Effect of Sustainably Sourced Protein Consumption on Nutrient Intake and Gut Health in Older Adults: A Systematic Review
Abstract
:1. Introduction
2. Methods
2.1. Eligibility Criteria
2.1.1. Population
2.1.2. Interventions
2.1.3. Comparators
2.1.4. Outcomes
2.1.5. Settings
2.1.6. Years, Language, and Publication Status
2.2. Information Sources
2.3. Search Strategy
2.4. Selection Process
2.5. Data Collection Process
2.6. Data Outcomes
2.6.1. Outcomes
- Dietary adherence or intervention: Score and adherence to a particular diet
- Nutrient intake: Energy, fat, carbohydrates, total protein, vegetable protein, animal protein and fibre.
- Food Groups: Meats, fish and poultry; fruit and vegetables; legumes; and breads, grains and cereals.
- Gut microbiome: Measurement of microbiota and inflammation status including but not limited to inflammatory markers, α-diversity, taxonomies, phenolic profiles, microbial levels or short chain fatty acids
- Health: Body mass index (BMI), self-rated health, non-communicable diseases, cholesterol, muscle mass and grip strength.
2.6.2. Other Variables
- Author, year, and country
- Study design, sample size, mean age, gender, dietary exposure, duration of follow up.
- Dietary measurement tool, dietary pattern assessment, adherence to diet.
2.7. Study Risk of Bias Assessment
2.8. Effect Measures
3. Results
3.1. Study Selection
3.2. Study Characteristics
3.2.1. Population and Settings
3.2.2. Study Design and Intervention
3.3. Risk of Bias in Studies
3.3.1. Bias Due to Confounding
3.3.2. Bias Arising from Measurement of the Exposure
3.3.3. Bias in Selection of Participants into Study
3.3.4. Bias Due to Post-Exposure Interventions/Missing Data/Measurement of the Outcome/Selection of the Reported Result
3.4. Results of Individual Studies
3.4.1. Adherence to Diet
3.4.2. Microbiota/Inflammatory Outcomes
3.4.3. Food Group Intake
3.4.4. Nutrient Intake
3.4.5. Health Status
4. Discussion
Limitations of Evidence and the Review Process
5. Implications for Practice, Policy and Future Research
6. Registration and Protocol
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Author, Year (Country) | Study Design | Sample Size (n) | Age Mean (SD) Years | Female n (%) | Dietary Intervention/ Exposure | Outcomes | Duration (Months) |
---|---|---|---|---|---|---|---|
André, 2021 [57] (France) | Cross-sectional | 698 | 73.1 (4.4) | 432 (61.9) | Mediterranean vs. prudent vs. traditional vs. complex carbs | Circulating 3-OH FAs, a proxy of LPS-type endotoxins burden. | Dietary survey conducted after 24 months |
Berendsen, 2018 [58] (The Netherlands) Recruited from five EU centres | Randomised multicentre, single-blind, controlled trial | 1141 | 71.0 (4.0) | 631 (55) | Mediterranean-like diet (NU-AGE diet) with counselling and dietary advice vs. control | Dietary intake | 12 months follow up |
Farsijani, 2022 [59] (USA) | Cross-sectional | 775 | 84.2 (4.0) | 0 (0) | Usual food intake to measure total daily protein intake | Microbial DNA extraction from stool sample for gut microbiome profiling (16S rRNA gene sequencing) | Mailed FFQ to MrOS mean of 4.6 (SD 11.7) days after stool collection. |
