Protein intake, sources and distribution impact on muscle protein synthesis and muscle mass in older adults. However, it is less clear whether dietary protein influences muscle strength. Data were obtained from the Researching Eating Activity and Cognitive Health (REACH) study, a cross-sectional study aimed at investigating dietary patterns, cognitive function and metabolic syndrome in older adults aged 65–74 years. Dietary intake was assessed using a 4-d food record and muscle strength using a handgrip strength dynamometer. After adjusting for confounders, in female older adults (n 212), total protein intake (β = 0⋅22, P < 0⋅01); protein from dairy and eggs (β = 0⋅21, P = 0⋅03) and plant food sources (β = 0⋅60, P < 0⋅01); and frequently consuming at least 0⋅4 g/kg BW per meal (β = 0⋅08, P < 0⋅01) were associated with higher BMI-adjusted muscle strength. However, protein from meat and fish intake and the coefficient of variance of protein intake were not related to BMI-muscle strength in female older adults. No statistically significant associations were observed in male participants (n = 113). There may be sex differences when investigating associations between protein intake and muscle strength in older adults. Further research is needed to investigate these sex differences.

Adequate dietary protein intake is important in human subjects for maintaining muscle turnover, determining the protein content of tissues and thus the preservation of muscle mass and function as we age. A screening tool to assess if an older individual is likely to have a lower dietary protein intake (predicted probability of protein intake ≤1⋅0 g/kg per d), has been developed for a Netherlands dietary profile, but this has not been validated in a UK population. This study aimed to adapt and then validate the protein screening tool for use in a UK population. Amendment of the tool was undertaken using data from UK BioBank and the UK National Diet and Nutrition Survey to reflect protein sources in the UK diet. Validation of the amended version of the protein screener screening tool was conducted using protein intake derived from a food frequency questionnaire (FFQ) in a sample of UK adults (n = 184) (age range 18–91 years) as the reference standard. Using the FFQ, 40 % of respondents (n = 74) reported a protein intake of ≤1⋅0 g per kg body mass. The discriminative accuracy of the amended screener was tested using receiver operating characteristic (ROC) curves. The area under the curve for the ROC was 0⋅731 (95 % CI 0⋅657, 0⋅805), indicating that the amended screener may be a valid tool to screen for individuals consuming ≤1⋅0 g/kg adjusted BM/d in an adult UK population. This protein screener tool is a potential method to screen individuals with a likelihood of habitually consuming protein intakes of ≤1⋅0 g/kg per d. Further validation is needed using a more robust dietary intake methodology and for specific groups, such as older adults. The screener may be applicable across healthcare, clinical and research applications.

Adequate protein intake is essential for the maintenance of whole-body protein mass. Different methodological approaches are used to substantiate the evidence for the current protein recommendations, and it is continuously debated whether older adults require more protein to counteract the age-dependent loss of muscle mass, sarcopenia. Thus, the purpose of this critical narrative review is to outline and discuss differences in the approaches and methodologies assessing the protein requirements and, hence, resulting in controversies in current protein recommendations for healthy older adults. Through a literature search, this narrative review first summarises the historical development of the Food and Agriculture Organization/World Health Organization/United Nations University setting of protein requirements and recommendations for healthy older adults. Hereafter, we describe the various types of studies (epidemiological studies and protein turnover kinetic measurements) and applied methodological approaches founding the basis and the different recommendations with focus on healthy older adults. Finally, we discuss important factors to be considered in future studies to obtain evidence for international agreement on protein requirements and recommendations for healthy older adults. We conclude by proposing future directions to determine ‘true’ protein requirements and recommendations for healthy older adults.

This study aimed to investigate the association between individual and combinations of macronutrients with premature death, CVD and dementia. Sex differences were investigated. Data were utilised from a prospective cohort of 120 963 individuals (57 % women) within the UK Biobank, who completed ≥ two 24-h diet recalls. The associations of macronutrients, as percentages of total energy intake, with outcomes were investigated. Combinations of macronutrients were defined using k-means cluster analysis, with clusters explored in association with outcomes. There was a higher risk of death with high carbohydrate intake (hazard ratios (HR), 95 % CI upper v. lowest third 1·13 (1·03, 1·23)), yet a lower risk with higher intakes of protein (upper v. lowest third 0·82 (0·76, 0·89)). There was a lower risk of CVD with moderate intakes (middle v. lowest third) of energy and protein (sub distribution HR (SHR), 0·87 (0·79, 0·97) and 0·87 (0·79, 0·96), respectively). There was a lower risk of dementia with moderate energy intake (SHR 0·71 (0·52, 0·96)). Sex differences were identified. The dietary cluster characterised by low carbohydrate, low fat and high protein was associated with a lower risk of death (HR 0·84 (0·76, 0·93)) compared with the reference cluster and a lower risk of CVD for men (SHR 0·83 (0·71, 0·97)). Given that associations were evident, both as single macronutrients and for combinations with other macronutrients for death, and for CVD in men, we suggest that the biggest benefit from diet-related policy and interventions will be when combinations of macronutrients are targeted.

