Prevalence of protein intake below recommended in community‐dwelling older adults: a meta‐analysis across cohorts from the PROMISS consortium

European Horizon 2020 PROMISS Project ‘PRevention Of Malnutrition In Senior Subjects in the EU’, (grant agreement no. 678732). The content only reflects the author’s view and the commission is not responsible for any use that may be made of the information it contains.Background: Lower protein intake in older adults is associated with loss of muscle mass and strength. The present study aimed to provide a pooled estimate of the overall prevalence of protein intake below recommended (according to different cut-off values) among community-dwelling older adults, both within the general older population and within specific subgroups. Methods: As part of the PRevention Of Malnutrition In Senior Subjects in the EU (PROMISS) project, a meta-analysis was performed using data from four cohorts (from the Netherlands, UK, Canada, and USA) and four national surveys [from the Netherlands, Finland (two), and Italy]. Within those studies, data on protein and energy intake of community-dwelling men and women aged ≥55 years were obtained by either a food frequency questionnaire, 24 h recalls administered on 2 or 3 days, or food diaries administered on 3 days. Protein intake below recommended was based on the recommended dietary allowance of 0.8 g/kg body weight (BW)/d, by using adjusted BW (aBW) instead of actual BW. Cut-off values of 1.0 and 1.2 were applied in additional analyses. Prevalences were also examined for subgroups according to sex, age, body mass index (BMI), education level, appetite, living status, and recent weight loss. Results: The study sample comprised 8107 older persons. Mean ± standard deviation protein intake ranged from 64.3 ± 22.3 (UK) to 80.6 ± 23.7 g/d [the Netherlands (cohort)] or from 0.94 ± 0.38 (USA) to 1.17z ± 0.30 g/kg aBW/d (Italy) when related to BW. The overall pooled prevalence of protein intake below recommended was 21.5% (95% confidence interval: 14.0–30.1), 46.7% (38.3–55.3), and 70.8% (65.1–76.3) using the 0.8, 1.0, and 1.2 cut-off value, respectively. A higher prevalence was observed among women, individuals with higher BMI, and individuals with poor appetite. The prevalence differed only marginally by age, education level, living status, and recent weight loss. Conclusions: In community-dwelling older adults, the prevalence of protein intake below the current recommendation of 0.8 g/kg aBW/d is substantial (14–30%) and increases to 65–76% according to a cut-off value of 1.2 g/kg aBW/d. To what extent the protein intakes are below the requirements of these older people warrants further investigation.publishersversionpublishe

Specific food preferences of older adults with a poor appetite. A forced-choice test conducted in various care settings

A poor appetite in older adults is an important determinant of reduced food intake and undernutrition. Food preferences may influence food intake. The aim of this study was to investigate food preferences of older adults with a poor appetite and compare these with preferences of older adults with a good appetite. Older adults (n = 349, aged 65–101 years) in nursing/residential care homes, hospitals or at home receiving home care participated in a computer-based forced-choice food preference assessment. Self-reported appetite in the past week was classified as ‘good’ or ‘poor’ using a validated instrument. Food preferences were determined by counting the relative frequency of choices for food images according to 11 dichotomous categories: high/low 1) protein; 2) fat; 3) carbohydrates; 4) fiber; 5) variation; and 6) animal/vegetarian proteins; 7) sweet/savory taste; 8) solid/liquid texture; 9) dairy/non-dairy; with/without 10) sauce or 11) color variation. Specific food preferences in participants with a poor appetite were identified by one-sample t-tests comparing frequencies to the expected value of 48. Preference differences between those with a good and a poor appetite were analyzed using GLM adjusting for confounders. The results showed that older adults with a poor appetite (n = 113; 32.4%) preferred variation (51.6 vs. 48, P < 0.001), color variation (55.9 vs. 48, P < 0.01), non-dairy (53.0 vs. 48, P < 0.001), high-fiber (51.8 vs. 48, P < 0.05), and solid texture (53.5 vs. 48, P < 0.05). Participants with a poor appetite had a higher frequency score for variation than participants with a good appetite (51.6 vs. 48.5, P < 0.001). In conclusion, older adults with a poor appetite may have specific food preferences. Their preference for variation differs from those with a good appetite. These results may be used to develop meals that are preferred by older adults with poor appetite in order to increase food intake and prevent undernutrition

