Long-term Efficacy of High-protein Diets a Systematic Review

Abstruse

Background: Evidence that high-protein diets are an constructive strategy for the maintenance of long-term weight loss is limited.

Objective: The objective was to decide the efficacy of a higher protein intake on the maintenance of weight loss later 64 wk of follow-upwardly.

Design: Lxx-nine good for you women with a mean (±SD) age of 49 ± 9 y and a body mass alphabetize (in kg/one thousandⁱⁱ) of 32.viii ± 3.5 completed an intensive 12-wk weight-loss program and 52 wk of follow-up to compare the furnishings on weight-loss maintenance of a high-protein (HP) diet (34% of free energy) or a high-saccharide (HC) diet (64% of energy).

Results: Hateful (±SD) weight loss was non significantly unlike between groups: (HP: four.6 ± five.5 kg; HC: 4.4 ± half-dozen.1 kg). Protein intake (g) from dietary records at 64 wk was directly related to weight loss (P < 0.0001), accounting for 15% of the variance. Protein intake as a percentage of energy was also related to weight change (P = 0.003), accounting for x% of the variance. In the upper tertile (88 yard protein/d), weight loss was half-dozen.5 ± 7.5 and 3.4 ± 4.4 kg (P = 0.03) in the two lower tertiles, respectively. This difference did not translate to a difference in primal fat loss between groups. Lipids, glucose, insulin, C-reactive protein, and homocysteine all improved with weight loss and were not significantly dissimilar betwixt groups. HDL cholesterol rose by 20%. Higher serum vitamin B-12 was observed in the HP group, and folate concentrations were non significantly different between groups.

Conclusions: A reported higher protein intake appears to confer some weight-loss benefit. Cardiovascular disease run a risk factors, biomarkers of disease, and serum vitamins and minerals improved with no differences between groups.

INTRODUCTION

Numerous brusque-term studies and a recent meta-regression of these studies take shown that college-protein, reduced-saccharide weight-loss diets are associated with greater fatty loss and reduced lean mass loss compared with diets higher in carbohydrate or lower in poly peptide (one). Notwithstanding, few studies have been longer than 6 mo. In a follow-up to an intensive 6-mo weight-loss trial, Due et al (two, three) reported in 2004 that at 12 mo there was greater abdominal fat loss in subjects assigned to a high-protein diet with similar but statistically nonsignificant, results at 24 mo. Similarly, in a 12-mo study, McAuley et al (4) reported improved weight-loss maintenance (−6.half-dozen kg) with a higher-protein diet than with a high-carbohydrate diet (−4.4 kg) or a loftier-fatty diet (−v.5 kg); however, the differences between the diets were relatively small.

In contrast, nosotros previously reported long-term information for individuals with type 2 diabetes and obese subjects with hyperinsulinemia; no differences in weight loss were observed betwixt subjects assigned to a higher-poly peptide diet and those assigned to a higher-carbohydrate diet (5, half-dozen). Similarly to our long-term results, the 12-mo results from the Atkins diet (a depression-carbohydrate, loftier-protein, high-fat diet) studies showed no pregnant difference betwixt the nutrition groups despite significant differences beingness seen at 6 mo (seven).

Thus, in that location is limited testify in the literature that a college protein intake during weight loss is a significant factor for long-term success. In this article we written report on the results of our i-y follow-upward of an intensive 12-wk weight-loss trial (eight). The aim of the study was to determine the efficacy of a higher-poly peptide dietary design on maintenance of weight loss, effects on cardiovascular disease risk factors, and markers of bone health after 64 wk.

SUBJECTS AND METHODS

Subjects

The participants, study pattern, and dietary interventions were described previously (viii). Briefly, women were recruited by public advertisement and screened by questionnaire. The inclusion criteria were as follows: women aged xx–65 y, torso mass alphabetize (BMI; in kg/thousand²) between 27 and xl, and no history of renal or liver illness or type 1 or type two diabetes. One hundred nineteen women met the selection criteria and were randomly assigned to handling. All subjects gave written informed consent to participate in the study, which was approved by the Human Ethics Committee of the Commonwealth Scientific and Industrial Research System, Human Nutrition, Adelaide, Commonwealth of australia. Lxx-nine women completed the 64-wk study. Twoscore women withdrew from the written report earlier completion, 17 on the high-protein (HP) diet and 23 on the high-saccharide (HC) diet ( Figure 1). Subject characteristics at baseline are presented in Table 1.

FIGURE 1.

Schematic representation of randomization.

Figure one.

Schematic representation of randomization.

TABLE i

Baseline characteristics (week 0) according to reported protein intake and original diet allotment ¹

	RLP (n = 46)	RHP (n = 27)	LP (n = 38)	HP (northward = 41)
Historic period (y)	49.79 ± 9.3	50.nine ± ix.9	49.9 ± 9.vi	49.ix ± 9.7
Weight (kg)	84.7 ± 10.half dozen	88.v ± 13.i	85.6 ± 11.7	85.nine ± 11.iv
BMI (kg/mtwo)	31.8 ± 5.9	33.one ± 3.5	32.5 ± three.four	35.6 ± three.3
Total cholesterol (mmol/L)	5.84 ± 1.06	5.79 ± 1.13	five.85 ± 0.99	5.76 ± 1.15
Triacylglycerols (mmol/50)	1.51 ± 0.threescore	1.xl ± 0.75	1.57 ± 0.77	one.30 ± 0.51
HDL cholesterol (mmol/L)	i.21 ± 0.24	1.28 ± 0.37	1.17 ± 0.28	1.34 ± 0.32
LDL cholesterol (mmol/L)	iii.89 ± 0.88	3.83 ± ane.01	3.9 ± 0.viii	3.82 ± 1.00
Glucose (mmol/50)	v.96 ± 0.56	6.28 ± 0.61	6.08 ± 0.58	vi.07 ± 0.57
Insulin (mIU/Fifty)	11.18 ± five.10	seven.98 ± three.18	10.83 ± 5.02	nine.01 ± 4.45

	RLP (n = 46)	RHP (n = 27)	LP (northward = 38)	HP (n = 41)
Historic period (y)	49.79 ± 9.3	l.9 ± 9.9	49.9 ± 9.6	49.9 ± 9.seven
Weight (kg)	84.vii ± x.vi	88.5 ± 13.1	85.half dozen ± eleven.7	85.9 ± 11.iv
BMI (kg/m2)	31.8 ± five.9	33.1 ± three.five	32.5 ± iii.4	35.6 ± 3.3
Total cholesterol (mmol/Fifty)	5.84 ± i.06	five.79 ± ane.13	v.85 ± 0.99	5.76 ± one.15
Triacylglycerols (mmol/L)	1.51 ± 0.lx	1.40 ± 0.75	1.57 ± 0.77	ane.thirty ± 0.51
HDL cholesterol (mmol/50)	1.21 ± 0.24	1.28 ± 0.37	i.17 ± 0.28	ane.34 ± 0.32
LDL cholesterol (mmol/L)	3.89 ± 0.88	3.83 ± i.01	3.nine ± 0.viii	3.82 ± 1.00
Glucose (mmol/L)	5.96 ± 0.56	6.28 ± 0.61	vi.08 ± 0.58	six.07 ± 0.57
Insulin (mIU/L)	11.18 ± five.10	7.98 ± 3.eighteen	x.83 ± 5.02	9.01 ± 4.45

i

All values are x̄ ± SD. RLP, reported low protein; RHP, reported loftier protein; LP, low protein; HP, high protein. Between-group differences were analyzed by i-factor ANOVA. In that location were no significant differences betwixt the groups.

