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Weight Loss Favorably Modifies Anthropometrics andReverses the Metabolic Syndrome in PremenopausalWomenIngrid E. Lofgren PhDac, Kristin L. Herron PhDa, Kristy L. West PhDa, Tosca L. ZernPhDa, Rhonda A. Brownbill PhDb, Jasminka Z. Ilich PhDb, Sung I. Koo PhDa & Maria LuzFernandez PhDa

a Department of Nutritional Sciences (I.E.L., K.L.H., K.L.W., T.L.Z., S.I.K., M.L.F.),University of Connecticut, Storrs, Connecticutb School of Allied Health (R.A.B., J.Z.I.), University of Connecticut, Storrs, Connecticutc Department of Animal & Nutritional Sciences, The University of New Hampshire,Durham, New Hampshire (I.E.L.)Published online: 18 Jun 2013.

To cite this article: Ingrid E. Lofgren PhD, Kristin L. Herron PhD, Kristy L. West PhD, Tosca L. Zern PhD, Rhonda A.Brownbill PhD, Jasminka Z. Ilich PhD, Sung I. Koo PhD & Maria Luz Fernandez PhD (2005) Weight Loss Favorably ModifiesAnthropometrics and Reverses the Metabolic Syndrome in Premenopausal Women, Journal of the American College ofNutrition, 24:6, 486-493, DOI: 10.1080/07315724.2005.10719494

To link to this article: http://dx.doi.org/10.1080/07315724.2005.10719494

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Original Research

Weight Loss Favorably Modifies Anthropometrics andReverses the Metabolic Syndrome in PremenopausalWomen

Ingrid E. Lofgren, PhD, Kristin L. Herron, PhD, Kristy L. West, PhD, Tosca L. Zern, PhD, Rhonda A. Brownbill, PhD,Jasminka Z. Ilich, PhD, Sung I. Koo, PhD, and Maria Luz Fernandez, PhD

Department of Nutritional Sciences (I.E.L., K.L.H., K.L.W., T.L.Z., S.I.K., M.L.F.), School of Allied Health (R.A.B., J.Z.I.),University of Connecticut, Storrs, Connecticut, Department of Animal & Nutritional Sciences, The University of New Hampshire,Durham, New Hampshire (I.E.L.)

Key words: premenopausal women, body composition, weight loss, insulin resistance, metabolic syndrome

Objective: To determine the effects of a weight loss program, including dietary modifications, increasedphysical activity and dietary supplement (L-carnitine or placebo) on anthropometrics, leptin, insulin, themetabolic syndrome (MS) and insulin resistance in overweight /obese premenopausal women.

Methods: Participants consumed a hypocaloric diet; 30% protein, 30% fat and 40% carbohydrate in additionto increasing number of steps/day. Carnitine supplementation followed a randomized double blind protocol.Protocol lasted for 10 weeks. Seventy subjects (35 in the control and 35 in the carnitine group) completed theintervention. Anthropometrics, plasma insulin and leptin concentrations and body composition were measured.The number of subjects with the MetSyn and insulin resistance, were assessed at baseline and post-intervention.

Results: Because there were no significant differences between the carnitine and the placebo groups for allmeasured parameters, participants were grouped together for all analysis. Subjects decreased total energy(�26.6%, p � 0.01) and energy from carbohydrate (�17.3%, p � 0.01) and increased energy from protein by67% (p � 0.01) and number of steps/day (42.6%, p � 0.01). Body weight (�4.6%, p � 0.001), body mass index(�4.5%, p � 0.01), waist circumference (�6.5%, p � 0.01), total fat mass (�1.7%, p � 0.01), trunk fat mass(�2.0%, p � 0.01), insulin (� 17.9%, p � 0.01) and leptin (�5.9%, p � 0.05) decreased after the intervention.Ten of 19 participants with insulin resistance became insulin sensitive and 7 of 8 participants with the MetSynno longer had the syndrome after the intervention.

Conclusion: Moderate increases in physical activity and a hypocaloric/high protein diet resulted in multiplebeneficial effects on body anthropometrics and insulin sensitivity. Realistic dietary and physical activity goalsmust be the focus of intervention strategies for overweight and obese individuals.

