INDONESIAN FAMILY LIFE SURVEY

该提案描述了将于#年在印度尼西亚进行的一项家庭调查。 1992年印度尼西亚家庭生活调查(IFLS)。这项调查将集中在 四个专题领域：生育率、计划生育和避孕；婴儿 和儿童健康和生存；移民和就业；以及健康， 老年人口的经济、社会功能。样品将会 由爪哇、苏门答腊岛、巴厘岛、西努沙登加拉岛、 加里曼丹和苏拉威西，占印尼人口的94% 人口。家庭组成和经济数据将从 所有抽样的家庭。此外，还将有详细的采访 有一个50岁以下的未婚女子和她的配偶，还有一个家庭 50岁以上会员及其配偶。人体测量将是 被认为是曾经结过婚的女性被告，她的丈夫和她的孩子 孩子们。通过抽样将获得可观的规模经济 老年人口和年轻人口同时出现。这项调查将 还将收集大量社区信息，这些信息将链接到 家庭观察。将对生成的数据集进行彻底编辑 并被记录下来以供广泛传播，因为根本目的是公开的 人口研究的微观数据集的可用性。 这一独特的数据集将支持深度研究，这是通过 现有印度尼西亚调查数据，关于与以下方面有关的相关主题 生育率、儿童和成人健康、移徙和就业、婚姻和 家庭构成和代际关系。加入了 个人、家庭和社区数据将显著改善 用于评估在运行的政策和计划的信息库 社区层面。

This proposal describes a household survey to be fielded in Indonesia in 1992, the Indonesian Family Life Survey (IFLS). The survey will focus on four topic areas: fertility, family planning, and contraception; infant and child health and survival; migration and employment; and the health, economic, and social functioning of the older population. The sample will consist of 7000 households in Java, Sumatra, Bali, West Nusa Tenggara, Kalimantan, and Sulawesi, representing 94 percent of the Indonesian population. Household composition and economic data will be collected from all sampled households. In addition, there will be detailed interviews with an ever-married woman less than 50 and her spouse, and a household member over 50 and his/her spouse. Anthropometric measurements will be taken for the ever-married woman respondent, her husband and her young children. Substantial economies of scale will be gained through sampling the older and the younger population at the same time. The survey will also collect extensive community information that will be linked to the household observations. The resulting dataset will be thoroughly edited and documented for wide dissemination, since a fundamental aim is public availability of a microlevel dataset for population research. This unique dataset will support in-depth research, not possible with existing Indonesian survey data, on interrelated topics relating to fertility, child and adult health, migration and employment, marriage and household composition, and intergenerational relations. The joining of individual, family, and community data will significantly improve the information base for assessing policies and programs that operate at the community level.