Multilevel modelling has become a popular analytical approach for many demographic and health outcomes. The objective of this paper is to systematically review studies which used multilevel modelling in demographic research in Africa in terms of the outcomes analysed, common findings, theoretical rationale, questions addressed, methodological approaches, study design and data sources. The review was conducted by searching electronic databases such as Ebsco hosts, Science Direct, ProQuest, Scopus, PubMed and Google scholar for articles published between 2010 and 2021. Search terms such as neighbourhood, social, ecological and environmental context were used. The systematic review consisted of 35 articles, with 34 being peer-reviewed journal articles and 1 technical report. Based on the systematic review community-level factors are important in explaining various demographic outcomes. The community-level factors such as distance to the health facility, geographical region, place of residence, high illiteracy rates and the availability of maternal antenatal care services influenced several child health outcomes. The interpretation of results in the reviewed studies mainly focused on fixed effects rather than random effects. It is observed that data on cultural practices, values and beliefs, are needed to enrich the robust evidence generated from multilevel models.

多层次建模已成为许多人口和健康结果的流行分析方法。本文的目的是系统地回顾在非洲人口研究中使用多层次模型的研究，包括分析结果、共同发现、理论基础、解决的问题、方法论、研究设计和数据来源。该审查是通过搜索 Ebsco Hosts、Science Direct、ProQuest、Scopus、PubMed 和 Google Scholar 等电子数据库来查找 2010 年至 2021 年间发表的文章。使用了邻里、社会、生态和环境背景等搜索术语。系统评价包括 35 篇文章，其中 34 篇是同行评审的期刊文章和 1 篇技术报告。根据系统评价，社区层面的因素对于解释各种人口结果非常重要。社区层面的因素，如距医疗机构的距离、地理区域、居住地、高文盲率和孕产妇产前保健服务的可用性，影响了一些儿童健康结果。回顾研究中对结果的解释主要集中在固定效应而不是随机效应。据观察，需要有关文化习俗、价值观和信仰的数据来丰富多层次模型生成的有力证据。