-1-004)the National Natural Science Foundation of China(No.12126602,No.82030102)the National Key R&D Program of China(No.2017YFC0211700).
文摘Backgrounds::Cardiovascular disease(CVD)remains the leading cause of deaths nationwide.However,little is understood about its temporal trend and corresponding influence on longevity improvements.We aimed to describe the updated tendency in CVD mortality and to quantify its impact on life expectancy(LE)increase in China.Methods::All-cause mortality rates were calculated with population sizes from the National Bureau of Statistics and death counts from the National Health Commission.We estimated CVD mortality rates by allocating age-and sex-based mortality envelopes to each CVD subtype based on its proportion derived from the Disease Surveillance Points system.The probability of CVD premature deaths and LE were calculated with life tables and we adopted Arriaga’s method to quantitate age-and cause-specific contributions to LE gains.Results::During 2013 to 2018,the age-standardized mortality rate of CVD decreased from 289.69(95%confidence interval[CI]:289.03,290.35)/100,000 to 272.37(95%CI:271.81,272.94)/100,000,along with a decline in probability of CVD premature deaths from 9.05%(95%CI:9.02%,9.09%)to 8.13%(95%CI:8.10%,8.16%).The gap in CVD mortality across sexes expanded with more remarkable declines in females,especially for those aged 15 to 64 years.Among major subtypes,the probability of premature deaths from hemorrhage stroke declined fastest,while improvements of ischemic stroke and ischemic heart disease were limited,and there was an increase in stroke sequelae.LE in China reached 77.04(95%CI:76.96,77.12)years in 2018 with an increase of 1.38 years from 2013.Of the total LE gains,21.15%(0.29 years)were attributed to reductions of CVD mortality in the overall population,mostly driven by those aged>65 years.Conclusions::The general process in reducing CVD mortality has contributed to longevity improvements in China.More attention should be paid to prevention and control of atherosclerotic CVD and stroke sequelae,especially for the elderly.Working-age males also deserve additional attention due to inadequate improvements.
