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Background: The association between dietary protein intake and the risk of mortality is still controversial. The present study aimed to examine the associations between dietary total, animal and plant protein intake and all‐cause and cause‐specific mortality. Methods: Community‐dwelling men aged ≥ 70 years were recruited from local government areas surrounding Concord Hospital in Sydney, New South Wales for the Concord Health and Ageing in Men Project (CHAMP). The research dietitian administered a standardised validated diet history questionnaire to capture baseline dietary intake. In total, 794 men participated in a detailed diet history interview at the third wave. Adequacy of protein intake was assessed by comparing participant intake with the Nutrient Reference Values. Total protein intake was categorised into quintiles. Sources of protein were also captured. Mortality was ascertained through the New South Wales death registry. Cox proportional hazard models were used to assess the association between dietary total, animal and plant protein intake and risk of mortality. Results: The mean age of the CHAMP men was 81 years. In total, 162 men died during a median follow‐up of 3.7 years. Of these, 54 (33.3%) and 49 (30.2%) men died due to cancer and cardiovascular disease, respectively. There were U‐shaped associations between protein intake and all‐cause and cancer mortality. In multiple adjusted analysis, the second (hazard ratio [HR] = 0.38; 95% confidence interval [CI] = 0.18–0.82) and third (HR = 0.36; 95% CI = 0.16–0.82) quintiles of protein intakes were significantly associated with reduced risk of all‐cause and only second quintile (HR = 0.47; 95% CI = 0.10–0.93) of protein intake was significantly associated with cancer mortality. Each serve increase in animal protein was significantly associated with 12% (HR = 1.12; 95% CI = 1.00–1.26) and 23% (HR = 1.23; 95% CI = 1.02–1.49) increased risk of all‐cause mortality and cancer mortality respectively. Conversely, each serve increase in plant protein intake was significantly associated with 25% (HR = 0.75; 95% CI 0.61–0.92) and 28% (HR = 0.72; 95% CI = 0.53–0.97) reduced risk of all‐cause and cancer mortality, respectively. No such associations were observed for cardiovascular disease mortality. Conclusions: Both second and third quintiles of total protein intake were associated with reduced all‐cause and cancer mortality. Plant protein was inversely associated with all‐cause and cancer mortality, whereas animal protein intake was positively associated with mortality. Key points: Our findings suggest a U‐shaped association between life expectancy and total protein intake, in which lifespan is greatest among people with 93–113 g day–1 total protein intake, a level that might be considered moderate in Australia but high in other countries.Both second and third quintiles of total protein intake (range between 79.23 and 107.19 g day–1) were associated with reduced risk of all‐cause and cancer mortality.Higher consumption of animal‐derived proteins was associated with greater mortality risk, whereas this association was reversed when protein consumption was replaced with plant‐derived protein. [ABSTRACT FROM AUTHOR]

Objective: To determine the impacts of using a whole grain food definition on measurement of whole grain intake compared with calculation of total grams of intake irrespective of the source.Design: The Australian whole grain database was expanded to identify foods that comply with the Healthgrain whole grain food definition (≥30 % whole grains on a dry weight basis, whole grain ingredients exceeds refined grain and meeting accepted standards for healthy foods based on local regulations). Secondary analysis of the National Nutrition and Physical Activity Survey (NNPAS) 2011-2012 dietary intake data included calculation of whole grain intakes based on intake from foods complying with the Healthgrain definition. These were compared with intake values where grams of whole grain in any food had been included.Setting: Australia.Participants: Australians (≥2 years) who participated in the NNPAS 2011-2012 (n 12 153).Results: Following expansion of the whole grain database, 214 of the 609 foods containing any amount of whole grain were compliant with the Healthgrain definition. Significant mean differences (all P < 0·05) of 2·84-6·25 g/d of whole grain intake (5·91-9·44 g/d energy adjusted) were found when applying the Healthgrain definition in comparison with values from foods containing any whole grain across all age groups.Conclusions: Application of a whole grain food definition has substantial impact on calculations of population whole grain intakes. While use of such definitions may prove beneficial in settings such as whole grain promotion, the underestimation of total intake may impact on identification of any associations between whole grain intake and health outcomes. [ABSTRACT FROM AUTHOR]

