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Journal of the American College of Nutrition, Vol. 26, No. 2, 163-169 (2007)
Published by the American College of Nutrition

Low Carbohydrate, High Fat Diet Increases C-Reactive Protein during Weight Loss

Janet W. Rankin, PhD and Abigail D. Turpyn

Department of Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg, Virginia

Address reprint requests to: Janet W. Rankin, PhD, Professor, Department of Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg VA 24061-0430. E-mail: jrankin{at}vt.edu


   ABSTRACT
TOP
 FOOTNOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Objective: Chronic inflammation is associated with elevated risk of heart disease and may be linked to oxidative stress in obesity. Our objective was to evaluate the effect of weight loss diet composition (low carbohydrate, high fat, LC or high carbohydrate, low fat, HC) on inflammation and to determine whether this was related to oxidative stress.

Methods: Twenty nine overweight women, BMI 32.1 ± 5.4 kg/m2, were randomly assigned to a self-selected LC or HC diet for 4 wks. Weekly group sessions and diet record collections helped enhance compliance. Body weight, markers of inflammation (serum interleukin-6, IL-6; C-reactive protein, CRP) oxidative stress (urinary 8-epi-prostaglandin F2{alpha}, 8-epi) and fasting blood glucose and free fatty acids were measured weekly.

Results: The diets were similar in caloric intake (1357 kcal/d LC vs. 1361 HC, p=0.94), but differed in macronutrients (58, 12, 30 and 24, 59, 18 for percent of energy as fat, carbohydrate, and protein for LC and HC, respectively). Although LC lost more weight (3.8 ± 1.2 kg LC vs. 2.6 ± 1.7 HC, p=0.04), CRP increased 25%; this factor was reduced 43% in HC (p=0.02). For both groups, glucose decreased with weight loss (85.4 vs. 82.1 mg/dl for baseline and wk 4, p<0.01), while IL-6 increased (1.39 to 1.62 pg/mL, p=0.04). Urinary 8-epi varied differently over time between groups (p<0.05) with no consistent pattern.

Conclusion: Diet composition of the weight loss diet influenced a key marker of inflammation in that LC increased while HC reduced serum CRP but evidence did not support that this was related to oxidative stress.

Key words: inflammation, oxidative stress, obesity, weight loss, diet composition

Abbreviations: 8-epi=8-epi-prostaglandin F2{alpha} • CRP=C-reactive protein • LC=high fat, high protein, low carbohydrate diet • HC=low fat, moderate protein, high carbohydrate diet • IL-6=interleukin 6 • BMI=body mass index • NEFA=non-esterified fatty acids • ROS=reactive oxygen species


   INTRODUCTION
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 CONCLUSION
 ACKNOWLEDGMENTS
 REFERENCES
 
The proportion of overweight and obese US adults and children continues to rise with each national survey conducted. The most recent data from the NHANES survey in 2001–2002 shows that 65.1% of adults are overweight and 30.4% are obese [1]. Low carbohydrate weight loss diets are currently one of the more popular weight loss strategies with an estimated 20 million people using this diet worldwide [2].

Traditionally, nutritionists have cautioned against use of LC diets because the high fat and cholesterol intake was thought to cause an increase in blood lipids and thus heart disease. However, recently a number of laboratories have reported that weight loss and blood lipid changes are at least comparable or even superior with a LC compared to a low fat, HC approach [3–6].

Although important, elevated blood lipids are only one risk factor for heart disease. Many people develop heart disease concurrent with normal blood lipids. One blood marker, C-reactive protein (CRP), for example, appears to increase heart disease risk independent of blood lipids [7, 8]. CRP, an acute phase protein, is an index of chronic, low level inflammation. Elevated production of pro-inflammatory mediators has been noted in adipose tissue as well as circulating mononuclear cells in obese individuals [9]. It has been suggested that these inflammatory factors may activate endothelial cells, stimulating further release of cytokines and growth factors associated with the migration of lymphocytes and macrophages into smooth muscle cells in vessel walls.

Obesity is associated with higher concentrations of serum CRP [8, 10], suggesting one mechanism linking obesity to increased heart disease risk. The causes of high CRP are not entirely clear but weight loss usually reduces levels of this protein [11]. Although specific dietary effects on CRP in obesity have not been fully elucidated, dietary patterns rich in fruits, vegetables and grains [12, 13] and high in fiber [14] are reported to be associated with lower CRP while high trans fat [15] and glycemic load [16] diets are associated with higher CRP in epidemiological studies. Clinical trials are needed to confirm the effect of dietary manipulation on serum CRP.