Ghosh, 2020 [60] (Ireland) Recruited from five EU study centres | Randomised multicentre, single-blind, controlled trial | 612 | 71 (range: 65–79) | 326 (53) | Mediterranean-like diet (NU-AGE diet) + counselling + dietary advice vs. control | Gut microbiome profile | 12 months follow up |
Gutierrez-Díaz, 2016 [61] (Spain) | Cross-sectional | 74 (50 yrs and above) 50–65 yrs: n = 37 ≥65 yrs: n = 37 | 71.3 (11.2) (Mean for subgroups not reported) | Not reported for ≥65 years subset. Total sample: 54 (73) | Mediterranean diet score | Anthopometric data, microbiological and phenolic metabolite assessment of fecal specimens. | Cross sectional |
Li, 2021 [62] (USA) | Cohort | 303 | 71 (4.0) | 0 (0) | hPDI | Gut microbiome profile | 12 months follow up |
Maroto-Rodriguez, 2022 [63] (Spain) | Cohort | 1880 | 68.65 (6.38) | 971 (51.56) | hPDI & uPDI | Health outcomes recorded at baseline and frailty status recorded at follow up | Follow up was on average 40 months |
Maskarinec, 2019 [64] (USA) | Cohort | 1735 | 69.2 (at stool collection) | 877 (50.5) | HEI-2010, AHEI-2010, aMED, and DASH diet | Association of diet quality with measures of stool microbial community structure. | Main analysis is cross sectional |
Ruiz-Saavedra, 2020 [65] (Spain) | Cross-sectional | 40 (≥65 yrs) Total sample: n = 73 | 2 sub-groups: 50–65 years and 65–95 years (mean not reported) | Not reported for ≥65 subset. Total sample: 53 (73) | DII, EDII, HEI, AHEI, DQI-I, MMDS, and rMED | Major phylogenetic types of the intestinal microbiota determined by qPCR and SCFAs | Cross-sectional |
Shikany, 2019 [66] (USA) | Cross-sectional | 517 | 84.3 (4.1) | 0 (0) | 2 dietary patterns: Western and Prudent. | Diversity of gut bacterial microbiota | Dietary assessment completed within a mean (SD) 4.6 (11.7) days of the stool sample collection |
Trichopoulou, 2003 [67] (Greece) | Cohort | 4369 (≥65 yrs) Total sample n = 22,043 | 3 sub-groups: <55 years, 55–64 years, and ≥65 years (mean not reported) | Not reported for ≥65 subset. Total 13,143 (60) | Mediterranean diet | Mortality | 44 months follow up |
Zhang, 2021 [68] (Taiwan) | Cohort | 59 | Female: 77.7 (7.6) Male: 85.3 (8.4) | 30 (51) | Plant-based, antioxidant-rich smoothies and sesame seed snacks | Antioxidant ability and gut microbial composition | Follow up at 2 and 4 months |
Author, Year | Dietary Measurement Tool | Dietary Pattern Assessment | Adherence to Diet | Main Findings |
---|---|---|---|---|
André, 2021 [57] | FFQ (By registered dietitian) | Med diet: Score ranged from 0, low adherence to 18, high adherence. Carbs/traditional/prudent diet: Factor analysis with tertile range (upper tertile = higher adherence). | Med diet: Mean score: 10.7 (SD 2.0) n = 698 Low (<9): n = 187 (27.0%) Medium (10–12): n = 264 (38.0%) High (>12): n = 247 (35.0%) Carbs/traditional/prudent diet: Low: n = 232 (33.2%) Medium: n = 233 (33.4%) High: n = 233 (33.4%) | Plant-based dietary patterns were associated with lower 3-OH FA concentrations, and thus a lower LPS burden, which is considered a potent trigger of inflammatory response. |
Berendsen, 2018 [58] | Self-reported 7-day records (with prior training) | NU-AGE index score, with diet compliance ranging from 0 (low) to 160 (high). | Baseline mean score (SD): Control group: 82.6 (16.5) Diet group: 82.6 (15.3) Follow-up mean score (SD): Control group: 84.6 (16.1) Diet group: 105.7 (17.6) | The NU-AGE dietary intervention may be a feasible strategy to improve dietary intake in an aging European population. |