TABLE 1

Baseline characteristics (week 0) according to reported protein intake and original diet allocation ⁱ

	RLP (n = 46)	RHP (n = 27)	LP (n = 38)	HP (n = 41)
Age (y)	49.79 ± 9.three	50.9 ± 9.9	49.ix ± nine.6	49.ix ± ix.7
Weight (kg)	84.7 ± x.six	88.v ± xiii.i	85.vi ± 11.7	85.9 ± 11.4
BMI (kg/m2)	31.8 ± 5.9	33.ane ± 3.five	32.5 ± three.4	35.6 ± 3.3
Total cholesterol (mmol/L)	5.84 ± i.06	5.79 ± ane.13	5.85 ± 0.99	5.76 ± 1.xv
Triacylglycerols (mmol/Fifty)	1.51 ± 0.60	one.40 ± 0.75	1.57 ± 0.77	1.xxx ± 0.51
HDL cholesterol (mmol/L)	1.21 ± 0.24	i.28 ± 0.37	i.17 ± 0.28	i.34 ± 0.32
LDL cholesterol (mmol/50)	3.89 ± 0.88	three.83 ± 1.01	3.nine ± 0.8	iii.82 ± 1.00
Glucose (mmol/50)	5.96 ± 0.56	6.28 ± 0.61	six.08 ± 0.58	6.07 ± 0.57
Insulin (mIU/Fifty)	11.18 ± five.10	7.98 ± 3.eighteen	x.83 ± 5.02	9.01 ± iv.45

	RLP (n = 46)	RHP (due north = 27)	LP (northward = 38)	HP (due north = 41)
Historic period (y)	49.79 ± 9.3	50.nine ± ix.9	49.9 ± ix.half dozen	49.9 ± 9.seven
Weight (kg)	84.7 ± ten.6	88.5 ± thirteen.1	85.half-dozen ± 11.7	85.9 ± 11.4
BMI (kg/m2)	31.8 ± 5.nine	33.ane ± iii.five	32.5 ± 3.iv	35.6 ± 3.three
Total cholesterol (mmol/Fifty)	5.84 ± 1.06	5.79 ± 1.thirteen	5.85 ± 0.99	5.76 ± one.15
Triacylglycerols (mmol/Fifty)	i.51 ± 0.lx	ane.40 ± 0.75	1.57 ± 0.77	1.thirty ± 0.51
HDL cholesterol (mmol/L)	ane.21 ± 0.24	1.28 ± 0.37	i.17 ± 0.28	one.34 ± 0.32
LDL cholesterol (mmol/L)	iii.89 ± 0.88	3.83 ± ane.01	3.9 ± 0.8	iii.82 ± one.00
Glucose (mmol/Fifty)	5.96 ± 0.56	half-dozen.28 ± 0.61	6.08 ± 0.58	vi.07 ± 0.57
Insulin (mIU/Fifty)	eleven.18 ± 5.10	7.98 ± 3.18	10.83 ± v.02	9.01 ± 4.45

1

All values are x̄ ± SD. RLP, reported low protein; RHP, reported loftier protein; LP, depression poly peptide; HP, high protein. Between-group differences were analyzed by one-gene ANOVA. There were no significant differences betwixt the groups.

Report design

The study had a parallel design with subjects randomly assigned to i of 2 isocaloric 5600-kJ dietary interventions for 64 wk (12 wk of intensive weight loss and 52 wk of follow-upwards). The planned dietary interventions were an HP nutrition (high in protein, depression in saturated fatty; 34% of free energy from poly peptide, xx% of energy from fat, and 46% of energy from saccharide) or an HC diet (low in saturated fat, 17% of free energy from protein, 20% of energy from fat, and 64% of free energy from saccharide); both diets had <10% of energy from saturated fatty. During the initial 12-wk weight-loss phase, the subjects attended individual consultations with 2 dietitians every 4 wk. During the 52-wk follow-up, participants were asked to follow the same regimen every bit during the short-term study if they could, but those consuming the HP diet could substitute chicken, fish, or pork for crimson meat, whereas those consuming the HC diet could omit biscuits and substitute them with more bread, potatoes, or rice. Participants attended the CSIRO clinic at 3 monthly intervals (3, half dozen, nine, and 12 mo) after the end of the brusk-term intervention and had an individual consultation with a qualified dietitian. They were asked to keep a 3-d weighed food record earlier each visit, and energy and macronutrient intakes were calculated past using DIET iv Nutritional Calculation software (Xyris Software, Highgate Hill, Queensland, Australia), which is based on Australian food-composition tables and food manufacturers' data.

Body weight and composition

Subjects were weighed (model AMZ14; Mercury Digital Scales, Tokyo, Japan) in light vesture and without shoes after an overnight fast at each visit. Height was measured with a stadiometer (Seca, Hamburg, Germany) at calendar week 0. Body mass alphabetize (BMI) was calculated by weight (kg)/pinnacle² (m). Dual-energy Ten-ray absorptiometry (DXA) (Norland Medical Systems, Fort Atkinson, WI) was performed at weeks 0 and 64 (Royal Adelaide Hospital, Adelaide, Australia).

Urinalysis

Drove of full 24-h urine output commenced at 0700 (not including the starting time morning void) on the mean solar day earlier the subjects attended the research dispensary and concluded at 0700 on the day of dispensary omnipresence (including first forenoon void) at weeks 0 and 64. Urine samples were measured at the Institute of Medical and Veterinary Science (IMVS), (Adelaide, S Commonwealth of australia) for creatinine, urea, calcium, phosphate, and sodium with the utilise of proprietary techniques on an Olympus AU5400 chemical science analyzer (Tokyo, Nippon). Deoxypyridinoline and pyridinoline were measured by using HPLC and expressed per mmol creatinine.

Biochemistry

Fasting blood samples were collected at baseline and the stop of the study in tubes containing either no additives for lipids, insulin, C-reactive poly peptide (CRP), or sodium fluoride/EDTA for glucose measurements. Plasma or serum was isolated by centrifugation at 2000 × g for 10 min at 5 °C (GS-6R centrifuge; Beckman, Fullerton, CA) and frozen at −20 °C. Biochemical assays were performed in a single assay at the completion of the study. Plasma glucose and serum total cholesterol (TC) and triacylglycerol concentrations were measured with a Cobas-Bio centrifugal analyzer (Roche Diagnostica, Basel, Switzerland) by using enzymatic kits (Hoffmann-La Roche Diagnostica, Basel, Switzerland) and control sera. Serum HDL-cholesterol concentrations were measured with a Cobas-Bio analyzer (Roche Diagnostica) after precipitation of LDL cholesterol and VLDL cholesterol with polyethylene glycol 6000 solution. A modified Friedewald equation was used to calculate LDL cholesterol (9). Insulin was determined in duplicate with a radioimmunoassay kit (Pharmacia & Upjohn Diagnostics AB, Uppsala, Sweden). CRP was measured with an enzymatic kit (Roche, Indianapolis, IN) on a Hitachi auto analyzer (Roche, Indianapolis, IN). Serum homocysteine, atomic number 26, ferritin, folate, and vitamin B-12 were measured at weeks 0 and 64 at IMVS (Adelaide, South Australia).

Statistics

Statistical analyses were performed with the use of SPSS 14.0 for WINDOWS (SPSS Inc, Chicago, IL). The prescription for poly peptide in the original written report was 110 thou/d. We defined compliance at eighty% of this original prescription and plant that this was the top tertile of reported poly peptide intake (8). For results at 64 wk, outcomes were related in linear regression models and repeated-measures ANOVA to both assigned diet and to actual intake at 64 wk (at the everyman compliance point). Both absolute levels at 64 wk adapted for baseline values and changes over 64 wk were modeled. Significance was set at P < 0.05. Values are reported equally means ± SDs unless otherwise stated.

RESULTS

Weight

Overall weight loss in the two allocated groups was non significantly dissimilar: iv.vi ± v.5 and 4.4 ± vi.i kg in the HP and HC groups, respectively. Ratios of urinary urea to creatinine at 64 wk were non significantly unlike, which suggests poor compliance with the allocated diets. Still, when bodily protein intake, calculated from dietary records at 64 wk returned by 72 participants, was used as a benchmark, weight loss was greater (P = 0.03) in the reported high-protein group (RHP; >88 g protein/d; upper tertile) than in the reported low-poly peptide group (RLP): 6.5 ± 7.v kg (n = 27) compared with 3.4 ± 4.4 kg (n = 45) ( Table 2). To ostend these results nosotros divided the grouping by urinary urea excretion at week 64 into the upper tertile and the lower ii tertiles. Nosotros observed a similar weight loss (P = 0.05) when we divided the group on this footing (6.iii ± 7.9 compared with 3.6 ± 4.2 kg; loftier compared with low urinary urea).