A possible mechanism for an increase in inflammation in obese individuals is an increase in oxidative stress, an imbalance between production and elimination of reactive oxygen species (ROS). Recent studies have clarified an association between obesity and higher oxidative stress markers [17] as well as a possible connection between oxidative stress and a chronic inflammatory state [9, 17]. A hypothesized sequence of events includes accumulation of cellular ROS perpetuating inflammation via activation of redox-sensitive nuclear transcription factors, such as AP-1 and NF-{kappa}B, and subsequent increase in expression of inflammatory proteins [18].

Although research is limited, diets high in fat have been shown in several studies to be associated with higher markers of oxidative stress in both animals [19, 20] and humans [21]. As many LC diets are high in fat and low in dietary antioxidants provided from fruits, vegetables, and whole grains, those who follow the diet may be more susceptible to oxidative stress. The connection between oxidative stress consequent to dietary macronutrient composition and inflammation has not been well studied in obese humans.

Our hypothesis for this study was that individuals following a low carbohydrate, high fat diet would demonstrate higher markers of oxidative stress and inflammation compared to similar individuals following a low fat, higher carbohydrate traditional weight loss diet.


   MATERIALS AND METHODS
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 CONCLUSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Subjects
Thirty- two female subjects, aged 32–45, were recruited from a local community and screened for contraindications to energy restriction and weight loss as well as for medical conditions (diabetes, cardiovascular disease, hypertension, rheumatoid arthritis, Crohn's disease, lupus) or medications known to influence inflammation. All subjects were pre-menopausal, weight stable for at least 6 months, nonsmokers, BMI >24.5 kg/m2 (average 32.1±5.4 kg/m2, range 24.6–43.6), sedentary (less than 5 hrs exercise per week), but otherwise healthy. Ethnicity was primarily Caucasian (2 African American, 2 Asian, 1 Indian, 28 Caucasian). All subjects were required to obtain medical clearance from their physician prior to starting the study. Subjects were requested to immediately discontinue any supplement use upon acceptance into the study so that no subjects consumed any supplements within 2 wks of the start of the study. The study was approved by the Institutional Review Board of Virginia Tech and all subjects provided written informed consent. Three subjects discontinued the study of their own volition during the first week so the results for 29 women are presented.

Design and Procedures
Subjects were randomly assigned to follow either an ad libitum low carbohydrate, high fat, high protein (LC) diet or a calorie restricted high carbohydrate, low fat, low protein (HC) diet for 4 wks. LC dieters were provided with a copy of "The New Diet Revolution" by Robert Atkins [22] as well as additional handouts prepared by the experimenters during the 4 wks to help them follow the diet. HC diet subjects were provided with an exchange system plan based on their body weight. Energy goals for the HC diets were determined by using estimated resting metabolic rate [23] to result in estimated loss of 0.5–1.0 kg/wk. This resulted in energy goals of 1300, 1500, or 1700 kcal/d (depending on body weight) and macronutrient goals at 15–20% protein, 20–25% fat, and 60% carbohydrate. All subjects attended a weekly education and social support session (separate sessions for the diet groups). Subjects were asked to complete 4 d food records (3 week days and 1 weekend day) during each week that were discussed and then collected to assess compliance. Diet records were analyzed using the nutrition analysis software (Food Processor® dietary analysis software, ESHA Research, Version 8.1; 2003).

Subjects came to the laboratory every 7 d at the same time each week between 7:00 and 9:30 am in a fasted state. Subjects were asked to collect all their urine for 24 h prior to the laboratory visit. Subjects were weighed on a calibrated scale, waist and hip circumferences were measured, and blood samples were collected via venipuncture. Total volume of the urine collections was measured. Two samples of the remaining urine were frozen at –80°C for later analysis of 8-epi-prostaglandin-F2{alpha} and creatinine. The blood samples were allowed to clot and then centrifuged at 1070 x g for 15 min. Serum was collected and stored in separate aliquots, frozen at –80 for later analysis of CRP, IL-6, non-esterified fatty acids (NEFA), and glucose.

