Relationship between dietary characteristics and heel quantitative ultrasound parameters in postmenopausal women from the OsteoLaus cohort.
A LanyanPedro-Manuel Marques-VidalA MétraillerElena Gonzalez RodriguezDidier HansEnisa ShevrojaOlivier LamyPublished in: Scientific reports (2024)
The role of dietary patterns in the development of osteoporosis is unclear. The heel quantitative ultrasound (QUS) is a potential alternative to Dual X-Ray Absorptiometry. Nutrients, foods, dietary patterns and compliance to dietary guidelines were compared between the lowest and the highest tertiles of QUS parameters [Broadband Ultrasound Attenuation (BUA), Speed of Sound (SOS), Stiffness Index (SI)], using data from the OsteoLaus cohort. Participants in the highest tertiles of QUS parameters (385 for BUA, 397 for SOS, 386 for SI) were younger, of higher body weight, and had less major osteoporotic fractures. Women in the highest tertiles of SI and BUA consumed more fat (35.1 ± 0.4 vs 33.9 ± 0.4 and 34.9 ± 0.4 vs 33.8 ± 0.4 gr/day for SI and BUA, respectively, p < 0.05), and complied less frequently with dairy intake guidelines [odds ratio (95% confidence interval): 0.70 (0.53-0.92) and 0.72 (0.55-0.95) for SI and BUA, respectively, p < 0.05] than women in the lowest tertile. No differences were found regarding dietary patterns, healthy dietary scores, or compliance to dietary guidelines. Postmenopausal women in the highest QUS tertiles were younger, of higher weight and BMI, consumed more monounsaturated fatty acids and less dairy and calcium than women in the lowest tertiles. No differences were found between QUS tertiles regarding dietary patterns.
Keyphrases
- postmenopausal women
- bone mineral density
- body weight
- polycystic ovary syndrome
- room temperature
- magnetic resonance imaging
- fatty acid
- high resolution
- pregnancy outcomes
- body mass index
- body composition
- weight gain
- dual energy
- adipose tissue
- cervical cancer screening
- physical activity
- contrast enhanced ultrasound
- weight loss
- computed tomography
- magnetic resonance
- metabolic syndrome
- pregnant women
- big data
- type diabetes
- risk assessment
- mass spectrometry
- data analysis