INTRODUCTION

Prevalence of overweight and obesity continues to escalate[1]. While the ultimate goal is to prevent excess weight, preventionof further weight gain and promotion of weight loss in overweight/obese individuals are needed. Aerobic exercise beneficially im-pacts weight as well as the plasma lipid profile, via decreasedtriglycerides (TG) and increased high density lipoprotein choles-terol (HDL-C) [2]. Since exercise is a cornerstone in the battle

against obesity [3] and coronary heart disease (CHD) [2], recom-mendations for exercise duration and intensity levels have beenmade [4]. Ideally, an exercise routine is adopted and maintainedfor life [5]. Therefore, perceived barriers of overweight/obesepatients must be considered when prescribing exercise [6]. Inaddition, studies have shown that similar weight loss [5] andcardiorespiratory improvements [7] are achieved from both mod-erate and high intensity aerobic exercise. Because of the impor-tance that the hormone environment [8] and body composition

Abbreviations: CHD�coronary heart disease, CPT-1�carnitine palmitoyltransferase, DM2�diabetes mellitus type 2, DXA�dual X-ray absorption, FFQ�food frequencyquestionnaire, HDL-C�HDL cholesterol, IPAQ�international physical activity questionnaire, LCFA�long chain fatty acid, LDL-C�LDL-cholesterol, MS�metabolicsyndrome, NDS�nutrient database system, TG-triglycerides.

Address reprint requests to: Maria Luz Fernandez, PhD, University of Connecticut, Department of Nutritional Sciences 3624 Horsebarn Road Extension, U 4017, Storrs,CT 06269. E-mail: maria-luz.fernandez@uconn.edu

Journal of the American College of Nutrition, Vol. 24, No. 6, 486–493 (2005)Published by the American College of Nutrition

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[9] play in weight loss, evaluating the effects of a weight lossprogram on these parameters is vital.

Both insulin, a regulator of lipogenesis/lipolysis [10], andleptin, a regulator of energy expenditure and appetite control[8], are typically elevated in obesity [11] and decrease withweight loss [12]. Evidence has shown that decreased percentbody fat and insulin levels may increase lipolysis, resulting inincreased fatty acid utilization for energy [10]. In addition,active muscle fibers utilize circulating free fatty acids andmuscle TG for energy [13]. Therefore, combining calorie restric-tion with increased physical activity potentially enhances fat oxi-dation and decreases fat mass. Other mechanisms that could en-hance fat oxidation are also intriguing. For example, carnitine is anintegral component in long chain fatty acid (LCFA) transport inthe mitochondria for �-oxidation [14]. Supplemental carnitine hasbeen shown to increase weight loss in animals [15] and increaseLCFA oxidation in adults (3g carnitine/day) [16]. However, pre-vious studies utilizing 2 to 5 g/day of supplemental carnitineyield inconsistent results [17]. For example, Villani et al did notfind changes in total body mass or fat mass in moderately obesewomen after providing 2 g carnitine/day but did report anincrease in resting energy expenditure [18].

Because of the myriad of problems associated with obesity,including insulin resistance, diabetes mellitus type 2 (DM2),the metabolic syndrome (MS), and CHD, weight loss interven-tions must target multiple risk factors. These risk factors in-clude body composition, lipid profile, and hormonal milicu.The present study was performed to explore the impact of aweight loss program, including dietary modification, increasedphysical activity, and carnitine supplementation, on anthropo-metric and body composition measures and plasma insulin andleptin concentrations. We hypothesized that weight loss wouldfavorably affect those parameters associated with the MS andinsulin resistance. We also hypothesized that carnitine supple-mentation would enhance the intervention effects.

METHODS

Materials

Enzymatic total cholesterol (TC) and TG kits were obtainedfrom Roche-Diagnostics (Indianapolis, IN). Acetyl coenzymeA (acetyl CoA), carnitine acyltransferase, EDTA, aprotonin,sodium azide, 5,5�-dithiobis(2-nitrobenzoic acid) (DTNB), andphenyl methyl sulfonyl fluoride (PMSF) were obtained fromSigma Chemical (St. Louis, MO). Malonaldehyde bis (diethylacetal) was obtained from Aldrich (Arlington Heights, IL).Human insulin and leptin specific RIA kit were from LincoResearch (St. Charles, MO). L-carnitine L-tartrate (active) andplacebo supplements were provided by Lonza (Fair Lawn, NJ).

