Bean Consumption Accounts for Differences in Body Fat and Waist Circumference: A Cross-Sectional Study of 246 Women.
Larry A TuckerPublished in: Journal of nutrition and metabolism (2020)
Beans and other legumes have multiple nutritional qualities that reduce the risk of many diseases. However, the link between legume intake and obesity remains unclear. Therefore, the present study was designed to examine the association between bean intake, body fat percentage (BF%), and waist circumference, in 246 women. BF% was measured using dual-energy X-ray absorptiometry (DXA). Bean intake was assessed using the Block Food Frequency Questionnaire and indexed using total cups of bean-based food items and also factor scores derived from a factor analysis showing adherence to a bean-based dietary pattern. Bean consumption was expressed as cups per 1000 kilocalories. R\egression results showed that the relationship between bean intake (total cups) and BF% was inverse and linear (F = 7.4, P=0.0069). Moreover, with bean consumption being divided into tertiles, there were mean differences across groups in BF% (F = 7.4, P=0.0008) and waist circumference (F = 4.2, P=0.0164). Specifically, women who consumed moderate or high amounts of beans had less body fat and smaller waists than those with low intakes. Similarly, using tertiles to categorize participants based on adherence to a bean-based dietary pattern, developed using factor analysis, those with low adherence had higher BF% (F = 7.9, P=0.0005) and larger waists (F = 4.5, P=0.0118) than their counterparts. The associations remained significant after adjusting for potential confounders. In conclusion, beans and other legumes seem to have dietary qualities that may be beneficial in the battle against obesity.
Keyphrases
- body mass index
- dual energy
- weight gain
- body weight
- polycystic ovary syndrome
- computed tomography
- type diabetes
- metabolic syndrome
- weight loss
- body composition
- physical activity
- pregnant women
- total hip arthroplasty
- pregnancy outcomes
- risk assessment
- mass spectrometry
- bone mineral density
- image quality
- high intensity
- cervical cancer screening
- data analysis