INDONESIAN FAMILY LIFE SURVEY

这项建议叙述了将于2004年在印度尼西亚进行的一项住户调查。 1992年，印度尼西亚家庭生活调查。 调查将重点关注 四个专题领域：生育、计划生育和避孕;婴儿 和儿童健康与生存;移徙与就业;以及保健、 老年人口的经济和社会功能。 样品将 包括爪哇、苏门答腊、巴厘、西努沙登加拉、 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 所有抽样家庭。 此外，还会有详细的采访 一个50岁以下的已婚妇女和她的配偶， 50岁以上的人及其配偶。 人体测量将是 被认为是已婚妇女的回答，她的丈夫和她的年轻人 孩子 通过抽样将获得可观的规模经济 老年人和年轻人同时。 调查将 还收集广泛的社区信息，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 并记录在案，以便广泛传播，因为一个基本目标是公开 提供用于人口研究的微观数据集。 这个独特的数据集将支持深入的研究，这是不可能的， 印度尼西亚现有的调查数据， 生育率、儿童和成人健康、移徙和就业、婚姻和 家庭组成和代际关系。 的加盟 个人、家庭和社区数据将显著改善 评估政策和方案的信息库， 社区一级。

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.