Study Population

Eighty-five overweight/obese, premenopausal women wererecruited from the University and surrounding communities.

The seventy women (74% Caucasian) who completed the pro-tocol were between 20 and 45 years of age and had a BMIbetween 25 to 37 kg/m2. Subjects were excluded if they werepregnant, lactating, or had a history of CHD, diabetes, kidneyor liver disease. Using the International Physical Activity Ques-tionnaire (IPAQ) [19], the majority of participants consideredthemselves to be sedentary to moderately active.

Experimental Design

The 10-week study protocol was approved by the Universityof Connecticut Institutional Review Board. Informed consentwas given by all participants. The first component, dietarymodification, entailed caloric restriction and modified macro-nutrient composition. Caloric need was estimated from theHarris-Benedict formula (utilized because of ease of use in theclinical setting), and multiplied by a low activity factor of 1.2.The expected energy distribution of the diet during the protocolwas 30% protein, 30% fat, and 40% carbohydrate. Carbohy-drate consumption was decreased to prevent inhibition from thefirst carnitine-dependent LCFA transport protein, carnitinepalmitoyltransferase I (CPT-I) [14, 20]. However, a moderatecarbohydrate restriction (40%) was chosen to help maintaindietary compliance. Participants received menus with expectedcaloric level and macronutrient composition. In addition, partici-pants received groceries specified in the menus except for skimmilk, condiments, butter or margarine. The second interventioncomponent was increased physical activity as monitored by apedometer. The third component, carnitine supplementation, uti-lized a double-blind, randomization to active (3 grams/day ofcarnitine) or placebo (3 grams/day of cellulose) pills.

On day zero, subjects were assigned a calorie level, andreceived a pedometer and the menus, groceries, and supplementfor that week. They were instructed to record any deviationsfrom the menu and to consume three active or placebo pillswith breakfast and lunch. Log sheets were provided to recorddaily supplement intake. Subjects continued collecting grocer-ies, menus, and supplements weekly.

Two separate fasting (12 h) blood samples were collectedduring weeks 1, 5, and 10. Blood was collected into tubescontaining 0.15 g/100 g EDTA. Plasma was separated bycentrifugation at 1,500 � g for 20 min at 4°C, and placed intovials containing PMSF (0.05 g/100g), sodium azide (0.01g/100g) and aprotonin (0.01g/100g). Samples were then placedinto �80° freezer until analysis. Plasma samples were used todetermine plasma lipids and hormone concentrations.

Dietary Assessment

Baseline dietary data was collected utilizing a 120 item foodfrequency questionnaire (FFQ) developed by the Fred Hutchin-son Cancer Research Center (Seattle, Washington). One par-ticipant did not have a complete FFQ and it was not included inthe analysis. Participants recorded how many times, on aver-age, in the past three months they had consumed each food

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listed. Participants selected serving size based on pictures ofsmall, medium, and large food items provided with the FFQ.Menus from 3 non-consecutive weeks during the interventionperiod (15 weekdays and 6 weekend days) were entered intothe Nutrient Database Systems (NDS) for Research, version4.05_33 (Nutrition Coordinating Center, University of Minne-sota) for analysis. Using NDS data, compliance with caloricrestriction and macronutrient composition was evaluated.

Physical Activity Assessment

Participants completed the IPAQ (short version, 4 items) onday zero to determine baseline activity. This IPAQ has beenshown to collect reliable and valid data on physical activity[19]. During the first week, baseline number of steps wasdetermined utilizing Omron HJ-104 pedometers (OmronHealthcare, Inc., Vernon Hills, IL). Each pedometer was cali-brated to individual participant’s stride according to the man-ufacturer’s instructions. Briefly, stride length was determinedfrom the amount of ground covered in 10 strides at the samepre-measured spot. Pedometers were calibrated at least oneother time during the protocol. The pedometer counts thenumber of steps/24 h period, after which, it resets to zero.Standard deviation is � 5% (personal communication withOmron Healthcare). This pedometer also has a 7-day memoryfunction. Daily log sheets were collected from participantsweekly. Subjects were selected at random to verify the reportednumber of steps/day compared to values saved in the 7 daymemory. At the beginning of week 2, participants were in-structed to walk 1500 additional steps than those at baseline.The steps/day goal was increased by 1500 steps two additionaltimes at weeks 4 and 6 for a total increase of 4500 steps/day.

