Low-Density Lipoprotein Subclass Distribution Pattern

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Original Research

Low-Density Lipoprotein Subclass Distribution Patternand Adiposity-Associated Dyslipidemia in

Postmenopausal Women

Kevin C. Maki, PhD, Michael H. Davidson, MD, Mary Sue Cyrowski, RD, Ann C. Maki, MS, RD, Phyllis Marx, MD

Chicago Center for Clinical Research, Chicago, Illinois

Key words: lipoproteins, hyperlipidemia, obesity, body fat distribution

Objective: A predominance of small, dense low-density lipoprotein (LDL) particles (subclass pattern B) isassociated with increased risk for coronary heart disease and is characterized by elevated triglycerides anddepressed high-density lipoprotein (HDL) cholesterol concentrations. The present analysis was undertaken toassess the impact of LDL subclass distribution pattern and adiposity on serum lipids in postmenopausal women.

Methods: Anthropometric measurements and fasting lipid data were obtained from 254 postmenopausalwomen 70 years of age or younger, not receiving sex hormone replacement, who were participating in a clinicaltrial designed to assess the influence of hormone replacement regimens on coronary heart disease risk markers.

Results: The prevalence of LDL subclass pattern B was 32%. Triglyceride levels were higher and HDLcholesterol lower (both p 0.001) in women with pattern B vs. pattern A, but total and LDL cholesterol levelsdid not differ. LDL subclass pattern contributed independently to the variance in HDL cholesterol ( p 0.001) andlog e triglyceride ( p 0.001) concentrations explained by anthropometric variables (waist circumference or bodymass index). Compared to women with LDL subclass pattern A and waist circumference below the median valueof 83.0 centimeters, those with pattern B and waist 83.0 centimeters had markedly lower HDL cholesterollevels [44.0 (41.647.4) vs. 57.2 (54.160.3) mg/dL, mean (95% CI)] and increased triglyceride concentrations[geometric mean 147.8 (131.6165.7) vs. 95.4 (88.2102.5) mg/dL].

Conclusions: These data suggest that adiposity and LDL subclass distribution pattern are independentdeterminants of plasma triglyceride and HDL cholesterol concentrations in postmenopausal women.

INTRODUCTION

A predominance of small, dense low-density lipoprotein(LDL) particles (LDL subclass pattern B) is associated with a2- to 3-fold increase in risk for coronary heart disease [14].LDL subclass pattern B is also characterized by several abnor-malities of the plasma lipid profile, notably elevated triglycer-ides and depressed high-density lipoprotein (HDL) cholesterolconcentrations [14] as well as other metabolic disturbancesincluding insulin resistance, glucose intolerance and a hyper-coagulable state [57]. In addition, small, dense LDL particlesmay have heightened atherogenicity due to greater susceptibil-ity to oxidative modification and higher affinity for arterial wall

proteoglycans [8]. Thus, the increased risk of coronary heartdisease associated with the LDL pattern B phenotype may besecondary to the atherogenic influence of small, dense LDLparticles, the cluster of metabolic disturbances which accom-pany this phenotype or a combination of these factors [910].

Family studies have shown linkage of LDL particle size toloci on chromosomes 6, 11, 16 and 19 [8]. One-third to one-half of the variance in peak LDL particle diameter is explained bygenetic factors [1011]. Excess body fat, particularly abdom-inal fat, is associated with LDL subclass pattern B, as well aselevated triglycerides and depressed HDL cholesterol [1214].

Katzel and colleagues studied the interaction between LDLsubclass pattern and adiposity among 160 men [15]. Those with

Abbreviations: BMI body mass index, EPAT Eating Pattern Assessment Tool, HDL high-density lipoprotein, LDL low-density lipoprotein, Log e natural logarithm,MET metabolic equivalents.

Funding for this research was provided by Novo Nordisk Pharmaceuticals, Inc., Princeton, NJ.

Address reprint requests to: Kevin C. Maki, PhD, Chicago Center for Clinical Research, 515 North State Street, 27 th Floor, Chicago, Illinois 60610.

