肥胖显著增加勃起功能障碍风险：一项基于观察性研究的荟萃分析

doi:10.16139/j.1007-9610.2025.06.07

摘要/Abstract

摘要：

目的：通过荟萃分析量化评估肥胖与勃起功能障碍（ED）风险的关联。方法：遵循PRISMA指南，系统检索中英文数据库（截至2025年3月），纳入观察性研究（队列、横断面、病例对照研究），提取调整后效应值（OR及95%CI）。采用美国卫生保健研究与质量局(AHRQ)量表评估研究质量，随机效应模型合并效应值，并通过亚组分析（地域、肥胖定义）和敏感性分析验证结果稳健性。结果：共纳入10项研究（n=230 744），9项为横断面研究。荟萃分析显示，肥胖显著增加ED风险（随机效应OR=1.80，95% CI: 1.29~2.51），异质性较高（I²=99.9%）。亚组分析表明，美国人群关联强度（OR=2.10，95% CI: 1.23~3.60）高于中国人群（OR=1.16，95% CI: 1.05~1.28）；以BMI≥25 kg/m³为肥胖标准时，效应值最高（OR=3.05，95% CI: 2.06~4.51）。敏感性分析证实结果稳健（排除任一研究后OR波动范围1.60~1.94）。结论：肥胖是ED的重要危险因素，其效应强度受地域及肥胖定义影响。建议欧美人群以BMI≥30 kg/m²作为干预阈值，亚洲人群需关注BMI≥25 kg/m³的代谢风险。

关键词: 肥胖, 勃起功能障碍, 荟萃分析, 观察性研究

Abstract:

Objective To quantify the association between obesity and erectile dysfunction (ED) risk through a meta-analysis. Methods Following PRISMA guidelines, systematic searches of Chinese and English databases (up to March 2025) were conducted to include observational studies (cohort, cross-sectional, case-control). Adjusted effect sizes (OR and 95% CI) were extracted. Study quality was assessed using the Agency for Healthcare Research and Quality(AHRQ) scale, and a random-effects model was applied to pool effect sizes. Subgroup analyses (geographic region, obesity definitions) and sensitivity analyses were performed to validate robustness. Results Ten studies (n=230 744), including nine cross-sectional studies, were included. The meta-analysis revealed that obesity significantly increased ED risk (random-effects OR=1.80, 95% CI: 1.29-2.51), with high heterogeneity (I²=99.9%). Subgroup analyses indicated stronger associations in USA populations (OR=2.10, 95% CI: 1.23-3.60) than in Chinese populations (OR=1.16, 95% CI: 1.05-1.28). The highest effect size was observed when using BMI≥25 kg/m³ as the obesity threshold (OR=3.05, 95% CI: 2.06-4.51). Sensitivity analyses confirmed robust results (OR: 1.60-1.94 after excluding any single study). Conclusions Obesity is a critical risk factor for ED, with effect strength influenced by geographic region and obesity definitions. Interventions targeting BMI≥30 kg/m² in Western populations and metabolic risks at BMI≥25 kg/m³ in Asian populations are recommended.

Key words: Obesity, Erectile dysfunction (ED), Meta-analysis, Observational studies

中图分类号:

R589.2

姬阆, 郝少龙, 孙海涛, 孙武青, 马纪红, 白日星, 韩威. 肥胖显著增加勃起功能障碍风险：一项基于观察性研究的荟萃分析[J]. 外科理论与实践, 2025, 30(06): 494-502.

JI Lang, HAO Shaolong, SUN Haitao, SUN Wuqing, Ma Jihong, BAI Rixing, HAN Wei. Obesity significantly increases the risk of erectile dysfunction: a meta-analysis based on observational studies[J]. Journal of Surgery Concepts & Practice, 2025, 30(06): 494-502.

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StudyID	Country	Design	n	Obesity measure	OR(95% CI)	Adjusted vars
Lin et al. 2024^[6]	China	Cross-sectional	3 594	BMI	1.21(1.08-1.34)	Age, race, marital status, education level, PIR, smoking, drinking, recreational activity, CVD, hypercholesterolemia, hypertension, diabetes, urinary creatinine
Yang et al. 2025^[7]	USA	Cross-sectional	3 947	Relative fat mass	1.03(1.01-1.05)	Age, race, education, marital status, PIR, smoking, alcohol, diabetes, hypertension, TC, LDL-C, TG
Xu et al. 2023^[11]	USA	Cross-sectional	3 380	VAI	1.4(1.01-1.95)	Age, alcohol use, hypertension, smoking, diabetes, family poverty ratio, etc.
Andersen et al. 2008^[12]	Denmark	Cross-sectional	1 181	BMI ≥30 kg/m²	2.74(1.1-6.8)	Age, smoking, alcohol consumption, physical activity, committed relationship
Cheng et al. 2007^[13]	China	Cross-sectional	923	BMI ≥25 kg/m²	2.47(1.08-5.67)	Age, GHQ score, smoking status, physical activity
Fung et al. 2004^[14]	USA	Prospective Cohort	570	BMI ≥28 kg/m²	2.02(1.05-3.89)	Age, smoking, hypertension, diabetes, hypercholesterolemia, hypertriglyceridemia
Huang et al. 2023^[15]	USA	Cross-sectional	3 625	METS-VF≥6.63	3.47(2.83-4.24)	Age, race, education level, marital status, diabetes, hypertension, etc.
Pitta et al. 2023^[16]	Brazil	Cross-sectional	2 436	BMI	1.39(1.15-1.69)	Age, hypertension, diabetes, LUTS, depressive symptoms
Suarez Arbelaez et al. 2023^[17]	USA	Cross-sectional	210 130	BMI > 30 kg/m²	3.98(3.94-4.01)	Age, race, ethnicity, diabetes, hypertension, hyperlipidemia, ischaemic heart disease
Yu et al. 2024^[18]	China	Cross-sectional	958	BMI	1.1(1.01-1.19)	Age, WC, TG, HDL-C, diabetes, hypertension, smoking, drinking, physical activity

Study ID	Clear data source	Inclusion/exclusion criteria	Clear time period definition	Sample continuity	Assessor blinding	Quality assurance measures	Reasons for patient exclution	Confounder control	Missing data handing	Response rate/completeness	Follow-up information	Total score	Quality grade
Lin et al. 2024^[6]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Unclear	No	9	High
Yang et al. 2025^[7]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Unclear	No	9	High
Xu et al. 2023^[11]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Unclear	No	9	High
Andersen et al. 2008^[12]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	10	High
Cheng et al. 2007^[13]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	10	High
Fung et al. 2004^[14]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	11	High
Huang et al. 2023^[15]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Unclear	No	9	High
Pitta et al. 2023^[16]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	10	High
Suarez Arbelaez et al. 2023^[17]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Unclear	No	9	High
Yu et al. 2024^[18]	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	10	High