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TABRAP (TArget Birth Rate Acceptor Program) is a computer programmed model that provides a direct solution to the problem of determining the total annual numbers of contraceptive acceptors required to achieve a prescribed crude birth rate target path. Applied to an initial population for which age structure, the fertility schedule, and expected trends in life expectancy and age-specific proportions of females married are known, TABRAP incorporates the following factors: age at acceptance, with acceptors drawn from currently married nonusers; age-method-specific attrition rates of users; a potential fertility schedule of acceptors that allows for aging and sterility; and allowance both for postpartum anovulation and nine months for gestation to time properly the averted births. TABRAP generates annual data on acceptors, couple-years of use, births averted and age-specific fertility rates that meet the crude birth rate target. Resulting changes in population size, age structure and crude vital rates, also yielded, are invariant with respect to acceptor age and method mix. Assuming a target to reduce the crude birth rate from 45 to 30 in ten years, TABRAP is illustrated for seven mixes of acceptor age-method combinations applied to a population approximately that of Thailand, circa 1965. [ABSTRACT FROM AUTHOR]

This study is one of the few multivariate analyses of the relations of several demographic and socioeconomic variables to fertility and the use of contraception. For fertility, 56 of the 92 hypothesized paths are found to be significant at the .05 level or better. The five variables having a significant and direct effect on fertility, as shown by their path coefficients (p), are: duration of marriage (p = .721), spouse's cohort (p = -.093), spouse's age at marriage (p = .052), caste (p = -.071), and number of siblings of husband (p = .050). The use of contraception is affected by, in order of importance, the spouse's education (p = .267), the husband's education (p = .099), the husband's income (p = .089), and surplus children, i.e., number of living children exceeding ideal number of children (p = .059). Child mortality, which is linked to number of living children and thus indirectly to surplus children, is affected by, in order of importance, the number of children ever born (p = .723), the husband's education (p = -.166), the spouse's absence by death or separation (p = .084), and family structure (p = .035). The advantages and disadvantages of path analysis for this type of research are briefly mentioned. [ABSTRACT FROM AUTHOR]