| Literature DB >> 31191839 |
Fereshteh Pashayee-Khamene1, Hamed Kord-Varkaneh1, Mahdi Saber-Firoozi2, Behzad Hatami3, Bahram Rashidkhani1, Azita Hekmatdoost1.
Abstract
AIM: To evaluate the association between dietary protein sources with disease severity, malnutrition and anthropometric measurements in cirrhotic patients.Entities:
Keywords: Cirrhosis; Dietary Protein; Malnutrition
Year: 2019 PMID: 31191839 PMCID: PMC6536023
Source DB: PubMed Journal: Gastroenterol Hepatol Bed Bench ISSN: 2008-2258
General characteristics of the participants in the study based on tertiles of animal proteins and dairy and vegetable proteins
| P Value* | dairy and vegetable proteins | P Value* | tertiles of animal proteins | |||||
|---|---|---|---|---|---|---|---|---|
| tertile 3 (23) | tertile 2 (22) | Tertile1 (23) | tertile 3 (22) | tertile 2 (23) | Tertile1 (23) | |||
| 0.345 | 10.30±2.72 | 11.81±4.38 | 10.65±3.56 | 0.740 | 11.40±3.40 | 10.69±3.13 | 10.65±4.29 | MELD |
| CHILD-pugh | ||||||||
| 0.529 | 38.30% | 31.90% | 29.80% | 0.695 | 31.90% | 36.20% | 31.90% | mild |
| 25% | 35% | 40% | 35% | 30% | 35% | medium | ||
| 0% | 0% | 100% | 0% | 0% | 100% | severe | ||
| SGA | ||||||||
| 0.139 | 44.40% | 37% | 18.50% | 0.420 | 33.30% | 33.30% | 33.30% | well-nourished |
| 30.30% | 24.20% | 45.50% | 33.30% | 39.40% | 27.30% | moderately malnourished | ||
| 12.50% | 50% | 37.50% | 25.0% | 12.5% | 62.5% | severely malnourished | ||
| 0.74 | 55.65±11.92 | 58.04±10±26 | 50.34±11.85 | 0.898 | 55.40±12.78 | 53.78±11.68 | 54.73±11.01 | Age(years) |
| 0.027 | 18(36.7%) | 19(38.8%) | 12(24.5%) | 0.120 | 18(36.7%) | 18(36.7%) | 13(26.5%) | Sex(male) |
| 0.123 | 78.41±12.26 | 74.18±16.54 | 69.30±15.48 | 0.685 | 76.29±15.74 | 72.78±15.24 | 72.91±14.76 | Weight(kg) |
| 0.483 | 27.68±4.42 | 26.39±4.83 | 25.95±5.7 | 0.624 | 26.71±4.91 | 25.93±4.79 | 27.38±5.37 | BMI (kg/m2) |
| 0.580 | 1.08±0.54 | 0.92±0.49 | 0.94±0.60 | 0.426 | 1.04±0.65 | 0.86±0.34 | 1.05±0.59 | TST |
| 0.984 | 29.01±4.06 | 28.90±5.21 | 29.17±5.37 | 0.207 | 28.36±4.34 | 28.21±4.78 | 30.49±5.20 | MAC |
| 0.756 | 25.29±3.46 | 25.61±3.78 | 26.13±4.04 | 0.197 | 24.84±3.00 | 25.41±3.83 | 26.81±4.15 | MAMC |
| 0.045 | 68.91±23.48 | 59.65±22.78 | 51.42±21.75 | 0.266 | 63.92±22.74 | 63.52±21.78 | 53.80±25.30 | MS |
| 0.105 | 31.75±4.83 | 34.24±4.59 | 30.88±5.69 | 0.243 | 32.20±3.14 | 33.44±5.68 | 30.73±6.14 | MMP |
| 0.307 | 28.21±9.75 | 24.32±8.85 | 28.90±11.20 | 0.156 | 27.21±7.31 | 24.58±9.98 | 30.58±12.06 | FMP |
| 0.25 | 11.52±5.22 | 10.61±4.73 | 7.71±3.82 | 0.580 | 10.80±5.88 | 9.26±4.45 | 9.92±4.14 | VFP |
Obtained from ANOVA for continuous variables and χ2 test for categorical variables; BMI, body mass index; TST: Triceps Skinfold Thickness; MAC: Mid arm circumference; MAMC: Mid arm muscle circumference; MS: Muscle strength; MMP: Muscle mass percent; FMP: Fat mass percent; VFP: Visceral fat percent
