Dietary Protein Food Clusters and risk of functional limitation and disability (NuAge Study) Hélène Payette, U Sherbrooke (Qc) CAN Collaborators: P Gaudreau (U Montreal), JA Morais (McGill U) , B Shatenstein (U Montreal), M Sene (U Sherbrooke)
CONFLICT OF INTEREST DISCLOSURE I (and collaborators) have no potential conflict of interest to report
Dietary Protein Food Clusters and risk of functional limitation and disability (NuAge Study) Hélène Payette, U. Sherbrooke (Qc) CAN Collaborators: P Gaudreau, JA Morais, B Shatenstein, M Sene EUGMS, Nice, France September 2017
Study Design 95 Random sample Quebec Medicare database 90 n = 1,793 men/women Montreal/Sherbrooke (Qc, Can) 85 Eligibility 80 Good physical & mental health Functional independence 75 70 Follow-up Annual face-to-face interview 2003 2009 2013 6-month telephone interview 4 yrs annual follow-up
Eligibility criteria Inclusion • Community-dwelling men and women French or English speaking • Willing to commit for a 5-year period • Able to walk without help • Free of disabilities in activities of daily living • No cognitive impairment (3MS > 79) • Able to walk 100 metres and climb 10 stairs without rest • Able to sign informed consent Exclusion • Class II heart failure • COPD requiring home oxygen therapy or oral steroids • Inflammatory digestive diseases • Cancer (radiation therapy, chemotherapy or surgery 5 previous years)
Dietary assessment T0 : 3 non-consecutive 24 hrs recalls (2 week days + 1 weekend) modified USDA 5-step Multiple Pass Method Analysis % total protein intake contributed from each food group was calculated for each individual as [Protein from specific food group (g) / total protein intake (g)] * Dietary protein food clusters ** K-means to classify individuals into mutually exclusive groups Euclidean distances between each person & each cluster center in iterative process * Food groups contribution < 0.5% removed ** SAS (version 9.4) FASTCLUS procedure
Mean food groups contribution (%) to total daily protein intake Food groups % Cakes & cookies Cakes, pies, doughnut, pastries muffins, cookies, granola bars, etc. 3,61 Dairy Milk, cheese, yoghurt, cream 15,22 Dairy desserts Puddings, ice cream, ice milk, frozen yoghurt 0,98 Eggs Eggs, omelettes, quiche 2,95 Fast foods Pizza, hamburger, hot dog, french fries & other meals from fast-food restaurants 2,11 Fish & shellfish products Any fish & seafood fresh, frozen or canned 6,22 Fruits Any fruit 1,78 Fruit juices Any fruit juice no sugar added 0,69 Legumes & legume products Legumes, hummus, beans with pork, tofu, foods with soja or vegetable protein 2,96 Nuts & seeds Any nuts, peanuts, peanut or other nuts butter, sunflower seeds, other seeds 0,90
Mean food groups contribution (%) to total daily protein intake Food groups % Poultry products Chicken, turkey, duck 10,33 Potatoes Boiled, mashed or baked 1,96 Processed meats Sausages, hot dog, ham, cold cuts… 4,86 Red meat products Beef, lamb, pork, veal, liver, game, etc. 17,47 Refined grain bread & breakfast cereals Refined cold or hot cereals, white breads or rolls, bagels, 5,41 tortillas, waffle or pancakes unsweetened Rice & other grains Rice, rice noodle, couscous, bulgur, quinoa, etc. 1,21 Sauces, gravies, salad dressing Meat sauces, salad dressing, mayonnaise, dips 0,83 Soups Any kind 3,69 Salty snacks Chips, salted crackers, pretzels, popcorn, etc. 0,63 Vegetables Green, yellow, red & other vegetables 3,99 Wholegrain bread & breakfast cereals High fibre, whole wheat, multigrain or rye breads, rolls, 7,11 bagels, tortillas or cereals
Dietary protein food clusters generated with K means method Food groups 1 2 3 Dairy Milk, cheese, yoghurt, cream ++5 --7 --6 Eggs Eggs, omelettes, quiche ++8 - --5 Fast foods Pizza, hamburger, hot dog, french fries, etc. ++12 - - Fish & shellfish fresh, frozen or canned ++3 --3 --9 Fruits Any fruit ++10 --8 + Pasta Any kind, tomato, creamy sauce or meat ++4 --6 --7 Poultry Chicken, turkey, duck --2 --2 ++1 Potatoes Boiled, mashed or baked --11 ++5 --8 Processed meats Sausages, hot dog, ham, cold cuts… ++6 - --4 --1 ‡ Red meat Beef, lamb, pork, veal, liver, game, etc. ++1 --2 Refined grain Refined cereals, white breads, bagels, etc. - ++10 --10 Rice & other grains Rice, rice noodle, couscous, bulgur, quinoa - --9 ++3 Soups Any kind ++9 - - Wholegrain High fibre, whole wheat, multigrain /rye breads ++7 --4 + # position in cluster definition and greater consumption in food groups # position in cluster definition and lower consumption in food groups