Sex differences in consequences of musculoskeletal pain

STUDY DESIGN. Cross-sectional population-based study. OBJECTIVE. To study sex differences in consequences of musculoskeletal pain (MP): limited functioning, work leave or disability, and healthcare use. SUMMARY OF BACKGROUND DATA. MP is a major public health problem in developed countries due to high prevalence rates and considerable consequences. There are indications that consequences of MP differ for men and women. METHODS. Data of a Dutch population-based study were used, limited to persons 25 to 64 years of age (n = 2517). Data were collected by a postal questionnaire. RESULTS. Women with any MP report more healthcare use for MP, i.e., contact with a medical caregiver and use of medicines than men, while men report more work disability (ever in life) due to low back pain only, irrespective of work status. None of the sex differences can be explained by age, household composition, educational level, smoking status, overweight, physical activity, and pain catastrophizing. Older age was related to more limited functioning due to MP (women), work disability due to MP (men), and healthcare use due to MP (men and women). A one-person household was associated with work disability (women) and use of medicines (men). Low educational level was associated with limited functioning (men), work leave (men), contact with a medical caregiver (men), and work disability (men and women). Smoking was associated with limited functioning (men), work leave (women), and healthcare use (women). Physical inactivity was associated with limited functioning due to MP in women. Pain catastrophizing was associated with limited functioning, work leave, and healthcare use (men and women) and work disability (men). CONCLUSIONS. Consequences of MP show a slightly different pattern for men and women. Women with any MPreport more healthcare use for MP, while men report more work disability due to low back pain only. These sex differences can not be explained by general risk factors, but associations between these factors and consequences of MP show some sex differences

Gender differences in health-related quality of life among asthma patients

Objective. To identify and explain differences between men and women with asthma regarding health-related quality of life (HRQoL). Methods. A cross-sectional study was performed among 967 asthma patients recruited from general practice. Data were collected by means of a pulmonary function assessment, a face-to-face interview, and a written questionnaire. Results. Women with asthma reported lower scores on HRQoL in the age groups 16-34 and 56-75 years but not in the age group 35-55 years. In all age groups, women reported more severe dyspnea but had higher levels of pulmonary function. The poorer HRQoL reported by women could be explained by a more severe dyspnea and a higher level of medication use in women. Conclusions. The finding that women with asthma aged 16-34 and 56-75 years report poorer HRQoL than men is not due to a more severe disease state in terms of pulmonary obstruction but does seem to be related to a more severe subjective disease state in women than in men

Effect of personalized dietary advice to increase protein intake on food consumption and the environmental impact of the diet in community-dwelling older adults: results from the PROMISS trial

Purpose: Diet modelling studies suggest that increasing protein intake with no consideration for sustainability results in a higher environmental impact on the diet. To better understand the impact in real life, the aim of this study was to assess the effect of dietary advice to increase protein intake on food consumption and the environmental impact of the diet in community-dwelling older adults. Methods: Food consumption and environmental impact were analyzed among 124 Dutch older adults with lower habitual protein intake (< 1.0 g/kg adjusted body weight/day) participating in the six-month PROMISS trial. Dietary intake data from three 24-h dietary recalls, aided by food diaries, and results from life cycle assessments were used to examine the differences in changes in food consumption and environmental impact between those who received dietary advice to isocalorically increase protein intake to ≥ 1.2 g/kg aBW/d (Protein + ; n = 84) and those who did not receive dietary advice (Control; n = 40). Results: Compared to the Control, Protein + increased protein intake from animal-based food products (11.0 g protein/d, 95% CI 6.6–15.4, p < 0.001), plant-based food products (2.1 g protein/d, 95% CI 0.2–4.0, p = 0.031) and protein-enriched food products provided during the trial (18 g protein/d, 95% CI 14.5–21.6, p < 0.001) at the 6-month follow-up. Diet-associated greenhouse gas emissions increased by 16% (p < 0.001), land use by 19% (p < 0.001), terrestrial acidification by 20% (p = 0.01), and marine eutrophication by 16% (p = 0.035) in Protein + compared to the Control. Conclusion: This study found that dietary advice increased protein intake, favoring animal-based protein, and increased the environmental impact of the diet in older adults. Trial registration: ClinicalTrials.gov. NCT03712306. October 2018

