Paper | Published:

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

International Journal of Obesity volume 28, pages 661670 (2004) | Download Citation


  • A Corrigendum to this article was published on 16 August 2004


OBJECTIVE: To compare the long-term compliance and effects of two low-fat diets differing in carbohydrate to protein ratio on body composition and biomarkers of cardiovascular disease risk in obese subjects with hyperinsulinemia.

DESIGN: Outpatient, parallel, clinical intervention study of two groups of subjects randomly assigned to either a standard protein (SP; 15% protein, 55% carbohydrate) or high-protein (HP; 30% protein, 40% carbohydrate) diet, during 12 weeks of energy restriction (6.5 MJ/day) and 4 weeks of energy balance (8.3 MJ/day). Subsequently, subjects were asked to maintain the same dietary pattern for the succeeding 52 weeks with minimal professional support.

SUBJECTS: A total of 58 obese, nondietetic subjects with hyperinsulinemia (13 males/45 females, mean age 50.2 y, mean body mass index (BMI) 34.0 kg/m2, mean fasting insulin 17.8 mU/l) participated in the study.

MEASUREMENTS: Body composition, blood pressure, blood lipids, fasting glucose, insulin, CRP and sICAM-1 were measured at baseline and at weeks 16 and 68. Urinary urea/creatinine ratio was measured at baseline, week 16 and at 3 monthly intervals thereafter.

RESULTS: In total, 43 subjects completed the study with similar dropouts in each group (P=0.76). At week 68, there was net weight loss (SP −2.9±3.6%, HP −4.1±5.8%; P<0.01) due entirely to fat loss (P<0.001) with no diet effect. Both diets significantly increased HDL cholesterol concentrations (P<0.001) and decreased fasting insulin, insulin resistance, sICAM-1 and CRP levels (P<0.05). Protein intake was significantly greater in HP during the initial 16 weeks (P<0.001), but decreased in HP and increased in SP during 52-week follow-up, with no difference between groups at week 68, indicating poor long-term dietary adherence behaviour to both dietary patterns.

CONCLUSION: Without active ongoing dietary advice, adherence to dietary intervention is poor. Nonetheless, both dietary patterns achieved net weight loss and improvements in cardiovascular risk factors.


Overweight and obesity are associated with significant risk factors for coronary heart disease, such as dyslipidaemia, insulin resistance, type II diabetes and hypertension.1,2 The prevalence of obesity is increasing at a rapid rate in industrialised countries,3,4 and has become a major public health problem, with significant implications for morbidity, mortality4,5 and socioeconomic cost.6 Consequently, there is a critical need for effective weight reduction and maintenance strategies to combat this growing epidemic.

Despite considerable attempts by obese individuals to lose weight and maintain weight loss,7 there is currently no scientific consensus on the optimal dietary methods for weight loss and prevention of weight regain.8,9 Although most physicians and dietitians recommend conventional methods that emphasise a high-carbohydrate, low-fat intake, dietary strategies of this nature are associated with only modest weight loss and poor long-term compliance.4,10,11 Hence, there has been a plethora of nonscientifically based weight-loss and maintenance strategies published in the lay press.

Several short-term, randomised, controlled studies have shown that the substitution of some dietary carbohydrate for protein in low-fat diets (≤30%) enhances weight loss,12,13 and is associated with favourable changes in body composition through a preferential loss in body fat and/or the sparing of lean tissue13,14,15 as well as potentially exerting beneficial effects on specific risk factors for cardiovascular disease (CVD) such as insulin sensitivity,3,12,14,16 glycemic control17 and the blood lipid profile.14,15,18 However, although this evidence suggests these diets may offer modest short-term metabolic advantages, to date, no known long-term clinical trials beyond 6 months have been conducted, describing their overall long-term efficacy and safety, compared to traditional, conventional low-fat, high-carbohydrate weight-loss diets. Therefore, the purpose of the present study was to evaluate the long-term effects and compliance of two low-fat diets differing in carbohydrate/protein ratio on weight loss, body composition and risk factors for coronary heart disease in hyperinsulinemic individuals, in a 68 week, outpatient trial.



A total of 66 obese, hyperinsulinemic subjects were recruited to participate in the study via public advertisement. Prior to the study commencement, all subjects completed a health screening questionnaire. Subjects were included if they were aged between 20 and 65 y, had a fasting serum insulin concentration greater than 12 mU/l, and a body mass index between 27 and 43 kg/m2. Potential subjects were excluded from participation if they had type-II diabetes, a history of clinically significant illness including liver, unstable cardiovascular, respiratory, gastrointestinal disease, malignancy, or were pregnant or lactating. The protocol and the potential risks and benefits of the study were fully explained to each subject before they provided written informed consent. All experimental procedures were approved by the Human Ethics Committee of the CSIRO (Commonwealth Scientific and Industrial Research Organisation).

