Department of Pediatric Surgery, Tongji Medical College, Maternal and Child Hospital of Hubei Province, Huazhong University of Science and Technology, Wuhan, 430070, Hubei, China.
Hubei University of Chinese Medicine, Wuhan, 430065, Hubei, China.
J Ovarian Res. 2024 Apr 3;17(1):74. doi: 10.1186/s13048-024-01357-9.
To comprehensively evaluate the effect of low birth weight on premature ovarian insufficiency.
We performed a systematic review of the literature by searching MEDLINE, EMBASE, Web of Science, Scopus, Wanfang and CNKI up to August 2023. All cohort and case-control studies that included birth weight as an exposure and premature ovarian insufficiency as an outcome were included in the analysis. Data were combined using inverse-variance weighted meta-analysis with fixed and random effects models and between-study heterogeneity evaluated. We evaluated risk of bias using the Newcastle Ottawa Scale and using Egger's method to test publication bias. All statistical analyses were performed with the use of R software.
Five articles were included in the review. A total of 2,248,594 women were included, including 21,813 (1%) cases of premature ovarian insufficiency, 150,743 cases of low birth weight, and 220,703 cases of macrosomia. We found strong evidence that changed the results of the previous review that low birth weight is associated with an increased risk of premature ovarian insufficiency (OR = 1.15, 95%CI 1.09-1.22) in adulthood compared with normal birth weight. No effect of macrosomia on premature ovarian insufficiency was found.
Our meta-analysis showed strong evidence of an association between low birth weight and premature ovarian insufficiency. We should reduce the occurrence of low birth weight by various methods to avoid the occurrence of premature ovarian insufficiency.
全面评估低出生体重对卵巢早衰的影响。
我们系统地检索了 MEDLINE、EMBASE、Web of Science、Scopus、万方和中国知网，截至 2023 年 8 月，以获取相关文献。分析中包括了将出生体重作为暴露因素和卵巢早衰作为结局的队列研究和病例对照研究。使用固定效应模型和随机效应模型，通过逆方差加权荟萃分析对数据进行合并，并评估了组间异质性。我们使用纽卡斯尔-渥太华量表（Newcastle Ottawa Scale）评估偏倚风险，并使用 Egger 方法检验发表偏倚。所有的统计分析均使用 R 软件进行。
综述共纳入 5 篇文章。共有 2248594 名女性纳入分析，其中 21813 例（1%）为卵巢早衰，150743 例为低出生体重，220703 例为巨大儿。我们发现强有力的证据改变了之前的综述结果，即与正常出生体重相比，低出生体重与成年后患卵巢早衰的风险增加相关（OR=1.15，95%CI 1.09-1.22）。巨大儿与卵巢早衰之间没有关联。
我们的荟萃分析显示，低出生体重与卵巢早衰之间存在关联。我们应该通过各种方法降低低出生体重的发生，以避免卵巢早衰的发生。