Dietary Protein Food Clusters 1 (n = 781) → High fish & pasta + dairy & wholegrain Low red meat, poultry, potatoes 2 (n = 499) → High red meat & potatoes Low poultry, fish, wholegrain, pasta 3 (n = 498) → High poultry, rice & grains Low red & processed meat, eggs, dairy
Analyses Stratified Random Sample Strata: 1. Sex 2. Region (Sherbrooke, Montreal, Laval) 3. Age (70 ± 2 yrs, 75 ± 2 yrs, 80 ± 2 yrs) → SAS “survey” procedures (version 9.3) results weighed for age, sex and region
Frailty Markers Nutrition Physical Energy Mobility Strength activity ≥ 5% PASE score Vitality Gait speed Grip strength self-reported subscale weight loss < mean-1SD SF-36 < 1m/s < mean-1SD last 12 m by age & sex < mean-1SD by age, sex OR by age & sex BMI < 22 18.1% 23.9% 9.5% 21.7% 13.6% Prevalence of frailty criteria at baseline Sourial et al., J Gerontol 2012
Baseline Characteristics of Participants across Protein Food Clusters Fish, Red meat Poultry, Rice P Pasta & Dairy & Potatoes & Grains 39.9% 43.2% 33.9% 0.009 Men, % 74.1 ± 4.0 73.7 ± 3.8 73.9 ± 4.6 N.S. Age, y 27.5 ± 4.5 28.2 ± 4.4 27.4 ± 4.7 N.S. BMI, Kg/m 2 7.5 9.6 5.6 0.062 Smoking, % 53.3 54.5 44.7 0.002 Married, % Education, yrs 13.3 ± 4.7 12.7 ± 4.1 12.8 ± 4.4 0.002 Burden of disease 3.6 ± 2.7 3.5 ± 2.4 4.0 ± 3.3 N.S. (0-70) 5.4 3.0 4.8 0.001 Frail, % Physical activity 93.8 ± 48.0 93.5 ± 43.7 90.8 ± 48.8 N.S. PASE (0-793)
Baseline Protein & Energy Intake across Protein Food Clusters Fish, Red meat & Poultry, Rice P Pasta & Dairy Potatoes & Grains Total Protein Intake 73.0 ± 21.5 75.8 ± 21.9 73.7 ± 20.1 0.006 (g/day) Protein 1.10 ± 0.33 1.13 ± 0.28 1.13 ± 0.31 < 0.001 (g/kg/day) Protein % 15.1 13.8 12.0 (g/kg/day < 0.8) 0.06 Protein % 58.9 64.1 66.6 (g/kg/day ≥ 1.0) Energy 1784 ± 473 1843 ± 522 1717 ± 494 0.003 (Kcal/day)
4 th yr follow-up Disability ( ≥ 1 ADL) ( Katz & Akom, 1976 ) Incidence = 13.6% Self-reported functional limitations (Nagi, 1976) Do you have difficulties: - Reaching or extending your arms above your shoulders? - Stooping, crouching, or kneeling down? - Pushing or pulling large objects like a living room chair? - Lifting 4,5 kg from the floor, like a heavy bag or groceries? - Handling small objects, like picking up a coin from a table? - Stand for long period (around 15 min)? Without or with little or some difficulty = 0 Lot of difficulty or unable to do or don’t do on doctor’s order = 1 Score range (0-6) (1 rst FU) 0,44 ± 0.9 (2 nd FU) 0,55 ± 0.93 (3 rd FU) 0,69 ± 1.17 P = 0.177
Risk associated with protein intake over 3 yrs across protein food clusters Protein % Protein % (g/kg/day < 0.8) (g/kd /day ≥ 1.0) Fish, Pasta Ref ref & Dairy Red meat & Potatoes 1.20 (1.15, 1.25) 0.73 (0.70, 0.76) OR (95% CI) Poultry, Rice & Grains 0.91 (0.88, 0.95) 1.33 (1.29, 1.39) OR (95% CI) Generalized Estimating Equations adjusted for age, sex, marital status, education, burden of disease, BMI, PASE, Kcal
Risk associated with physical functioning over 4 yrs across protein food clusters NAGI score** % ≥ 1 ADL* β ± SE OR (95% CI) p Fish, Pasta ref ref & Dairy Red meat - 0.03 ± 0.005 1.57 (1.52, 1.63) & Potatoes < 0.001 Poultry, 0.14 ± 0.005 1.30 (1.26, 1.34) Rice & Grains < 0.001 *Generalized Estimating Equations **Linear Mixed Model Adjusted for age, sex, marital status, education, burden of disease, BMI, PASE, Kcal
Summary As compared to fish/pasta/dairy protein cluster, Red meat/potatoes ↑ incidence of low pro intake & disability ↓ risk of functional limitation Poultry/rice ↓ incidence of low pro intake ↑ incidence of disability & risk of functional limitation
Conclusions Dietary protein food patterns are associated with : current protein & energy intake 3-yr risk of low protein intake 4-yr risk of functional limitiation & disability In a generally healthy & well nourished elderly population
Conclusions More research is needed In larger samples In different populations With different food habits And longer follow-up
This project has received funding from the European Union’s Horizon 2020 research and innovation programme, grant n ° 678732.
Previous study 2986 men & women, aged 19 – 72 y Framingham 3 rd Generation Study 6 protein food clusters : Fast food/full-fat dairy, Fish, Red meat, Chicken, Low-fat milk, Legumes Over a 6-yrs follow-up NO association with appendicular lean mass, quadriceps strength, or bone mineral density after adjustment for potential confounders Mangano et al. Am J Clin Nutr 2017
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