Of the subjects, a total of 43 completed the entire 68-week study protocol (Table 1). Six subjects withdrew before study commencement due to work or family commitments. No subject dropped out during the course of the study due to symptomatic adverse effects; one became pregnant and another underwent major cardiac surgery during the study; while a further 15 subjects discontinued participation in the program and did not attend the final clinic visit at week 68. Subjects on antihypertensive or lipid-lowering medication were asked to maintain all medications at prestudy doses. Most subjects were sedentary at prior to study commencement and no specific guidelines regarding physical activity was provided.

Table 1: Comparison of baseline physical characteristics between subjects who completed the study and those who dropped out of the study

Experimental protocol

Subjects were matched on the basis of age, gender, BMI and fasting serum insulin concentrations at screening and then randomly allocated to consumption of either a standard protein (SP) or high-protein (HP) diet. The 68-week study was conducted on an outpatient basis and consisted of three periods, a 12-week energy restriction period (6 500 kJ/day or 30% caloric restriction) followed by a 4-week period at energy balance with the same macronutrient composition. The data from these periods have been previously reported.17 After 16 weeks, subjects were asked to maintain a similar dietary pattern as best as they could for the next 52 weeks (12-month follow-up period). Every effort was made to encourage subjects to remain in the study and attend follow-up clinic visits at 3-monthly intervals in an attempt to gain a greater understanding of the long-term adherence and maintenance of these dietary strategies.

At weeks 0, 16 and 68, subjects visited the Royal Adelaide Hospital for a whole-body dual energy X-ray absorptiometry scan to determine body composition. On 2 consecutive days at weeks 0 and 16 and on a single day at week 68 after an overnight fast, subjects attended the CSIRO clinic, during which body mass, height and resting blood pressure were measured prior to a venous blood sample being drawn for determination of blood lipids, glucose, insulin, C-reactive protein, soluble intracellular adhesion molecule-1 (sICAM-1), and creatinine concentrations. Subjects also attended the clinic at weeks 29, 42 and 55 for a body weight measurement only. A 24-h urine sample was collected on an outpatient basis at baseline, week 16 and at 3 monthly intervals thereafter for the subsequent assessment of the urea/creatinine ratio to determine dietary compliance. All testing was conducted at the same time of day to avoid circadian effects.


Subjects in both groups met with a qualified dietitian prior to the study to review the components of the relevant diet, and then every 2 weeks thereafter up to week 16 for 15–30 min to discuss dietary issues. During the 12-week energy restriction period, the prescribed HP diet consisted of 30% of energy from protein (110 g/day), 40% of energy from carbohydrate (CHO; 140 g/day) and 30% from fat (50 g/day), while the SP diet consisted of 15% of energy from protein (60 g/day), 55% of energy from CHO (200 g/day) and 30% from fat (50 g/day). During the succeeding 4-week energy balance period, caloric intake was increased by approximately 30% with a further 7 g of protein in the SP diet and 21 g in the HP diet. Further details and differences between the two diets during these periods have been previously described.17 For the 12-month follow-up period, subjects were asked to continue the same dietary pattern followed during the previous periods of the study; but were not provided with any foodstuffs or professional dietary counselling.

Group training was provided in the use of scales and keeping food records. Throughout the 12-week energy restriction and 4-week energy balance periods, each subject completed weighed daily diet checklists of all foods and was assessed by the same dietician at 2-week intervals. Three consecutive days (one weekend and 2 weekdays) of the checklist from each 2-week period were analysed using ‘Diet/1 Nutrient Calculation’ software (Xyris Software 1998, Highgate Hill, Australia). This program had no missing values for the nutrients of interest and as the diet was very prescriptive unusual foods were infrequently encountered. Recipes were entered as proportions of the original ingredients. The database had been extensively modified by our group to add new foods and recipes. During the 12-month follow-up period, subjects completed a food frequency questionnaire at 3 monthly intervals, which was subsequently analysed for nutrient composition.19

Height, body mass and body composition

Body height was measured to the nearest 0.1 cm using a stadiometer (SECA, Hamburg, Germany) with subjects barefoot in the free-standing position. Body weight was measured with subjects wearing light clothing with no shoes to the nearest 0.05 kg, using calibrated electronic digital scales (Mercury, AMZ 14, Tokyo, Japan). Body composition (fat mass of soft tissue and lean mass of soft tissue) was assessed by whole-body dual X-ray absorptiometry (DEXA; Norland densitometer XR36; Norland Medical Systems, Fort Atkinson, WI, USA); with a coefficient of variation of 2.3±0.9% for total fat mass and 2.1±0.4% for total lean mass.

