Associations between obesity, metabolic health, and the risk of breast cancer in East Asian women

Systematic Review and Meta-Analysis of Lifestyle and Reproductive Factors Associated with Risk of Breast Cancer in Asian Women

BACKGROUND

Assessing breast cancer risks from lifestyle and reproductive factors is critical for developing population-specific risk prediction tools. However, limited studies have evaluated these risks in recent Asian birth cohorts.

METHODS

We systematically reviewed articles published from January 2010 to December 2023, examining breast cancer risk factors in Asian women. Data were described narratively, estimates pooled, and prevalence and attributable proportions compared across Asian populations.

RESULTS

Of the 128 studies reviewed, 103 reported adjusted effect sizes for meta-analysis. Lifestyle and reproductive factors were predictive of breast cancer risk in Asian women, with varying impacts on premenopausal and postmenopausal women. Relative risks were similar within Asian populations and in comparison to European populations, except for menarche, menopause, and hormone receptor therapy. However, risk factor distributions differed across populations. While alcohol intake (21%) and oral contraceptive use (20%) emerged as the most attributable modifiable risk factors in Europeans, passive smoking (24%) and higher BMI (17%, ≥24 kg/m2 among postmenopausal women) were predominant in Asians.

CONCLUSIONS

Our study shows that while the effects of lifestyle and reproductive breast cancer risk factors are largely similar across different populations, their distributions vary.

IMPACT

Our analysis underscores the importance of considering population-specific risk factor distributions when developing risk prediction tools for Asian populations.

Discrepancy Between Genetically Predicted and Observed BMI Predicts Incident Type 2 Diabetes

OBJECTIVE

Obesity is a key predictor of type 2 diabetes (T2D). However, metabolic complications are not solely due to increased BMI. We hypothesized that differences between genetically predicted BMI and observed BMI (BMI-diff) could reflect deviation from individual set point and may predict incident T2D.

RESEARCH DESIGN AND METHODS

From the UK Biobank cohort, we selected participants of European ancestry without T2D (n = 332,154). The polygenic risk score for BMI was calculated via Bayesian regression and continuous shrinkage priors (PRS-CS). According to the BMI-diff, the 10-year risk of T2D was assessed using multivariable Cox proportional hazards model. Independent data from the Korean Genome and Epidemiology Study (KoGES) cohort from South Korea (n = 7,430) were used for replication.

RESULTS

Participants from the UK Biobank were divided into train (n = 268,041) and test set (n = 115,119) to establish genetically predicted BMI. In the test set, the genetically predicted BMI explained 7.1% of the variance of BMI, and there were 3,599 T2D cases (3.1%) during a 10-year follow-up. Participants in the higher quintiles of BMI-diff (more obese than genetically predicted) had significantly higher risk of T2D than those in the lowest quintile after adjusting for observed BMI: the adjusted hazard ratio of the 1st quintile (vs. 5th quintile) was 1.61 (95% CI 1.26-2.05, P < 0.001). Results were consistent among individuals in the KoGES study. Moreover, higher BMI than predicted was associated with impaired insulin sensitivity.

CONCLUSIONS

Having a higher BMI than genetically predicted is associated with an increased risk of T2D. These findings underscore the potential to reassess T2D risk based on individual levels of obesity using genetic thresholds for BMI.

Association of metabolic obesity phenotypes with risk of overall and site-specific cancers: a systematic review and meta-analysis of cohort studies

BACKGROUND

Adiposity is a known risk factor for certain cancers; however, it is not clear whether the risk of cancer differs between individuals with high adiposity but different metabolic health status. The aim of this systematic literature review and meta-analysis of cohort studies was to evaluate associations between metabolic obesity phenotypes and overall and site-specific cancer risk.

METHODS

PubMed and Embase databases were used to identify relevant cohort studies up to the 6th of June 2023. Random-effects models were used to estimate summary relative risks (SRRs) and 95% confidence intervals (CIs) for the association between metabolic obesity phenotypes and cancer risk. Certainty of evidence was assessed using the Cochrane methods and the GRADE tool. This study is registered with PROSPERO, number CRD42024549511.

