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Long-term effects of a high-protein weight-loss diet^1,2,3

¹ From CSIRO Human Nutrition, Adelaide, Australia

² Supported in part by a Medical Research grant from Meat and Livestock Australia.

³ Address reprint requests and correspondence to PM Clifton, PO Box 10041, Adelaide BC, South Australia, Australia, 5000. E-mail: peter.clifton{at}csiro.au.

	ABSTRACT

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

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

Objective: The objective was to determine the efficacy of a higher protein intake on the maintenance of weight loss after 64 wk of follow-up.

Design: Seventy-nine healthy women with a mean (±SD) age of 49 ± 9 y and a body mass index (in kg/m²) of 32.8 ± 3.5 completed an intensive 12-wk weight-loss program and 52 wk of follow-up to compare the effects on weight-loss maintenance of a high-protein (HP) diet (34% of energy) or a high-carbohydrate (HC) diet (64% of energy).

Results: Mean (±SD) weight loss was not significantly different between groups: (HP: 4.6 ± 5.5 kg; HC: 4.4 ± 6.1 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 10% of the variance. In the upper tertile (88 g protein/d), weight loss was 6.5 ± 7.5 and 3.4 ± 4.4 kg (P = 0.03) in the 2 lower tertiles, respectively. This difference did not translate to a difference in central fat loss between groups. Lipids, glucose, insulin, C-reactive protein, and homocysteine all improved with weight loss and were not significantly different between groups. HDL cholesterol rose by 20%. Higher serum vitamin B-12 was observed in the HP group, and folate concentrations were not significantly different between groups.

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

Key Words: Weight loss • high-protein diet • abdominal fat • body composition

	INTRODUCTION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Numerous short-term studies and a recent meta-regression of these studies have shown that higher-protein, reduced-carbohydrate weight-loss diets are associated with greater fat loss and reduced lean mass loss compared with diets higher in carbohydrate or lower in protein (1). However, few studies have been longer than 6 mo. In a follow-up to an intensive 6-mo weight-loss trial, Due et al (2, 3) 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 (–6.6 kg) with a higher-protein diet than with a high-carbohydrate diet (–4.4 kg) or a high-fat diet (–5.5 kg); however, the differences between the diets were relatively small.

In contrast, we previously reported long-term data for individuals with type 2 diabetes and obese subjects with hyperinsulinemia; no differences in weight loss were observed between subjects assigned to a higher-protein diet and those assigned to a higher-carbohydrate diet (5, 6). Similarly to our long-term results, the 12-mo results from the Atkins diet (a low-carbohydrate, high-protein, high-fat diet) studies showed no significant difference between the diet groups despite significant differences being seen at 6 mo (7).

Thus, there is limited evidence in the literature that a higher protein intake during weight loss is a significant factor for long-term success. In this article we report on the results of our 1-y follow-up of an intensive 12-wk weight-loss trial (8). The aim of the study was to determine the efficacy of a higher-protein dietary pattern on maintenance of weight loss, effects on cardiovascular disease risk factors, and markers of bone health after 64 wk.

	SUBJECTS AND METHODS

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Subjects
The participants, study design, and dietary interventions were described previously (8). Briefly, women were recruited by public advertisement and screened by questionnaire. The inclusion criteria were as follows: women aged 20–65 y, body mass index (BMI; in kg/m²) between 27 and 40, and no history of renal or liver disease or type 1 or type 2 diabetes. One hundred nineteen women met the selection criteria and were randomly assigned to treatment. 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 Organization, Human Nutrition, Adelaide, Australia. Seventy-nine women completed the 64-wk study. Forty women withdrew from the study before completion, 17 on the high-protein (HP) diet and 23 on the high-carbohydrate (HC) diet (Figure 1). Subject characteristics at baseline are presented in Table 1.

View larger version (13K): [in this window] [in a new window]   FIGURE 1.. Schematic representation of randomization.

Body weight and composition
Subjects were weighed (model AMZ14; Mercury Digital Scales, Tokyo, Japan) in light clothing and without shoes after an overnight fast at each visit. Height was measured with a stadiometer (Seca, Hamburg, Germany) at week 0. Body mass index (BMI) was calculated by weight (kg)/height² (m). Dual-energy X-ray absorptiometry (DXA) (Norland Medical Systems, Fort Atkinson, WI) was performed at weeks 0 and 64 (Royal Adelaide Hospital, Adelaide, Australia).

Urinalysis
Collection of total 24-h urine output commenced at 0700 (not including the first morning void) on the day before the subjects attended the research clinic and ended at 0700 on the day of clinic attendance (including first morning void) at weeks 0 and 64. Urine samples were measured at the Institute of Medical and Veterinary Science (IMVS), (Adelaide, South Australia) for creatinine, urea, calcium, phosphate, and sodium with the use of proprietary techniques on an Olympus AU5400 chemistry analyzer (Tokyo, Japan). Deoxypyridinoline and pyridinoline were measured by using HPLC and expressed per mmol creatinine.