Blood pressure

Resting blood pressure was measured by automated oscillometry (Dinamap™, 845XT/XT-IEC, Tampa, FL, USA), with subjects in a seated position.

Biochemical analysis

Fasting blood samples were collected in tubes containing either no additives for lipids, insulin, C-reactive protein, sICAM-1 and creatinine, or sodium fluoride/EDTA for glucose measurements. Plasma or serum was isolated by centrifugation at 2000 g for 10 min at 5°C (Beckman GS-6R centrifuge; CA, USA) and frozen at −20°C. Urine samples to assess dietary compliance and creatinine clearance were frozen at −80°C in polyethylene tubes. Biochemical assays were performed in a single assay at the completion of the study. Plasma glucose and serum total cholesterol and triacylglycerol concentrations were measured on a Cobas-Bio centrifugal analyser (Roche Diagnostica, Basel, Switzerland) by using enzymatic kits (Hoffmann-La Roche Diagnostica, Basel, Switzerland) and control sera. Plasma HDL-cholesterol concentrations were measured using a Cobas-Bio analyser after precipitation of LDL-C and VLDL-C with polyethylene glycol 6000 solution. A modified Friedewald equation was used to calculate LDL-C.20 Insulin was determined in duplicate using a radioimmunoassay kit (Pharmacia & Upjohn Diagnostics AB, Uppsala, Sweden). The homeostatic model assessment (HOMA) was used as a surrogate measure of insulin sensitivity based on fasting glucose and insulin concentrations,21 calculated as ((fasting serum insulin level (μU/l) × fasting glucose level (mg/dl))/22.5). C-reactive protein was measured using an enzymatic kit (Roche, Indianapolis, IN, USA), on a Hitachi autoanalyser (Roche, Indianapolis, IN, USA) and sICAM-1 samples were analysed by ELISA (immunoKontact, Switzerland). Plasma and urinary urea and creatinine were measured in one run on a Hitachi autoanalyser (Roche, Indianapolis, IN, USA) at the end of the study. Creatinine clearance was calculated (urine creatinine (μmol/l) × urine volume (ml))/(plasma creatinine (μmol/l) × min) and changes were compared after normalisation for lean body mass.22,23

Statistical analysis

Participants who failed to complete the entire 68-week study period were excluded from the final analysis and reported as dropouts. The final results are taken from all 43 subjects who remained in the study and attended the final clinic visit at week 68 (SP=22, HP=21). An intention-to-treat analysis in this group of 43, with missing data for interim time points (ie weeks 29, 42 and 55) replaced by last observation carried forward, was applied to the measure of body weight.

Two sets of analyses were conducted. Univariate analysis of variance (ANOVA) with repeated measures was used to determine the effects of the treatment, time of measurement and their interactions on the dependant measures. The between subject factors was the diet (ie, HP or SP) and gender with the time of measurement of the dependent variable as the within-subject factor. Since a primary objective of the current study was to determine the overall long-term effects of the dietary intervention for the entire study period, a separate analysis was conducted using time points collected at weeks 0 and 68 only to examine changes from baseline to the end of the study. Where ANOVA showed a statistically significant time effect, pairwise comparisons using a Bonferroni correction factor for multiple comparisons was performed. In the case of a significant diet by time effect, a comparison of diets at each time point and paired t-tests were used to compare means within each group. Independent Student's t-tests were used to compare group means at baseline, end points and for changes in dependent variables between diets. The rates of dropouts and difference in characteristics between treatment groups were compared by chi-square (χ2) tests. Results have been presented as percentage changes to facilitate clinical interpretation, although all analyses involved absolute values and were performed with SPSS for Windows 11.5.0 (SPSS Inc., Chicago, IL, USA). Statistical significance was set at an α level of P<0.05. Unless otherwise specified, all data values cited in the text, and shown in tables and figures, represent means±standard error of the mean (s.e.m.).


Subject attrition, diet composition and compliance

Overall, a total of 43 subjects (74%) completed the 68-week study protocol. There were no significant differences between the two dietary groups for the percentage of subjects who had dropped out of the study (SP 24.1%, HP 27.6%; P=0.76) and their physical characteristics (Table 1).