Sample Analysis
Serum was analyzed for high sensitivity C-reactive protein (CRP) and high sensitivity interleukin-6 (IL-6) using ELISA (United Biotech, Inc.; Mountain View, CA and R&D systems; Minneapolis, MN, respectively). Serum glucose was measured by an enzymatic colorimetric assay (Stanbio, Boerne, TX). Serum NEFA were analyzed by an enzymatic colorimetric assay adapted for microplate (Wako, Richmond, VA). All analyses were done in duplicate. If values for duplicates for ELISA were more than 20% different, an additional analysis was performed. The coefficients of variation (CV) for CRP, IL-6, 8 epi were 13.2, 7.6, and 13.0, respectively. Glucose and NEFA measures were re-analyzed if the CV > 10%, the average CV for these two measures was 3.5 and 3.2, respectively. Urine collections (24h) were analyzed in duplicate for urinary 8-epi-prostaglandin-F2{alpha} using a competitive enzyme linked ELISA (Oxis International, Portland, OR). Urinary creatinine was measured in each urine sample (Stanbio) and the amount of 8-epi-prostaglandin-F2{alpha} was normalized to urinary creatinine.

Statistics
Baseline characteristics of subjects (Table 1) were compared using t-test. All other dependent measures with weekly values were analyzed using mixed model repeated measures ANOVA with SPSS (version 13.0). Post hoc differences among means were detected using Tukey's LSD test. Changes in dependent measures from baseline to week four were calculated and compared using t-test. Associations between dependent measures were analyzed using Pearson Product moment correlation. A p value < 0.05 considered to be significant.


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  		Table 1. Baseline Subject Characteristics

 

   RESULTS
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
CONCLUSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Body Weight
Sixty-five percent of subjects began the study with a BMI greater than 30. All subjects lost a significant amount of weight (p<0.01), but LC lost more than HC (3.8±1.2kg LC vs. 2.6±1.7 HC, p<0.05) especially during the first week (Table 2).


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  		Table 2. Body Weight, Serum and Urinary Metabolites at Baseline and Each Week of the Intervention

 
Diet Records
There were no significant differences in the baseline diet of the two groups (Table 3). Reported caloric intake between the groups was remarkably similar during the weight reduction period in spite of very different macronutrient composition of the diets. Not surprisingly, the lowest energy intake for both groups was reported for the first week of the diet; energy intake was maintained at this reduced level through the study. Both groups modified their macronutrient consumption to report consuming close to that composition requested throughout the four weeks of the experiment so that proportion of macronutrients was different throughout the weight loss period. Among the antioxidant vitamins examined, vitamin C and vitamin A consumption were higher for HC than LC during the weight loss period but no differences were observed for vitamin E consumption between groups (Table 3).


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  		Table 3. Average Energy, Macronutrients, and Antioxidant Vitamin Intake from for HC and LC

 
Serum Measures
Seventy-two percent of subjects had baseline serum CRP concentration ≥ 2 mg/L and 34% had values ≥ 5 mg/L. Only one subject had a baseline serum glucose concentration greater than 100 mg/dl. Initial serum CRP was positively correlated to serum NEFA (r = 0.44, p = 0.01), glucose (r = .52, p = 0.004), waist circumference (r = 0.45, p = 0.02), and IL-6 (r = 0.46, p = 0.01) with a trend for correlation to BMI (r = 0.36, p = 0.056). In addition, baseline serum glucose correlated with serum IL-6 (r = 0.54, p = 0.002) and NEFA (r = 0.38, p = 0.04). Baseline urinary 8 epi did not correlate with any other factor.

Serum glucose decreased slightly over the 4 weeks of dieting for both groups with no difference between the groups (85.2 vs. 82.5 mg/dl for baseline and wk 4, p < 0.01). The reduction in serum glucose over the weight loss period was negatively correlated to the change in serum NEFA (r = –0.55, p = 0.002) and tended to be correlated to initial serum CRP (r = –0.37, p = 0.51). Serum IL-6 increased about 16% for groups combined (1.39 to 1.62 pg/mL, p = 0.04) but there was no difference in the response by diet and no factors correlated with change in IL-6 (Table 2). Serum NEFA increased for both groups during weight loss by the first week of the diet. The increase from baseline to week 4 was greater for LC than HC.