Farsijani, 2022 [59] | Self-reported Brief FFQ (Block 98.2 MrOS) | Total daily protein intake (g/d) was estimated from the collected FFQs. Data was recorded by quartile of energy adjusted protein intake. | Q1: ≤55.44 g/d, n = 194 (25.0%) Q2: 55.45–61.17 g/d, n = 193 (24.9%) Q3: 61.18–67.98 g/d, n = 194 (25.0%) Q4: ≥67.99 g/d, n = 194 (25.1%) | Higher protein consumptions from either animal or vegetable sources were associated with higher gut microbiome diversity. |
Ghosh, 2020 [60] | Self-reported 7-day records (with prior training) | NU-AGE index score, with diet compliance ranging from 0 (low) to 160 (high). | Dietary variations within the intervention group were significantly different from the control group (envfit p < 0.006). Intervention group: increased intake of fibres, vitamins (C, B6, B9, thiamine) and minerals (Cu, K, Fe, Mn, Mg). Control: Increase in fat intake (saturated fats and mono-unsaturated fatty acids) relative to the intervention group. | Increasing adherence to the NU-AGE diet was associated with higher gut microbiome diversity |
Gutierrez-Díaz, 2016 [61] | FFQ 24 h dietary intake | Med Diet Score (MDS) calculated based on eight dietary components, with a possible range of 0–8 points. Cut-off for greater adherence and health-promoting effects was 4 points. | Total sample (50 years and above) MDS < 4 points: n = 32 (43%) MDS ≥ 4 points: n = 42 (57%) Diet scores not reported for >65 years subgroup | Older subjects (>65 years), and subjects with sedentary habits exhibited higher values for the fecal content of phenylacetic, 4-hydroxyphenylacetic, and phthalic acids. |
Li, 2021 [62] | Validated FFQ | hPDI was derived from FFQ. Scores were summed to give a hPDI score of 18 (lowest) to 90 (highest). | hPDI score, mean (SD): Q1: 46.5 (2.6) n = 59 (19.6%) Q2: 51.3 (0.9) n = 62 (20.4%) Q3: 54.4 (0.9) n = 60 (19.8%) Q4: 58.0 (1.2) n = 62 (20.4%) Q5: 64.1 (2.8) n = 60 (19.8%) | A greater adherence to a healthy plant-based diet was associated with a microbial profile characterized by a higher abundance of multiple species. |
Maroto-Rodriguez, 2022 [63] | A validated computerised face-to-face diet history (DH-ENRICA) developed from EPIC cohort study in Spain | hPDI was derived from FFQ. Scores were summed to give hPDI and uPDI scores of 18 (lowest) to 90 (highest) and then categorized into 3 tertiles. | hPDI, mean score (SD): Total: 59.73 (5.73) n = 1880 T1: 52.43 (2.62) n = 429 (23%) T2: 58.60 (1.71) n = 765 (41%) T3: 65.56 (3.22) n = 686 (36%) uPDI, mean score (SD): Total: 54.85 (5.32) n = 1880 T1: 50.32 (3.13) n= 879 (47%) T2: 56.83 (1.37) n = 639 (34%) T3: 62.38 (2.52) n = 362 (19%) | In older adults, the hPDI was associated with lower risk of frailty, while the opposite was found for the uPDI. |