Anthropomentric Measurements

Weight was measured to the closest 0.5 lb and height wasmeasured to the closest 0.5 inch on a portable stadiometer/scale[21]. Weight and height were converted into metric measures tocalculate BMI (kg/m2). Waist circumference (WC) was mea-sured midway between the lowest rib and iliac crest to thenearest 0.1 cm [21, 22]. Hip circumference was measured at thewidest point on the hip. These measurements were utilized forthe waist to hip ratio (WHR). Blood pressure was measured onthe right arm using a Welch Allyn, Tycos blood pressure cuff(Welch Allyn, Arden, North Carolina) with the participantseated, following a 5-minute rest.

Body Composition

Body composition was obtained utilizing dual X-ray ab-sorption (DXA) with a Lunar DPX-MD machine (GE MedicalSystems, Madison, WI). DXA is a reliable technology for bodycomposition in research [23] and data suggest that it has betterreproducibility than skinfold thickness, bioelectrical impedance[24], and near infrared interactance [25] in obese women. DXA

scans and analysis were performed in the Bone and MineralMetabolism Lab at the University of Connecticut. The upperweight limit for the table was 114 kg and subjects were posi-tioned to fit completely within the scanning area. Qualityassurance of the DXA machine was performed daily. Thecoefficients of variation for this study were 0.629% and0.268% for percent of total and trunk fat and 0.567% and0.916% for grams of total and trunk fat.

Plasma Glucose, Insulin and Leptin

Plasma glucose was determined enzymatically using Wakokits (Wako Chemicals USA, Richmond, VA) [26]. Plasmainsulin was measured using Linco RIA kits (Linco Research,Inc, St. Charles, MI) that utilize double-antibody/PEG tech-nique [27]. Plasma leptin was also analyzed utilizing LincoRIA kits and was very similar to the plasma insulin method.100 �L of plasma were incubated with 125I-labeled humanleptin, normal rabbit IgG and rabbit anti-human leptin serum.After overnight incubation, a precipitating reagent containinggoat anti-rabbit IgG serum was added; samples were mixed,and incubated for 20 min. Then, samples were centrifuged at2500 � g for 20 minutes, liquid was decanted, and tubescontaining the pellet were counted for 1 minute using a CobraII-Auto Gamma Counting System.

Classification of Subjects with Insulin Resistance orthe Metabolic Syndrome

Insulin resistance is defined as an impaired metabolic re-sponse to the body’s own insulin [28, 29] and is characterizedby decreased capacity of insulin to promote typical glucosedisposal. The homeostasis model assessment (HOMA) [30]was used to calculate insulin resistance according to the fol-lowing equation: HOMA insulin resistance � fasting insulin(�U/mL) � fasting glucose (mmol/L) � 22.5. HOMA has beenshown to be reliable for measuring insulin resistance in variouspopulations when more invasive methods are not feasible [30].Based on the equation, subjects were classified as havinginsulin resistance if calculated value was � 3.8 [31].

The subjects were classified as having the MS if 3 of the 5risk factors delineated by the Adult Treatment Panel III (ATPIII) were present: a fasting plasma glucose � 110 mg/dL(� 6.11 mmol/L), WC of � 88 cm, fasting TG � 150 mg/dL(� 1.70 mmol/L), fasting HDL-C of � 50 ( � 1.30 mmol/L)and blood pressure � 130 mm Hg (systolic) or � 85 mm Hg(diastolic) [32].

Plasma Lipids

Our laboratory has participated in the Centers for DiseaseControl - National Heart, Lung and Blood Institute Lipid Stan-dardization Program since 1989 for quality control and stan-dardization for plasma TC, HDL-C and TG assays. Coefficientsof variance during the study period were 0.76–1.42 for TC,

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1.71–2.72 for HDL-C and 1.64–2.47 for TG. TC was deter-mined enzymatically [33]. HDL-C was measured in the super-natant after precipitation of apo B-containing lipoproteins [34]and LDL-C was determined using the Friedewald equation[35]. TG were determined adjusting for free glycerol [36].