Development and validation of a short food questionnaire to screen for low protein intake in community-dwelling older adults: The Protein Screener 55+ (Pro55+)

In old age, sufficient protein intake is important to preserve muscle mass and function. Around 50% of older adults (65+ y) consumes 1.0 g/kg adjusted body weight (BW)/day (d). There is no rapid method available to screen for low protein intake in old age. Therefore, we aimed to develop and validate a short food questionnaire to screen for low protein intake in community-dwelling older adults. We used data of 1348 older men and women (56–101 y) of the LASA study (the Netherlands) to develop the questionnaire and data of 563 older men and women (55–71 y) of the HELIUS study (the Netherlands) for external validation. In both samples, protein intake was measured by the 238-item semi-quantitative HELIUS food frequency questionnaire (FFQ). Multivariable logistic regression analysis was used to predict protein intake 1.0 g/kg adjusted BW/d (based on the HELIUS FFQ). Candidate predictor variables were FFQ questions on frequency and amount of intake of specific foods. In both samples, 30% had a protein intake 1.0 g/kg adjusted BW/d. Our final model included adjusted body weight and 10 questions on the consumption (amount on average day or frequency in 4 weeks) of: slices of bread (number); glasses of milk (number); meat with warm meal (portion size); cheese (amount and frequency); dairy products (like yoghurt) (frequency); egg(s) (frequency); pasta/noodles (frequency); fish (frequency); and nuts/peanuts (frequency). The area under the receiver operating characteristic curve (AUC) was 0.889 (95% CI 0.870–0.907). The calibration slope was 1.03 (optimal slope 1.00). At a cut-off of 0.8 g/kg adjusted BW/d, the AUC was 0.916 (96% CI 0.897–0.936). Applying the regression equation to the HELIUS sample, the AUC was 0.856 (95% CI 0.824–0.888) and the calibration slope 0.92. Regression coefficients were therefore subsequently shrunken by a linear factor 0.92. To conclude, the short food questionnaire (Pro55+) can be used to validly screen for protein intake 1.0 g/kg adjusted BW/d in community-dwelling older adults. An online version can be found at www.proteinscreener.nl. External validation in other countries is recommended

Comparison of protein intake per eating occasion, food sources of protein and general characteristics between community-dwelling older adults with a low and high protein intake

Background & aims: Adequate protein intake is required to maintain muscle health in old age, but a low protein intake is very common in older adults. There is little insight in the general and dietary profile of older adults with a low protein intake. Therefore, this study aimed to compare community-dwelling older adults with a low and a high protein intake with regard to protein intake per eating occasion, food sources of protein and general participant characteristics. Methods: Data were used from 727 Dutch community-dwelling older adults aged ≥70 years. Protein intake at meal and snack moments was measured with two non-consecutive dietary record assisted 24-h recalls. Low protein intake was defined as below the Recommended Dietary Allowance of 0.8 g protein per kg adjusted body weight per day (g/kg aBW/d). Differences in protein and food intakes between those with a low and a high protein intake were assessed with the Mann–Whitney U test and Chi-square test. Eating occasions were compared with regard to differences between the low and high protein intake group by using MANOVA. Characteristics of older adults with low protein intake were selected by using a multiple logistic backward elimination procedure. Results: Low protein intake was present in 15% of the participants. At all eating occasions, median protein intake was lower in the low compared to the high protein intake group (breakfast, 7.8 vs. 10.8 g; lunch, 12.6 vs. 24.3 g; dinner, 21.8 vs. 31.1 g; snack moments, 6.7 vs. 9.7 g; P < 0.001), and was also consistently lower relative to energy intake. The contribution of animal protein to total protein intake was lower among the low protein intake group. Both groups obtained most protein from dairy, meat and cereals, but meat contributed less (21.5 vs. 28.2%) and cereals more (21.9 vs. 19.6%) among the low than the high protein intake group (all P < 0.01). Differences in protein intake, percentage of energy from protein and contribution of animal to total protein intake between the groups were largest at lunch compared to the other eating occasions. Out of a long list of variables, low protein intake was only associated with following a diet, being obese vs. normal-weight and drinking alcohol on none vs. some but <5 days/week (P < 0.05). Conclusions: At all eating occasions, Dutch community-dwelling older adults with a protein intake <0.8 g/kg aBW/d ate less protein (also relative to their energy intake) and a lower proportion of animal protein compared to those with a high protein intake. These differences were largest at lunch. Major food sources of protein – in both groups – were dairy, meat and cereals. We could only identify following a diet, being obese and not drinking alcohol as general characteristics of older adults with a low protein intake.</p