Maskarinec, 2019 [64] | QFFQ covering over 180 food items | Scores for 4 diets were calculated. Score ranges shown in next column. In all 4 diets the higher the score the higher the adherence to the diet. | HEI-2010, score range: T1: 35.2—68.4, n = 578 (33.3%) T2: 68.5—77.7, n = 579 (33.4%) T3: 77.8—99.1, n = 578 (33.3%) AHEI-2010, score range: T1: 35.6—64.5, n = 578 (33.3%) T2: 64.6—73.0, n = 579 (33.4%) T3: 73.1—99.4, n = 578 (33.3%) aMED, score range: T1: 0–3, n = 643 (37.1%) T2: 4–5, n = 627 (36.1%) T3: 6–9, n = 465 (26.8%) DASH, score range: T1: 9–22, n = 631 (36.4%) T2: 23–26, n = 545 (31.4%) T3: 27–38, n = 559 (32.2%) | Diet quality was strongly associated with fecal microbial alpha diversity and beta diversity and several genera previously associated with human health |
Ruiz-Saavedra, 2020 [65] | Semi-QFFQ | Scores for 7 dietary indices were calculated for the total sample (aged 50–95 years). | Subgroup >65 years, mean score (SD) (n = 40): DII: 0.98 (2.02) EDII: 1.02 (0.69) HEI: 54.46 (10.16) AHEI: 58.39 (6.88) DQI-I: 46.60 (5.96) MMDS: 3.13 (1.49) rMED: 6.15 (2.03) | DII, HEI, DQI-I and MMDS were identified as predictors of Faecalibacterium prausnitzii levels, AHEI and MMDS were negatively associated with Lactobacillus group. HEI, AHEI and MMDS were positively associated with fecal SCFAs. |
Shikany, 2019 [66] | Block 98.2 MrOS FFQ (NutritionQuest) | Final factor scores were calculated through analysis of the FFQs. Adherence to the dietary patterns was divided into quartiles, with Quartile 1 representing the lowest adherence and Quartile 4 representing the highest adherence. | Western diet: Q1: n = 130 (25.0%) Q2: n = 129 (25.0%) Q3: n = 129 (25.0%) Q4: n = 129 (25.0%) Prudent diet Q1: n = 130 (25.0%) Q2: n = 129 (25.0%) Q3: n = 129 (25.0%) Q4: n = 129 (25.0%) | Significant associations between measures of gut microbial composition and dietary patterns. |
Trichopoulou, 2003 [67] | Semi-QFFQ administered by specially trained interviewers | Mediterranean-diet score ranged from 0 (minimal adherence to the traditional Mediterranean diet) to 9 (maximal adherence) | Subgroup >65 years, Med diet score range: T1: Score 0–3, n = 1598 (36.6%) T2: Score 4–5, n = 1829 (41.9%) T3: Score 6–9, n = 942 (21.5%) | Greater adherence to the traditional Mediterranean diet is associated with a significant reduction in total mortality |
Zhang, 2021 [68] | Consumption of specified smoothies and snacks | Each serving of a plant-based smoothie contained 1 exchange of vegetables (2 kinds), 1 exchange of fruits (2 kinds), and 1 exchange of nuts. | All participants were provided with 5 servings of plant-based smoothies and 3 servings of sesame seed snacks per week. Participants received these for a 4-month period. | Consumption of Plant-based smoothies and snacks prompted significant decreases in observed bacterial species and their richness. |
RoB 2.0 | D1 | D2 | D3 | D4 | D5 | Overall | ||
---|---|---|---|---|---|---|---|---|
Berendsen, 2018 [58] | Low | Low | Low | Low | Low | Low | ||
Ghosh, 2020 [60] | Low | Low | Low | Low | Low | Low | ||
ROBINS-E | D1 | D2 | D3 | D4 | D5 | D6 | D7 | Overall |
Andre, 2021 [57] | Low | Some concerns | Low | Low | Low | Low | Low | Some concerns |
Farsijani, 2022 [59] | Some concerns | Some concerns | Low | Low | Low | Low | Low | Some concerns |
Gutierrez-Diaz, 2016 [61] | Some concerns | Some concerns | Low | Low | Low | Low | Low | Some concerns |
Li, 2021 [62] | Some concerns | Some concerns | Low | Low | Low | Low | Low | Some concerns |