TABLE 2

Change from baseline (week 0) in weight and body limerick (by dual-energy X-ray absorptiometry) by reported dietary intake and original diet allocation ¹

	RLP (n = 30)	RHP (due north = 22)	LP (n = 22)	HP (northward = 27)
Weight (kg)	3.4 ± iv.iv	6.5 ± seven.5	4.4 ± 6.1	four.vi ± 5.five
Total fatty (kg)	2.7 ± three.1	iv.7 ± 4.2	3.v ± 3.8	3.v ± 3.viii
Central fat (chiliad)	1.vii ± i.5	2.3 ± 2.	ii.0 ± 1.viii	one.8 ± i.9
Peripheral fat (kg)	0.9 ± ane.viii	two.4 ± ii.1 2	1.5 ± 2.0	one.4 ± 2.one

	RLP (n = xxx)	RHP (n = 22)	LP (n = 22)	HP (north = 27)
Weight (kg)	3.iv ± 4.4	6.5 ± 7.5	4.4 ± 6.i	4.6 ± 5.five
Total fatty (kg)	2.7 ± iii.i	4.seven ± iv.two	3.5 ± 3.eight	iii.v ± 3.8
Central fatty (chiliad)	1.vii ± 1.v	2.3 ± 2.	two.0 ± 1.8	one.8 ± one.nine
Peripheral fat (kg)	0.9 ± 1.8	two.iv ± 2.ane 2	1.5 ± 2.0	ane.4 ± 2.1

1

All values are x̄ ± SD. RLP, reported low protein; RHP, reported high protein; LP, low protein; HP, high protein. Information were analyzed by repeated-measures ANOVA and univariate ANOVA.

ii

Significantly different from the RLP groups, P < 0.05.

TABLE 2

Change from baseline (calendar week 0) in weight and body limerick (by dual-energy Ten-ray absorptiometry) by reported dietary intake and original nutrition allotment ¹

	RLP (north = 30)	RHP (n = 22)	LP (northward = 22)	HP (n = 27)
Weight (kg)	iii.4 ± 4.4	6.5 ± 7.5	4.4 ± 6.1	iv.6 ± 5.v
Total fatty (kg)	2.vii ± 3.1	iv.7 ± iv.2	3.five ± 3.eight	iii.5 ± 3.8
Central fatty (g)	1.7 ± i.five	two.3 ± two.	two.0 ± 1.viii	ane.8 ± 1.nine
Peripheral fat (kg)	0.9 ± 1.8	2.4 ± two.1 ii	1.five ± 2.0	1.4 ± ii.1

	RLP (n = 30)	RHP (n = 22)	LP (n = 22)	HP (n = 27)
Weight (kg)	iii.four ± 4.four	6.5 ± seven.v	4.4 ± 6.1	four.6 ± 5.five
Full fat (kg)	ii.7 ± iii.1	four.7 ± iv.ii	iii.5 ± iii.8	3.five ± 3.eight
Central fatty (g)	1.7 ± 1.v	2.3 ± 2.	ii.0 ± 1.8	i.8 ± one.9
Peripheral fat (kg)	0.9 ± 1.8	2.4 ± two.ane two	1.five ± 2.0	1.4 ± 2.1

1

All values are x̄ ± SD. RLP, reported low poly peptide; RHP, reported high protein; LP, depression poly peptide; HP, high protein. Data were analyzed past repeated-measures ANOVA and univariate ANOVA.

two

Significantly dissimilar from the RLP groups, P < 0.05.

Dietary intake

The nutrition records of the 72 subjects who completed the 64-wk study and provided diet records showed that at that place was poor compliance with the original assigned diet. Free energy intake increased with fourth dimension by ≈24% (P < 0.001), with no difference between original diet groups. By 64 wk, the percent of energy as protein declined with time overall (P < 0.001), with a time-by-diet interaction (eleven% decrease in the HP grouping compared with a 2% increment in the HC group; P < 0.001), and so that there was only a 3.6% difference in energy as protein, which, although notwithstanding statistically pregnant, was non large enough to be of biological significance. Accented protein intake decreased in the HP grouping past 10 thousand/d and increased in the HC group past ≈xx g/d (time-by-diet interaction; P < 0.001). Fat intake increased past twenty g/d (P < 0.001), with no differences between groups, whereas carbohydrate intake increased past 41 g in the HP group and did not change in the HC grouping (time upshot: P = 0.013; time-past-diet interaction: P < 0.001). At 64 wk, the carbohydrate intake in grams was the same in both groups. When the group was divided by reported protein intake every bit described above, energy intake reported in absolute terms and as a per centum energy from protein, absolute fat intake, and the percentage of energy every bit carbohydrate were all statistically different ( Table iii). Although reported protein intake in the RHP group was higher by 19-27 chiliad/d at all fourth dimension points, reported energy intake was only higher at 64 wk. The percentages of free energy from fat and saturated fat were the aforementioned at all time points.

TABLE three

Dietary intake from 3 d of weighed food records at 64 wk past reported dietary intake and past original diet allotment ⁱ

	RLP (northward = 46)	RHP (north = 27)	P	LP (n = 36)	HP (due north = 37)	P
Energy (kJ)	6220 ± 1201 two	6944 ± 1166	<0.05	6391 ± 1312	6583 ± 1157
Protein
(g)	72.2 ± 10.9	109.4 ± 14.6	<0.001	77.0 ± 16.8	94.6 ± 22.9	<0.001
(% of energy)	18.9 ± iii.1	25.vii ± iv.7	<0.001	xix.half dozen ± 3.8	23.two ± 5.5	<0.01
Fat
(g)	46.3 ± 19.7	56.1 ± 19.4	<0.05	48.4 ± 22.8	51.four ± 17.i
(% of energy)	27.0 ± 7.5	29.7 ± viii.half dozen		27.v ± 9.1	28.5 ± vi.eight
Carbohydrate
(g)	189.2 ± 42.0	175.five ± 54.6		189.five ± 49.seven	179.0 ± 44.six
(% of energy)	52.0 ± eight.1	42.7 ± 9.7	<0.001	50.8 ± 10.three	46.4 ± 8.9	0.05
Alcohol	4.two ± 8.5	ii.seven ± 4.0		4.5 ± 8.six	2.9 ± v.5
Saturated fatty (% of energy)	10.1 ± three.four	10.7 ± three.4		ane.viii ± 3.three	1.3 ± 2.5
MUFA (% of energy)	x.0 ± iii.5	12.0 ± iv.iii	<0.05	25.7 ± 8.iv	27.ii ± ten.viii
PUFA (% of free energy)	4.two ± 2.0	3.9 ± 1.4		ten.ane ± four.1	ten.5 ± 2.7
Alcohol (% of energy)	1.8 ± iii.iv	1.1 ± i.6		ten.3 ± 4.2	11.2 ± 3.half-dozen
Fiber (one thousand)	24.four ± seven.9	30.0 ± 11.5	<0.05	4.3 ± 2.ii	3.nine ± one.5
Fe (mg) 3	11.4 ± 2.7	15.4 ± 3.iii	<0.001	11.7 ± 3.3	fourteen.0 ± 3.4	<0.01

