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Abstract：
Nonhuman primate (NHP) studies are crucial to biomedical research. NHPs are the species most similar to humans in lifespan, body size, and hormonal profiles. Planning research requires statistical power evaluation, which is difficult to perform when lacking directly relevant preliminary data. This is especially true for NHP developmental programming studies, which are scarce. We review the sample sizes reported, challenges, areas needing further work, and goals of NHP maternal nutritional programming studies. The literature search included 27 keywords, for example, maternal obesity, intrauterine growth restriction, maternal high-fat diet, and maternal nutrient reduction. Only fetal and postnatal offspring studies involving tissue collection or imaging were included. Twenty-eight studies investigated maternal over-nutrition and 33 under-nutrition; 23 involved macaques and 38 baboons. Analysis by sex was performed in 19; minimum group size ranged from 1 to 8 (mean 4.7 ± 0.52, median 4, mode 3) and maximum group size from 3 to 16 (8.3 ± 0.93, 8, 8). Sexes were pooled in 42 studies; minimum group size ranged from 2 to 16 (mean 5.3 ± 0.35, median 6, mode 6) and maximum group size from 4 to 26 (10.2 ± 0.92, 8, 8). A typical study with sex-based analyses had group size minimum 4 and maximum 8 per sex. Among studies with sexes pooled, minimum group size averaged 6 and maximum 8. All studies reported some significant differences between groups. Therefore, studies with group sizes 3-8 can detect significance between groups. To address deficiencies in the literature, goals include increasing age range, more frequently considering sex as a biological variable, expanding topics, replicating studies, exploring intergenerational effects, and examining interventions.
摘要：
非人灵长类动物(NHP)研究对生物医学研究至关重要。NHP是寿命中与人类最相似的物种，身体尺寸,和荷尔蒙档案。规划研究需要统计能力评估,当缺乏直接相关的初步数据时，这是难以执行的。对于NHP发展规划研究尤其如此，这是稀缺的。我们回顾了报告的样本量，挑战,需要进一步工作的领域，和NHP产妇营养规划研究的目标。文献检索包括27个关键词，例如,产妇肥胖，宫内生长受限,产妇高脂肪饮食，和母体营养减少。仅包括涉及组织收集或成像的胎儿和产后后代研究。28项研究调查了孕妇的过度营养和33项营养不足；23只涉及猕猴和38只狒狒。在19人中进行了性别分析；最小组大小为1至8（平均4.7±0.52，中位数4，模式3），最大组大小为3至16（8.3±0.93，8，8）。在42项研究中汇总了性别；最小组大小为2至16（平均5.3±0.35，中位数6，模式6），最大组大小为4至26（10.2±0.92，8，8）。一项基于性别分析的典型研究显示，每个性别的群体规模最小为4，最大为8。在汇集性别的研究中，最小组大小平均为6，最大为8。所有研究都报告了组间的一些显著差异。因此,3-8组大小的研究可以检测组间的显著性.为了解决文献中的不足，目标包括增加年龄范围，更频繁地将性别视为生物学变量，扩展主题，复制研究，探索代际效应，并检查干预措施。