Energy intake did not differ between the diet groups during either the 12-week energy restriction, 4-week energy balance or the 12-month follow-up phase (Table 2). As prescribed, the protein intake was higher and the carbohydrate intake was lower with the HP diet compared to the SP diet during the energy restrictive and energy balance periods (P<0.001). However, during the 12-month follow-up there was a significant time by diet interaction for these macronutrient variables (P<0.001) such that protein intake increased significantly with the SP diet and decreased with the HP diet, while carbohydrate intake increased with the SP diet but remained unchanged in the HP group (Table 2). Consequently, there was no difference between the two diet groups for either carbohydrate or protein intake after 3 and 6 months of follow-up, respectively. Dietary fat intake did not differ between the diets throughout the entire study period. Dietary cholesterol was higher and dietary fibre lower with the HP diet than with the SP diet during the energy restriction and energy balance phases. During the 12-month follow-up there was a significant time by diet effect (P<0.001), whereby cholesterol intake increased and fibre intake decreased to a greater extent with the SP diet than with the HP diet such that there was no difference in either cholesterol or fibre intake between the diet groups during the 12 month follow-up.

Table 2: Nutrient composition of the intervention diets throughout the study

The effects of the diets on the urinary urea/creatinine ratio are presented in Figure 1. For the subjects who completed the study, urinary urea/creatinine ratio was not different between diets at week 0 (P=0.48) and increased by week 16 in HP (P=0.001). During the 12-month follow-up there was a time by diet interaction (P=0.001), whereby the urinary urea/creatinine ratio increased in SP and decreased in HP, such that there was no difference between the diets during this period (P=0.62), indicating poor long-term dietary adherence for both dietary patterns.

Figure 1
Figure 1

Urinary urea/creatinine ratio prior to and after 16 weeks of energy control (involving active dietary counselling) and during a 12-month follow-up during which subjects were not provided with active dietary counselling advice on a conventional protein diet (black circles) or high-protein diet (white circles). Values are means±s.e.m. *P=0.001 significantly different from baseline, P=0.02 significantly different between groups, P<0.05 significant change from week 16. NB, not all subjects provided complete 24-h urine collections at week 29 (SP, N=20; HP, N=20), week 42 (SP, N=20; HP, N=19), week 55 (SP, N=19; HP, N=19).

Body weight and body composition

The change in body weight over the duration of the study is presented in Figure 2. After 12 weeks of energy restriction and 4 weeks of energy balance, the mean weight loss was 8.5±0.6 kg, but the decrease in weight was not affected by the diet composition (SP −9.1±0.7%, HP −8.7±0.7%; P=0.44). At week 68, there was a significant regain in weight, but weight remained significantly lower (3.5%) than baseline, with no effect of dietary composition (SP −2.9±0.8%, HP −4.1±1.3%; P=0.44).

Figure 2
Figure 2

Body weight during 12 weeks of energy restriction and 4 weeks of energy balance, and 12 months of follow-up on a conventional protein diet (black circles) or high-protein diet (white circles). Values are means±s.e.m. *P<0.001 significantly lower than baseline, P<0.001 significant increase in weight from week 16–68. There was no effect of diet or a time by diet interaction. NB, not all subjects attended interim clinic visits at week 29 (SP, N=20; HP, N=21), week 42 (SP, N=21; HP, N=19), week 55 (SP, N=19; HP, N=19). Analysis was conducted on an intention to treat basis in which values from previous time point were carried forward in the case of a missing value.

The effects of the diets on lean body and fat mass are shown in Table 3. For all subjects, fat mass and lean body mass were significantly reduced with weight loss at week 16. During the 12-month follow-up, lean mass returned to baseline levels, and although fat mass also increased, it remained significantly lower than baseline at week 68. There was no effect of dietary composition on either tissue compartment.

Table 3: Lean body mass, fat mass, bone mass, blood pressure, C-reactive protein, soluble intracellular adhesion molecule-1, fasting plasma glucose, insulin, insulin sensitivity and creatinine clearance prior to and after 12 weeks of energy restriction, 4 weeks of energy balance, and 12 months of follow-up on a conventional protein or high-protein diet

For bone mineral content there was a significant time by gender effect (P=0.001), such that in males, bone mineral content was higher than baseline at week 68 (P=0.01), whereas no significant change was evident in the females. There was no effect of diet or any diet by gender interaction on bone mineral content (Table 3).