RESULTS

A total of 15,556 records were screened, and 31 publications covering 15 unique cohort studies were included in this analysis. Of these studies, 22 were evaluated as being at low risk of bias and 9 at moderate risk of bias. Compared to metabolically healthy normal-weight individuals (MHNW), metabolically unhealthy overweight/obese (MUOW/OB) individuals had a higher risk of overall (SRR = 1.21, 95% CI = 1.02-1.44, n = 3 studies, high certainty) and obesity-related cancers (SRR = 1.42, 95% CI = 1.15-1.74, n = 3, very low certainty). Specifically, MUOW/OB individuals were at higher risk of cancers of the postmenopausal breast (SRR = 1.32, 95% CI = 1.17-1.48, n = 7, low certainty), colorectum (SRR = 1.24, 95% CI = 1.16-1.31, n = 6, moderate certainty), endometrium (SRR = 2.31, 95% CI = 2.08-2.57, n = 4, high certainty), thyroid (SRR = 1.42, 95% CI = 1.29-1.57, n = 4, moderate certainty), kidney (SRR = 1.71, 95% CI = 1.40-2.10, n = 3, low certainty), pancreas (SRR = 1.35, 95% CI = 1.24-1.47, n = 3, high certainty), liver (SRR = 1.81, 95% CI = 1.36-2.42, n = 2, moderate certainty), gallbladder (SRR = 1.42, 95% CI = 1.17-1.73, n = 2, high certainty), bladder (SRR = 1.36, 95% CI = 1.19-1.56, n = 2, moderate certainty), and stomach (SRR = 1.50, 95% CI = 1.12-2.01, n = 2, high certainty). In addition, we found elevated risks of most of these cancers among individuals classified as MUNW and MHOW/OB phenotypes compared to those with MHNW phenotype. Our stratified analyses according to metabolic obesity phenotypes suggested that the elevated risks of some cancers were stronger in individuals with MUOW/OB versus those with MHOW/OB or MUNW phenotypes.

CONCLUSION

These findings suggest that both higher adiposity and metabolic dysfunction were independently associated with increased risk of several cancers, with the strongest associations generally observed among those with both metabolic dysfunction and obesity.

Trends in breast cancer mortality attributable to metabolic risks in Chinese women from 1990 to 2019: an age-period-cohort analysis

Objective

Metabolic risks (MRs) are the primary determinants of breast cancer (BC) mortality among women. This study aimed to examine the changing trends in BC mortality associated with MRs and explore how they related to age, time period, and birth cohorts in Chinese women aged 25 and above.

Methods

Data were sourced from the Global Burden of Disease Study 2019 (GBD2019). The BC mortality trajectories and patterns attributable to MRs were assessed using Joinpoint regression. The age-period-cohort (APC) model was employed to evaluate cohort and time period effects.

Results

The age-standardized mortality rate (ASMR) of BC mortality linked to MRs displayed an escalating trend from 1990 to 2019, demonstrating an average annual percentage change (AAPC) of 1.79% (95% CI: 1.69~1.87). AAPCs attributable to high fasting plasma glucose (HFPG) and high body mass index (HBMI) were 0.41% (95% CI: 0.32~0.53) and 2.75% (95% CI: 2.68~2.82), respectively. APC analysis revealed that BC mortality due to HBMI in women aged 50 and above showed a rise with age and mortality associated with HFPG consistently demonstrated a positive correlation with age. The impact of HBMI on BC mortality significantly outweighed that of HFPG. The risk of BC mortality linked to HBMI has steadily increased since 2005, while HFPG demonstrated a trend of initial increase followed by a decrease in the period effect. Regarding the cohort effect, the relative risk of mortality was greater in the birth cohort of women after the 1960s of MRs on BC mortality, whereas those born after 1980 displayed a slight decline in the relative risk (RR) associated with BC mortality due to HBMI.

Conclusion

This study suggests that middle-aged and elderly women should be considered as a priority population, and control of HBMI and HFPG should be used as a primary tool to control metabolic risk factors and effectively reduce BC mortality.

Evaluation of Association Between Menstrual Cycle Timing and Quantitative Background Parenchymal Enhancement on Breast MRI in Premenopausal Women

OBJECTIVES

To evaluate the influence of menstrual cycle timing on quantitative background parenchymal enhancement and to assess an optimal timing of breast MRI in premenopausal women.

METHODS

A total of 197 premenopausal women were enrolled, 120 of which were in the malignant group and 77 in the benign group. Two radiologists depicted the regions of interest (ROI) of the three consecutive biggest slices of glandular tissue in the unaffected side and calculated the ratio (=[SIpost - SIpre]/SIpre) in ROI from the precontrast and early phase to assess BPE quantitatively. Association of BPE with menstrual cycle timing was compared in three categories. The relationships between BPE and age /body mass index (BMI) were also explored.

RESULTS

We found that the BPE ratio presented lower in patients with the follicular phase (day1-14) compared to the luteal phase (day15-30) in the benign group (P = .036). Also, the BPE ratio presented significantly lower in the proliferative phase (day5-14) than the menstrual phase (day1-4) and the secretory phase(day15-30) in the benign group (P = .006). While the BPE ratio was not significantly different among the respective weeks (1-4) of the menstrual cycle in the benign group (P > .05). In the malignant group, the BPE ratio did not significantly differ between/among any menstrual cycle phase or week (all P > .05).