Maroto-Rodriguez, 2022 [63] | Low | Some concerns | Low | Low | Low | Low | Low | Some concerns |
Maskarinec, 2019 [64] | Low | Some concerns | Low | Low | Low | Low | Low | Some concerns |
Ruiz-Saavedra, 2020 [65] | Low | Some concerns | Low | Low | Low | Low | Low | Some concerns |
Shikany, 2019 [66] | Some concerns | Some concerns | Low | Low | Low | Low | Low | Some concerns |
Trichopoulou, 2003 [67] | Low | Some concerns | Low | Low | Low | Low | Low | Some concerns |
Zhang, 2021 [68] | Some concerns | High | Low | Low | Low | Low | Low | High |
Author, Year | Microbiology |
---|---|
André, 2021 [57] | 3-OHFAs pmol/mL (SD) Med diet adherence: Low: 276.7 (110.4), Medium: 261.8 (92.9), High: 263.7 (99.7) Comp carbs adherence: Low: 270.6 (118.7), Medium: 266.1 (87.2), High: 262.6 (92.6) Trad diet adherence: Low: 249.9 (83.4), Medium: 258.6 (91.4), High: 290.8 (118.4) Prudent diet adherence: Low: 283.0 (114.6), Medium: 261.1 (85.2), High: 255.3 (97.3) |
Farsijani, 2022 [59] | α-diversity Higher protein intake from vegetable sources compared to lower intake from vegetable sources was associated with higher Chao1 and Shannon indices (overall p < 0.05). Higher protein intake from animal sources compared to lower intake from animal sources was associated with higher Shannon and Inverse Simpson indices (overall p < 0.05). |
Ghosh, 2020 [60] | Taxonomies Adherence to the Mediterranean diet led to increased abundance of specific taxa that were positively associated with several markers of lower frailty and improved cognitive function, and negatively associated with inflammatory markers including C-reactive protein and interleukin-17. |
Gutierrez-Díaz, 2016 [61] | Phenolic profiles (μg/mL) Subgroup age ≥ 65 yrs (n = 37): Phenylacetic acid: 16.56 (20.38) Phenylpropionic acid: 10.03 (9.82) Benzoic acid: 0.54 (0.97) 3-hydroxyphenylacetic acid: 0.22 (0.28) |
Li, 2021 [62] | Taxonomies A higher hPDI score was significantly associated with 7 microbial species, with: Higher relative abundance (%) of: Bacteroides cellulosilyticus (2.58%; 95% CI: 1.39, 3.77) and Eubacterium eligens (1.37%; 95% CI: 0.55, 2.20) Lower abundance (%) of: Ruminococcus torques (−1.09%; 95% CI: −1.67, −0.50), Ruminococcus gnavus (−1.10%; 95% CI: −1.69, −0.52), Clostridium leptum (−0.66%; 95% CI: −1.03, −0.30), Lachnospiraceae bacterium 1_4_56faa (−0.29%; 95% CI: −0.45, −0.12), and Erysipelotrichaceae bacterium 21_3 (−0.12%; 95% CI: −0.18, −0.05) |
Maskarinec, 2019 [64] | α-diversity (Shannon), mean (95% CI) HEI-2010, T1: 6.03 (5.89, 6.17), T2: 6.15 (6.01, 6.28), T3: 6.15 (6.01, 6.29) AHEI-2010, T1: 6.02 (5.88, 6.15), T2: 6.13 (6.00, 6.27), T3: 6.14 (6.00, 6.28) aMED, T1: 6.05 (5.91, 6.18), T2: 6.11 (5.97, 6.24), T3: 6.16 (6.02, 6.31) DASH, T1: 6.07 (5.94, 6.21), T2: 6.11 (5.98, 6.25), T3: 6.17 (6.03, 6.31) Phylum Actinobacterium, mean (95% CI) HEI-2010, T1: 2.01 (1.80, 2.23), T2: 1.69 (1.47, 1.90), T3: 1.65 (1.43, 1.87) AHEI-2010, T1: 1.91 (1.69, 2.12), T2: 1.78 (1.56, 1.99), T3: 1.67 (1.45, 1.88) aMED, T1: 1.98 (1.76, 2.19), T2: 1.70 (1.49, 1.91), T3: 1.60 (1.37, 1.82) DASH, T1: 1.94, (1.72, 2.16), T2: 1.73 (1.52, 1.95), T3: 1.63 (1.41, 1.86) |