	RLP (northward = 46)	RHP (northward = 27)	P	LP (northward = 36)	HP (n = 37)	P
Free energy (kJ)	6220 ± 1201 2	6944 ± 1166	<0.05	6391 ± 1312	6583 ± 1157
Protein
(g)	72.2 ± 10.9	109.4 ± 14.6	<0.001	77.0 ± xvi.8	94.6 ± 22.9	<0.001
(% of energy)	18.ix ± 3.1	25.7 ± four.seven	<0.001	19.six ± 3.eight	23.2 ± 5.five	<0.01
Fat
(g)	46.3 ± 19.7	56.1 ± 19.iv	<0.05	48.4 ± 22.viii	51.4 ± 17.one
(% of free energy)	27.0 ± 7.5	29.seven ± eight.vi		27.5 ± 9.ane	28.five ± 6.8
Saccharide
(g)	189.2 ± 42.0	175.5 ± 54.6		189.v ± 49.vii	179.0 ± 44.6
(% of free energy)	52.0 ± 8.one	42.7 ± ix.7	<0.001	50.eight ± 10.3	46.4 ± 8.9	0.05
Alcohol	four.2 ± eight.5	ii.vii ± 4.0		4.v ± 8.6	2.ix ± 5.5
Saturated fat (% of energy)	10.1 ± 3.iv	10.7 ± three.iv		one.8 ± three.3	1.3 ± ii.v
MUFA (% of energy)	10.0 ± 3.5	12.0 ± 4.3	<0.05	25.7 ± viii.iv	27.ii ± 10.viii
PUFA (% of energy)	four.2 ± two.0	3.ix ± 1.iv		ten.1 ± iv.one	10.5 ± 2.7
Booze (% of energy)	1.8 ± 3.4	one.1 ± 1.6		ten.3 ± 4.two	xi.2 ± iii.vi
Fiber (yard)	24.four ± 7.ix	thirty.0 ± 11.5	<0.05	iv.3 ± 2.2	3.9 ± 1.5
Atomic number 26 (mg) iii	eleven.4 ± 2.7	xv.4 ± 3.iii	<0.001	11.7 ± three.3	14.0 ± three.4	<0.01

1

RLP, reported low protein; RHP, reported high protein; LP, low poly peptide; HP, loftier protein. Between-group differences were analyzed by 1-gene ANOVA.

2

x̄ ± SD (all such values).

3

In that location was a differential effect of nutrition such that iron intake was college in the HP grouping than in the LP group and in the RHP grouping than in the RLP group.

TABLE 3

Dietary intake from 3 d of weighed food records at 64 wk by reported dietary intake and by original diet allocation ^ane

	RLP (n = 46)	RHP (northward = 27)	P	LP (northward = 36)	HP (north = 37)	P
Energy (kJ)	6220 ± 1201 2	6944 ± 1166	<0.05	6391 ± 1312	6583 ± 1157
Protein
(g)	72.two ± 10.9	109.iv ± xiv.6	<0.001	77.0 ± 16.8	94.6 ± 22.nine	<0.001
(% of free energy)	eighteen.nine ± 3.ane	25.vii ± 4.7	<0.001	19.6 ± 3.eight	23.2 ± 5.5	<0.01
Fat
(thousand)	46.3 ± xix.7	56.one ± nineteen.4	<0.05	48.4 ± 22.8	51.4 ± 17.i
(% of energy)	27.0 ± seven.5	29.7 ± 8.half dozen		27.5 ± nine.one	28.v ± half-dozen.8
Carbohydrate
(grand)	189.2 ± 42.0	175.five ± 54.6		189.5 ± 49.seven	179.0 ± 44.vi
(% of energy)	52.0 ± 8.one	42.seven ± 9.7	<0.001	50.8 ± x.3	46.4 ± eight.ix	0.05
Alcohol	4.2 ± eight.5	2.7 ± iv.0		4.five ± 8.six	2.nine ± 5.5
Saturated fatty (% of energy)	10.ane ± 3.4	x.7 ± three.4		1.8 ± 3.3	1.3 ± 2.5
MUFA (% of energy)	ten.0 ± 3.5	12.0 ± four.3	<0.05	25.7 ± 8.4	27.2 ± x.eight
PUFA (% of free energy)	4.two ± 2.0	three.9 ± one.4		10.1 ± four.1	x.5 ± 2.7
Alcohol (% of energy)	1.8 ± 3.4	i.one ± 1.half-dozen		ten.3 ± 4.2	11.two ± 3.6
Fiber (g)	24.4 ± 7.9	30.0 ± xi.5	<0.05	4.3 ± 2.ii	3.ix ± 1.5
Fe (mg) 3	11.4 ± ii.7	15.4 ± iii.3	<0.001	xi.7 ± 3.3	14.0 ± 3.4	<0.01

	RLP (northward = 46)	RHP (n = 27)	P	LP (n = 36)	HP (n = 37)	P
Free energy (kJ)	6220 ± 1201 2	6944 ± 1166	<0.05	6391 ± 1312	6583 ± 1157
Protein
(yard)	72.ii ± x.9	109.4 ± fourteen.6	<0.001	77.0 ± 16.8	94.vi ± 22.9	<0.001
(% of energy)	18.9 ± 3.1	25.7 ± 4.7	<0.001	19.half dozen ± three.viii	23.two ± v.5	<0.01
Fat
(yard)	46.3 ± 19.7	56.1 ± 19.4	<0.05	48.4 ± 22.8	51.iv ± 17.ane
(% of energy)	27.0 ± 7.5	29.7 ± viii.6		27.5 ± 9.ane	28.5 ± six.eight
Carbohydrate
(g)	189.2 ± 42.0	175.5 ± 54.6		189.v ± 49.vii	179.0 ± 44.half-dozen
(% of energy)	52.0 ± eight.1	42.7 ± 9.seven	<0.001	l.viii ± 10.3	46.4 ± 8.9	0.05
Booze	4.2 ± 8.5	ii.7 ± 4.0		4.5 ± 8.6	2.ix ± 5.5
Saturated fatty (% of energy)	x.ane ± 3.4	10.7 ± 3.4		1.8 ± 3.3	one.three ± 2.5
MUFA (% of free energy)	10.0 ± 3.5	12.0 ± 4.3	<0.05	25.seven ± viii.4	27.2 ± 10.8
PUFA (% of energy)	4.2 ± ii.0	3.nine ± 1.4		ten.1 ± 4.1	10.v ± 2.7
Alcohol (% of free energy)	1.viii ± iii.4	i.1 ± 1.six		10.3 ± 4.2	11.two ± 3.6
Fiber (thousand)	24.iv ± 7.ix	30.0 ± 11.5	<0.05	4.3 ± 2.two	3.9 ± ane.5
Atomic number 26 (mg) 3	xi.4 ± 2.seven	15.4 ± 3.3	<0.001	eleven.7 ± iii.iii	14.0 ± 3.iv	<0.01

1

RLP, reported low poly peptide; RHP, reported high poly peptide; LP, low protein; HP, high protein. Between-group differences were analyzed by one-gene ANOVA.

two

x̄ ± SD (all such values).

3

There was a differential upshot of diet such that atomic number 26 intake was higher in the HP group than in the LP group and in the RHP group than in the RLP grouping.

Regression analysis

Considering of this convergence in diets, the whole group was treated equally ane intervention group, and multiple regression was used to examine the relation betwixt reported intake and weight and lipid outcomes. The intake of protein (g) was directly related to weight loss after 64 wk (P < 0.0001), which accounted for 15% of the variance in weight loss. With the adjustment for screening weight and the addition of CRP grouping (which was defined as above or beneath the median level of two.five mg/L, P = 0.026), the total variance deemed for increased to 27%. On univariate assay, protein as a percentage of energy was also related to alter in weight (P = 0.003) and deemed for 10% of the variance. Fasting insulin was unrelated to change in weight at 64 wk. In a regression equation that included both protein and saccharide (g), protein intake remained a highly significant predictor of weight loss (P < 0.01). Full and percentage of energy consumed equally fat or total energy intake were unrelated to weight outcomes.