Multiple linear regression analysis that shows the association between animal proteins and dairy and vegetable proteins and anthropometric variables
| animal proteins | dairy and vegetable proteins | |||
|---|---|---|---|---|
| β |
| β |
| |
| MELD | 0.176 | 0.196 | -0.195 | 0.163 |
| Weight(kg) | 0.061 | 0.646 | 0.282 | 0.037 |
| BMI(kg/m2) | 0.042 | 0.759 | 0.244 | 0.076 |
| TST | -0.064 | 0.633 | 0.327 | 0.017 |
| MAC | -0.184 | 0.162 | 0.112 | 0.414 |
| MAMC | -0.195 | 0.151 | -0.018 | 0.902 |
| MS | -0.068 | 0.493 | 0.353 | 0.000 |
| MMP | -0.177 | 0.066 | -0.176 | 0.080 |
| FMP | 0.157 | 0.158 | 0.187 | 0.104 |
| VFP | 0.081 | 0.526 | 0.326 | 0.012 |
All variables were adjusted for age, sex, smoking, andalcohol. BMI, body mass index; TST: Triceps Skinfold Thickness ; MAC: Mid arm circumference; MAMC: Mid arm muscle circumference; MS: Muscle strength; MMP: Muscle mass percent; FMP: Fat mass percent; VFP: Visceral fat percent
Odds ratios of disease severity and malnutrition based on the tertiles of protein consumption
| Variables | tertiles of animal proteins | P trend | tertiles of animal proteins | P trend | ||||
|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 1 | 2 | 3 | |||
| Child-Pugh | ||||||||
| Crude model | 1.00 | 0.66(0.18-2.34) | 0.87(0.25-3.02) | 0.824 | 1.00 | 0.72(0.21, 2.47) | 0.43(0.11, 1.58) | 0.205 |
|
| 1.00 | 0.52(0.13-2.01) | 0.67(0.17-2.67) | 0.335 | 1.00 | 0.53(0.13-2.04) | 0.28(0.06-1.29) | 0.102 |
|
| 1.00 | 0.59 (0.14-2.52) | 0.72(0.16-3.27) | 0.714 | 1.00 | 0.57 (0.12-2.71) | 0.22(0.04-1.20) | 0.076 |
| SGA | ||||||||
| Crude model | 1.00 | 0.83(0.25-2.75) | 0.77(0.23-2.57) | 0.672 | 1.00 | 3.3(0.91-11.92) | 1.1(0.34-3.55) | 0.073 |
|
| 1.00 | 1.04(0.27-3.95) | 1.21(0.30-4.89) | 0.778 | 1.00 | 0.35(0.08-1.52) | 0.34(0.07-1.54) | 0.191 |
|
| 1.00 | 1.20(0.28-5.08) | 1.29(0.27-5.99) | 0.747 | 1.00 | 0.13(0.01-0.99) | 0.14(0.02-0.95) | 0.074 |
| MELD | ||||||||
| Crude model | 1.00 | 1.20(0.36-3.99) | 2.70(.80-9.06) | 0.106 | 1.00 | 1.30(0.40-4.20) | 0.83(0.25-2.70) | 0.767 |
|
| 1.00 | 1.16(0.30-4.40) | 3.55(0.86-14.57) | 0.74 | 1.00 | 1.64(0.43-6.28) | 1.32(0.31-5.59) | 0.726 |
|
| 1.00 | 1.43(0.34-6.07) | 4.27(0.87-20.83) | 0.067 | 1.00 | 1.002(0.21-4.63) | 0.84(0.18-3.89) | 0.809 |
Model 1: adjusted for BMI and energy intake;
Model 2: adjusted for age, sex, alcohol, smoking, body mass index, and energy intake
Dietary protein sources intakes in categories of CHILD-pugh and SGA. Data are analyzed using one-way ANOVA. SGA: subjective global assessment
| CHILD-pugh | SGA | ||||||
|---|---|---|---|---|---|---|---|
| Mild | Moderateand Severe | P-Value | Well-nourished | Moderately malnourished | Severely malnourished | P-Value | |
| Animal proteins intake | 4.09±2.68 | 4.49±3.5 | 0.69 | 4.13±2.52 | 4.52±3.32 | 3.26±2.56 | 0.54 |
| Dairy and vegetable proteins intakes | 4.26±2.39 | 3.38±1.73 | 0.23 | 4.50±2.24 | 3.67±2.31 | 3.40±1.68 | 0.27 |
serving±SE