Urinary Carnitine

Urinary carnitine was determined by a spectrophotometricmethod. Briefly, 1 ml of perchloric acid was added to 1 ml ofsample and mixed. After centrifugation at 5,000 � g for 10 minat 4° C, 200 �l of 1.75 M of potassium phosphate was added tothe supernatant, mixed and centrifuged at 5,000 � g for 5 minat 4° C. 500 �l of the supernatant were then mixed with 2.5 �lof 5 M potassium hydroxide and incubated in a water bath for15 min at 60° C. Following incubation, 120 �l of perchloricacid were added, mixed and centrifuged at 5,000 � g for 5 minat 4° C. From this mixture, 100 �l were mixed with 1 ml of 0.1M Tris buffer and 100 �l of 1 mM DTNB. In a timed sequence,5 �l of carnitine acetyltransferase and 30 �l of acetyl-CoAwere added to this final mixture every 30 sec. Samples wereincubated at RT for 15 min and read on a Spectrophotometer(Biomate 3, Thermo Spectronic, Rochester, NY) at 412 nm.Calculations were performed to determine concentrations oftotal acid soluble carnitine (TASC) in �M.

Statistical Analysis

Values are reported as mean � standard deviation. Paired ttests compared changes in anthropometric, body compositionmeasurements and glucose, insulin, and leptin concentrationsbetween baseline and post-treatment. p � 0.05 was consideredsignificant. Utilizing paired t-tests and Pearson correlations, nostatistical significance was found due to L-carnitine supple-mentation in any of the measured parameters, therefore, datafor all 70 subjects were pooled to evaluate the effects of weightloss (due to dietary modifications and increased physical ac-tivity) in all measured parameters. Data were analyzed usingSPSS version 12.0 (SSPS, Chicago, IL). A non-parametric rankWilcoxon test was used to evaluate the number of subjectshaving metabolic syndrome and insulin resistance at baselineand post-intervention. A stepwise linear regression was con-ducted to evaluate the major determinants of weight loss (in-creased physical activity, caloric reduction, increased intake ofprotein or decreased intake of carbohydrate). Similarly,changes in hormones were evaluated by a stepwise linearregression to determine the major determinants of the observedreductions in leptin and insulin. All data were analyzed usingSPSS version 12.0 (SSPS, Chicago, IL).

RESULTS

The significant increase observed in urinary TASC in par-ticipants consuming carnitine strongly suggests protocol com-pliance. Urinary TASC significantly increased from 128.9 �

145.3 �M at baseline to 583.4 � 295.2 �M (p � 0.01) at 10weeks in participants taking carnitine,. Participants consumingthe placebo had a comparable baseline TASC value to thosetaking carnitine (113.6 � 77.6 �M). A the end of the interven-tion subjects taking the placebo had a significantly lower con-centration of TASC compared to the carnitine group (160.1 �

145.0 �M), p � 0.001). Because there were no significant maineffects due to active or placebo supplementation, all partici-pants were grouped together for analysis.

Baseline mean age, weight, and BMI were 29.4 � 8.8 years,79.4 � 11.1 kg, and 29.6 � 3.2 kg/m2, respectively. Meansystolic and diastolic blood pressures were 118.2 � 7.3 mm Hgand 76.6 � 6.9 mm Hg, respectively. There were no significantchanges in blood pressure at 10 weeks. Participants had a meandecrease in energy intake of 2288.1 kJ (�26.6%) (p � 0.01)(Table 1).

Expected caloric intake was 6453 kJ and actual intake was6304 kJ; this was a decrease from baseline (8592 kJ) as deter-mined by the FFQ. Compared to the expected macronutrientdiet composition (40%, 30%, 30%), the actual intake was42.1%, 28.1%, and 31.8% of carbohydrates, protein, and fat,respectively. The energy provided by carbohydrates decreasedby 17.3% (p � 0.01) and energy provided by protein increasedby 67.3% (p � 0.01). There was no change in total fat intakeduring the protocol (Table 1) because the significant decreasein saturated and polyunsaturated fat consumption was balancedby the significant increase in monounsaturated fat consumption(p � 0.01). Mean alcohol intake significantly decreased(� 86.1%, P � 0.01) from baseline as did mean intake ofdietary cholesterol (�32.5% p � 0.01). There was no change indietary fiber intake from baseline to 10 weeks.