Blood pressure

Systolic blood pressure did not change significantly in either group during the study (Table 3). At baseline, diastolic blood pressure was significantly higher in the male compared to female subjects. For all subjects, diastolic BP did not change significantly during the first 16 weeks of the study (P=0.10); however during the 12 month follow-up phase there was a significant time by gender interaction (P=0.03), whereby diastolic BP fell significantly in the male subjects, but did not change in female subjects, such that there were no differences between genders at week 68 (Table 3). There was no effect of diet observed for changes in diastolic BP.

Fasting glucose, insulin, HOMA and inflammatory markers

Fasting glucose concentrations did not change significantly in either group during the study (Table 3). At week 68, CRP, sICAM-1, fasting insulin concentrations and HOMA had decreased significantly from baseline by 14–30%, but this was not affected by dietary composition (Table 3).

Serum lipids

Fasting serum triacylglycerol, total cholesterol and LDL cholesterol concentrations were reduced by both dietary interventions during the first 16 weeks of the study, but increased during the 12 month follow-up, such that there was no difference compared to baseline at week 68 (Table 4). Fasting serum HDL concentrations had increased by 15% in both diet groups at week 68. There was no significant effect of diet or gender for changes in any of the blood lipid variables during the study.

Table 4: Fasting lipid concentrations prior to and after 12 weeks of energy restriction, 4 weeks of energy balance and 12 months of follow-up consuming a conventional protein or high-protein diet

Creatinine clearance

Creatinine clearance was only assessed in some of the subjects (SP, N=15; HP, N=14). Creatinine clearance significantly increased from baseline to week 68 in both dietary groups (P<0.01), with no effect of dietary composition evident (P=0.38); Table 3.


The main findings of this study were that the prescription of a low-fat diet, higher in protein and lower in carbohydrate, was equally effective as a dietary strategy for long-term weight loss and CVD risk factors compared to a conventional dietary approach, over a 68-week period. However, the attrition rate was relatively high and long-term compliance was poor, making it difficult to ascertain differential long-term metabolic advantages or disadvantages of these macronutrient compositions.

Since protein is more satiating than CHO,24,25 it could be theorised that increased protein consumption may offer a greater weight loss/maintenance advantage over the long-term. However, in the present study, subjects regained weight during the 12-month follow-up period, with no differences in either body weight or total energy intake between the two dietary groups. Moreover, dietary composition fluctuated in both groups and differences in the carbohydrate to protein ratio were not maintained. This was further reflected by changes in 24 h urinary urea–creatinine ratio (a biomarker of protein intake), indicating that during the follow-up, neither dietary pattern was sustained. Dietary compliance is a likely function of psychological issues, such as frequency of dietary counselling and group support, rather than macronutrient composition, per se.26,27 It has been demonstrated in overweight, nondiabetic subjects that regular individualised dietary counselling over a long-term duration resulted in greater changes for positive dietary habits and weight loss, compared with subjects offered no personalised advice.28,29 Skov et al13 achieved high compliance to ad libitum low-fat dietary interventions of either HP or SP over a 6-month treatment period by providing participants with free of charge access to a shop that supplied a large selection of foods. These researchers reported greater weight loss following the HP diet that was most likely due to a reduced energy intake.13 Our subjects did not receive dietary counselling or key foods during the 12-month follow-up. It is possible, therefore, that poor dietary compliance during the follow-up was a function of a lack of active clinical support, which may be required for adherence to a HP diet to facilitate weight loss and/or maintenance. Similarly, Foster et al30 used a free living approach with minimal professional contact and showed no significant difference in weight loss between a low-carbohydrate, HP, high-fat ‘Atkins diet’ and a conventional high-carbohydrate diet (2.5 vs 4.4%) after 12 months in obese men and women and reported poor adherence to both interventions. This evidence, taken together with the fact that there was a relatively high drop out rate observed in these studies, suggests that long-term adherence to either a HP or conventional SP diet in the absence of professional support may be difficult.

Despite the absence of a differential effect between the dietary treatments for weight loss/maintenance, subjects weighed approximately 3.5% less after the intervention. DEXA analysis revealed that this was entirely fat loss, with the preservation of lean body tissue. A weight reduction of this magnitude is associated with potential health benefits,31 such as an elevation of HDL cholesterol and improved insulin sensitivity observed in this study, and could reduce the prevalence of obesity from 25 to 15% in the general population.32

The subjects in this study were hyperinsulinemic, which in addition to obesity, is a major risk factor for glucose intolerance, type II diabetes and CVD.33 Sustained weight loss with either diet resulted in reduced fasting insulin levels and HOMA that moved towards normalisation. Two recent diabetes prevention studies involving obese persons with impaired glucose tolerance have demonstrated that over an average 3-y period weight loss equivalent to that observed in the present study reduced the risk and delayed the onset of diabetes.28,29