Journal of the American College of Nutrition, Vol. 19, No. 1, 2330 (2000)Published by the American College of Nutrition

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LDL subclass pattern B had higher triglycerides and lowerHDL cholesterol at any level of adiposity (percent body fat),compared to those with LDL pattern A [15]. These data supportthe concept that the genetic factors underlying LDL subclassdistribution amplify the unfavorable effects of obesity on tri-glyceride and HDL cholesterol concentrations in men. Thismay have implications for coronary heart disease risk, partic-ularly in light of the rapidly growing body of evidence dem-onstrating the importance of triglyceride-rich lipoproteins inthe atherogenic process [16].

The present analysis was designed to test the hypothesis thatpostmenopausal women with LDL subclass pattern B wouldhave greater disturbances of the plasma lipid profile (highertriglycerides and lower HDL cholesterol) than women withLDL pattern A at any level of adiposity. A secondary objectivewas to assess and compare the utility of body mass index andwaist circumference as indicators of adiposity-related dyslipi-demia in postmenopausal women.

MATERIALS AND METHODS

The dataset used for these analyses consisted of informationcollected at baseline from a group of 270 postmenopausalwomen who participated in a clinical trial designed to assessthe influence of three hormone replacement regimens on cor-onary heart disease risk markers. All subjects provided writteninformed consent and the study protocol was approved by aninstitutional review board (Schulman Associates, Cincinnati,OH). An additional 229 women were screened but did notqualify for participation.

Eligible women were less than 71 years of age with naturalor surgically-induced menopause at least 12 months prior torandomization, confirmed by a plasma estradiol level 20pg/mL. Exclusion criteria included use of hormone replacementor lipid-altering agents within 10 weeks of the baseline plasmalipid measurements. Also excluded were women whose bodymass index was 31.5 kg/m 2 , who were heavy smokers ( 20cigarettes per day) or alcohol users ( 14 alcoholic drinks perweek) or who engaged in substance abuse. Women with un-controlled hypertension (systolic pressure 160 mm Hg, ordiastolic pressure 95 mm Hg) or elevated triglycerides ( 350mg/dL at two consecutive visits) were excluded. Other medicalconditions excluding participation were history of stroke, pan-creatitis, gallbladder disease, thrombophlebitis or thromboem-bolic disorders, myocardial infarction within six months, ab-normal genital bleeding of unknown etiology, an abnormalmammogram suspicious for malignancy, the presence of he-patic enzymes more than twice the upper limit of normal,diabetes mellitus or other endocrine disease (except hypothy-roidism adequately treated with a stable dose of thyroid re-placement), and significant psychiatric disorders. Women usingbeta-adrenergic blockers, high doses of thiazide diuretics ( 25mg/d of hydrochlorothiazide or its equivalent), erythromycin,

immunosuppressants, systemic corticosteroids or anticoagu-lants were also excluded.

Blood for baseline biochemical measures, including aplasma lipid profile, glucose, insulin, and hemoglobin A 1C , wascollected after an overnight fast at two baseline visits, approx-imately 14 days apart. The mean of two values obtained onseparate days was used in the analyses for all biochemicalvariables except LDL subclass distribution pattern and hemo-globin A 1C , which were measured once at the final baselinevisit. Plasma lipid profiles included total cholesterol, HDLcholesterol, triglycerides and calculated values for LDL cho-lesterol. LDL subclass pattern was determined once from aplasma sample obtained at the final baseline visit.

Biochemical Analyses

Except for LDL subclass distribution, all biochemical as-says were completed by Quest Nichols Institute, San Juan

Capistrano, CA. Quest Nichols Institute participates in theCenters for Disease Control and Prevention/National Heart,Lung, and Blood Institute lipid measurement standardizationprogram. LDL subclass distribution measurements were com-pleted by Atherotech, Inc., Birmingham, AL.