CONCLUSION

It seems more suitable for Asian women whose lesions need to follow up or are suspected of malignant to undergo breast MRI within the 1st to 14th day of the menstrual cycle, especially on the 5th to 14th day.

Metabolic obesity phenotypes and obesity-related cancer risk in the National Health and Nutrition Examination Survey

INTRODUCTION

Body mass index (BMI) fails to identify up to one-third of normal weight individuals with metabolic dysfunction who may be at increased risk of obesity-related cancer (ORC). Metabolic obesity phenotypes, an alternate metric to assess metabolic dysfunction with or without obesity, were evaluated for association with ORC risk.

METHODS

National Health and Nutrition Examination Survey participants from 1999 to 2018 (N = 19,500) were categorized into phenotypes according to the metabolic syndrome (MetS) criteria and BMI: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obese (MHO) and metabolically unhealthy overweight/obese (MUO). Adjusted multivariable logistic regression models were used to evaluate associations with ORC.

RESULTS

With metabolic dysfunction defined as ≥1 MetS criteria, ORC cases (n = 528) had higher proportions of MUNW (28.2% vs. 17.4%) and MUO (62.6% vs. 60.9%) phenotypes than cancer-free individuals (n = 18,972). Compared with MHNW participants, MUNW participants had a 2.2-times higher ORC risk [OR (95%CI) = 2.21 (1.27-3.85)]. MHO and MUO participants demonstrated a 43% and 56% increased ORC risk, respectively, compared to MHNW, but these did not reach statistical significance [OR (95% CI) = 1.43 (0.46-4.42), 1.56 (0.91-2.67), respectively]. Hyperglycaemia, hypertension and central obesity were all independently associated with higher ORC risk compared to MHNW.

CONCLUSIONS

MUNW participants have a higher risk of ORC than other abnormal phenotypes, compared with MHNW participants. Incorporating metabolic health measures in addition to assessing BMI may improve ORC risk stratification. Further research on the relationship between metabolic dysfunction and ORC is warranted.

18F-FDG uptake of visceral adipose tissue on preoperative PET/CT as a predictive marker for breast cancer recurrence

Glucose utilization by visceral adipose tissue (VAT) reflects inflammatory activity, which also promotes tumor growth and carcinogenesis. The effect of metabolically active VAT on survival outcomes in breast cancer is unknown. We investigated survival outcomes in patients with breast cancer based on the standardized uptake value (SUV) of VAT (SUVmean-VAT) using ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT). A total of 148 patients with breast cancer were divided into high- and low groups according to their SUVmean-VAT and SUVmax-tumor. Clinical characteristics and survival outcomes were compared between the groups. High SUVmean-VAT was associated with poor recurrence-free survival (RFS; hazard ratio [HR], 2.754; 95% confidence interval [CI], 1.090-6.958, p = 0.032) and distant metastasis-free survival (DMFS; HR, 3.500; 95% CI, 1.224-10.01, p = 0.019). Multivariate analysis showed that high SUVmean-VAT was a significant factor for poor RFS and poor DMFS (p = 0.023 and 0.039, respectively). High SUVmax-tumor was significantly associated with short RFS (p = 0.0388). Tumors with a high SUV tended to have a short DMFS, although the difference was not significant (p = 0.0718). Our findings showed that upregulated glucose metabolism in the VAT measured using ¹⁸F-FDG PET/CT may be a prognostic biomarker for adverse outcomes in breast cancer.

Use of Breast Cancer Risk Factors to Identify Risk-Adapted Starting Age of Screening in China

Importance

Although current guidelines highlight the need for earlier screening in women at increased risk of breast cancer in China, data on risk-adapted starting ages of screening are limited.

Objective

To explore the risk-adapted starting age of breast cancer screening in China, with comprehensive consideration of breast cancer risk factors.

Design, Setting, and Participants

A multicenter community-based cohort study was conducted under the framework of the Cancer Screening Program in Urban China. Data were collected from January 1, 2013, to December 31, 2018, for unscreened community-dwelling women aged 40 to 74 years without a history of cancer, kidney dysfunction, or severe heart, brain, or lung disease. Data analysis was performed from October 1, 2021, to August 16, 2022.

Exposures

Baseline characteristics associated with breast cancer, including first-degree family history of breast cancer, benign breast disease, breastfeeding, age at menarche, and body mass index.

