Sania Ayesha, Sudfeld Christopher R, Danaei Goodarz, Fink Günther, McCoy Dana C, Zhu Zhaozhong, Fawzi Mary C Smith, Akman Mehmet, Arifeen Shams E, Barros Aluisio J D, Bellinger David, Black Maureen M, Bogale Alemtsehay, Braun Joseph M, van den Broek Nynke, Carrara Verena, Duazo Paulita, Duggan Christopher, Fernald Lia C H, Gladstone Melissa, Hamadani Jena, Handal Alexis J, Harlow Siobán, Hidrobo Melissa, Kuzawa Chris, Kvestad Ingrid, Locks Lindsey, Manji Karim, Masanja Honorati, Matijasevich Alicia, McDonald Christine, McGready Rose, Rizvi Arjumand, Santos Darci, Santos Leticia, Save Dilsad, Shapiro Roger, Stoecker Barbara, Strand Tor A, Taneja Sunita, Tellez-Rojo Martha-Maria, Tofail Fahmida, Yousafzai Aisha K, Ezzati Majid, Fawzi Wafaie
ICAP and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York city, New York, USA
Department of Global Health and Population, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA.
BMJ Open. 2019 Oct 3;9(10):e026449. doi: 10.1136/bmjopen-2018-026449.
To determine the magnitude of relationships of early life factors with child development in low/middle-income countries (LMICs).
Meta-analyses of standardised mean differences (SMDs) estimated from published and unpublished data.
We searched Medline, bibliographies of key articles and reviews, and grey literature to identify studies from LMICs that collected data on early life exposures and child development. The most recent search was done on 4 November 2014. We then invited the first authors of the publications and investigators of unpublished studies to participate in the study.
Studies that assessed at least one domain of child development in at least 100 children under 7 years of age and collected at least one early life factor of interest were included in the study.
Linear regression models were used to assess SMDs in child development by parental and child factors within each study. We then produced pooled estimates across studies using random effects meta-analyses.
We retrieved data from 21 studies including 20 882 children across 13 LMICs, to assess the associations of exposure to 14 major risk factors with child development. Children of mothers with secondary schooling had 0.14 SD (95% CI 0.05 to 0.25) higher cognitive scores compared with children whose mothers had primary education. Preterm birth was associated with 0.14 SD (-0.24 to -0.05) and 0.23 SD (-0.42 to -0.03) reductions in cognitive and motor scores, respectively. Maternal short stature, anaemia in infancy and lack of access to clean water and sanitation had significant negative associations with cognitive and motor development with effects ranging from -0.18 to -0.10 SDs.
Differential parental, environmental and nutritional factors contribute to disparities in child development across LMICs. Targeting these factors from prepregnancy through childhood may improve health and development of children.
确定低收入/中等收入国家（LMICs）早期生活因素与儿童发育之间关系的程度。
对已发表和未发表数据估计的标准化均值差异（SMD）进行荟萃分析。
我们检索了Medline、关键文章和综述的参考文献以及灰色文献，以识别来自LMICs的研究，这些研究收集了早期生活暴露和儿童发育的数据。最近一次检索于2014年11月4日进行。然后，我们邀请了出版物的第一作者和未发表研究的调查人员参与该研究。
评估至少100名7岁以下儿童的至少一个儿童发育领域，并收集至少一个感兴趣的早期生活因素的研究纳入该研究。
使用线性回归模型评估每项研究中父母和儿童因素对儿童发育的SMD。然后，我们使用随机效应荟萃分析得出各研究的汇总估计值。
我们从21项研究中检索了数据，包括13个LMICs的20882名儿童，以评估14种主要风险因素的暴露与儿童发育之间的关联。母亲接受过中等教育的儿童与母亲接受过小学教育的儿童相比，认知得分高0.14标准差（95%可信区间0.05至0.25）。早产分别与认知和运动得分降低0.14标准差（-0.24至-0.05）和0.23标准差（-0.42至-0.03）相关。母亲身材矮小、婴儿期贫血以及缺乏清洁水和卫生设施与认知和运动发育存在显著负相关，影响范围为-0.18至-0.10标准差。
不同的父母、环境和营养因素导致LMICs儿童发育存在差异。从孕前到儿童期针对这些因素可能会改善儿童的健康和发育。