Prospective associations of poor diet quality with long-term incidence of protein-energy malnutrition in community-dwelling older adults:The Health, Aging, and Body Composition (Health ABC) Study

Background: Protein-energy malnutrition (PEM) is amajor problem in older adults.Whether poor diet quality is an indicator for the longterm development of PEM is unknown. Objective: The aim was to determine whether poor diet quality is associated with the incidence of PEM in community-dwelling older adults. Design:We used data on 2234 US community-dwelling older adults aged 70-79 y of the Health, Aging, and Body Composition (Health ABC) Study. In 1998-1999, dietary intake over the preceding year was measured by using a Block food-frequency questionnaire. Indicators of diet quality include the Healthy Eating Index (HEI), energy intake, and protein intake. Outcomes were determined annually by using measured weight and height and included the following: 1) incident PEM [body mass index (in kg/m2) <20, involuntary weight loss of ≥5% in the preceding year at any follow-up examination, or both] and 2) incident persistent PEM (having PEM at 2 consecutive follow-up examinations). Associations of indicators of diet quality with 4-y and 3-y incidence of PEM and persistent PEM, respectively, were examined by multivariable Cox regression analyses. Results: The quality of the diet, as assessed with the HEI, was rated as "poor" for 6.4% and as "needs improvement" for 73.0% of the participants. During follow-up, 24.9% of the participants developed PEM and 8.5% developed persistent PEM. A poor HEI score was not associated with incident PEM or persistent PEM. Lower baseline energy intake was associated with a lower incidence of PEM (HR per 100-kcal/d lower intake: 0.98; 95% CI: 0.97, 0.99) and persistent PEM (HR: 0.97; 95% CI: 0.95, 0.99), although lower baseline protein intake was observed to be associated with a higher incidence of persistent PEM (HR per 10-g/d lower intake: 1.15; 95% CI: 1.03, 1.29). Conclusions: These findings do not indicate that a poor diet quality is a risk factor for the long-term development of PEM in communitydwelling older adults, although there is an indication that lower protein intake is associated with higher PEM risk

Personalized Dietary Advice to Increase Protein Intake in Older Adults Does Not Affect the Gut Microbiota, Appetite or Central Processing of Food Stimuli in Community-Dwelling Older Adults: A Six-Month Randomized Controlled Trial

Expert groups argue to raise the recommended daily allowance for protein in older adults from 0.8 to 1.2 g/kg/day to prevent undernutrition. However, protein is thought to increase satiety, possibly through effects on gut microbiota and central appetite regulation. If true, raising daily protein intake may work counterproductively. In a randomized controlled trial, we evaluated the effects of dietary advice aimed at increasing protein intake to 1.2 g/kg adjusted body weight/day (g/kg aBW/day) on appetite and gut microbiota in 90 community-dwelling older adults with habitual protein intake <1.0 g/kg aBW/day (Nintervention = 47, Ncontrol = 43). Food intake was determined by 24-h dietary recalls and gut microbiota by 16S rRNA sequencing. Functional magnetic resonance imaging (fMRI) scans were performed in a subgroup of 48 participants to evaluate central nervous system responses to food-related stimuli. Both groups had mean baseline protein intake of 0.8 ± 0.2 g/kg aBW/day. At 6 months’ follow-up this increased to 1.2 ± 0.2 g/kg aBW/day for the intervention group and 0.9 ± 0.2 g/kg aBW/day for the control group. Microbiota composition was not affected, nor were appetite or brain activity in response to food-related stimuli. Increasing protein intake in older adults to 1.2 g/kg aBW/day does not negatively impact the gut microbiota or suppress appetite