Ruiz-Saavedra, 2020 [65] | Microbiological parameters: Significant differences were observed in most of the microbiological parameters analyzed according to age. Subjects over 65 years of age presented lower fecal levels of Bacteroides-Prevotella-Porphyromonas group, Clostridia cluster XIVa and Faecalibacterium, as well as all the short chain fatty acids determined. Blood parameters are within the normal physiological ranges and were similar between the groups evaluated except for MDA, IL-8, IL-12 and TNF-α, whose concentration is higher in subjects over 65 years of age. Microbial levels for sub group >65 years: Bacteroides-Prevotella-Porphyromonas (Log10 n ◦ cells/g feces): 8.79 (0.69) Clostridia cluster XIVa (Log10 n ◦ cells/g feces): 6.45 (1.54) Faecalibacterium prausnitzii (Log10 n ◦ cells/g feces): 6.42 (1.31) Acetic acid (mM): 23.18 (14.45) Propionic acid (mM): 9.50 (7.46) Butyric acid (mM): 8.44 (7.94) |
Shikany, 2019 [66] | α-diversity, mean (SD) Western diet: Shannon: Total sample: 3.39 (0.61), Q1: 3.42 (0.66), Q2: 3.43 (0.62), Q3: 3.38 (0.60), Q4: 3.32 (0.57) Inverse Simpson: Total sample: 15.9 (9.8), Q1: 16.9 (10.2), Q2: 16.6 (10.8), Q3: 15.9 (9.8), Q4: 14.3 (8.3) Prudent diet: Shannon: Total sample: 3.39 (0.61), Q1: 3.38 (0.63), Q2: 3.44 (0.59), Q3: 3.36 (0.61), Q4: 3.38 (0.62) Inverse Simpson: Total sample: 15.9 (9.8), Q1: 15.9 (9.8), Q2: 16.8 (10.3), Q3: 15.4 (10.0), Q4: 15.6 (9.4) Beta-diversity In multivariable-adjusted models, greater adherence to the Western pattern was positively associated with families Mogibacteriaceae and Veillonellaceae and genera Alistipes, Anaerotruncus, CC115, Collinsella, Coprobacillus, Desulfovibrio, Dorea, Eubacterium, and Ruminococcus, while greater adherence to the prudent pattern was positively associated with order Streptophyta, family Victivallaceae, and genera Cetobacterium, Clostridium, Faecalibacterium, Lachnospira, Paraprevotella, and Veillonella. Beta diversity measures were significantly associated with both Western and prudent patterns in multivariable-adjusted analyses. |
Zhang, 2021 [68] | α-diversity and SCFAs, at baseline, month 2 and month 4, mean (SD) Acetic acid (µmol/g): 40.98 (16.83), 38.59 (17.86), 30.10 (17.26) Propionic acid (µmol/g) 40.88 (19.21), 42.26 (20.48), 38.89 (20.85) Butyric acid (µmol/g) 36.06 (18.20), 31.61 (16.76), 34.21 (19.06) Chao1: 391.1 (112.5), 301.2 (85.4), 310.2 (77.9) ACE: 387.9 (111.4), 294.6 (78.9), 308.8 (77.9) Shannon 5.09 (0.74), 4.98 (0.68), 5.00 (0.66) Simpson 0.92 (0.06), 0.92 (0.05), 0.93 (0.04) Changes in SCFA content in the feces were not significantly different after 2 and 4 months of intervention Gut microbiota, at baseline, month 2 and month 4, mean (SD) After adjusting for age, gender, and intervention compliance, the older adults were found to have significantly decreased levels of the following bacterial taxa: class Bacilli, genus Streptococcus, genus Ruminiclostridium_5, class Deltaproteobacteria, phylum Actinobacteria, class Bifidobacteriales, and phylum Patescibacteria and increased levels of genus Lactobacillus after 2 and 4 months relative to the baseline. There were significant increases in the phylum Bacteroidetes and species Bacteroides thetaiotaomicron after 2 months and in the genus Agathobacter after 4 months relative to the baseline. There were no appreciable differences in the ratios of Firmicutes and Bacteroidetes—an indicator that is strongly associated with several diseases—at the baseline and 2 and 4 months after the commencement of the intervention (6.6, 4.0, and 6.85, respectively). |
