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  1. 1
    084970

    Levels, age patterns and trends of sterility in selected countries South of the Sahara.

    Larsen U

    In: International Population Conference / Congres International de la Population, Montreal 1993, 24 August - 1st September. Volume 1, [compiled by] International Union for the Scientific Study of Population [IUSSP]. Liege, Belgium, IUSSP, 1993. 593-603.

    Using data collected in cooperation with the World Fertility Surveys (WFS) and the Demographic and Health Surveys (DHS) the aim was to determine the levels, age patterns, and trends of sterility in benin, Burundi, Cameroon, Ghana, Ivory Coast, Kenya, Lesotho, Liberia, Mali, Mauritania, Nigeria, Senegal, Sudan, Togo, and Uganda. In sub-Saharan Africa, 10 countries completed a WFS survey from 1977 to 1982. From 1986 to 1991 a DHS survey was carried out in 13 countries. In Sudan, Lesotho and Mauritania only ever married women were eligible for interview. All women (generally age 15-49) were eligible in the rest of the sub-Saharan countries. The selected samples included women who had been sexually active at least 5 years. Subsequently the levels and range patterns of sterility were estimated for each country and by produce within each country. The inhibiting effect of sterility on fertility was also assessed. Age-specific rates of sterility were estimated by the subsequently infertile estimator. At age 34, the proportions sterile reached .41 in Cameroon, .11 in Burundi, and intermediate levels in the rest of the countries. Burundi had the lowest prevalence of sterility at all ages, Cameroon had the highest up to about age 42, and at older ages Sudan and Lesotho ranked highest. In general, sterility rose moderately up to age 35 and then more rapidly after age 40. Sterility was particularly prevalent along major rivers, lakes, and coastal areas. Sterility was relatively high around Lake Victoria as well as in the Coast region of Kenya in 1977-78. Primary sterility was less than 3% in Burundi, Ghana, Kenya, Togo, and in Ondo state, Nigeria; 3-5% in Lesotho, Liberia, Mali, and Nigeria (1990), Senegal, Sudan (1989-90) and Uganda; and 5% or more in Cameroon, Nigeria (1981-82), and Sudan (1978-79). Differential disease patterns caused the most variation in age-specific rates of sterility. Under the hypothesis of Burundi levels of age specific sterility and unchanged fertility, and African woman in the age range from 20 to 44 would have an additional .5 to 2 children.
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  2. 2
    795858

    Screening procedures for detecting errors in maternity history data.

    Brass W

    In: United Nations. Economic and Social Commission for Asia and the Pacific, World Fertility Survey, and International Institute for Population Studies. Regional Workshop on Techniques of Analysis of World Fertility Survey data: report and selected papers. New York, UN, 1979. 15-36. (Asian Population Studies Series No. 44)

    The World Fertility Survey provides data from national maternity history inquiries. Detecting trends and differentials is only as accurate as the data collected. Where evidence suggests error, the analysis may be restricted to obtaining only a measure of fertility level. The basic data is the date and order of birth of each live born child for a sample of women in the reproductive period, according to the current age of the women and their duration of marriage. The cohort marker is usually separated into 7 5-year classes determined by age at interview; sample of women is representative of the female population of childbearing age. Total births for each cohort are allocated to different periods preceding the survey date. Reading down the columns gives the births to different cohorts over different ranges in the same time interval preceding the survey. To detect omissions, check the overall sex ratio and the sex ratios by periods; examine the trends of infant mortality by cohorts and periods; an excess of male mortality over female indicates poor reporting of dead female children and/or of sex (a common omission). From data on age of mother and number of surviving children at the survey and estimates of mortality level, the numbers of births at preceding periods may be calculated.
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