The aim of the present study was to determine whether the association between body mass index (BMI) and the intake of macronutrients varies along the BMI distribution of German adults. Based on a sample of 9214 men and women aged 18–80 years from the representative cross-sectional German National Nutrition Survey (NVS) II, quantile regression was used to investigate the association between BMI and the intake of macronutrients independent of energy intake and other predictors. In both sexes, BMI was positively associated with the intake of total protein and animal protein over its entire range and negatively associated with vegetable protein. A negative association between BMI and the intake of polysaccharides was found along the entire range of BMI in men. There was a weak negative association between BMI and the intake of total fat and saturated fatty acids observed in normal-weight-range women only. In conclusion, the association between BMI and the intake of macronutrients varies along the BMI range. Animal protein intake is positively associated with BMI independent of energy intake in both sexes whereas only in men an inverse association of polysaccharide intake with BMI was shown.

We aimed to investigate the associations of poor oral health cross-sectionally with diet quality and intake in older people. We also examined whether change in diet quality is associated with oral health problems. Data from the British Regional Heart Study (BRHS) comprising British males aged 71–92 years and the Health, Aging and Body Composition (HABC) Study comprising American males and females aged 71–80 years were used. Dental data included tooth loss, periodontal disease, dry mouth and self-rated oral health. Dietary data included diet quality (based on Elderly Dietary Index (BRHS) and Healthy Eating Score (HABC Study)) and several nutrients. In the BRHS, change in diet quality over 10 years (1998–2000 to 2010–2012) was also assessed. In the BRHS, tooth loss, fair/poor self-rated oral health and accumulation of oral health problems were associated with poor diet quality, after adjustment. Similar associations were reported for high intake of processed meat. Poor oral health was associated with the top quartile of percentage of energy content from saturated fat (self-rated oral health, OR 1·34, 95 % CI 1·02, 1·77). In the HABC Study, no significant associations were observed for diet quality after adjustment. Periodontal disease was associated with the top quartile of percentage of energy content from saturated fat (OR 1·48, 95 % CI 1·09, 2·01). In the BRHS, persistent low diet quality was associated with higher risk of tooth loss and accumulation of oral health problems. Older individuals with oral health problems had poorer diets and consumed fewer nutrient-rich foods. Persistent poor diet quality was associated with oral health problems later in life.

Protein is important for growth, maintenance and protection of the body. Both adequacy of protein quantity and protein quality in the diet are important to guarantee obtaining all the essential amino acids. Protein–energy malnutrition is widely present in developing countries such as Nigeria and might result in stunting and wasting. Needs for protein differ depending on age and physiological status and are higher during growth, pregnancy and lactation. The present review assessed protein quantity and quality in diets of Nigerian infants, children, adolescents, and pregnant and lactating women. Literature reviews and calculations were performed to assess adequacy of Nigerian protein intake and to examine the Nigerian diet. The digestible indispensable amino acid score was used to calculate protein quality of nine Nigerian staple foods and of a mixture of foods. The Nigerian population had mostly adequate protein intake when compared with the most recent protein recommendations by the FAO (2013) and WHO/FAO/UNU (2007). An important exception was the protein intake of adolescent girls and pregnant and lactating women. Most of the assessed Nigerian plant-based staple foods were of low protein quality and predominantly lacked the amino acid lysine. The addition of animal-source foods can bridge the protein quality gap created by predominance of plant-based foods in the Nigerian diet. The methodology of this review can be applied to other low- and middle-income countries where diets are often plant-based and lack variety, which might influence protein intake adequacy.

