Anthropometric measures and metabolic rate in association with risk of breast cancer (United States)
| Autor: | R. Jean Hine, Mark S. Eberhardt, Stan C. Freni, Angelo Turturro |
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| Rok vydání: | 1996 |
| Předmět: |
Adult
Cancer Research medicine.medical_specialty National Health and Nutrition Examination Survey Breast Neoplasms Body Mass Index Breast cancer Risk Factors Internal medicine Confidence Intervals Elbow Odds Ratio Medicine Humans Nutritional Physiological Phenomena Aged Hip Anthropometry business.industry Body Weight Cancer Confounding Factors Epidemiologic Odds ratio Middle Aged medicine.disease Confidence interval Body Height United States Postmenopause Skinfold Thickness Endocrinology Metabolism Oncology Adipose Tissue Basal metabolic rate Body Constitution Regression Analysis Female Basal Metabolism business Energy Intake Body mass index Biomarkers Demography Follow-Up Studies |
| Zdroj: | Cancer causescontrol : CCC. 7(3) |
| ISSN: | 0957-5243 |
| Popis: | To investigate whether cancer risk-reduction seen in calorie-restricted animals also applies to breast cancer in women, we have analyzed data from the first National Health and Nutrition Examination Survey in the United States and subsequent follow-up surveys. During the follow-up of one to 155 months, 182 out of 7,622 women developed breast cancer. Due to biased under-reporting of dietary intake, the analysis did not examine calorie intake as an exposure variable, but rather focused on anthropometric measures and metabolic rate as biomarkers of nutritional balance. Multiple Cox regression analysis showed elevated odds ratios (OR) for height, elbow width, and skinfolds among postmenopausal women. ORs for the fifth quintile were 2.0 (95 percent confidence interval [CI] = 1.0-3.8), 2.3 (CI = 1.2-4.7), and 2.0 (CI = 1.0-4.0), respectively. Weight (OR = 2.5, CI = 1.2-5.1) and resting metabolic rate (OR = 2.0, CI = 1.0-4.0) were significant relative to the second quintile. Bitrochanteric breadth, sitting height, body fat, body mass index, or combination variables were not associated with cancer risk. It was concluded that in the analysis of breast cancer data, skeletal measures ought to be considered as routine potential confounders, and that using measured rather than estimated metabolic rates may improve risk prediction. |
| Databáze: | OpenAIRE |
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