Tong Yan, Zhou Tinghong, Kong Yao, Liu Zhaoxia, Lai Zhiqing
Center for Reproductive Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang Jiangxi Province, China.
Department of Ultrasonic, The Second Affiliated Hospital of Nanchang University, Nanchang Jiangxi Province, China.
Int J Surg. 2025 Jun 27. doi: 10.1097/JS9.0000000000002883.
An elevated body mass index (BMI) is recognized as a significant risk factor for uterine cancer. This is especially true for endometrial cancer, which accounts for over 90% of uterine cancer cases. However, establishing a causal relationship and accurately measuring its impact on a population scale requires comprehensive epidemiological validation.
We investigated the influence of increased BMI (≥25 kg/m2) on the burden of uterine cancer by utilizing the Global Burden of Disease (GBD) 2021 data covering the period from 1990 to 2021, with a particular emphasis on mortality and disability-adjusted life years (DALYs). Age-standardized morbidity rates were evaluated to compute the estimated annual percentage change (EAPC) through linear regression analyses. Demographic decomposition techniques were employed to analyze the contributions of population growth, aging, and the accumulation of risk factors. A comparison of national performance was made against sociodemographically-adjusted theoretical minimum risk levels using frontier analysis. Additionally, Bayesian age-period-cohort (BAPC) modeling was utilized to project trends in disease burden through 2036. To establish causality between obesity classifications (BMI 30-34.9, 35-39.9, and ≥40 kg/m2) and the subtypes of endometrial cancer (endometrioid versus non-endometrioid), we performed a two-sample Mendelian randomization (MR) analysis with multivariable adjustments, leveraging data from IEU OpenGWAS. The analysis was further fortified by inverse variance-weighted (IVW) methods and pleiotropy-resistant MR strategies, complemented by sensitivity assessments to verify robustness.
The GBD analysis revealed a consistent global rise in the burden of uterine cancer attributable to elevated BMI (≥25 kg/m2) over the last three decades. Age-standardized DALYs rates (ASDR) and mortality rates (ASMR) exhibited a strong correlation with the Socio-Demographic Index (SDI). The morbidity was notably highest among individuals aged 60-74 years, who accounted for the largest number of deaths and DALYs, while those aged ≥90 years had the highest age-specific mortality rates. The burden was most pronounced in high-income regions of North America and areas with elevated SDI. Projections suggested an increase in global mortality, DALYs, age-standardized mortality rates (ASMR), and disability-adjusted rates (ASDR) across all age demographics through 2036 in the absence of targeted preventative measures. The multivariable-adjusted MR analysis validated a dose-dependent causal link, indicating that Class I obesity (BMI 30-34.9 kg/m2) was associated with a 27% heightened risk of endometrioid carcinoma (95% CI 1.19-1.36; P<0.001), which is below the existing screening thresholds. A gradual increase in risk for endometrioid cancer was identified across obesity Classes I-III, independent of confounding variables, while no association was found for non-endometrioid subtypes. The results' robustness was affirmed through IVW and pleiotropy-resistant MR methodologies.
An elevated body mass index (BMI) is a modifiable causal factor for uterine cancer, especially endometrial cancer. This type of cancer disproportionately affects older populations and regions with high socio-demographic indices (SDI). Findings from Mendelian Randomization (MR) and the Global Burden of Disease (GBD) highlight the urgent need for targeted obesity interventions to reduce disease burden in vulnerable populations.
体重指数(BMI)升高被认为是子宫癌的一个重要危险因素。对于子宫内膜癌来说尤其如此,子宫内膜癌占子宫癌病例的90%以上。然而,要建立因果关系并准确衡量其对人群规模的影响,需要全面的流行病学验证。
我们利用涵盖1990年至2021年期间的《2021年全球疾病负担(GBD)》数据,研究BMI升高(≥25kg/m²)对子宫癌负担的影响,特别关注死亡率和伤残调整生命年(DALYs)。通过线性回归分析评估年龄标准化发病率,以计算估计年变化百分比(EAPC)。采用人口分解技术分析人口增长、老龄化和风险因素积累的贡献。使用前沿分析将国家表现与社会人口统计学调整后的理论最低风险水平进行比较。此外,利用贝叶斯年龄-时期-队列(BAPC)模型预测到2036年疾病负担的趋势。为了确定肥胖分类(BMI 30-34.9、35-39.9和≥40kg/m²)与子宫内膜癌亚型(子宫内膜样癌与非子宫内膜样癌)之间的因果关系,我们利用IEU OpenGWAS的数据进行了多变量调整的两样本孟德尔随机化(MR)分析。通过逆方差加权(IVW)方法和抗多效性MR策略进一步加强了分析,并辅以敏感性评估以验证稳健性。
GBD分析显示,在过去三十年中,全球范围内归因于BMI升高(≥25kg/m²)的子宫癌负担持续上升。年龄标准化DALYs率(ASDR)和死亡率(ASMR)与社会人口统计学指数(SDI)呈现出很强的相关性。发病率在60-74岁的人群中尤其高,这些人占死亡人数和DALYs的最大比例,而≥90岁的人群年龄特异性死亡率最高。负担在北美高收入地区和SDI较高的地区最为明显。预测表明,在没有针对性预防措施的情况下,到2036年,所有年龄人口的全球死亡率、DALYs、年龄标准化死亡率(ASMR)和伤残调整率(ASDR)都会增加。多变量调整后的MR分析验证了剂量依赖性因果关系,表明I类肥胖(BMI 30-34.9kg/m²)与子宫内膜样癌风险升高27%相关(95%CI 1.19-1.36;P<0.001),这低于现有的筛查阈值。在肥胖I-III类中,子宫内膜样癌风险逐渐增加,与混杂变量无关,而未发现与非子宫内膜样癌亚型有关联。通过IVW和抗多效性MR方法证实了结果的稳健性。
体重指数(BMI)升高是子宫癌尤其是子宫内膜癌的一个可改变的因果因素。这种癌症对老年人群和社会人口统计学指数(SDI)高的地区影响尤为严重。孟德尔随机化(MR)和全球疾病负担(GBD)的研究结果凸显了针对肥胖进行干预以减轻弱势群体疾病负担的迫切需求。