If weight changes at the end of the report months are expressed every bit a percent, so both protein in grams (r = 0.39, P = 0.001), the percentage of energy as protein (r = 0.36, P = 0.002), and the percentage of energy as carbohydrate (r = −0.24, P = 0.04) were related to changes in weight. The 24-h ratio of urinary urea to creatinine—a marking of the validity of the diet records—was different at 64 wk (38 ± ten compared with 32 ± 7; P ≤ 0.05 for the RHP and RLP groups, respectively). It was correlated with protein intake in grams, both before and after adjustment for baseline values (P = 0.001). A further compliance marker, serum vitamin B-12, was also related to protein intake before and after adjustment for baseline levels (P < 0.001 for both).

Torso composition by DXA

Full body fat at 64 wk, later adjustment for baseline total fat, was related to carbohydrate intake in grams (P = 0.001) and inversely to poly peptide intake in grams (P = 0.052) (r ^two = 0.83 for the whole equation). Abdominal fatty at 64 wk after baseline adjustment was also related to carbohydrate intake in grams (P = 0.001, r ² = 0.55). When dietary variables expressed equally a percentage of energy were entered into the model, the pct of energy equally poly peptide was inversely related to intestinal fat (P = 0.013) and to limb fat (−two.3, P = 0.026), which accounted for 48% and 83% of the variance in these variables, respectively, after adjustment for baseline variables.

The change in total torso fat was related to the reported percentage of free energy as protein at 64 wk (r = 0.43, P = 0.006) and inversely related to the pct of free energy equally carbohydrate (r = −0.47, P = 0.003), but, on multiple regression, only the latter remained pregnant. Changes in total and limb fat were also inversely related to carbohydrate intake in grams (P = 0.001 and P = 0.004; r ² = 0.25 for the whole equation) and protein intake in grams (P = 0.044 and P = 0.017; r ² = 0.23 for the whole equation) on multiple regression. Changes in abdominal fat were related only to saccharide in grams (r = −0.35, P = 0.015).

The ratio of fat to lean tissue at the end of the study was related (r ² = 0.eight), afterwards baseline adjustment, to sugar intake in grams (P = 0.001) and to carbohydrate intake equally a percentage of energy (P = 0.004). The change in the ratio was too inversely related to saccharide intake in grams at 64 wk (r = −0.48, P = 0.001), to carbohydrate intake as a per centum of free energy (P = 0.04), and to total energy intake (P = 0.026; r ⁱⁱ = 0.18 for the whole equation). Greater changes in full weight were associated with greater changes in the ratio of fat to lean tissue (r = 0.46, P < 0.001), ie, in that location was no proportional loss of fat and lean tissue with greater weight loss. Changes in body composition are presented in Tabular array 2.

Glucose, insulin, lipids, and C-reactive poly peptide

Overall, glucose had decreased significantly past the end of the study, by xi.5% (from 6.1 ± 0.half dozen to 5.four ± 0.seven mmol/Fifty; P < 0.0001 for time), with no difference between allocated or reported protein groups ( Table 4). The change in glucose was positively correlated with weight alter (r = 0.293, P < 0.01). Insulin decreased overall by 23% (P < 0.01), with no deviation between allocated or reported protein groups. Baseline BMI and insulin and weight at 64 wk were not related.

TABLE 4

Change from baseline (week 0) in lipids, glucose, and insulin by reported dietary intake and original diet allocation ¹

	RLP (northward = 45)	RHP (n = 26)	LP (due north = 38)	HP (n = forty)
LDL cholesterol mmol/L	−0.55 ± 0.76	−0.54 ± 0.89	−0.48 ± 0.75	−0.57 ± 0.87
Triacylglycerols (mmol/L)	−0.xiv ± 0.68	−0.34 ± 0.86	−0.21 ± 0.89	−0.xix ± 0.52
HDL cholesterol mmol/L	0.31 ± 0.19	0.34 ± 0.25	0.31 ± 0.23	0.36 ± 0.22
Glucose (mmol/L)	−0.58 ± 0.71	−0.76 ± 0.43	−0.57 ± 0.82	−0.70 ± 0.39
Insulin (mIU/Fifty)	−2.54 ± iii.72	−two.79 ± iii.11	−ane.23 ± 6.88	−two.92 ± 3.50

	RLP (north = 45)	RHP (due north = 26)	LP (n = 38)	HP (north = 40)
LDL cholesterol mmol/L	−0.55 ± 0.76	−0.54 ± 0.89	−0.48 ± 0.75	−0.57 ± 0.87
Triacylglycerols (mmol/Fifty)	−0.14 ± 0.68	−0.34 ± 0.86	−0.21 ± 0.89	−0.19 ± 0.52
HDL cholesterol mmol/Fifty	0.31 ± 0.19	0.34 ± 0.25	0.31 ± 0.23	0.36 ± 0.22
Glucose (mmol/Fifty)	−0.58 ± 0.71	−0.76 ± 0.43	−0.57 ± 0.82	−0.70 ± 0.39
Insulin (mIU/L)	−2.54 ± three.72	−ii.79 ± 3.11	−1.23 ± vi.88	−2.92 ± 3.50

1

All values are x̄ ± SD. RLP, reported low protein; RHP, reported high protein; LP, depression protein; HP, high protein. Data were analyzed by using repeated-measures ANOVA and univariate ANOVA. There were no significant differences betwixt the groups.

Tabular array 4

Change from baseline (calendar week 0) in lipids, glucose, and insulin by reported dietary intake and original nutrition resource allotment ⁱ

	RLP (due north = 45)	RHP (n = 26)	LP (n = 38)	HP (n = 40)
LDL cholesterol mmol/L	−0.55 ± 0.76	−0.54 ± 0.89	−0.48 ± 0.75	−0.57 ± 0.87
Triacylglycerols (mmol/L)	−0.14 ± 0.68	−0.34 ± 0.86	−0.21 ± 0.89	−0.nineteen ± 0.52
HDL cholesterol mmol/L	0.31 ± 0.nineteen	0.34 ± 0.25	0.31 ± 0.23	0.36 ± 0.22
Glucose (mmol/L)	−0.58 ± 0.71	−0.76 ± 0.43	−0.57 ± 0.82	−0.lxx ± 0.39
Insulin (mIU/L)	−two.54 ± 3.72	−2.79 ± 3.xi	−i.23 ± 6.88	−two.92 ± 3.fifty

	RLP (n = 45)	RHP (north = 26)	LP (n = 38)	HP (n = xl)
LDL cholesterol mmol/L	−0.55 ± 0.76	−0.54 ± 0.89	−0.48 ± 0.75	−0.57 ± 0.87
Triacylglycerols (mmol/L)	−0.14 ± 0.68	−0.34 ± 0.86	−0.21 ± 0.89	−0.19 ± 0.52
HDL cholesterol mmol/L	0.31 ± 0.xix	0.34 ± 0.25	0.31 ± 0.23	0.36 ± 0.22
Glucose (mmol/L)	−0.58 ± 0.71	−0.76 ± 0.43	−0.57 ± 0.82	−0.seventy ± 0.39
Insulin (mIU/50)	−two.54 ± 3.72	−2.79 ± 3.11	−one.23 ± 6.88	−2.92 ± iii.l

1

All values are x̄ ± SD. RLP, reported low poly peptide; RHP, reported loftier poly peptide; LP, low protein; HP, high protein. Data were analyzed past using repeated-measures ANOVA and univariate ANOVA. There were no significant differences between the groups.

CRP was reduced at the end of the report (from 5.4 ± 4.9 to 4.1 ± 4.ix mg/L; P < 0.05), with no differences between groups and no relation with macronutrient limerick. When those subjects with a CRP > 10 mg/50 were omitted from the analysis, the reduction became stronger: from three.viii ± 2.3 to 2.7 ± ii.1 mg/L (P < 0.001).

At the terminate of the study, triacylglycerol was reduced by 0.21 mmol/50 (P < 0.01), with no difference betwixt groups (Table iv). On multiple regression, the change in triacylglycerol after adjustment for screening triacylglycerol was related to the percentage of poly peptide in the nutrition only (P = 0.005), which accounted for 33% of the variance. On multiple regression, accented triacylglycerol at 64 wk was inversely related, after adjustment for baseline triacylglycerol, to the change in weight over 64 wk (P = 0.001) and to carbohydrate in grams (P = 0.01) at visit one, which accounted for 40% of the variance.