From baseline to 10 weeks, there was a significant increase(42.6%) of steps/day (3816, p � 0.01). TC, LDL-C, and TG

Table 1. Comparisons of Dietary Intake and Number ofSteps/Day at Baseline and 10 Weeks1

Baseline 10 Weeks

Sample Size 69 69Total Calories (kJ) 8592.2 � 3149.5a 6304.1 � 502.7b

Carbohydrates (% Energy) 50.9 � 10.1a 42.1 � 1.2b

Total Fat (% Energy) 32.7 � 7.7 31.8 � 1.1Saturated Fat (%

Energy) 11.0 � 2.9a 9.7 � 0.5b

Monounsaturated Fat (%Energy) 12.3 � 3.2a 13.8 � 0.7b

Polyunsaturated Fats (%Energy) 6.8 � 1.9a 6.0 � 0.4b

Protein (% Energy) 16.8 � 3.3a 28.1 � 1.0b

Alcohol (% Energy) 1.8 � 2.8a 0.25 � 0.71b

Dietary Cholesterol (mg) 305.4 � 185.4a 206.2 � 16.9b

Dietary Fiber (g) 19.1 � 7.6a 19.8 � 1.9b

Steps Taken per Day 8950.9 � 3434.5a 12764.0 � 4642.1b

1Values are presented as mean � SD for N � 69 participants. Values in the same

row with different superscripts are significantly different as determined by paired

t-test (p � 0.01)

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decreased by 8%, 12.3%, and 19.5% (P � 0.01), respectively.Values were 4.7 � 1.0, 2.6 � 0.6, and 1.1 � 0.5 mmol/L atbaseline and 4.3 � 0.7, 2.3 � 0.6, and 0.7 � 0.1 mmol/L after10 weeks, respectively. In contrast, there were no changes inHDL-C from baseline to 10 weeks. Values were 1.57 � 0.28mmol\L at baseline and 1.59 � 0.32 mmol/L post-intervention.

Body weight, BMI, and WC decreased by 4.6% (p � 0.01),4.5% (p � 0.01), and 6.5% (p � 0.01), respectively (Table 2).Hip circumference and the WHR significantly decreased by 5%(p � 0.01) and 1.6% (p � 0.01), respectively. The interventionproduced no significant changes in bone mineral density butdid significantly change body composition measures (Table 3).Total body fat decreased by 4.0% (p � 0.001) and this corre-sponded to a decrease of 2.5 kg of fat mass (Table 3). Trunk fatalso decreased by 4.7% (p � 0.001), a decrease of 1.3 kg of fatmass. Although there was a loss of lean tissue grams, thepercent of lean tissue for whole body and trunk increasedrelative to fat mass by 3.0% and 3.4% respectively.

Plasma glucose levels did not change, but there were sig-nificant decreases in plasma concentrations of both insulin(17.9%, p � 0.01) and leptin (5.9%, p � 0.001) (Table 4). Atbaseline, 19 participants presented with insulin resistance ascalculated by the HOMA equation and 7 participants presentedwith the MS. Following the intervention, only 9 exhibited insulinresistance (P � 0.01) and 1 subject had the MS (P � 0.05). At 10weeks, the intervention resulted in a 53% decrease in participants

classified with insulin resistance and an 86% decrease in partici-pants classified with the MS (Fig. 1).

The major determinant of weight loss was the reduction indietary carbohydrate. Carbohydrate intake explained 7.2% ofthe changes in weight loss. No other parameter including num-ber of steps or reduction in calorie explained the changes inweight. For the changes in leptin there were two significantmodels. The first model was the changes in weight, whichexplained 43% of the changes, and the second one includedchanges in weight plus the change in number of steps taken perday (negative correlation). Thus the combination of weightreduction and increases in number of steps per day explained48% of the changes. Changes in trunk fat, total body fat, waistcircumference, glucose and insulin concentrations were notexplained by any factor.