There was a significant interaction of groups over time for serum CRP response to the diets (Table2). Serum CRP increased over the experimental period for LC and decreased in the HC group (+25% vs. –43% respectively, p = 0.02). The divergence of the two groups in average CRP occurred within the first week of the diet. Change in serum CRP from baseline to week 4 was different for LC than HC (1.4 ± 2.3 vs –2.1 ± 1.9, p = .0001). Fig. 1 shows that all subjects in HC had either a reduction or no change in serum CRP during the weight loss period while most of LC had an increase, regardless of their initial serum CRP values.


Figure 1
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  		Fig. 1. "LC = low carbohydrate, HC = high carbohydrate. Values are individual subjects."

 
Urine Factors
There was not a consistent effect of weight loss on 8-epi excretion when groups were combined (Table 2). A significant interaction between groups over time did not appear to be meaningful as concentrations for both groups oscillated over time with no clear pattern (p = 0.035). Neither baseline nor the change in urinary 8-epi were correlated to any other variable measured.


   DISCUSSION
 
The most important finding from this study is that macronutrient composition of a weight loss diet influenced the inflammatory state as indicated by serum CRP. A LC weight loss diet was associated with an increase while a HC diet was associated with a reduction in serum CRP. This was in spite of the fact that, as in other studies [5, 6, 24], the LC diet group lost more weight than the HC diet group.

Numerous studies have shown an association between BMI and serum CRP [9, 25]. The mechanism for higher serum CRP in obesity is not entirely clear but has been suggested to be secondary to interrelated factors such as increased cytokine release from adipocytes, insulin resistance, and oxidative stress [9, 26, 27]. Hyperglycemia and elevated NEFA secondary to insulin resistance can increase production of ROS and inflict cellular oxidative stress [9, 27].

Most but not all studies examining the effect of weight loss on serum CRP demonstrated a reduction of this inflammatory marker in response to diet-induced weight loss [26]. For example, two studies reported 26 and 32% reductions in serum concentrations of CRP in obese women who lost an average of 7.9 and 14.5 kg over 12 wk [28] or 14 months [11], respectively. The reduction in serum CRP in both studies were correlated with magnitude of weight change [11, 28]. As weight loss tends to improve insulin resistance and reduce measures of oxidative stress [9], this supports a relationship between these factors and inflammation but does not identify their cause and effect relationship.

The potential interactive effect of dietary composition on the inflammatory response to weight loss is not possible to determine from most of the published studies due to lack of dietary control and/or comparison between various compositions. However, it is interesting that one study observed a 37% reduction in inflammatory markers in non-obese rheumatoid arthritis patients who lost weight via semi-fasting but no change in patients who lost a similar amount of weight using a LC diet [29]. In other words, the LC diet appeared to interfere with the normal reduction in inflammation with weight loss. Several clinical trials using obese individuals compared the effect of LC to HC diets on serum CRP and other inflammatory indicators. Two studies found no specific effect of diet composition of the weight loss diet in that reduction in serum CRP was associated with magnitude of weight lost but not diet macronutrient mix [30, 31]. The third study found that both a LC and a HC diet reduced serum CRP but that the LC diet was actually superior for reduction in this factor when subjects began with elevated serum CRP [32]. Interestingly, the subjects who began the study with low or intermediate serum CRP and were assigned to the LC diet had an increase in their average serum CRP.

Many studies report a correlation between serum CRP and other inflammatory markers such as IL-6 [33] in obese individuals. IL-6 is known to induce release of CRP from liver but the relationship between IL-6 and CRP is not simplistic. Some studies find that IL-6 and CRP change in concert with dietary manipulation [12, 33]; other studies report substantial reductions in serum CRP but no effect on IL-6 following weight loss [34, 35]. We did not observe an increase in IL-6 following LC in spite of an increase in CRP. Clearly, other factors are involved in regulating CRP release and the lack of concurrent change in serum IL-6 with serum CRP in our study is not unusual.

Dietary compliance could cloud the interpretation of some of the studies examining the effect of diet composition of a weight loss diet on inflammation. For example, in one study [5, 32], dietary compliance to a LC diet was poor by the 6 month blood CRP measurement point. Although carbohydrate intake was different between groups (37% and 51% of energy and approximately 151 and 804 g of carbohydrate for LC and HC, respectively) this is not close to the goal of less than 30 g per day carbohydrate for the LC requested by the investigators. There would be less expectation of a different metabolic response to the two diets with this low degree of dietary compliance compared to our study where LC subjects reported ≤ 12% of energy from carbohydrate on all diet record periods over 4 wks.