HDL cholesterol was higher at the finish of the study with no upshot of reported poly peptide intake (1.26 ± 0.31 to 1.58 ± 0.twoscore mmol/50; P < 0.001) (Table iv). Change in HDL cholesterol was related to CRP group at 64 wk (r = 0.269 P = 0.018), with an increment of 0.39 mmol/Fifty in those with a CRP concentration below the median (<2.5 mg/Fifty) and an increase of 0.27 mmol/L in those with a CRP concentration above the median. In the grouping with an above-median CRP merely a low triacylglycerol concentration, changes in HDL cholesterol were greater in the HP group (0.29 compared with 0.17 mmol/L; diet-past-triacylglycerol interaction, P = 0.013). Changes in triacylglycerol and HDL were inversely related (r = −0.33, P = 0.003), but the modify in weight was unrelated to the modify in HDL cholesterol.

The change in LDL cholesterol at 64 wk was considerable (−0.55 ± 0.fourscore mmol/50; P < 0.001), with no difference between nutrition groups (Tabular array 4). The alter in LDL cholesterol was significantly greater in the high triacylglycerol group (>1.5 mmol/Fifty at baseline) than in the low triacylglycerol group (<1.5 mmol/L at baseline), with a change of −0.97 mmol/50 compared with −0.39 mmol/L (P = 0.005), ie, a change of thirty% compared with 12%. On multiple regression, the change in LDL cholesterol was related to screening TC and triacylglycerol group, which together deemed for 23% of the variance. There were no dietary predictors of the change in LDL cholesterol change, nor was the amount of weight loss related.

Biomarkers, vitamins, and minerals

Weight loss had a positive effect on both biomarkers of disease and plasma vitamins and minerals, with significant decreases in homocysteine and increases in vitamin B-12 and ferritin. Equally a issue of increased atomic number 26 intake, transferrin decreased and transferrin saturation and hemoglobin increased significantly ( Table five). Serum vitamin B-12 was related to protein as a percentage of energy (P < 0.001) and protein in grams (P < 0.001) at 64 wk afterwards adjustment for baseline levels.

Table v

Alter from baseline (week 0) in vitamin B-12, homocysteine, folate, urinary urea, hemoglobin, iron, ferritin, transferrin, and transferrin saturation past reported dietary intake and original nutrition allocation ¹

	RLP (northward = 45)	RHP (northward = 26)	LP (north = 38)	HP (n = twoscore)
Vitamin B-12 (nmol/L) ii , 3	x.82 ± 54.93	91.81 ± 88.83	23.28 ± 109.67	67.83 ± 83
Homocysteine (μmol/L) 2	−one.33 ± 1.39	−1.72 ± 1.28	−one.43 ± ane.49	−ane.45 ± 1.thirty
Folate (nmol/Fifty) 2	3.01 ± viii.88	1.37 ± nine.twenty	3.81 ± 9.46	1.07 ± vii.99
Urea (mmol/24 h) two , 3	84 ± 120	147 ± 129	83 ± 126	176 ± 119
Hemoglobin (mg/L) four	1.29 ± 5.11	1.38 ± 6.19	0.92 ± iv.96	1.90 ± 6.25
Fe (μmol/50)	1.3 ± 4.29	0.62 ± six.0	0.42 ± 0.51	i.53 ± four.six
Ferritin (μg/Fifty) two , 3	x.16 ± 31.69	25.38 ± 82.66	ix.47 ± 38.20	32.05 ± 72.00
Transferrin (μg/L) 2	−4.42 ± 2.83	−iv.79 ± 4.01	−5.10 ± 3.64	−iv.58 ± 3.82
Transferrin saturation (%) 2	6.2 ± seven.half dozen	5.9 ± 10.ii	5.four ± viii.6	6.six ± 7.9

	RLP (north = 45)	RHP (northward = 26)	LP (north = 38)	HP (north = twoscore)
Vitamin B-12 (nmol/L) two , 3	x.82 ± 54.93	91.81 ± 88.83	23.28 ± 109.67	67.83 ± 83
Homocysteine (μmol/L) 2	−ane.33 ± ane.39	−1.72 ± one.28	−1.43 ± 1.49	−i.45 ± one.30
Folate (nmol/L) two	iii.01 ± 8.88	one.37 ± 9.20	3.81 ± ix.46	1.07 ± 7.99
Urea (mmol/24 h) 2 , 3	84 ± 120	147 ± 129	83 ± 126	176 ± 119
Hemoglobin (mg/L) four	1.29 ± 5.11	i.38 ± 6.19	0.92 ± 4.96	1.90 ± 6.25
Iron (μmol/L)	ane.3 ± 4.29	0.62 ± 6.0	0.42 ± 0.51	1.53 ± four.6
Ferritin (μg/Fifty) ii , 3	x.16 ± 31.69	25.38 ± 82.66	9.47 ± 38.20	32.05 ± 72.00
Transferrin (μg/L) 2	−4.42 ± 2.83	−4.79 ± 4.01	−five.x ± 3.64	−iv.58 ± 3.82
Transferrin saturation (%) ii	6.2 ± 7.6	5.9 ± ten.ii	five.4 ± eight.six	6.half-dozen ± vii.9

i

All values are x̄ ± SD. RLP, reported low protein; RHP, reported high protein; LP, depression protein; HP, high protein. Data were analyzed by using repeated-measures ANOVA and univariate ANOVA.

ii

Main event of fourth dimension: P ≤ 0.01,

three

There was a nutrition-by-fourth dimension interaction such that vitamin B-12 and urinary urea increased more than in both the RHP and HP groups than in the RLP and LP groups (P ≤ 0.01). Ferritin increased more only in the RHP group.

4

Main result of time: P ≤ 0.05.

TABLE 5

Change from baseline (calendar week 0) in vitamin B-12, homocysteine, folate, urinary urea, hemoglobin, iron, ferritin, transferrin, and transferrin saturation past reported dietary intake and original diet allocation ¹

	RLP (n = 45)	RHP (n = 26)	LP (n = 38)	HP (north = 40)
Vitamin B-12 (nmol/50) two , 3	10.82 ± 54.93	91.81 ± 88.83	23.28 ± 109.67	67.83 ± 83
Homocysteine (μmol/L) 2	−1.33 ± 1.39	−1.72 ± 1.28	−1.43 ± one.49	−1.45 ± one.30
Folate (nmol/L) 2	three.01 ± 8.88	one.37 ± 9.20	iii.81 ± 9.46	1.07 ± seven.99
Urea (mmol/24 h) 2 , 3	84 ± 120	147 ± 129	83 ± 126	176 ± 119
Hemoglobin (mg/L) four	1.29 ± 5.xi	1.38 ± vi.19	0.92 ± 4.96	1.90 ± six.25
Fe (μmol/L)	one.3 ± 4.29	0.62 ± 6.0	0.42 ± 0.51	i.53 ± four.6
Ferritin (μg/L) 2 , iii	ten.16 ± 31.69	25.38 ± 82.66	9.47 ± 38.20	32.05 ± 72.00
Transferrin (μg/L) 2	−4.42 ± 2.83	−4.79 ± 4.01	−5.10 ± 3.64	−4.58 ± three.82
Transferrin saturation (%) 2	six.2 ± 7.six	five.9 ± 10.2	5.4 ± 8.half dozen	6.half dozen ± 7.nine

