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American household structure in transition.

The number of U.S. households rose by 58 percent between 1960 and 1983, with nontraditional household types accounting for most of the increase. Whereas the number of households containing married couples with children younger than 18 rose by only four percent over the period, one-parent households increased by 175 percent; one-person households, by 173 percent; and households composed of unmarried couples, by 331 percent. In 1983, households maintained by married couples constituted six in 10 U.S. households; the second most common household type--adults living alone--accounted for about one-quarter of all households. Lone parents living with their children represent nearly one in 10 households. Almost all of these parents are women--of whom two-thirds are separated or divorced, one-quarter have never been married, and fewer than one in 10 are widows. Among adults living alone, women aged 45 and older predominate; but the rate at which the practice has been adopted since 1960 has been greatest among those under age 45. Most of the growth in the number of one-person households occurred during the 1970s. The increase in cohabitation--most of it also in the 1970s--has similarly been concentrated in the younger age-groups. The living arrangements of children younger than 18 have changed accordingly over the two decades. Since 1960, the number of children living with two parents has declined by nearly one-fifth, and the number living with one parent--generally the mother--has more than doubled.(ABSTRACT TRUNCATED AT 250 WORDS)

Adolescent↗

Methods and issues in the projection of population health status.

The discussion of strategies for forecasting health status changes in human populations often becomes immersed in efforts to utilize simple projection strategies that will produce crude projections. The motivation behind this effort is that simple projection strategies have limited data requirements and the crude projection strategies will be, in some ill-defined sense, robust (i.e., insensitive to assumptions). Actually there is a wide range of projection tools available. It seems appropriate to appraise the nature and attributes of each when considering the uses to which the projections will be put. For example, simple models are not necessarily more robust than more sophisticated procedures, especially for longer term temporal projections. Clearly we have many examples in developed countries where the use of simple actuarial or demographic projections has underestimated the true cost of a health programme by factors of 200-300%. The reason why the failures of such simple projection efforts become so rapidly manifest is that the programmes, once implemented, are expanded to meet the population's needs. In projecting only health services or utilization one has nearly a self-fulfilling prophecy--that resource constraints or the actual organization of the programme will directly determine the course of the level and mixture of health services consumption. Therefore failure to base the projections on a detailed model of underlying population needs leads in such cases to grossly inaccurate results. Clearly, projecting a population's health needs requires even more data than projecting health service requirements. Such information constraints require the use of a model to organize data from multiple objective and subjective sources, and to reflect the best scientific understanding of the processes involved. This article briefly discussed the application of 2 such models. One was designed for the analysis of discrete state health changes using population and vital statistics data, the other described both discrete and continuous changes using data from longitudinally followed community populations. One is designed to work only with detailed aggregate data with heavy inputs from scientific experts; the other deals with relatively information-rich measurements. Both can be modified on the basis of expert judgement to deal with simulations of a multiplicity of possible interventions. Both appropriately calculate the relative costs and benefits of select health initiatives.(ABSTRACT TRUNCATED AT 400 WORDS)

Actuarial Analysis↗

Women's lives in transition: a qualitative analysis of the fertility decline in Bangladesh.

The fertility decline that began in Bangladesh in the late 1980s and continues has prompted diverse theories to explain it. In this qualitative analysis of 21 focus-group sessions with rural women ranging in age from the teens to late 40s and living in the villages of the Matlab area, the women's perceptions of their changing society and of the influence of the family planning program are examined. The women's statements reveal their awareness of the social and economic transition they are undergoing and their interest in family-size limitation, which is bolstered by a strong family planning program. Although the shifts in economic and social circumstances are not large, in conjunction with the strong family planning program they constitute a powerful force for change in attitudes, ideas, and behavior among these women.

Adolescent↗