The Vertical Auto Profile II method was used to assess theconcentration of cholesterol carried in large, buoyant (LDL 1and LDL 2 ) and small, dense (LDL 3 and LDL 4 ) LDL particles,as described elsewhere in detail [1718]. Briefly, the VerticalAuto Profile II method utilizes single vertical spin densitygradient ultracentrifugation to separate the various plasma li-poprotein fractions. After centrifugation, the cholesterol con-tent of the tube is continuously analyzed and digitized. Acholesterol absorbance curve profile is generated by plottingdigitized absorbance units on the Y axis and the relative gra-dient position on the X axis. A deconvolution program is usedto separate the different lipoprotein classes and subclasses.Subjects with 50% of their LDL cholesterol in the small,dense fractions (LDL 3 LDL 4 ) were classified as having thesmall, dense LDL phenotype (LDL subclass pattern B).

Plasma cholesterol, triglyceride and glucose concentrationswere determined with a Hitachi 914 analyzer (BoehringerMannheim, Indianapolis, Indiana) which employs enzymaticmethods. HDL cholesterol was quantified after precipitation of lower-density lipoproteins with phosphotungstate and magne-sium. LDL cholesterol in mg/dL was calculated using thefollowing equation: LDL cholesterol total cholesterol HDLcholesterol triglycerides/6.25 [19]. This equation loses accu-racy when the plasma triglyceride level exceeds 400 mg/dL.Accordingly, no LDL cholesterol value was calculated in caseswhere triglycerides were above this level. Hemoglobin A 1Cwas measured with a VARIANT Analyzer (Bio-Rad Labora-tories, Hercules, CA) by ion exchange high performance liquidchromatography. Plasma insulin concentration was assessed byradioimmunoassay (Linco Scientific, St. Charles, MO).

LDL Subclass Pattern B

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Questionnaires

Subjects completed a standard medical history question-naire that was used to identify possible exclusion criteria and toassess smoking and alcohol consumption habits. The StanfordSeven-Day Physical Activity Recall questionnaire was used toestimate energy expended during sleep, light, moderate, hard

and very hard activities [20]. Hours of activity in each categorywere multiplied by constants to produce estimates of energyexpenditure. Estimated energy expenditure from each of thesecategories was then summed to produce a physical activityscore in metabolic equivalent-hours per week (one metabolicequivalent-hour represents approximately one kilocalorie perkilogram of body weight). Dietary intake was assessed withsection one of the Eating Pattern Assessment Tool thatconsists of questions relating to intake of foods in 11 categories[21]. Lower scores indicate lower consumption of foods high infat, saturated fats and cholesterol. A score of approximately 28or below is consistent with the dietary recommendations of the

National Cholesterol Education Program.

Anthropometric Measurements

Body weight and height were measured in light clotheswithout shoes. Body mass index was calculated as weight inkilograms divided by squared height in meters. Waist wasmeasured in duplicate at the minimum circumference betweenthe lowest rib and the iliac crest. If values differed by more than0.5 cm, a third measurement was obtained, and the two closestvalues were averaged.

Statistical Methods

Statistical analyses were completed using the Statview 4.5(Abacus Concepts, Berkeley, CA) and JMP 3.1 (SAS Institute,Cary NC) software packages. Plasma insulin, triglycerides andphysical activity score were not normally distributed. Naturallogarithm transformations produced acceptable distributionsfor insulin and triglycerides, but not physical activity score.Accordingly, physical activity score was ranked, and the rankswere used in multivariate analyses. Analysis of variance,Mann-Whitney U and Pearson chi-square tests were employedto assess differences in characteristics of subjects with LDLsubclass patterns A and B.

Least squares linear regression models were fit for log etriglyceride, HDL cholesterol and LDL cholesterol in order totest the null hypothesis that the regression lines for waistcircumference and body mass index on plasma lipid levels werecoincident for women with LDL subclass patterns A and B[22]. A single regression model approach was used as describedby Kleinbaum and colleagues [22]:

y 1 x1 2 x2 3 x1 x2 error

where y is the lipid variable under investigation, x 1 is ananthropometric variable (waist or body mass index) and x 2 is

LDL subclass pattern (0 A, 1 B). If the coincident lineshypothesis was rejected, additional tests were run to assesspossible differences in slopes and intercepts. F-ratios calculatedfor these tests used the mean squared error from the full modelas the denominator [22]. Separate regression models were alsofit for women with the two LDL subclass patterns. Correlationcoefficients are reported to express the strength of the relation-ship between anthropometric measures and plasma lipid vari-ables within LDL subclass categories. Analysis of variance wasemployed to assess the influence of adiposity and LDL subclassdistribution pattern on mean serum lipid concentrations using amedian split to classify women into high and low catego-ries for waist and body mass index.