	RLP (due north = 45)	RHP (n = 26)	LP (northward = 38)	HP (north = 40)
Vitamin B-12 (nmol/Fifty) two , 3	10.82 ± 54.93	91.81 ± 88.83	23.28 ± 109.67	67.83 ± 83
Homocysteine (μmol/L) 2	−1.33 ± 1.39	−ane.72 ± 1.28	−1.43 ± one.49	−1.45 ± 1.30
Folate (nmol/50) 2	3.01 ± 8.88	one.37 ± ix.20	3.81 ± ix.46	1.07 ± 7.99
Urea (mmol/24 h) 2 , 3	84 ± 120	147 ± 129	83 ± 126	176 ± 119
Hemoglobin (mg/L) four	1.29 ± 5.11	1.38 ± half-dozen.xix	0.92 ± iv.96	1.xc ± 6.25
Iron (μmol/L)	ane.3 ± iv.29	0.62 ± 6.0	0.42 ± 0.51	1.53 ± four.vi
Ferritin (μg/Fifty) ii , 3	ten.sixteen ± 31.69	25.38 ± 82.66	9.47 ± 38.20	32.05 ± 72.00
Transferrin (μg/L) 2	−4.42 ± 2.83	−4.79 ± 4.01	−v.10 ± 3.64	−iv.58 ± iii.82
Transferrin saturation (%) 2	6.2 ± 7.6	5.9 ± 10.2	5.4 ± 8.6	6.half dozen ± 7.nine

ane

All values are x̄ ± SD. RLP, reported depression poly peptide; RHP, reported high protein; LP, depression protein; HP, high protein. Data were analyzed by using repeated-measures ANOVA and univariate ANOVA.

two

Main outcome of time: P ≤ 0.01,

iii

In that location was a diet-past-time interaction such that vitamin B-12 and urinary urea increased more in both the RHP and HP groups than in the RLP and LP groups (P ≤ 0.01). Ferritin increased more only in the RHP group.

iv

Main consequence of fourth dimension: P ≤ 0.05.

Bone markers and bone mineral density

Overall, decreases in the 24-h urinary bone turnover markers—ratio of dexoypyridinoline to creatinine (from 21.0 ± 8.9 to eighteen.0 ± 6.0 nmol/mmol; P < 0.05) and the ratio of pyridinoline to creatine (from 73.6 ± 33.8 to 64.5 ± 18.6 nmol/mmol; P < 0.05) were observed at the finish of the study, with no differences between diets and no relation with weight loss or any dietary components. Calcium excretion was not different from baseline (week 0) at 64 wk (4.2 ± 2.6 compared with 4.0 ± 2.9 mmol/24 h). The ratio of calcium to creatinine decreased (P < 0.001), with no relation with weight changes, treatment, or reported nutrition. Bone density had not changed significantly by the stop of the study (from 1.03 ± 0.ane to 1.04 ± 1.0 g/cm²; NS).

DISCUSSION

The main finding of the present written report was that weight loss was greater in the study participants who reported consuming a higher-protein diet, both in grams and as a per centum of energy. Overall, there were wellness benefits of sustained weight loss in all participants, irrespective of protein intake; glucose, CRP, LDL cholesterol, and triacylglycerol remained lower than baseline, and HDL cholesterol increased significantly. Sugar intake was a significant predictor of modify in full and intestinal fat and displaced protein intake in multiple regression, except when the macronutrients were expressed in absolute amounts. Clearly, both macronutrients are important, just which is the most significant depends on the variable of interest. Beneficial effects on the ratio of fat to lean tissue appeared to exist greater as weight loss increased. Information technology is of interest that we found protein to be a predictor of weight loss, because Krieger et al (ane) did not in a meta-regression of 87 studies nor did Bravata et al (x) in a meta-assay of 94 studies. Krieger et al (2006) report that lower carbohydrate diets (<42% of energy) were associated with a greater loss of weight of 1.74 kg and a greater loss of fat mass of two.05 kg (i). In 2006, Krieger et al (ane) identified 5 trials of half-dozen mo duration up to September 2005, just no 12-mo trials were reported. Many of the studies included in these meta-analyses were very-low-carbohydrate diets, the results of which may not reverberate the macronutrient composition but rather the drastic way of the dietary restriction. Simply the report by Skov et al (11) used interventions that were similar in style in both groups, and the higher-protein group had 137 one thousand/d less carbohydrate, and protein increased by 0.6 chiliad/kg. This leads to a reduction of ≈20% in reported energy intake and 3.4-kg departure in fat mass. Interesting omissions from the meta-analysis include the studies by Dansinger et al in 2004 (12), Samaha et al in 2003 (thirteen), Seshadri et al in 2004 (14), Foster et al in 2003 (vii), 2 of which were 12-mo studies (Foster et al and Dansinger et al) in which the differences between a very-low-carbohydrate diet and a low-fat diet had narrowed considerably and were not statistically pregnant. Bravata et al (x), in their review, included very short-term trials of but v d or more, and many of the trials were non designed to examine the question of whether macronutrient limerick specifically plays a office in weight loss and only a few were designed examine the effects on cardiovascular disease risk factors. Thus, not surprisingly, the predictors of weight loss in obese persons were caloric content and diet duration and not macronutrient composition. Triacylglycerol concentrations were predicted by carbohydrate amount in grams/d, equally was fasting insulin in healthy subjects.

A lower carbohydrate intake results in either a higher fat or a higher protein intake or both, and very-low-carbohydrate diets well-nigh invariably result in higher saturated fat intakes (seven, fifteen); therefore, information technology is also important to consider overall fatty intake and type of fat when considering the effects of any particular macronutrient on metabolic variables, such as serum lipids, and the study by Bravata et al did not include this data on protein and type of fat in its analysis of lipid changes.

Relatively few long-term studies of the efficacy of higher-protein diets in weight loss of ≥12 mo have been conducted, 2 of which are from our ain group (5, 6). Curt-term weight loss with a college-poly peptide diet is associated with larger reductions in triacylglycerol in women with high triacylglycerol, who also benefited more from this dietary pattern because they lost more fat mass with a higher-protein nutrition (8). Although this relation was not seen at the terminate of this study, the decrease in triacylglycerol was positively related to the proportion of poly peptide in the diet in the whole group, and it may exist that the smaller number remaining in the study did non give usa the power to meet any between-group differences based on the baseline fasting triacylglycerol concentration.

In a study by McAuley et al published in 2006 (4) in a grouping like in size to ours, weight loss from baseline at 12 mo was sustained in all three nutrition groups (high protein, high fat, and high saccharide); no differences in the accented amount of weight loss was observed betwixt groups, although the number of individuals achieving a weight loss of ≥10% was greater in the high-protein and high-fat groups at 12 mo. Poly peptide intake was the same in all 3 groups at this time point, but differences in fat and carbohydrate intake remained. Triacylglycerols improved in the loftier-protein group and HDL cholesterol increased in the high-fatty group only at the stop of the report (4). In some other report, Due et al (2) found that although weight loss was not significantly greater in subjects in the high-poly peptide group (half dozen.ii kg) than in the usual protein group (4.three kg) after 12 mo, the high-poly peptide group had a 10% greater reduction in intraabdominal adipose tissue, opposite our findings After 2 y, both groups tended to maintain their 12-mo weight loss; yet, >50% were lost to follow-upwardly (2). Potential mechanisms for improved weight-loss maintenance with a higher-protein diet may be increased satiety with poly peptide intake, which may be mediated by increased leptin sensitivity (16).

All of the studies mentioned herein analyzed group results on an intention-to-treat basis and not on the basis of reported dietary intake. Clearly, it is of import to know what proportion of persons can achieve a lower-carbohydrate, higher-protein diet, simply it is equally important to know what benefits can be achieved in those who comply with such a diet. This is obscured in an intention-to-treat assay.

Although baseline CRP did not significantly predict weight changes every bit they did in the large Cardiovascular Wellness Study (17), the CRP group contributed to the prediction of weight loss by protein intake. In improver, the CRP group predicted changes in HDL cholesterol and interacted with protein intake in its relation with changes in HDL cholesterol.