The aim of the study was to investigate whether the interaction of physical activity (PA) and protein intake is associated with physical function (PF). The women from the Osteoporosis Risk Factor and Fracture Prevention Study (n 610) completed a questionnaire on lifestyle factors and PA and underwent PF and body composition measurements at baseline (BL) and over 3 years of follow-up (3y-FU). PA was categorised according to WHO cut-off PA = 0, 0 < PA < 2·5 and PA ≥ 2·5 h/week. Protein intake was calculated from the 3-d food record at baseline and categorised according to the Nordic Nutrition Recommendations <1·1 and ≥1·1 g/kg body weight (BW). The results showed in univariate ANOVA at the baseline and at the 3-year follow-up, women with high PA ≥ 2·5 h/week and protein intake ≥ 1·1 g/kg BW had higher grip strength adjusted for BMI, higher mean number of chair rises, faster mean walking speed, higher modified mean short physical performance battery score and lower mean fat mass compared with other interaction groups. High PA and protein intake were associated with lower BMI despite significantly higher energy intake. In conclusion, higher PA and protein intake interaction was associated with greater PF and lower fat mass, but the association with relative skeletal muscle index and muscle mass was inconclusive. The present study gives noteworthy information for preventing sarcopenia.

The present study investigated the association between protein intake and lean mass according to obesity status over a 12-year period. Data on 4412 participants aged 40–69 years were obtained from the Korean Genome and Epidemiology Study. The usual dietary protein intake of these participants was assessed at baseline using a semi-quantitative FFQ. Body composition was measured using bioelectrical impedance analysis at baseline and after a 12-year follow-up. Linear mixed-effects models were used to examine the associations between lean mass after a 12-year follow-up and protein intake at baseline. After adjusting for covariates and lean mass at baseline, comparisons between the highest and lowest tertiles revealed that dietary protein intake was positively associated with lean mass in both men (β = 0·79, P = 0·001) and women (β = 0·28, P = 0·082) after the 12-year period; however, those differences were attenuated after additional adjustment for fat mass at baseline and were stronger in the normal-weight group (men, β = 0·85, P = 0·002; women, β = 0·97, P < 0·001) but were not detected in the obese group. In the obese group, age (men, β = 4·08, P < 0·001; women, β = 2·61, P < 0·001) and regular physical activity (men, β = 0·88, P = 0·054; women, β = 0·76, P < 0·001) were significantly associated with lean mass after 12 years of follow-up. The results of the present study showed that protein intake may contribute to the prevention of ageing-related lean mass loss; however, the impact of this intake may vary depending on obesity status. Therefore, the maintenance of a healthy body weight during ageing through enhanced protein intake is likely to confer health benefits.

Sufficient protein intake has been suggested to be important for preventing physical frailty, but studies show conflicting results which may be explained because not all studies address protein source and intake of other macronutrients and total energy. Therefore, we studied 2504 subjects with data on diet and physical frailty, participating in a large population-based prospective cohort among subjects aged 45+ years (the Rotterdam Study). Dietary intake was assessed with a FFQ. Frailty was defined according to the frailty phenotype as the presence of at least three out of the following five symptoms: weight loss, low physical activity, weakness, slowness and fatigue. We used multinomial logistic regression models to evaluate the independent association between protein intake and frailty using two methods: nutrient residual models and energy decomposition models. With every increase in 10 g total, plant or animal protein per d, the odds to be frail were 1·06 (95 % CI 0·98, 1·15), 0·87 (95 % CI 0·71, 1·07) and 1·07 (95 % CI 0·99, 1·15), respectively, using the nutrient residual method. Using the energy partition model, we observed that the odds to be frail were lower with higher vegetable protein intake (OR per 418·4 kJ (100 kcal): 0·61, 95 % CI 0·39, 0·97), however, results disappeared when adjusting for physical activity. For energy intake from any source we observed that with every 418·4 kJ (100 kcal) increase, the odds to be frail were 5 % lower (OR: 0·95, 95 % CI 0·93, 0·97). Our results suggest that energy intake, but not protein specifically, is associated with less frailty. Considering other macronutrients, physical activity and diet quality seems to be essential for future studies on protein and frailty.

Higher protein intake, and particularly higher leucine intake, is associated with attenuated loss of lean body mass (LBM) over time in older individuals. Dietary leucine is thought to be a key mediator of anabolism. This study aimed to assess this relationship over 6 years among younger and older adult Danes. Dietary leucine intake was assessed at baseline and after 6 years in men and women, aged 35–65 years, participating in the Danish cohort of the WHO-MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) study (n 368). Changes in LBM over the 6 years were measured by bioelectrical impedance using equations developed for this Danish population. The association between leucine and LBM changes was examined using multivariate linear regression and ANCOVA analyses adjusted for potential confounders. After adjustment for baseline LBM, sex, age, energy intake and physical activity, leucine intake was associated with LBM change in those older than 65 years (n 79), with no effect seen in those younger than 65 years. Older participants in the highest quartile of leucine intake (7·1 g/d) experienced LBM maintenance, whereas lower intakes were associated with LBM loss over 6 years (for trend: β=0·434, P=0·03). Sensitivity analysis indicated no effect modification of sex or the presence of CVD. Greater leucine intake in conjunction with adequate total protein intake was associated with long-term LBM retention in a healthy older Danish population. This study corroborates findings from laboratory investigations in relation to protein and leucine intakes and LBM change. A more diverse and larger sample is needed for confirmation of these results.