Main Outcomes and Measures

Outcomes included breast cancer diagnosis and age at diagnosis. Risk-adapted starting age of screening was defined as the age at which women with different levels of breast cancer risk attained a 10-year cumulative risk level similar to women aged 50 years in the general population.

Results

Of the 1 549 988 women enrolled in this study, 3895 had breast cancer (median follow-up, 4.47 [IQR, 3.16-6.35] years). Participants were divided into different risk groups according to breast cancer risk scores (driven by risk factors including first-degree family history of breast cancer, benign breast disease, breastfeeding, age at menarche, and body mass index). Using the 10-year cumulative risk of breast cancer at age 50 years in the general population as a benchmark (2.65% [95% CI, 2.50%-2.76%]), the optimal starting age of screening for women with high, medium, or low risk of breast cancer was identified as 43, 48, or after 55 years, respectively. An online calculator was developed to calculate an individual's optimal starting age of screening.

Conclusions and Relevance

This study identifies the risk-adapted starting age of breast cancer screening based on the principle of equal management of equal risks, which may inform updates of current screening guidelines.

Elevation of Serum Spermidine in Obese Patients: Results from a Cross-Sectional and Follow-Up Study

Background: Spermidine, a natural polyamine, appears to be a promising intervention for the treatment of obesity in animal studies, but epidemiological studies on the association between spermidine and obesity are inadequate. Methods: In the cross-sectional study, a total of 4230 eligible Chinese rural participants aged ≥ 35 years at baseline were recruited, of whom 1738 completed the two-year follow-up. Serum spermidines were measured using high-performance liquid chromatography with a fluorescence detector. Obesity and change in BMI were used as outcomes. Multivariable logistic regression analysis was applied to obtain the odds ratios (ORs) and 95% confidence intervals (CIs). Results: Participants who were obese had higher serum spermidine concentrations than those who were of normal weight (median (IQR), 27.2 ng/mL (14.8−53.4 ng/mL) vs. 23.8 ng/mL (12.8−46.6 ng/mL), p = 0.002). Compared with participants in the first quartile, those in the third quartile (OR 1.327, 95% CI 1.050 to 1.678) and the fourth quartile (OR 1.417, 95% CI 1.121 to 1.791) had a significantly increased risk of prevalent obesity after adjustment for confounding factors. In the follow-up study, participants in the third quartile (OR 0.712, 95% CI 0.535 to 0.946) and the fourth quartile (OR 0.493, 95% CI 0.370 to 0.657) had significantly lower risks of an increase in BMI after adjustment for confounding factors, with the lowest quartile as the reference. Meanwhile, we found a nonlinear relationship between spermidine and BMI in the follow-up study (p < 0.001). Conclusions: Serum spermidine was positively associated with increased odds of obesity in the cross-sectional study but reduced odds of an increase in BMI in the follow-up study among Chinese adults. Future studies are warranted to determine the exact mechanism underlying the association between spermidine and obesity and the scope for interventions.

Prolonged or Transition to Metabolically Unhealthy Status, Regardless of Obesity Status, Is Associated with Higher Risk of Cardiovascular Disease Incidence and Mortality in Koreans

The risk of chronic disease and mortality may differ by metabolic health and obesity status and its transition. We investigated the risk of cardiovascular disease (CVD) and cancer incidence and mortality according to metabolic health and obesity status and their transition using the nationally representative Korea National Health and Nutrition Examination Survey (KNHANES) and the Ansan-Ansung (ASAS) cohort of the Korean Genome and Epidemiology Study. Participants that agreed to mortality linkage (n = 28,468 in KNHANES and n = 7530 adults in ASAS) were analyzed (mean follow-up: 8.2 and 17.4 years, respectively). Adults with no metabolic risk factors and BMI <25 or ≥25 kg/m2 were categorized as metabolically healthy non-obese (MHN) or metabolically healthy obese (MHO), respectively. Metabolically unhealthy non-obese (MUN) and metabolically unhealthy obese (MUO) adults had ≥1 metabolic risk factor and a BMI < or ≥25 kg/m2, respectively. In KNHANES participants, MUN, and MUO had higher risks for cardiovascular mortality, but not cancer mortality, compared with MHN adults. MHO had 47% and 35% lower risks of cancer mortality and all-cause mortality, respectively, compared to MHN. Similar results were observed in the ASAS participants. Compared to those persistently MHN, the risk of CVD was greater when continuously MUN or MUO. Transitioning from a metabolically healthy state to MUO also increased the risk of CVD. Few associations were found for cancer incidence. Using a nationally representative cohort and an 18-year follow-up cohort, we observed that the risk of CVD incidence and mortality and all-cause mortality, but not cancer incidence or mortality, increases with a continuous or a transition to an unhealthy metabolic status in Koreans.