Purpose: The relative advantages of dietary analysis methods, particularly in identifying dietary patterns associated with bone mass, have not been investigated. We evaluated principal component analysis (PCA), partial least-squares (PLS) and reduced-rank regressions (RRR) in determining dietary patterns associated with bone mass.Methods: Data from 1182 study participants (45.9% males; aged 50 years and above) from the North West Adelaide Health Study (NWAHS) were used. Dietary data were collected using a food frequency questionnaire (FFQ). Dietary patterns were constructed using PCA, PLS and RRR and compared based on the performance to identify plausible patterns associated with bone mineral density (BMD) and content (BMC).Results: PCA, PLS and RRR identified two, four and four dietary patterns, respectively. All methods identified similar patterns for the first two factors (factor 1, “prudent” and factor 2, “western” patterns). Three, one and none of the patterns derived by RRR, PLS and PCA were significantly associated with bone mass, respectively. The “prudent” and dairy (factor 3) patterns determined by RRR were positively and significantly associated with BMD and BMC. Vegetables and fruit pattern (factor 4) of PLS and RRR was negatively and significantly associated with BMD and BMC, respectively.Conclusions: RRR was found to be more appropriate in identifying more (plausible) dietary patterns that are associated with bone mass than PCA and PLS. Nevertheless, the advantage of RRR over the other two methods (PCA and PLS) should be confirmed in future studies. [ABSTRACT FROM AUTHOR]

Background: Despite increased use of dietary pattern methods in nutritional epidemiology, there have been few direct comparisons of methods. Older adults are a particularly understudied population in the dietary pattern literature. This study aimed to compare dietary patterns derived by principal component analysis (PCA) and cluster analysis (CA) in older adults and to examine their associations with socio-demographic and health behaviours. Methods: Men (n = 1888) and women (n = 2071) aged 55-65 years completed a 111 -item food frequency questionnaire in 2010. Food items were collapsed into 52 food groups and dietary patterns were determined by PCA and CA. Associations between dietary patterns and participant characteristics were examined using Chi-square analysis. The standardised PCA-derived dietary patterns were compared across the clusters using one-way ANOVA. Results: PCA identified four dietary patterns in men and two dietary patterns in women. CA identified three dietary patterns in both men and women. Men in cluster 1 (fruit, vegetables, wholegrains, fish and poultry) scored higher on PCA factor 1 (vegetable dishes, fruit, fish and poultry) and factor 4 (vegetables) compared to factor 2 (spreads, biscuits, cakes and confectionery) and factor 3 (red meat, processed meat, white-bread and hot chips) (mean, 95 % CI; 0.92, 0.82-1.02 vs. 0.74, 0.63-0.84 vs. -0.43, -0.50- -0.35 vs. 0.60 0.46-0.74, respectively). Women in cluster 1 (fruit, vegetables and fish) scored highest on PCA factor 1 (fruit, vegetables and fish) compared to factor 2 (processed meat, hot chips cakes and confectionery) (1.05, 0.97-1.14 vs. -0.14, -0.21--0.07, respectively). Cluster 3 (small eaters) in both men and women had negative factor scores for all the identified PCA dietary patterns. Those with dietary patterns characterised by higher consumption of red and processed meat and refined grains were more likely to be Australian-born, have a lower level of education, a higher BMI, smoke and did not meet physical activity recommendations (all P< 0.05). Conclusions: PCA and CA identified comparable dietary patterns within older Australians. However, PCA may provide some advantages compared to CA with respect to interpretability of the resulting dietary patterns. Older adults with poor dietary patterns also displayed other negative lifestyle behaviours. Food-based dietary pattern methods may inform dietary advice that is understood by the community. [ABSTRACT FROM AUTHOR]