The investigators felt that the deconvolution model em-ployed to assess LDL subclasses provided a poor fit to theobserved data for 12 subjects. Separate analyses were com-pleted for which these women were excluded. Since doing sodid not materially alter the results, only data from the full studysample are presented.

RESULTS

LDL subclass distribution was not measured for 12 of the270 women randomized because an inadequate volume of plasma was available. An additional four women were ex-cluded from the analyses because data for height were unavail-able. Therefore, the analyses presented herein represent datafrom 254 subjects.

Characteristics of the study sample categorized by LDL

subclass pattern are shown in Table 1. The prevalence of LDLsubclass pattern B was 32%. Women with pattern B wereslightly, but not significantly, older than those with pattern A.Dietary fat intake, as indicated by the Eating Pattern Assess-ment Tool, alcohol consumption and prevalence of currentcigarette smoking did not differ between LDL subclass groups.Body mass index ( p 0.037) and waist circumference( p 0.031) were significantly higher among women with LDLpattern B, while physical activity score was lower ( p 0.007).The race/ethnicity of subjects in both LDL subclass categorieswas predominantly caucasian (non-Hispanic white). Use of antihypertensive medication and history of atherosclerotic dis-ease were infrequent in both groups ( 8%). Differences werenot significant, but the prevalence of these characteristics tended tobe higher among subjects with LDL subclass pattern A.

Table 2 summarizes the biochemical characteristics of theparticipants grouped by LDL subclass pattern. Women withLDL subclass pattern B did not differ from pattern A subjectswith regard to total cholesterol, non-HDL or LDL cholesterollevels. However, women with pattern B had marked elevationsin the concentration of cholesterol carried in the small, dense LDLfractions (LDL 3 LDL 4 , p 0.001), with proportionately less car-ried in the larger, more buoyant fractions (LDL 1 LDL 2 ,


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p 0.001). Women with LDL pattern B also showed the otherlipid abnormalities which characterize this phenotype, includingdepressed HDL cholesterol, elevated triglycerides and increasedtotal/HDL cholesterol ratio (all p 0.0001). Fasting plasma glu-cose ( p 0.031), insulin ( p 0.002) and hemoglobin A 1C

( p 0.016) levels were also significantly higher among those withLDL subclass pattern B.

The two anthropometric indicators used to assess adiposity,waist and body mass index, were significantly correlated in thissample (r 0.77, p 0.001). The null hypothesis of coincidentregression lines was not rejected for waist or body mass indexin relation to LDL cholesterol, but was rejected ( p 0.001) forboth anthropometric measures in relation to HDL cholesteroland log e triglycerides (Table 3). For these lipid parameters,intercepts of the regression lines were significantly differentbetween LDL subclass patterns A and B ( p 0.001). The re-gression lines for waist and body mass index did not differsignificantly in slope between the two LDL subclass groups.Nevertheless, for both anthropometric measures, clear trendswere present toward steeper slopes among women with LDLsubclass pattern B, with p-values for the non-parallelism testranging from 0.09 to 0.24. The relationships between waistcircumference and log e serum triglyceride and HDL cholesterolconcentrations according to LDL subclass distribution pattern

are shown graphically in Fig. 1 and 2.

Table 1. Characteristics of the Study Sample according toLow-Density Lipoprotein Subclass Pattern

VariableLDL Subclass

Pattern An 173

LDL SubclassPattern B

n 81

pValue

Age 1 58.9 (6.3) 60.2 (5.9) 0.118

Body mass index1

,(kg/m 2 ) 25.7 (3.3) 26.6 (2.8) 0.037Waist 1 , (cm) 82.3 (9.6) 85.1 (9.2) 0.031EPAT score (part 1) 1 22.8 (5.1) 22.2 (4.9) 0.347Alcohol intake 2 ,

ounces/week 1.0 0.3 0.478

(0.0, 3.0) (0.0, 3.0)Physical Activity 2 ,

(MET-hour/week)279.8 268.8 0.007

(257.0, 310.8) (249.1, 291.3)Caucasian, % 83.8 87.0 0.837Current smoker, % 14.2 13.8 0.924Antihypertensive

medication use, % 7.4 5.0 0.556History of

atheroscleroticdisease, % 6.9 2.5 0.154

Abbreviations: EPAT Eating Pattern Assessment Tool; LDL low-density li-poprotein; MET metabolic equivalents.1 Values are mean (SD).2 Values are median (25 th , 75 th percentile).