A further complication of obesity and insulin resistance that plays a central role in the pathogenesis of atherosclerosis is the dysfunction of the vascular endothelium via inflammatory mechanisms.34,35,36 sICAM-1 and CRP are two inflammatory molecules that are not only directly implicated in the atherosclerotic process,34,35 but levels of both have been identified as independent biomarkers of inflammation that predict the risk of CVD and future cardiac events.35,37,38 Prospective data also suggest that elevated baseline CRP levels are a potent independent risk predictor for the development of type II diabetes.39 Following the present interventions, subjects experienced substantial reductions of sICAM-1 and CRP levels. These decreases in CRP were similar to that observed after statin therapy40,41 that subsequently reduced the risk of cardiovascular events among those patients with heightened vascular inflammation as indicated by elevated CRP levels.41,42

After 68 weeks of treatment, HDL cholesterol levels were 15% higher with both dietary strategies, comparable to the level of change reported with pharmacologic treatment, such as fibric acid and niacin.43 HDL is an important risk factor for CVD.43,44 It has been suggested that an increase of 1% in HDL-cholesterol concentrations may constitute a 3% decrease in risk of heart disease.44 Therefore, this relatively large increase in HDL concentrations would likely translate to a reduction in cardiovascular risk. However, the mechanism for this effect is unclear. Although HDL concentrations increase as body weight decreases,45,46 which could explain some of this effect observed in the present study, the increases are considerably greater than those expected from a moderate weight loss alone.45 These data suggest that factors other than weight loss are important for controlling HDL-cholesterol concentrations. Overall, this evidence indicates both dietary patterns provide useful long-term strategies for weight reduction, restoration of insulin sensitivity, increasing HDL cholesterol levels and may have the potential to diminish the degree of inflammation (lower sICAM-1 and CRP levels) that may assist in attenuating the development of disease, including diabetes and reduce the development of CVD.

An often cited concern with HP diets is the potential adverse effects on renal function and bone health. The data presented here demonstrate that subjects on both dietary patterns experienced no bone loss. Additionally, observational studies conducted over 4 y have demonstrated a positive association between protein intake and bone mineral density,47,48 such that persons in the highest quartile of protein intake (17–28%) had the smallest loss of bone mineral density.47 In some subjects, we also measured creatinine clearance to examine the long-term effects of protein intake on renal function. Both diets exhibited a significant increase in creatinine clearance over the 68-week study period. This effect could be explained by the fact that compared to baseline both treatment groups increased protein loads throughout the study, which may have induced renal adaptations that increased creatinine clearance. In support of this contention, Brändle et al49 showed a strong positive relationship between chronic protein intake and glomerular filtration rate (GFR) in normal individuals. Correspondingly, Skov et al23 demonstrated over a 6-month intervention period in obese subjects that the consumption of an ad libitum low fat, HP (25% energy diet) increased GFR, compared to subjects that consistently consumed a SP (12% energy diet); but no adverse effect on renal function was evident. These researchers further reported in the same experiment that the HP diet was associated with a diminished bone mineral content loss.50 Together, this data suggest apparent long-term safety of a prescribed HP diet, at least up to 30% of dietary energy, in healthy individuals for bone health and kidney function.

This study has several limitations. Due to the relatively small sample number and minimal professional supervision during follow-up that may have limited compliance, there still remains insufficient evidence to provide clear recommendation for the role of an HP, low-fat diet for weight reduction and prevention of CVD. Further controlled research with larger sample sizes is required with greater emphasis on behaviour modification in an attempt to gain greater compliance in order to elucidate the long-term safety and efficacy of this dietary strategy. Research in this area should also be further extended to include at risk populations, such as diabetics. In addition, we did not provide any assessment of physical activity. Consequently, the contribution of any changes in exercise habits on the metabolic end points could not be determined. Thus, given the established role of regular exercise for weight loss maintenance,51,52 future long-term follow-up studies of this nature should provide concurrent assessment of physical activity and incorporate an exercise intervention.

In summary, our findings indicate that in obese, hyperinsulinemic subjects, over a 68-week period, prescribing a low-fat, HP diet offers no greater advantages or disadvantages for weight loss, markers of CVD and dietary adherence compared to a conventional SP diet. However, due to poor dietary compliance, no conclusions can be made in relation to the direct long-term metabolic effects of a HP diet.


  1. 1.