It is acknowledged that most of the diets compared in these studies, including ours, varied in protein in addition to fat and carbohydrate. It is possible that the variation in amount or type of dietary protein plays a role in these effects on inflammation. Although it is not possible with our design to exclude protein as a factor as a factor in the differential effect on serum CRP, another study comparing two diets that varied in carbohydrate and protein but kept fat constant and relatively low (30% of energy) did not observe a difference in serum CRP response between the weight loss diets [36]. However, additional research should be conducted that clarifies the role of each macronutrient in the inflammatory response.

Our hypothesis was that diet composition would influence oxidative stress and this would subsequently increase inflammation. This was based on other research that showed that increased production of ROS can occur secondary to a higher fat diet. Several diet manipulation studies in rodents or rabbits support a connection between high fat diet and oxidative stress [19, 20]. There is limited human evidence for a connection between high fat diet and oxidative stress in that 12 d of consumption of a high fat (50%), low fiber diet increased hydroxyl radical content of the feces 13 fold and plasma malondialdehyde concentration 47% higher relative to a similar period on a low fat (20%), high fiber diet [21]. However, our study did not support a link between dietary macronutrient composition and oxidative stress. It is possible that urinary 8-epi is not the best marker to detect a change in oxidative stress under these conditions or that the method used was not specific enough to detect changes (i.e. cross reactivity with other compounds). There is controversy about the best marker for oxidative stress [37]. For example, Dragsted et al [38] reported that resistance of plasma lipids to oxidation but not urinary 8 epi were improved by consumption of 600 g of fruits and vegetables per day. Further research using multiple markers will be needed to clarify whether diet composition influences inflammation through oxidative stress.

If oxidative stress is a link between diet composition and inflammation, the use of vitamin and other supplements that could influence inflammation or oxidative stress by subjects in some trials could explain some of the results that conflict with our own. For example, the subjects studied by Yancy et al. consumed a supplement that contained various vitamins and fish oil [6]. Many other studies do not report whether there were restrictions, provisions, or measurements of supplement use. Other factors that could complicate interpretation of the diet- oxidative stress- inflammation link include use of subjects that smoked [32] or used medications (e.g. lipid lower medications) that are known to have anti-inflammatory effects. We excluded subjects who smoked, used medications or vitamins that could affect inflammation or oxidative stress.

We acknowledge that our study had limitations. For example, although we counseled subjects each week, there was variability among subjects in compliance to the dietary goals. However, as mentioned previously, the compliance to the diet was closer to goals than many other studies examining the connection between diet and inflammation. Studies using controlled feeding of subjects to improve dietary compliance as well as measurement of a wider complement of inflammatory and oxidative stress markers should be conducted. Finally, the brief period of the study does not allow conclusions as to the longer term effect of dietary composition on inflammation markers.


   CONCLUSION
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSION
ACKNOWLEDGMENTS
 REFERENCES
 
Our study demonstrated an increase in serum C-reactive protein during weight loss when following a LC but a decrease when the diet was HC. This suggests an increase in risk of heart disease for subjects on LC. The changes in CRP were not reflected by similar dichotomous changes in serum IL-6 or a urinary measure of oxidative stress. Further study is required to clarify the relationship between macronutrient composition and systemic inflammation but our study suggests that a HC weight loss diet is preferable to LC to reduce an inflammatory factor associated with higher risk of cardiovascular disease.


   ACKNOWLEDGMENTS
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSION
 ACKNOWLEDGMENTS
REFERENCES
 
The authors would like to thank Janet Rinehart for her assistance in phlebotomy and laboratory support as well as Drs. Mary Dean Coleman and Sharon Nickols-Richardson for their assistance with subject selection, treatment, and diet analysis. Abigail Turpyn was supported by the Macromolecular Interfaces with Life Sciences (MILES) Integrative Graduate Education and Research Traineeship (IGERT) of the National Science Foundation under Agreement No. DGE-0333378.


   FOOTNOTES
TOP
 FOOTNOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Parts of this manuscript were presented at the 2005 Meeting of Southeast American College of Sports Medicine.

Received December 22, 2005. Accepted August 28, 2006.


   REFERENCES
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSION
 ACKNOWLEDGMENTS
 REFERENCES
 

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