High protein intake in early childhood is associated with obesity, suggesting possible adverse effects on other cardiometabolic outcomes. However, studies in adults have suggested beneficial effects of protein intake on blood pressure (BP) and lipid profile. Whether dietary protein intake is associated with cardiovascular and metabolic health in children is unclear. Therefore, we aimed to systematically review the evidence on the associations of protein intake with BP, insulin sensitivity and blood lipids in children. We searched the databases Medline, Embase, Cochrane Central and PubMed for interventional and observational studies in healthy children up to the age of 18 years, in which associations of total, animal and/or vegetable protein intake with one or more of the following outcomes were reported: BP; measures of insulin sensitivity; cholesterol levels; or TAG levels. In the search, we identified 6636 abstracts, of which fifty-six studies met all selection criteria. In general, the quality of the included studies was low. Most studies were cross-sectional, and many did not control for potential confounders. No overall associations were observed between protein intake and insulin sensitivity or blood lipids. A few studies suggested an inverse association between dietary protein intake and BP, but evidence was inconclusive. Only four studies examined the effects of vegetable or animal protein intake, but with inconsistent results. In conclusion, the literature, to date provides insufficient evidence for effects of protein intake on BP, insulin sensitivity or blood lipids in children. Future studies could be improved by adequately adjusting for key confounders such as energy intake and obesity.

Hypertension is highly prevalent among renal transplant recipients (RTR) and a risk factor for graft failure and cardiovascular events. Protein intake has been claimed to affect blood pressure (BP) in the general population and may affect renal function. We examined the association of dietary protein with BP and renal function in RTR. We included 625 RTR (age 53 (sd 13) years; 57 % male). Protein intake was assessed with a FFQ, differentiating between animal and plant protein. BP was measured according to a strict protocol. Creatinine clearance and albuminuria were measured as renal parameters. Protein intake was 83 (sd 12) g/d, of which 63 % derived from animal sources. BP was 136 (sd 17) mmHg systolic (SBP) and 83 (sd 11) mmHg diastolic (DBP). Creatinine clearance was 66 (sd 26) ml/min; albuminuria 41 (10–178) mg/24 h. An inverse, though statistically insignificant, association was found between the total protein intake and both SBP (β = − 2·22 mmHg per sd, P= 0·07) and DBP (β = − 0·48 mmHg per sd, P= 0·5). Protein intake was not associated with creatinine clearance. Although albuminuria was slightly higher in the highest tertile of animal protein intake compared with the lowest tertile (66 v. 33 mg/d, respectively, P= 0·03), linear regression analyses did not reveal significant associations between dietary protein and albuminuria. Protein intake exceeded the current recommendations. Nevertheless, within the range of protein intake in our RTR population, we found no evidence for an association of dietary protein with BP and renal function. Intervention studies focusing on different protein types are warranted to clarify their effect on BP and renal function in RTR.

Whether there are differences between countries in the validity of self-reported diet in relation to BMI, as evaluated using recovery biomarkers, is not well understood. We aimed to evaluate BMI-related reporting errors on 24 h dietary recalls (24-HDR) and on dietary questionnaires (DQ) using biomarkers for protein and K intake and whether the BMI effect differs between six European countries. Between 1995 and 1999, 1086 men and women participating in the European Prospective Investigation into Cancer and Nutrition completed a single 24-HDR, a DQ and one 24 h urine collection. In regression analysis, controlling for age, sex, education and country, each unit (1 kg/m2) increase in BMI predicted an approximately 1·7 and 1·3 % increase in protein under-reporting on 24-HDR and DQ, respectively (both P < 0·0001). Exclusion of individuals who probably misreported energy intake attenuated BMI-related bias on both instruments. The BMI effect on protein under-reporting did not differ for men and women and neither between countries on both instruments as tested by interaction (all P>0·15). In women, but not in men, the DQ yielded higher mean intakes of protein that were closer to the biomarker-based measurements across BMI groups when compared with 24-HDR. Results for K were similar to those of protein, although BMI-related under-reporting of K was of a smaller magnitude, suggesting differential misreporting of foods. Under-reporting of protein and K appears to be predicted by BMI, but this effect may be driven by ‘low-energy reporters’. The BMI effect on under-reporting seems to be the same across countries.