    , . Diet, obesity, and cardiovascular risk. N Engl J Med 2003; 348: 2057–2058.

  2. 2.

    , , , , , . The disease burden associated with overweight and obesity. JAMA 1999; 282: 1523–1529.

  3. 3.

    , , , . Prevalence and trends in obesity among US adults, 1999–2000. JAMA 2002; 288: 1723–1727.

  4. 4.

    , , , , , , , , . Overweight and obesity in Australia: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Med J Aust 2003; 178: 427–432.

  5. 5.

    , . The public health impact of obesity. Annu Rev Public Health 2001; 22: 355–375.

  6. 6.

    . The impact of obesity on health status: some implications for health care costs. Int J Obes Relat Metab Disord 1995; 19 (Suppl 6): S13–S16.

  7. 7.

    , , , , , . Prevalence of attempting weight loss and strategies for controlling weight. JAMA 1999; 282: 1353–1358.

  8. 8.

    , , , . High-protein weight-loss diets: are they safe and do they work? A review of the experimental and epidemiologic data. Nutr Rev 2002; 60: 189–200.

  9. 9.

    , . Environmental contributions to the obesity epidemic. Science 1998; 280: 1371–1374.

  10. 10.

    , , , , , . Dietary fat and body fat: an intervention study. Int J Obes Relat Metab Disord 1996; 20: 1022–1026.

  11. 11.

    , . Randomised comparison of diets for maintaining obese subjects' weight after major weight loss: ad lib, low fat, high carbohydrate diet v fixed energy intake. BMJ 1997; 314: 29–34.

  12. 12.

    , , , , , . High protein vs high carbohydrate hypoenergetic diet for the treatment of obese hyperinsulinemic subjects. Int J Obes Relat Metab Disord 1999; 23: 1202–1206.

  13. 13.

    , , , , . Randomized trial on protein vs carbohydrate in ad libitum fat reduced diet for the treatment of obesity. Int J Obes Relat Metab Disord 1999; 23: 528–536.

  14. 14.

    , , , , , , . A reduced ratio of dietary carbohydrate to protein improves body composition and blood lipid profiles during weight loss in adult women. J Nutr 2003; 133: 411–417.

  15. 15.

    , , , . Effect of a high-protein, high-monounsaturated fat weight loss diet on glycemic control and lipid levels in type 2 diabetes. Diabetes Care 2002; 25: 425–430.

  16. 16.

    , , , , , , , , , . Hypocaloric high-protein diet improves glucose oxidation and spares lean body mass: comparison to hypocaloric high-carbohydrate diet. Metabolism 1994; 43: 1481–1487.

  17. 17.

    , , , , , . Effect of a high-protein, energy-restricted diet on body composition, glycemic control, and lipid concentrations in overweight and obese hyperinsulinemic men and women. Am J Clin Nutr 2003; 78: 31–39.

  18. 18.

    , . Short-term effects of substituting protein for carbohydrate in the diets of moderately hypercholesterolemic human subjects. Metabolism 1991; 40: 338–343.

  19. 19.

    , , , , . The Anti Cancer Council of Victoria FFQ: relative validity of nutrient intakes compared with weighed food records in young to middle-aged women in a study of iron supplementation. Aust N Z J Public Health 2000; 24: 576–583.

  20. 20.

    , , . Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972; 18: 499–502.

  21. 21.

    , , , , , . Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412–419.

  22. 22.

    , , , , , . Should clearance be normalised to body surface or to lean body mass? Br J Clin Pharmacol 1981; 11: 523–526.

  23. 23.

    , , , , , . Changes in renal function during weight loss induced by high vs low-protein low-fat diets in overweight subjects. Int J Obes Relat Metab Disord 1999; 23: 1170–1177.

  24. 24.

    , , . Short-term effects of macronutrient preloads on appetite and energy intake in lean women. Physiol Behav 1998; 64: 279–285.

  25. 25.

    , . The effects of a high-carbohydrate, high-protein or balanced lunch upon later food intake and hunger ratings. Appetite 1999; 33: 119–128.

  26. 26.

    , . Dietary fat intake does affect obesity! Am J Clin Nutr 1998; 68: 1157–1173.

  27. 27.

    , , , , , , , . Self-help weight loss versus a structured commercial program after 26 weeks: a randomized controlled study. Am J Med 2000; 109: 282–287.

  28. 28.

    , , , , , , , , , , , , Finnish Diabetes Prevention Study Group. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001; 344: 1343–1350.

  29. 29.

    , , , , , , , Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346: 393–403.

  30. 30.