Table 2. Biochemical Characteristics of the Study Sampleaccording to Low-Density Lipoprotein Subclass Pattern

VariableLDL Subclass

Pattern An 173

LDL SubclassPattern B

n 81

pValue

Total cholesterol 1 (mg/dL) 228.5 (38.3) 224.9 (43.4) 0.495Non-HDL cholesterol 1

(mg/dL)172.9 (40.0) 177.7 (44.1) 0.381

LDL cholesterol 1 (mg/dL) 155.0 (36.3) 152.9 (38.3) 0.674LDL 1 LDL 2 cholesterol

1

(mg/dL)74.0 (19.0) 39.2 (15.7) 0.001

LDL 3 LDL 4 cholesterol1

(mg/dL)37.9 (15.9) 71.6 (19.6) 0.001

HDL cholesterol 1 (mg/dL) 55.7 (14.2) 47.1 (12.5) 0.001Triglycerides 2 (mg/dL) 98.9 133.8 0.001

(93.3, 104.6) (121.0, 147.8)Total/HDL cholesterol

ratio 14.35 (1.32) 5.07 (1.60) 0.001

Fasting plasma glucose 1

(mg/dL)92.7 (9.3) 96.6 (11.1) 0.031

Fasting plasma insulin 2

(mU/L)12.2 14.3 0.002

(11.6, 12.9) (13.0, 15.6)HbA 1c

1 , % 5.59 (0.47) 5.74 (0.51) 0.016

Abbreviations: HbA 1C hemoglobin A 1C ; HDL high-density lipoprotein;LDL low-density lipoprotein.1 Values are mean (SD).2 Values are geometric mean (95% confidence interval).

Table 3. Results of Least Squares Linear RegressionAnalyses Showing the Relationships between AnthropometricIndicators and Plasma Lipid Variables according to Low-Density Lipoprotein Subclass Pattern

Independent Variableand LDL Subclass

PatternIntercept Slope Pearson r

pValue

Dependent Variable LDL CholesterolConcentration (mg/dL)

Waist (cm)

Pattern A 159.7 0.057 0.015 0.845Pattern B 120.3 0.384 0.091 0.427

BMI (kg/m 2 )Pattern A 142.6 0.473 0.043 0.574Pattern B 156.7 0.142 0.010 0.926

Dependent Variable HDL CholesterolConcentration (mg/dL)

Waist (cm)Pattern A 80.3 0.300 0.202 0.008Pattern B 98.4* 0.602 0.439 0.001

BMI (kg/m 2 )Pattern A 82.5 1.037 0.244 0.001Pattern B 99.5* 1.968 0.448 0.001

Dependent Variable Log e TriglycerideConcentration (mg/dL)

Waist (cm)Pattern A 4.19 0.005 0.124 0.107Pattern B 3.47* 0.017 0.335 0.003

BMI (kg/m 2 )Pattern A 4.04 0.021 0.192 0.012Pattern B 3.77* 0.042 0.264 0.017

Abbreviations: BMI body mass index; HDL high-density lipoprotein;LDL low-density lipoprotein; log e natural logarithm.* Significantly different from value for those with LDL subclass pattern A( p 0.001).


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LDL cholesterol did not correlate significantly with anthro-pometric indicators of adiposity within either LDL subclasscategory ( p values 0.40). HDL cholesterol concentration wassignificantly inversely correlated with waist girth and bodymass index within both LDL subclass groups ( p 0.01). Sig-nificant positive associations were present for waist and bodymass index with log e triglyceride concentration among womenwith LDL subclass pattern B ( p 0.02). Among women withLDL subclass pattern A, log e triglyceride concentration wasassociated with body mass index ( p 0.02), but the associationdid not reach the 5% level of significance for waist circumfer-ence ( p 0.107, p 0.10).