DISCUSSION

Results from the current study show that moderate lifestylemodifications produce significant changes in weight, bodycomposition, BMI, WC and insulin and leptin concentrations,which led to a decreased number of participants classified withthe MetSyn and insulin resistance. Contrary to our initial hy-pothesis, carnitine supplementation did not significantly affectthe measured parameters; this finding is consistent with some

Table 3. Comparisons in Body Composition Parameters at Baseline and 10 Weeks1

Baseline 10 Weeks Percent Change Absolute Mean Change

Sample Size 70 70Total Body Fat (%) 42.8 � 5.0a 41.2 � 5.3b �4.0 1.6Total Body Fat (kg) 32.7 � 7.9a 30.3 � 7.9b �7.5 2.4Total Body Lean (%) 57.1 � 5.0a 58.8 � 5.3b 3.0 1.7Total Body Lean (kg) 42.5 � 4.5a 42.1 � 4.6b �0.96 0.4Trunk Fat (%) 41.7 � 4.5a 39.8 � 5.1b �4.7 1.9Trunk Fat (kg) 15.4 � 3.7a 14.1 � 3.9b �8.4 1.3Trunk Lean (%) 58.3 � 4.5a 60.2 � 5.1b 3.4 1.9Trunk Lean (kg) 20.8 � 2.4a 20.5 � 2.2b �1.7 0.3

1Values are presented as mean � SD for N � 70 participants. Values in the same row with different superscripts are significantly different as determined by paired t-test

(p � 0.001).2Percent change is the change seen at from baseline to ten weeks.3Absolute mean change is the change in values at 10 weeks from baseline.

Table 2. Comparison of Anthropometric Measures at Baseline and 10 Weeks1

Baseline 10 Weeks Percent Change2 Absolute Mean Change3

Sample Size 70 70Weight (kg) 79.4 � 11.1a 75.8 � 11.4b �4.6 3.6BMI (kg/m2) 29.6 � 3.2a 28.3 � 3.4b �4.5 1.3Waist Circumference (cm) 90.1 � 8.0a 84.3 � 7.8b �6.5 5.8Hip Circumference (cm) 110.7 � 9.6 105.1 � 9.4 �5.0 5.6Waist to Hip Ratio 0.817 � 0.070a 0.803 � 0.070b �1.59 0.014

1Values are presented as mean � SD for N � 70 participants. Values in the same row with different superscripts are significantly different as determined by paired t-test

(p � 0.01).2Percent change is the change seen at from baseline to ten weeks.3Absolute mean change is the change in values at 10 weeks from baseline.

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human and animal studies [18, 37]. One possible explanationcould be that carnitine is estimated to be 75% bioavailable indietary sources but only 5 to 18% bioavailable in supplementalsources [38]. Second, the intestinal carnitine transporter may besaturable [39]. All subjects consumed high amounts of carnitinein the designed diets, which were high in animal protein. Sinceall participants increased their protein intake by 67.3% regard-less of supplementation, the participants may have reachedtheir saturation points. Therefore, the participants may haveabsorbed the same amount of carnitine, while excreting theexcess supplemental carnitine.

The National Health and Nutrition Examination Surveys(NHANES) from 1971 to 2000 reported that females increasedcaloric intake by 21.7%, primarily due to increased carbohy-drate consumption [40]. Simultaneously, lifestyles have be-come increasingly sedentary [41]. From NHANES III (1988–1994) to NHANES 1999–2000, females aged 20 to 29 yearshad an 8.7% increase in obesity and those aged 30 to 39 yearsexperienced a 6.7% increase [42]. The largest increase (12.7%)was reported in women aged 60 to 69 years [42]. Thesestatistics suggest that females do not modify behavior as theyage and weight gain steadily continues. Strategies to promoteweight loss, weight maintenance, and changes in the biologicalparameters to enhance both need to be elucidated.

Andersen et al compared structured aerobic exercise toincreased lifestyle activity in overweight and obese adults [1,