    , , , , , , , , , . A randomized trial of a low-carbohydrate diet for obesity. N Engl J Med 2003; 348: 2082–2090.

  31. 31.

    , (ed), The Food and Nutrition Board, Institute of Medicine Committee to Develop Criteria for Evaluating the Outcomes of Approaches to Prevent and Treat Obesity. Weighing the options: criteria for evaluating weight management programs. National Academy Press: Washington, DC; 1995.

  32. 32.

    World Health Organisation. Obesity: preventing and managing the global epidemic. WHO Publications: Geneva; 1997.

  33. 33.

    , . Insulin resistance syndrome: options for treatment. South Med J 1999; 92: 2–15.

  34. 34.

    . Atherosclerosis—an inflammatory disease. N Engl J Med 1999; 340: 115–126.

  35. 35.

    , . Inflammatory bio-markers and cardiovascular risk prediction. J Intern Med 2002; 252: 283–294.

  36. 36.

    , , , , , , , . Markers of inflammation and cellular adhesion molecules in relation to insulin resistance in nondiabetic elderly: the Rotterdam study. J Clin Endocrinol Metab 2001; 86: 4398–4405.

  37. 37.

    , , , , . Plasma concentration of soluble intercellular adhesion molecule 1 and risks of future myocardial infarction in apparently healthy men. Lancet 1998; 351: 88–92.

  38. 38.

    , , , . C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med 2000; 342: 836–843.

  39. 39.

    , , , , . C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA 2001; 286: 327–334.

  40. 40.

    , , , . Effect of statin therapy on C-reactive protein levels: the pravastatin inflammation/CRP evaluation (PRINCE): a randomized trial and cohort study. JAMA 2001; 286: 64–70.

  41. 41.

    , , , , , , , Air Force/Texas Coronary Atherosclerosis Prevention Study Investigators. Measurement of C-reactive protein for the targeting of statin therapy in the primary prevention of acute coronary events. N Engl J Med 2001; 344: 1959–1965.

  42. 42.

    , , , , , , , . Inflammation, pravastatin, and the risk of coronary events after myocardial infarction in patients with average cholesterol levels. Cholesterol and Recurrent Events (CARE) Investigators. Circulation 1998; 98: 839–844.

  43. 43.

    , . Pharmacological management of high triglycerides and low high-density lipoprotein cholesterol. Curr Opin Pharmacol 2001; 1: 113–120.

  44. 44.

    . High-density lipoprotein cholesterol as an independent risk factor in cardiovascular disease: assessing the data from Framingham to the Veterans Affairs High-Density Lipoprotein Intervention Trial. Am J Cardiol 2000; 86: 19L–22L.

  45. 45.

    , . Effects of weight reduction on blood lipids and lipoproteins: a meta-analysis. Am J Clin Nutr 1992; 56: 320–328.

  46. 46.

    , , , , , . Effects of the National Cholesterol Education Program's Step I and Step II dietary intervention programs on cardiovascular disease risk factors: a meta-analysis. Am J Clin Nutr 1999; 69: 632–646.

  47. 47.

    , , , , , . Effect of dietary protein on bone loss in elderly men and women: the Framingham Osteoporosis Study. J Bone Miner Res 2000; 15: 2504–2512.

  48. 48.

    , , , . Protein consumption and bone mineral density in the elderly: the Rancho Bernardo Study. Am J Epidemiol 2002; 155: 636–644.

  49. 49.

    , , . Effect of chronic dietary protein intake on the renal function in healthy subjects. Eur J Clin Nutr 1996; 50: 734–740.

  50. 50.

    , , , , . Effect of protein intake on bone mineralization during weight loss: a 6-month trial. Obes Res 2002; 10: 432–438.

  51. 51.

    , , . Physical activity and weight maintenance. Int J Obes Relat Metab Disord 1999; 23 (Suppl 3): S50–S54.

  52. 52.

    , . Does physical activity prevent weight gain—a systematic review. Obes Rev 2000; 1: 95–111.

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We acknowledge Rosemary McArthur, Anne McGuffin, and Jodie Avery for assistance in performing these studies. This work was supported by a National Health and Medical Research Grant #158012 and a Dairy Research and Development Corporation Grant #CSHN100003

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  1. CSIRO Health Sciences and Nutrition, Adelaide, South Australia, Australia

    • G D Brinkworth
    • , M Noakes
    • , J B Keogh
    •  & P M Clifton
  2. Department of Medicine, University of Adelaide, Australia

    • N D Luscombe
    •  & G A Wittert


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Correspondence to P M Clifton.

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