County-based IMR and U5MR in Anhui and Henan provinces in China were estimated and analyzed by using the 1990 Census Data. Census was conducted on July 1,1990, the number of deaths only occurred in the first half year...County-based IMR and U5MR in Anhui and Henan provinces in China were estimated and analyzed by using the 1990 Census Data. Census was conducted on July 1,1990, the number of deaths only occurred in the first half year of 1990 was collected. In order to obtain the total population and total number of deaths in the same year, the total number of deaths in each eqersex group for the whole 1990 was then estimated by taking the death number in the first half of 1990 as the base and multiplying a coefficient, which varied in different age-sex-region groups. Two major adjustments for some possible underreporting cases in female birth and infant death were made. If the sex ratio at age 0 in some counties was beyond 1. 2, then it was taken as 1. 15 for rural counties and 1.10 for urban cities, which were the estimates of sex ratios for the children at ape 5 in the national 1% Population Sampling Survey in 1995. The adjustment for IMR were made by comparing the segment of the county lift table from age 15 through 59 with that from the same age groups in the international and Chinese Model Life Tables. The IMR in the county life table would be substituted by the one in the closest Model Life Talbe, if it was less than in the latter.The findings of the analysis may be summarized as fol1ows: (i) Total county-based IMR and U5MR were 33. 4 Per 1000 and 41. 4 per 1000 respectively, with great variations between urban cities (25. 4 per 1000 for IMR and 31. 4 per 1 000 for U5MR) and rural counties (35. 1 Per 1000 for IMR and 43. 6 per 1000 for U5MR). There were also sighficant differences in child mortality between nationally identified Poor counties and other counties in rural areas. In the opr counties the total IMR was 40. 7 per 1 000 living births in average while in non-opr counties it was only 33. 2 per 1000 in average (P < 0.05). The U5MR in opr counties was 25 percent higher than in non-opr counties (51. 5 vs 40. 9 Per 1 000 living births).(ii) Statistically significant correlation between child mortality and socio-economic variables was revealed from the data set, among which gross social economic products per capita was found to have the strongest relationship with child mortality. The neqative correlation was found between child mortality and a set of socalled' rich' variables including the gross social products, gr-oss agricultural products, gna industrial products and the proportions of high-educated population at county level, whereas the poSitive correlation was found between child mortality and a set of'poor' variables, such as proportions Of residents with lower 1evel of education and illiteracy rate.(iii) thfferences in child mortality between these two provinces were found, which were identical to the trends of differences in socio-economic indicators between them.tower child mortality proved to be associated with better socio-economic conditions(higher per capita products, higher proPortions of residents with higher level of education, lower proportion of less educated people and illiteracy) in province Henan.展开更多
文摘County-based IMR and U5MR in Anhui and Henan provinces in China were estimated and analyzed by using the 1990 Census Data. Census was conducted on July 1,1990, the number of deaths only occurred in the first half year of 1990 was collected. In order to obtain the total population and total number of deaths in the same year, the total number of deaths in each eqersex group for the whole 1990 was then estimated by taking the death number in the first half of 1990 as the base and multiplying a coefficient, which varied in different age-sex-region groups. Two major adjustments for some possible underreporting cases in female birth and infant death were made. If the sex ratio at age 0 in some counties was beyond 1. 2, then it was taken as 1. 15 for rural counties and 1.10 for urban cities, which were the estimates of sex ratios for the children at ape 5 in the national 1% Population Sampling Survey in 1995. The adjustment for IMR were made by comparing the segment of the county lift table from age 15 through 59 with that from the same age groups in the international and Chinese Model Life Tables. The IMR in the county life table would be substituted by the one in the closest Model Life Talbe, if it was less than in the latter.The findings of the analysis may be summarized as fol1ows: (i) Total county-based IMR and U5MR were 33. 4 Per 1000 and 41. 4 per 1000 respectively, with great variations between urban cities (25. 4 per 1000 for IMR and 31. 4 per 1 000 for U5MR) and rural counties (35. 1 Per 1000 for IMR and 43. 6 per 1000 for U5MR). There were also sighficant differences in child mortality between nationally identified Poor counties and other counties in rural areas. In the opr counties the total IMR was 40. 7 per 1 000 living births in average while in non-opr counties it was only 33. 2 per 1000 in average (P < 0.05). The U5MR in opr counties was 25 percent higher than in non-opr counties (51. 5 vs 40. 9 Per 1 000 living births).(ii) Statistically significant correlation between child mortality and socio-economic variables was revealed from the data set, among which gross social economic products per capita was found to have the strongest relationship with child mortality. The neqative correlation was found between child mortality and a set of socalled' rich' variables including the gross social products, gr-oss agricultural products, gna industrial products and the proportions of high-educated population at county level, whereas the poSitive correlation was found between child mortality and a set of'poor' variables, such as proportions Of residents with lower 1evel of education and illiteracy rate.(iii) thfferences in child mortality between these two provinces were found, which were identical to the trends of differences in socio-economic indicators between them.tower child mortality proved to be associated with better socio-economic conditions(higher per capita products, higher proPortions of residents with higher level of education, lower proportion of less educated people and illiteracy) in province Henan.