5]. In one study, there was no significant difference betweengroups in relation to the amount of weight lost, loss of fat massor fat free mass, or resting energy expenditure [1]. In thesecond study, there was no difference between groups in re-gards to improvements in weight, TC, and TG [5]. Therefore,increased physical activity could be promoted for weight lossand other health benefits for obese persons since both struc-tured aerobic exercise and increased lifestyle activity promotesimilar benefits. In the current study, anthropometric and bodycomposition data also support increasing lifestyle activities.The significant weight loss of the participants was mirrored bysignificant decreases in BMI and WC. WC has been shown tobe a proxy measurement of abdominal obesity, especially vis-ceral fat [43], and is associated with insulin resistance anddyslipidemia [44]. After controlling for BMI, WC significantlypredicts CHD and DM2 [43]. A WC � 88 cm is consideredhigh risk and � 88 cm is normal risk [21]. In this population,there was a mean decrease of 6.5% (P � 0.01) in WC from90.1 � 8.0 cm to 84.3 � 7.8 cm, therefore making this groupat lower risk. The decrease in WC was partly responsible forthe significant decrease in incidence of MS seen in this studysince a WC of � 88 cm is one of the five risk factors for thismultifaceted syndrome. Elevated TG and decreased HDL-C arealso risk factors for the MS. With this weight loss program, themean TG concentration decreased and there was no significantchange in mean HDL-C concentration. Other weight loss stud-ies utilizing low-fat diets have resulted in decreased plasmaHDL-C concentrations possibly due to decreased dietary fatintake [45]. HDL-C concentrations remained the same, possi-bly because our participants maintained dietary fat intake andincreased their exercise.

The body composition changes also provide support formodest lifestyle modifications. Though there were significantdecreases in grams of fat free mass, the overall percent of fatfree mass increased. Some loss of lean tissue during weight lossis unavoidable, but maintaining as much lean tissue as possibleis essential [46]. It is suggested that loss of lean tissue shouldnot exceed 30% of total mass loss. In agreement with theserecommendations, our population’s lean tissue loss accountedfor 14.2% of total mass loss (lean body mass lost/total bodymass lost * 100) and for 21.7% (trunk lean mass lost/total trunkmass lost * 100) of mass loss in the trunk.

Although no significant decrease in plasma glucose concen-trations occurred, insulin and leptin concentrations significantly

Fig. 1. Frequency of Insulin Resistance (black bar) and the MetabolicSyndrome (hatched bar) at Baseline and 10 Weeks post-intervention.Both insulin resistance (**p �0.01) and the metabolic syndrome (*p �

0.05) were significantly different post-intervention.

Table 4. Comparisons of Glucose, Insulin, and Leptin Concentrations at Baseline and 10 Weeks1

Baseline 10 weeks Percent Change Absolute Mean Change

Sample Size 70 70Glucose (mmol/L) 4.92 � 0.97 4.77 � 0.61 �2.8 0.15Insulin (�M/mL) 14.7 � 9.0a 12.0 � 6.5b �17.9 2.7Leptin (�g/L) 15.3 � 5.9a 14.4 � 6.8b �5.9 0.9

1Values are presented as mean � SD for N � 70 participants. Values in the same row with different superscripts are significantly different as determined by paired t-test

(p � 0.05). 2Percent change is the change seen at from baseline to ten weeks. 3Absolute mean change is the change in values at 10 weeks from baseline.

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decreased by 17.9% and 5.9%, respectively. Insulin activity hasbeen shown to decrease in the obese state, due to a decrease inlipolysis activation [47]. Furthermore, decreased body fat hasshown to increase lipolysis efficiency [10]. Volek et al [48]explored the effects of a very low carbohydrate diet on bodycomposition and insulin response and postulated that the ob-served decreases in insulin concentrations may have influencedboth weight and fat mass loss. Similar effects were observed inthe current study. The decreased carbohydrate intake withincreased protein intake reduced concentrations of insulin,thereby contributing to the overall weight loss and reduction infat mass. Leptin concentrations are higher in females than inmales, which may affect leptin transport into the central ner-vous system [12]. Therefore, larger reductions in leptin need tobe experienced by females to effect energy balance [12]. Thedecrease in insulin concentrations may have been responsiblefor the significant decrease in number of subjects with insulinresistance. Because unmanaged insulin resistance can result inDM2, weight loss strategies, such as the one utilized in thisstudy, need to be further researched.

In conclusion, an intervention consisting of a moderatehypocaloric diet with modified macronutrient composition, inaddition to increased daily physical activity, successfully im-pacted multiple risk factors for DM2 and CHD. The currentweight loss intervention beneficially changed body composi-tion, plasma lipids, and insulin and leptin concentrations. Mostimportantly, the number of subjects classified with insulinresistance and the metabolic syndrome were substantially re-duced. This study suggests that moderate lifestyle changes, iffollowed and maintained, can decrease the risk for chronicdisease.

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Received May 17, 2005; accepted October 18, 2005

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