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TOPLINE:
Accurate body fat measures are crucial for effective cancer prevention.
METHODOLOGY:
- Researchers conducted a case-control study including 1033 breast cancer cases and 1143 postmenopausal population controls from the MCC-Spain study.
- Participants were aged 20-85 years. BMI was calculated as the ratio of weight to height squared and categorized using World Health Organization standards: < 25, 25-29.9, 30-34.9, and ≥ 35.
- CUN-BAE was calculated using a specific equation and categorized according to the estimated percentage of body fat: < 35%, 35%-39.9%, 40%-44.9%, and ≥ 45%.
- Odds ratios (ORs) were estimated with 95% CIs for both measures (BMI and CUN-BAE) for breast cancer cases using unconditional logistic regression.
TAKEAWAY:
- Excess body weight attributable to the risk for breast cancer was 23% when assessed using a BMI value > 30 and 38% when assessed using a CUN-BAE value > 40% body fat.
- Hormone receptor stratification showed that these differences in population-attributable fractions were only observed in hormone receptor–positive cases, with an estimated burden of 19.9% for BMI and 41.9% for CUN-BAE.
- The highest categories of CUN-BAE showed an increase in the risk for postmenopausal breast cancer (OR, 2.13 for body fat ≥ 45% compared with the reference category < 35%).
- No similar trend was observed for BMI, as the gradient declined after a BMI ≥ 35.
IN PRACTICE:
“The results of our study indicate that excess body fat is a significant risk factor for hormone receptor–positive breast cancer in postmenopausal women. Our findings suggest that the population impact could be underestimated when using traditional BMI estimates, and that more accurate measures of body fat, such as CUN-BAE, should be considered,” the authors of the study wrote.
SOURCE:
This study was led by Verónica Dávila-Batista, University of Las Palmas de Gran Canaria in Las Palmas de Gran Canaria, Spain. It was published online in Journal of Epidemiology and Community Health.
LIMITATIONS:
The case-control design of the study may have limited the ability to establish causal relationships. BMI was self-reported at the time of the interview for controls and 1 year before diagnosis for cancer cases, which may have introduced recall bias. The formula for CUN-BAE was calculated from a sedentary convenience sample, which may not have been representative of the general population. The small sample size of cases that did not express hormone receptors was another limitation. The study’s findings may not be generalizable to non-White populations as non-White participants were excluded.
DISCLOSURES:
Dávila-Batista disclosed receiving grants from the Carlos III Health Institute. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
TOPLINE:
Accurate body fat measures are crucial for effective cancer prevention.
METHODOLOGY:
- Researchers conducted a case-control study including 1033 breast cancer cases and 1143 postmenopausal population controls from the MCC-Spain study.
- Participants were aged 20-85 years. BMI was calculated as the ratio of weight to height squared and categorized using World Health Organization standards: < 25, 25-29.9, 30-34.9, and ≥ 35.
- CUN-BAE was calculated using a specific equation and categorized according to the estimated percentage of body fat: < 35%, 35%-39.9%, 40%-44.9%, and ≥ 45%.
- Odds ratios (ORs) were estimated with 95% CIs for both measures (BMI and CUN-BAE) for breast cancer cases using unconditional logistic regression.
TAKEAWAY:
- Excess body weight attributable to the risk for breast cancer was 23% when assessed using a BMI value > 30 and 38% when assessed using a CUN-BAE value > 40% body fat.
- Hormone receptor stratification showed that these differences in population-attributable fractions were only observed in hormone receptor–positive cases, with an estimated burden of 19.9% for BMI and 41.9% for CUN-BAE.
- The highest categories of CUN-BAE showed an increase in the risk for postmenopausal breast cancer (OR, 2.13 for body fat ≥ 45% compared with the reference category < 35%).
- No similar trend was observed for BMI, as the gradient declined after a BMI ≥ 35.
IN PRACTICE:
“The results of our study indicate that excess body fat is a significant risk factor for hormone receptor–positive breast cancer in postmenopausal women. Our findings suggest that the population impact could be underestimated when using traditional BMI estimates, and that more accurate measures of body fat, such as CUN-BAE, should be considered,” the authors of the study wrote.
SOURCE:
This study was led by Verónica Dávila-Batista, University of Las Palmas de Gran Canaria in Las Palmas de Gran Canaria, Spain. It was published online in Journal of Epidemiology and Community Health.
LIMITATIONS:
The case-control design of the study may have limited the ability to establish causal relationships. BMI was self-reported at the time of the interview for controls and 1 year before diagnosis for cancer cases, which may have introduced recall bias. The formula for CUN-BAE was calculated from a sedentary convenience sample, which may not have been representative of the general population. The small sample size of cases that did not express hormone receptors was another limitation. The study’s findings may not be generalizable to non-White populations as non-White participants were excluded.
DISCLOSURES:
Dávila-Batista disclosed receiving grants from the Carlos III Health Institute. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
TOPLINE:
Accurate body fat measures are crucial for effective cancer prevention.
METHODOLOGY:
- Researchers conducted a case-control study including 1033 breast cancer cases and 1143 postmenopausal population controls from the MCC-Spain study.
- Participants were aged 20-85 years. BMI was calculated as the ratio of weight to height squared and categorized using World Health Organization standards: < 25, 25-29.9, 30-34.9, and ≥ 35.
- CUN-BAE was calculated using a specific equation and categorized according to the estimated percentage of body fat: < 35%, 35%-39.9%, 40%-44.9%, and ≥ 45%.
- Odds ratios (ORs) were estimated with 95% CIs for both measures (BMI and CUN-BAE) for breast cancer cases using unconditional logistic regression.
TAKEAWAY:
- Excess body weight attributable to the risk for breast cancer was 23% when assessed using a BMI value > 30 and 38% when assessed using a CUN-BAE value > 40% body fat.
- Hormone receptor stratification showed that these differences in population-attributable fractions were only observed in hormone receptor–positive cases, with an estimated burden of 19.9% for BMI and 41.9% for CUN-BAE.
- The highest categories of CUN-BAE showed an increase in the risk for postmenopausal breast cancer (OR, 2.13 for body fat ≥ 45% compared with the reference category < 35%).
- No similar trend was observed for BMI, as the gradient declined after a BMI ≥ 35.
IN PRACTICE:
“The results of our study indicate that excess body fat is a significant risk factor for hormone receptor–positive breast cancer in postmenopausal women. Our findings suggest that the population impact could be underestimated when using traditional BMI estimates, and that more accurate measures of body fat, such as CUN-BAE, should be considered,” the authors of the study wrote.
SOURCE:
This study was led by Verónica Dávila-Batista, University of Las Palmas de Gran Canaria in Las Palmas de Gran Canaria, Spain. It was published online in Journal of Epidemiology and Community Health.
LIMITATIONS:
The case-control design of the study may have limited the ability to establish causal relationships. BMI was self-reported at the time of the interview for controls and 1 year before diagnosis for cancer cases, which may have introduced recall bias. The formula for CUN-BAE was calculated from a sedentary convenience sample, which may not have been representative of the general population. The small sample size of cases that did not express hormone receptors was another limitation. The study’s findings may not be generalizable to non-White populations as non-White participants were excluded.
DISCLOSURES:
Dávila-Batista disclosed receiving grants from the Carlos III Health Institute. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.