Biochemistry
Fasting blood samples were collected at baseline and the end of the study in tubes containing either no additives for lipids, insulin, C-reactive protein (CRP), or sodium fluoride/EDTA for glucose measurements. Plasma or serum was isolated by centrifugation at 2000 x 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, iron, 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 protein in the original study was 110 g/d. We defined compliance at 80% of this original prescription and found that this was the top tertile of reported protein 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 lowest compliance point). Both absolute levels at 64 wk adjusted for baseline values and changes over 64 wk were modeled. Significance was set at P < 0.05. Values are reported as means ± SDs unless otherwise stated.

	RESULTS

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Weight
Overall weight loss in the 2 allocated groups was not significantly different: 4.6 ± 5.5 and 4.4 ± 6.1 kg in the HP and HC groups, respectively. Ratios of urinary urea to creatinine at 64 wk were not significantly different, which suggests poor compliance with the allocated diets. However, when actual protein intake, calculated from dietary records at 64 wk returned by 72 participants, was used as a criterion, 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-protein group (RLP): 6.5 ± 7.5 kg (n = 27) compared with 3.4 ± 4.4 kg (n = 45) (Table 2). To confirm these results we divided the group by urinary urea excretion at week 64 into the upper tertile and the lower 2 tertiles. We observed a similar weight loss (P = 0.05) when we divided the group on this basis (6.3 ± 7.9 compared with 3.6 ± 4.2 kg; high compared with low urinary urea).

Table 3

If weight changes at the end of the study months are expressed as a percentage, then 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 marker of the validity of the diet records—was different at 64 wk (38 ± 10 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).

Body composition by DXA
Total body fat at 64 wk, after adjustment for baseline total fat, was related to carbohydrate intake in grams (P = 0.001) and inversely to protein intake in grams (P = 0.052) (r² = 0.83 for the whole equation). Abdominal fat at 64 wk after baseline adjustment was also related to carbohydrate intake in grams (P = 0.001, r² = 0.55). When dietary variables expressed as a percentage of energy were entered into the model, the percentage of energy as protein was inversely related to abdominal fat (P = 0.013) and to limb fat (–2.3, 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 body fat was related to the reported percentage of energy as protein at 64 wk (r = 0.43, P = 0.006) and inversely related to the percentage of energy as carbohydrate (r = –0.47, P = 0.003), but, on multiple regression, only the latter remained significant. Changes in total and limb fat were also inversely related to carbohydrate intake in grams (P = 0.001 and P = 0.004; r² = 0.25 for the whole equation) and protein intake in grams (P = 0.044 and P = 0.017; r² = 0.23 for the whole equation) on multiple regression. Changes in abdominal fat were related only to carbohydrate in grams (r = –0.35, P = 0.015).

The ratio of fat to lean tissue at the end of the study was related (r² = 0.8), after baseline adjustment, to carbohydrate intake in grams (P = 0.001) and to carbohydrate intake as a percentage of energy (P = 0.004). The change in the ratio was also inversely related to carbohydrate intake in grams at 64 wk (r = –0.48, P = 0.001), to carbohydrate intake as a percentage of energy (P = 0.04), and to total energy intake (P = 0.026; r² = 0.18 for the whole equation). Greater changes in total weight were associated with greater changes in the ratio of fat to lean tissue (r = 0.46, P < 0.001), ie, there was no proportional loss of fat and lean tissue with greater weight loss. Changes in body composition are presented in Table 2.

Glucose, insulin, lipids, and C-reactive protein
Overall, glucose had decreased significantly by the end of the study, by 11.5% (from 6.1 ± 0.6 to 5.4 ± 0.7 mmol/L; 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 change (r = 0.293, P < 0.01). Insulin decreased overall by 23% (P < 0.01), with no difference between allocated or reported protein groups. Baseline BMI and insulin and weight at 64 wk were not related.

At the end of the study, triacylglycerol was reduced by 0.21 mmol/L (P < 0.01), with no difference between groups (Table 4). On multiple regression, the change in triacylglycerol after adjustment for screening triacylglycerol was related to the percentage of protein in the diet only (P = 0.005), which accounted for 33% of the variance. On multiple regression, absolute 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 1, which accounted for 40% of the variance.

HDL cholesterol was higher at the end of the study with no effect of reported protein intake (1.26 ± 0.31 to 1.58 ± 0.40 mmol/L; P < 0.001) (Table 4). Change in HDL cholesterol was related to CRP group at 64 wk (r = 0.269 P = 0.018), with an increase of 0.39 mmol/L in those with a CRP concentration below the median (<2.5 mg/L) and an increase of 0.27 mmol/L in those with a CRP concentration above the median. In the group with an above-median CRP but a low triacylglycerol concentration, changes in HDL cholesterol were greater in the HP group (0.29 compared with 0.17 mmol/L; diet-by-triacylglycerol interaction, P = 0.013). Changes in triacylglycerol and HDL were inversely related (r = –0.33, P = 0.003), but the change in weight was unrelated to the change in HDL cholesterol.

