Dataset Information

Association of Oophorectomy and Fat and Lean Body Mass: Evidence from a Population-Based Sample of U.S. Women.

ABSTRACT:

Background

Bilateral oophorectomy during a nonmalignant hysterectomy is frequently performed for ovarian cancer prevention in premenopausal women. Oophorectomy before menopause leads to an abrupt decline in ovarian hormones that could adversely affect body composition. We examined the relationship between oophorectomy and whole-body composition.

Methods

Our study population included cancer-free women 35 to 70 years old from the 1999-2006 National Health and Nutrition Examination Survey, a representative sample of the U.S.

Population

A total of 4,209 women with dual-energy x-ray absorptiometry scans were identified, including 445 with hysterectomy, 552 with hysterectomy and oophorectomy, and 3,212 with no surgery. Linear regression was used to estimate the difference in total and regional (trunk, arms, and legs) fat and lean body mass by surgery status.

Results

In multivariable models, hysterectomy with and without oophorectomy was associated with higher total fat mass [mean percent difference (β); β_oophorectomy: 1.61%; 95% confidence interval (CI), 1.00-2.28; β_hysterectomy: 0.88%; 95% CI, 0.12-1.58] and lower total lean mass [β_oophorectomy: -1.48%; 95% CI, -2.67, -1.15; β_hysterectomy: -0.87%; 95% CI, -1.50, -0.24) compared with no surgery. Results were stronger in women with a normal body mass index (BMI) and those <45 years at surgery. All body regions were significantly affected for women with oophorectomy, whereas only the trunk was affected for women with hysterectomy alone.

Conclusions

Hysterectomy with oophorectomy, particularly in young women, may be associated with systemic changes in fat and lean body mass irrespective of BMI.

Impact

Our results support prospective evaluation of body composition in women undergoing hysterectomy with oophorectomy at a young age.

SUBMITTER: Karia PS

PROVIDER: S-EPMC8258842 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundLittle is known about the association of changes in two body components, muscle and fat mass, with the risk of cardiovascular disease (CVD) among young adults. We investigated the association of changes in predicted lean body mass index (LBMI), appendicular skeletal muscle mass index (ASMI), and body fat mass index (BFMI) with the development of CVD among young adults.MethodsThis nationwide, population-based cohort study included 3 727 738 young adults [2 406 046 (64.5%) men and 1 321 692 (35.5%) women] aged 20-39 years without a previous history of CVD who underwent two health screening examinations during 2009-2010 and 2011-2012. Using validated and robust prediction equations, we calculated the changes in predicted LBMI, ASMI, and BFMI from the first to the second examinations.ResultsThe mean (SD) age was 32.2 (4.9) years, and 2 406 046 (64.5%) of the participants were men. A total of 23 344 CVD events were detected during 22 257 632 person-years of follow-up. Each 1 kg/m2 increase in predicted LBMI and ASMI change was associated with a reduced risk of CVD among men [adjusted hazard ratio (aHR): 0.86, 95% confidence interval (CI) 0.82-0.91; aHR: 0.76, 95% CI 0.69-0.82, respectively] and women (aHR: 0.77, 95% CI 0.63-0.95; aHR: 0.75, 95% CI 0.59-0.96). Each 1 kg/m2 increase in predicted BFMI change was associated with an increased risk of CVD among men (aHR: 1.16, 95% CI 1.10-1.22) and women (aHR: 1.32, 95% CI 1.06-1.65). In both sexes, decreases in predicted LBMI and ASMI were associated with greater CVD risk, and decreased predicted BFMI was associated with a reduced CVD risk. Those who maintained their BMI between -1 and +1 kg/m2 also had a decreased risk of CVD per 1 kg/m2 increase in predicted LBMI and ASMI change among men (aHR: 0.86, 95% CI 0.80-0.92; aHR: 0.85, 95% CI 0.76-0.95) and women (aHR: 0.62, 95% CI 0.47-0.83; aHR: 0.59, 95% CI 0.44-0.80) and had a greater risk of CVD per 1 kg/m2 increase in predicted BFMI change among men (aHR: 1.17, 95% CI 1.10-1.25) and women (aHR: 1.64, 95% CI 1.20-2.23). Regardless of changes in weight, such as from normal to obese or vice versa, these results were consistent.ConclusionsAmong young adults, increased predicted muscle mass or decreased predicted fat mass were associated with a reduced risk of development of CVD. Decreased predicted muscle mass or increased predicted fat mass were associated with an elevated risk of development of CVD.

Project description:Aromatase inhibitors (AIs) induce depletion of estrogen levels, causing bone loss and increased fracture risk in women with breast cancer. High-fat body mass (FBM) emerged as an independent factor associated with the prevalence of morphometric vertebral fractures (VFs) in patients undergoing AIs. We explored the role of lean body mass (LBM) and the interaction of LBM with FBM in predicting the occurrence of VFs in postmenopausal women who were either AI-naïve or AI-treated. A total of 684 consecutive breast cancer patients were enrolled in this cross-sectional study. Each woman underwent a dual-energy X-ray absorptiometry (DXA) scan, measuring bone mineral density (BMD), LBM, and FBM; VFs were assessed using a quantitative morphometric analysis of DXA images. After propensity score matching, the study population was restricted to 480 women, 240 AI-naïve and 240 AI-treated. We used multivariable logistic regression models to explore the associations between baseline characteristics, VF prevalence and the interaction between LBM, FBM and AI therapy. No interaction between LBM and AI therapy on VF prevalence was shown. Conversely, we reported a significant interaction between LBM, FBM and AI therapy (p = .0311). Among AI-treated women having LBM below and FBM above or equal the median value, VF prevalence was numerically higher (15/31; 48.4%) than in other subgroups (VF prevalence: 35.7% in high-LBM and low-FBM group, 23.2% in high-LBM and high-FBM group, and 19.8% in low-LBM and low-FBM group). Among AI-naïve women, the greatest VF proportion was observed in the subgroup with LBM and FBM below median value (25/92; 27.2%). This study suggests a synergism between LBM and FBM in predicting the morphometric VF in women with early breast cancer undergoing AIs. This observation is new and deserves further investigation. The assessment of body composition by DXA might be useful when estimating fracture risk in this population. © 2020 American Society for Bone and Mineral Research © 2020 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.