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Favourable body composition has been associated with higher dietary protein intake. However, little is known regarding this relationship in a population of Chinese Americans (CHA), who have lower BMI compared with other populations. The aim of the present study was to assess the relationship between dietary protein intake, fat mass (FM) and fat-free mass (FFM) in CHA. Data were from the Chinese American Cardiovascular Health Assessment (CHA CHA) 2010–2011 (n 1707); dietary intake was assessed using an adapted and validated FFQ. Body composition was assessed using bioelectrical impedance analysis. The associations between protein intake (% energy intake) and BMI, percentage FM (FM%), percentage FFM (FFM%), FM index (FMI) and FFM index (FFMI) were examined using multiple linear regression adjusted for age, sex, physical activity, acculturation, total energy intake, sedentary time, smoking status, education, employment and income. There was a significant positive association between dietary protein and BMI (B = 0·056, 95 % CI 0·017, 0·104; P = 0·005), FM (B = 0·106, 95 % CI 0·029, 0·184; P = 0·007), FM% (B = 0·112, 95 % CI 0·031, 0·194; P = 0·007) and FMI (B = 0·045, 95 % CI 0·016, 0·073; P = 0·002). There was a significant negative association between dietary protein and FFM% (B = −0·116, 95 % CI −0·196, −0·036; P = 0·004). In conclusion, higher dietary protein intake was associated with higher adiposity; however, absolute FFM and FFMI were not associated with dietary protein intake. Future work examining the relationship between protein source (i.e. animal) and body composition is warranted in this population of CHA.
Knowledge regarding association of dietary branched-chain amino acid (BCAA) and type 2 diabetes (T2D), and the contribution of BCAA from meat to the risk of T2D are scarce. We evaluated associations between dietary BCAA intake, meat intake, interaction between BCAA and meat intake and risk of T2D. Data analyses were performed for 74 155 participants aged 50−79 years at baseline from the Women’s Health Initiative for up to 15 years of follow-up. We excluded from analysis participants with treated T2D, and factors potentially associated with T2D or missing covariate data. The BCAA and total meat intake was estimated from FFQ. Using Cox proportional hazards models, we assessed the relationship between BCAA intake, meat intake, and T2D, adjusting for confounders. A 20 % increment in total BCAA intake (g/d and %energy) was associated with a 7 % higher risk for T2D (hazard ratio (HR) 1·07; 95 % CI 1·05, 1·09). For total meat intake, a 20 % increment was associated with a 4 % higher risk of T2D (HR 1·04; 95 % CI 1·03, 1·05). The associations between BCAA intake and T2D were attenuated but remained significant after adjustment for total meat intake. These relations did not materially differ with or without adjustment for BMI. Our results suggest that dietary BCAA and meat intake are positively associated with T2D among postmenopausal women. The association of BCAA and diabetes risk was attenuated but remained positive after adjustment for meat intake suggesting that BCAA intake in part but not in full is contributing to the association of meat with T2D risk.
It is well established that protein–energy malnutrition decreases serum insulin-like growth factor (IGF)-I levels, and supplementation of 30 g of whey protein daily has been shown to increase serum IGF-I levels by 8 % after 2 years in a clinical trial. Cohort studies provide the opportunity to assess associations between dietary protein intake and IGF axis protein levels under more typical eating conditions. In the present study, we assessed the associations of circulating IGF axis protein levels (ELISA, Diagnostic Systems Laboratories) with total biomarker-calibrated protein intake, as well as with dairy product and milk intake, among postmenopausal women enrolled in the Women's Health Initiative (n 747). Analyses were carried out using multivariate linear regression models that adjusted for age, BMI, race/ethnicity, education, biomarker-calibrated energy intake, alcohol intake, smoking, physical activity and hormone therapy use. There was a positive association between milk intake and free IGF-I levels. A three-serving increase in milk intake per d (approximately 30 g of protein) was associated with an estimated average 18·6 % higher increase in free IGF-I levels (95 % CI 0·9, 39·3 %). However, total IGF-I and insulin-like growth factor-binding protein 3 (IGFBP-3) levels were not associated with milk consumption and nor were there associations between biomarker-calibrated protein intake, biomarker-calibrated energy intake, and free IGF-I, total IGF-I or IGFBP-3 levels. The findings of the present study carried out in postmenopausal women are consistent with clinical trial data suggesting a specific relationship between milk consumption and serum IGF-I levels, although in the present study this association was only statistically significant for free, but not total, IGF-I or IGFBP-3 levels.
To develop and evaluate a pictorial, web-based version of the NCI diet history questionnaire (Web-PDHQ).
The Web-PDHQ and paper version of the DHQ (Paper-DHQ) were administered 4 weeks apart with 218 participants randomised to order. Dietary data from the Web-PDHQ and Paper-DHQ were validated using a randomly selected 4 d food record recording period (including a weekend day) and two randomly selected 24 h dietary recalls during the 4 weeks intervening between these two diet history administrations.
Research office in Reston, VA, USA.
Computer-literate men and women recruited through newspaper advertisements.
Mean correlation of energy and the twenty-five examined nutrients between the Web-PDHQ and Paper-DHQ was 0·71 and 0·51, unadjusted and energy-adjusted by the residual method, respectively. Moderate mean correlations (unadjusted 0·41 and 0·38; energy-adjusted 0·41 and 0·34) were obtained between both the Web-PDHQ and Paper-DHQ with the 4 d food record on energy and nutrients, but the correlations between the Web-PDHQ and Paper-DHQ with the 24 h recalls were modest (unadjusted 0·31 and 0·29; energy-adjusted 0·37 and 0·26). A subset of participants (n 48) completing the Web-PDHQ at the initial visit performed a retest on the same questionnaire 1 week later to determine repeatability, and the unadjusted mean correlation was 0·82.
These data indicate that the Web-PDHQ has comparable repeatability and validity to the Paper-DHQ but did not improve the relationship of the DHQ to other food intake measures (e.g. food records, 24 h recall).
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