Author, Year | Measure of Food Group | Fruit, Mean (SD) | Veg, Mean (SD) | Legumes, Mean (SD) | Poultry, Mean (SD) | Meat, Mean (SD) | Fish, Mean (SD) | Wholegrains/Bread/Cereal, Mean (SD) |
---|---|---|---|---|---|---|---|---|
André, 2021 [57] | adherence to Med diet, servings/ week adherence to Comp carbs diet, servings/ week adherence to Trad diet, servings/ week adherence to Prudent diet, servings/week | Low: 9.1 (6.6) Medium: 13.4 (6.6) High: 15.6 (5.4) Low: 12.9 (7.3) Medium: 13.3 (6.8) High: 13.0 (6.1) Low: 14.6 (7.1) Medium: 13.2 (6.2) High: 11.5 (6.5) Low: 10.2 (6.1) Medium: 12.6 (5.9) High: 16.3 (6.8) | Low: 8.4 (4.0) Medium: 9.9 (4.1) High: 11.8 (4.0) Low: 9.4 (4.0) Medium: 10.0 (4.0) High: 11.1 (4.5) Low: 10.2 (4.3) Medium: 10.5 (4.2) High: 9.8 (4.1) Low: 7.3 (3.5) Medium: 9.8 (2.9) High: 13.4 (3.6) | Low: 0.5 (0.5) Medium: 0.6 (0.7) High: 0.7 (0.6) Low: 0.4 (0.4) Medium: 0.6 (0.6) High: 0.8 (0.7) Low: 0.3 (0.4) Medium: 0.6 (0.5) High: 0.9 (0.8) Low: 0.6 (0.7) Medium: 0.6 (0.5) High: 0.6 (0.6) | Low: 1.6 (1.1) Medium: 1.8 (1.4) High: 1.9 (1.1) Low: 1.3 (0.9) Medium: 1.7 (1.0) High: 2.5 (1.5) Low: 1.9 (1.4) Medium: 1.8 (1.2) High: 1.7 (1.1) Low: 1.6 (1.1) Medium: 1.8 (1.2) High: 2.1 (1.4) | Low: 5.8 (3.0) Medium: 4.4 (2.4) High: 4.4 (1.9) Low: 4.8 (2.8) Medium: 5.0 (2.3) High: 4.5 (2.3) Low: 3.4 (2.0) Medium: 4.6 (1.9) High: 6.3 (2.6) Low: 5.0 (2.7) Medium: 5.0 (2.5) High: 4.3 (2.3) | Low: 1.9 (1.3) Medium: 2.9 (1.7) High: 3.6 (1.6) Low: 2.2 (1.4) Medium: 3.0 (1.5) High: 3.5 (1.8) Low: 2.8 (1.8) Medium: 2.9 (1.6) High: 2.9 (1.6) Low: 2.3 (1.3) Medium: 2.9 (1.7) High: 3.5 (1.7) | Low: 17.1 (6.0) Medium: 18.6 (5.0) High: 19.4 (4.3) Low: 16.5 (6.0) Medium: 19.1 (4.6) High: 19.9 (4.1) Low: 15.7 (6.2) Medium: 19.4 (4.2) High: 20.4 (3.3) Low: 16.7 (5.6) Medium: 19.0 (4.6) High: 19.8 (4.7) |
Berendsen, 2018 [58] | Control group, g/day Diet group (Med style diet), g/day | Baseline: 260.0 (158.7) Follow up: 255.7 (154.0) Baseline: 248.2 (140.2) Follow up: 268.2 (140.0) | Baseline: 221.4 (120.7) Follow up: 213.2 (125.7) Baseline: 214.5 (110.8) Follow up: 234.2 (103.7) | Baseline: 11.1 (20.0) Follow up: 10.8 (19.2) Baseline: 10.4 (20.9) Follow up: 17.6 (21.9) | Baseline: 41.2 (33.4) Follow up: 40.5 (31.4) Baseline: 40.5 (31.6) Follow up: 38.5 (27.9) | N/A | Baseline: 28.4 (29.3) Follow up: 24.9 (23.2) Baseline: 28.4 (25.3) Follow up: 37.1 (28.1) | Baseline: 54.4 (53.9) Follow up: 62.6 (60.7) Baseline: 55.7 (58.3) Follow up: 107.2 (66.4) |
Li, 2021 [62] | adherence to hPDI, servings/ day | Q1: 1.3 (0.8) Q2: 1.6 (0.6) Q3: 1.7 (0.8) Q4: 1.9 (1.1) Q5: 2.6 (1.4) | Q1: 3.2 (1.0) Q2: 3.4 (1.4) Q3: 3.5 (1.7) Q4: 3.9 (1.7) Q5: 4.6 (1.6) | Q1: 0.4 (0.2) Q2: 0.5 (0.2) Q3: 0.4 (0.2) Q4: 0.4 (0.2) Q5: 0.7 (0.5) | Not reported | Q1: 1.6 (0.5) Q2: 1.4 (0.5) Q3: 1.3 (0.6) Q4: 1.1 (0.4) Q5: 0.7 (0.4) | Q1: 0.3 (0.1) Q2: 0.4 (0.2) Q3: 0.3 (0.2) Q4: 0.4 (0.2) Q5:0.4 (0.2) | Q1: 1.6 (0.7) Q2: 1.7 (0.9) Q3: 2.1 (1.2) Q4: 1.9 (0.9) Q5:2.5 (1.7) |