Bone turnover decreased at the end of the study, every bit evidenced past the decrease in the ratio of dexoypyridinoline to creatinine and in the ratio of pyridinoline to creatine. This finding contrasts with the increment in bone turnover seen at the end of 12 wk of weight loss (8), which we were unable to explicate. Calcium excretion was not different at the end of the study, but the ratio of calcium to creatinine was reduced and information technology is also unclear why this happened. In contrast with other studies, total-torso bone mineral density was unchanged, which indicates that bone mass was preserved despite weight loss (18, nineteen). Unlike the results of Skov et al (11), who plant that a higher poly peptide intake was associated with a reduced loss of bone mass after 6 mo, we establish no effect of either allocated diet or reported poly peptide intake.

In the nowadays study there were sustained improvements in glucose, insulin, lipid, and CRP concentrations, which confirmed the results of our previous long-term studies (5, 6, twenty). In that location were also improvements in vitamin B-12 and markers of iron status, which suggests that meat protein intake increased overall compared with the prestudy nutrition.

In conclusion, a higher poly peptide intake appears to confer some weight-loss benefit afterward 64 wk. Overall, cardiovascular affliction gamble markers improved, but poly peptide intake per se did not appear to confer whatsoever extra benefit. Weight loss had a positive effect on biomarkers of illness, plasma vitamins, and minerals and markers of bone health.

Nosotros thank BEC Nordin in whose facility the DXA measurements were performed and Anne McGuffin, Kathryn Bastiaans, Rosemary McArthur, Mark Mano, Cherie Keatch, and Candita Sullivan for aid in the performance of this study.

The authors' responsibilities were as follows—PMC and MN: designed the report and contributed to the manuscript; PMC: performed the statistical analysis; JBK: wrote the manuscript, contributed to the statistical analysis, performed the dietary analysis, and was involved in the dietetic counseling. PMC and MN are the authors of the all-time-selling volume The CSIRO Full Wellbeing Nutrition, and JBK was a correspondent to this volume. This volume is based on the 12-wk intervention written report referred to in the nowadays report (8).

FOOTNOTES

2

Supported in part by a Medical Research grant from Meat and Livestock Commonwealth of australia.

REFERENCES

ane

Krieger

JW

,

Sitren

HS

,

Daniels

MJ

,

Langkamp-Henken

B

.

Effects of variation in poly peptide and saccharide intake on body mass and composition during free energy restriction: a meta-regression 1

.

Am J Clin Nutr

2006

;

83

:

260

–

74

.

2

Due

A

,

Toubro

S

,

Skov

AR

,

Astrup

A

.

Effect of normal-fatty diets, either medium or high in protein, on body weight in overweight subjects: a randomised 1-yr trial

.

Int J Obes Relat Metab Disord

2004

;

28

:

1283

–

90

.

3

Skov

AR

,

Toubro

S

,

Ronn

B

,

Holm

Fifty

,

Astrup

A

.

Randomized trial on protein vs carbohydrate in advertizing libitum fat reduced nutrition for the treatment of obesity

.

Int J Obes Relat Metab Disord

1999

;

23

:

528

–

36

.

4

McAuley

KA

,

Smith

KJ

,

Taylor

RW

,

McLay

RT

,

Williams

SM

,

Mann

JI

.

Long-term effects of pop dietary approaches on weight loss and features of insulin resistance

.

Int J Obes (Lond)

2006

;

30

:

342

–

9

.

five

Brinkworth

GD

,

Noakes

M

,

Parker

B

,

Foster

P

,

Clifton

PM

.

Long-term effects of communication to consume a loftier-protein, low-fat diet, rather than a conventional weight-loss diet, in obese adults with type 2 diabetes: one-year follow-upwardly of a randomised trial

.

Diabetologia

2004

;

47

:

1677

–

86

.

half-dozen

Brinkworth

GD

,

Noakes

M

,

Keogh

JB

,

Luscombe

ND

,

Wittert

GA

,

Clifton

PM

.

Long-term effects of a high-protein, low-carbohydrate nutrition on weight command and cardiovascular risk markers in obese hyperinsulinemic subjects

.

Int J Obes Relat Metab Disord

2004

;

28

:

661

–

70

.

7

Foster

GD

,

Wyatt

60 minutes

,

Colina

JO

, et al. .

A randomized trial of a low-sugar diet for obesity

.

Due north Engl J Med

2003

;

348

:

2082

–

90

.

8

Noakes

M

,

Keogh

JB

,

Foster

PR

,

Clifton

PM

.

Issue of an energy-restricted, high-poly peptide, low-fat diet relative to a conventional loftier-carbohydrate, low-fat diet on weight loss, trunk composition, nutritional status, and markers of cardiovascular health in obese women

.

Am J Clin Nutr

2005

;

81

:

1298

–

306

.

9

Friedewald

WT

,

Levy

RI

,

Fredrickson

DS

.

Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge

.

Clin Chem

1972

;

18

:

499

–

502

.

ten

Bravata

DM

,

Sanders

Fifty

,

Huang

J

, et al. .

Efficacy and safety of depression-sugar diets: a systematic review

.

JAMA

2003

;

289

:

1837

–

50

.

11

Skov

AR

,

Haulrik

N

,

Toubro

S

,

Molgaard

C

,

Astrup

A

.

Issue of protein intake on os mineralization during weight loss: a 6-calendar month trial

.

Obes Res

2002

;

10

:

432

–

8

.

12

Dansinger

ML

,

Gleason

JA

,

Griffith

JL

,

Selker

HP

,

Schaefer

EJ

,

Gleason

JA

,

Griffith

JL

,

Selker

HP

,

Schaefer

EJ

.

Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart illness risk reduction: a randomized trial

JAMA

2005

;

293

:

43

–

53

.

xiii

Samaha

FF

,

Iqbal

N

,

Seshadri

P

et al. .

A depression-sugar as compared with a depression-fat diet in severe obesity

.

N Engl J Med

2003

;

348

:

2074

–

81

.

14

Seshadri

P

,

Iqbal

N

,

Stern

L

, et al. .

A randomized study comparing the effects of a low-carbohydrate nutrition and a conventional nutrition on lipoprotein subfractions and C-reactive poly peptide levels in patients with severe obesity

.

Am J Med

2004

;

117

:

398

–

405

.

15

Noakes

M

,

Foster

PR

,

Keogh

JB

,

James

AP

,

Mamo

JC

,

Clifton

PM

.

Comparison of isocaloric very depression carbohydrate/high saturated fatty and high carbohydrate/low saturated fat diets on body limerick and cardiovascular risk

.

Nutr Metab (Lond)

2006

;

3

:

vii

.

16

Weigle

DS

,

Breen

PA

,

Matthys

CC

, et al. .

A high-protein diet induces sustained reductions in ambition, ad libitum caloric intake, and body weight despite compensatory changes in diurnal plasma leptin and ghrelin concentrations

.

Am J Clin Nutr

2005

;

82

:

41

–

viii

.

17

Barzilay

JI

,

Forsberg

C

,

Heckbert

SR

,

Cushman

K

,

Newman

AB

.

The clan of markers of inflammation with weight change in older adults: the Cardiovascular Health Report

.

Int J Obes (Lond)

2006

;

30

:

1362

–

7

.

18

Chao

D

,

Espeland

MA

,

Farmer

D

, et al. .

Effect of voluntary weight loss on bone mineral density in older overweight women

.

J Am Geriatr Soc

2000

;

48

:

753

–

nine

.

19

Pritchard

JE

,

Nowson

CA

,

Wark

JD

.

Bone loss accompanying diet-induced or exercise-induced weight loss: a randomised controlled study

.

Int J Obes Relat Metab Disord

1996

;

twenty

:

513

–

20

.

20

Keogh

JB

,

Luscombe-Marsh

ND

,

Noakes

M

,

Wittert

GA

,

Clifton

PM

.

Long-term weight maintenance and cardiovascular risk factors are not dissimilar post-obit weight loss on saccharide-restricted diets high in either monounsaturated fatty or poly peptide in obese hyperinsulinaemic men and women

.

Br J Nutr

2007

;

97

:

405

–

ten

.

© 2008 American Guild for Clinical Diet

sheehancuse1952.blogspot.com

Source: https://academic.oup.com/ajcn/article/87/1/23/4633298

Share this post