The change in LDL cholesterol at 64 wk was considerable (–0.55 ± 0.80 mmol/L; P < 0.001), with no difference between diet groups (Table 4). The change in LDL cholesterol was significantly greater in the high triacylglycerol group (>1.5 mmol/L at baseline) than in the low triacylglycerol group (<1.5 mmol/L at baseline), with a change of –0.97 mmol/L compared with –0.39 mmol/L (P = 0.005), ie, a change of 30% compared with 12%. On multiple regression, the change in LDL cholesterol was related to screening TC and triacylglycerol group, which together accounted 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. As a consequence of increased iron intake, transferrin decreased and transferrin saturation and hemoglobin increased significantly (Table 5). 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 after adjustment for baseline levels.

	DISCUSSION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
The main finding of the present study was that weight loss was greater in the study participants who reported consuming a higher-protein diet, both in grams and as a percentage of energy. Overall, there were health 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. Carbohydrate intake was a significant predictor of change in total and abdominal fat and displaced protein intake in multiple regression, except when the macronutrients were expressed in absolute amounts. Clearly, both macronutrients are important, but which is the most significant depends on the variable of interest. Beneficial effects on the ratio of fat to lean tissue appeared to be greater as weight loss increased. It is of interest that we found protein to be a predictor of weight loss, because Krieger et al (1) did not in a meta-regression of 87 studies nor did Bravata et al (10) in a meta-analysis 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 2.05 kg (1). In 2006, Krieger et al (1) identified 5 trials of 6 mo duration up to September 2005, but 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 reflect the macronutrient composition but rather the drastic style of the dietary restriction. Only the study by Skov et al (11) used interventions that were similar in style in both groups, and the higher-protein group had 137 g/d less carbohydrate, and protein increased by 0.6 g/kg. This leads to a reduction of 20% in reported energy intake and 3.4-kg difference in fat mass. Interesting omissions from the meta-analysis include the studies by Dansinger et al in 2004 (12), Samaha et al in 2003 (13), Seshadri et al in 2004 (14), Foster et al in 2003 (7), 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 significant. Bravata et al (10), in their review, included very short-term trials of only 5 d or more, and many of the trials were not designed to examine the question of whether macronutrient composition specifically plays a role 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, as 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 almost invariably result in higher saturated fat intakes (7, 15); therefore, it is also important to consider overall fat 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 information 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 own group (5, 6). Short-term weight loss with a higher-protein 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 diet (8). Although this relation was not seen at the end of this study, the decrease in triacylglycerol was positively related to the proportion of protein in the diet in the whole group, and it may be that the smaller number remaining in the study did not give us the power to see any between-group differences based on the baseline fasting triacylglycerol concentration.

In a study by McAuley et al published in 2006 (4) in a group similar in size to ours, weight loss from baseline at 12 mo was sustained in all 3 diet groups (high protein, high fat, and high carbohydrate); no differences in the absolute amount of weight loss was observed between 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. Protein intake was the same in all 3 groups at this time point, but differences in fat and carbohydrate intake remained. Triacylglycerols improved in the high-protein group and HDL cholesterol increased in the high-fat group only at the end of the study (4). In another study, Due et al (2) found that although weight loss was not significantly greater in subjects in the high-protein group (6.2 kg) than in the usual protein group (4.3 kg) after 12 mo, the high-protein 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; however, >50% were lost to follow-up (2). Potential mechanisms for improved weight-loss maintenance with a higher-protein diet may be increased satiety with protein 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 important to know what proportion of persons can achieve a lower-carbohydrate, higher-protein diet, but 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 analysis.

Although baseline CRP did not significantly predict weight changes as they did in the large Cardiovascular Health Study (17), the CRP group contributed to the prediction of weight loss by protein intake. In addition, 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, as evidenced by the decrease in the ratio of dexoypyridinoline to creatinine and in the ratio of pyridinoline to creatine. This finding contrasts with the increase in bone turnover seen at the end of 12 wk of weight loss (8), which we were unable to explain. Calcium excretion was not different at the end of the study, but the ratio of calcium to creatinine was reduced and it is also unclear why this happened. In contrast with other studies, total-body bone mineral density was unchanged, which indicates that bone mass was preserved despite weight loss (18, 19). Unlike the results of Skov et al (11), who found that a higher protein intake was associated with a reduced loss of bone mass after 6 mo, we found no effect of either allocated diet or reported protein intake.

In the present study there were sustained improvements in glucose, insulin, lipid, and CRP concentrations, which confirmed the results of our previous long-term studies (5, 6, 20). There were also improvements in vitamin B-12 and markers of iron status, which suggests that meat protein intake increased overall compared with the prestudy diet.

In conclusion, a higher protein intake appears to confer some weight-loss benefit after 64 wk. Overall, cardiovascular disease risk markers improved, but protein intake per se did not appear to confer any extra benefit. Weight loss had a positive effect on biomarkers of disease, plasma vitamins, and minerals and markers of bone health.

	ACKNOWLEDGMENTS

 
We 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 assistance in the performance of this study.

The authors' responsibilities were as follows—PMC and MN: designed the study 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 best-selling book The CSIRO Total Wellbeing Diet, and JBK was a contributor to this book. This book is based on the 12-wk intervention study referred to in the present study (8).

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