Author, Year | Measure of Nutrient Group | Energy, Mean (SD) (kcal/d) | Fat, Mean (SD) (% of kcal/d) | Carbohydrate, Mean (SD) (g/d) | Total Protein, Mean (SD) (g/d) | Veg/Plant Protein, Mean (SD) (g/d) | Animal Protein, Mean (SD) (g/d) | Fibre, Mean (SD) (g/d) |
---|---|---|---|---|---|---|---|---|
Farsijani, 2022 [59] | Total daily protein intake by quartile | Q1: 1710 (695) Q2: 1372 (568) Q3: 1355 (482) Q4: 1700 (622) Total sample: 1534 (620) | Q1: 41.8 (7.1) Q2: 40.2 (6.8) Q3: 41.3 (7.2) Q4: 40.0 (6.9) | % of kcal/d: Q1: 48.1 (7.5) Q2: 47.4 (7.0) Q3: 44.3 (7.4) Q4: 43.0 (6.9) | Q1: 55.3 (23.5) Q2: 52.3 (21.2) Q3: 57.4 (17.9) Q4: 81.8 (26.1) Total sample, 62.0 (10.8) | Q1: 25.7 (12.5) Q2: 22.1 (10.3) Q3: 21.8 (10.5) Q4: 28.8 (13.4) | Q1: 29.6 (15.1) Q2: 30.2 (13.8) Q3: 35.6 (11.8) Q4: 53.0 (18.4) | Q1: 16.1 (7.9) Q2: 14.9 (6.7) Q3: 14.7 (7.1) Q4: 18.8 (9.0) |
Li, 2021 [62] | Adherence to a high protein diet by quintile | Q1: 2353 (411) Q2: 2254 (512) Q3: 2069 (481) Q4: 1987 (510) Q5: 1921 (459) | Not reported | Q1: 275.0 (56.8) Q2: 273.0 (70.7) Q3: 251.0 (64.5) Q4: 241.0 (69.2) Q5: 254.0 (76.7) | Q1: 96.0 (17.5) Q2: 92.7 (23.9) Q3: 90.2 (23.7) Q4: 85.5 (20.8) Q5: 81.0 (18.7) | Q1: 28.6 (6.1) Q2: 30.3 (8.6) Q3: 30.1 (8.9) Q4: 30.0 (8.9) Q5: 35.0 (12.7) | Q1: 67.5 (14.5) Q2: 62.3 (17.4) Q3: 60.0 (17.3) Q4: 55.5 (14.1) Q5: 46.0 (16.2) | Q1: 21.8 (5.5) Q2: 24.5 (7.4) Q3: 24.1 (7.4) Q4: 25.2 (7.9) Q5: 30.4 (10.6) |
Maroto-Rodriguez, 2022 [63] | Adherence to a high protein diet by tertile | T1: 2335 (550) T2: 2053 (554) T3: 1815 (499) Total sample, 2031 (569) | Not reported | Not reported | Not reported | Not reported | Not reported | Not reported |
Maskarinec, 2019 [64] | Adherence to HEI, AHEI, aMED and DASH by tertile | HEI-2010: T1: 1957 (1050) T3: 1779 (766) AHEI-2010: T1: 1760 (887) T3: 1967 (833) aMED: T1: 1463 (615) T3: 2450 (1136) DASH: T1: 1618 (699) T3: 2109 (1082) | Not reported | Not reported | Not reported | Not reported | Not reported | Not reported |
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Jones, D.; Celis-Morales, C.; Gray, S.R.; Morrison, D.J.; Ozanne, S.E.; Jain, M.; Mattin, L.R.; Burden, S. Effect of Sustainably Sourced Protein Consumption on Nutrient Intake and Gut Health in Older Adults: A Systematic Review. Nutrients 2024, 16, 1398. https://doi.org/10.3390/nu16091398
Jones D, Celis-Morales C, Gray SR, Morrison DJ, Ozanne SE, Jain M, Mattin LR, Burden S. Effect of Sustainably Sourced Protein Consumption on Nutrient Intake and Gut Health in Older Adults: A Systematic Review. Nutrients. 2024; 16(9):1398. https://doi.org/10.3390/nu16091398
Chicago/Turabian StyleJones, Debra, Carlos Celis-Morales, Stuart R. Gray, Douglas J. Morrison, Susan E. Ozanne, Mahek Jain, Lewis R. Mattin, and Sorrel Burden. 2024. "Effect of Sustainably Sourced Protein Consumption on Nutrient Intake and Gut Health in Older Adults: A Systematic Review" Nutrients 16, no. 9: 1398. https://doi.org/10.3390/nu16091398
APA StyleJones, D., Celis-Morales, C., Gray, S. R., Morrison, D. J., Ozanne, S. E., Jain, M., Mattin, L. R., & Burden, S. (2024). Effect of Sustainably Sourced Protein Consumption on Nutrient Intake and Gut Health in Older Adults: A Systematic Review. Nutrients, 16(9), 1398. https://doi.org/10.3390/nu16091398