Waist circumference alone explained 8.6% of the variancein HDL cholesterol and 5.2% of the variance in log e triglycer-ide concentration ( p 0.001 for both). The addition of LDLsubclass pattern significantly ( p 0.001) increased the varianceexplained in HDL cholesterol and log e triglyceride concentra-tions to 14.1% for each. Body mass index alone explained

10.2% ( p

0.001) of the variance in HDL cholesterol and 5.9%( p 0.001) of the variance in log e triglyceride concentration.The combination of body mass index and LDL subclass patternexplained 16.3% of the variance in HDL cholesterol and 15.6%of the variance in log e triglyceride concentration ( p 0.001 forthe additional variance explained by LDL subclass pattern inboth models).

Analysis of variance using waist or body mass index des-ignated low and high based on a median split for the entirestudy sample and LDL subclass distribution pattern as inde-pendent variables was performed with lipid values as depen-dent variables. Results from these analyses are shown in Table4. No significant main effects were present for anthropometricmeasures or LDL subclass pattern with respect to LDL choles-terol concentration. Significant main effects were present foranthropometric measures (waist and body mass index) andLDL subclass pattern for both HDL cholesterol and triglycer-ides. As was the case for the linear regression analysis, theinteraction terms for waist or body mass index with LDLsubclass pattern did not reach the 5% level of significance withregard to HDL cholesterol or triglyceride concentrations ( pvalues all 0.14 or higher).

DISCUSSION

The results of the present investigation support the hypoth-esis that postmenopausal women with LDL subclass pattern Bwould have greater disturbances of the plasma lipid profile thanwomen with LDL pattern A. These results concur with thosefor men published by Katzel and colleagues [23]. Both studiesshowed that LDL subclass pattern B was associated with higherlevels of triglycerides and lower HDL cholesterol for a givendegree of adiposity. Differences were apparent even amongthose with body mass index and waist circumference in thenon-obese range. These cross-sectional studies add support tothe hypothesis that the genetic factors which predispose toexpression of the small, dense LDL phenotype enhance thedeleterious effects of increased adiposity on triglyceride andHDL cholesterol concentrations in men and women.

The lipid profile which characterizes LDL subclass patternB (elevated triglycerides, depressed HDL cholesterol and apredominance of small, dense LDL particles) reflects an un-derlying metabolic state which may influence responsiveness topreventive therapies and prove useful for guiding treatmentselection. Katzel and colleagues [23] found that a 10 kg weight

Fig. 1. Results of regression analyses for the relationship between waistcircumference and log e triglycerides according to LDL subclass distri-

bution pattern.

Fig. 2. Results of regression analyses for the relationship between waistcircumference and HDL cholesterol according to LDL subclass distri-bution pattern.




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loss produced changes of 15% and 34% in triglyceridelevels among obese men with LDL subclass patterns A and B,respectively ( p 0.01). However, the increase in HDL choles-terol was smaller among men with LDL pattern B (16% vs.10%, p 0.05).

Dreon et al. [24] showed that men with LDL subclasspattern B while consuming a reference diet high in fat (46% of energy) had a more favorable plasma lipid response uponswitching to a low-fat diet (24% of energy) than did men withpattern A during the reference diet phase. Men with pattern Bhad larger reductions in LDL cholesterol and apolipoprotein Band a trend toward a smaller decline in HDL cholesterol. Thesame group of investigators showed that the LDL cholesterolresponse to switching from a self-selected diet to one low in fatand high in carbohydrate differed according to parental LDLsubclass pattern in premenopausal women [25]. Women withtwo parents having LDL subclass pattern B showed the largestLDL cholesterol change ( 36 mg/dL). Those with one patternB parent showed an intermediate response ( 9 mg/dL), whilethe LDL response was minimal ( 2 mg/dL) in women whoseparents both had LDL subclass pattern A. In the Stanford

Coronary Risk Intervention Program, intensive risk factor mod-ification ( vs. usual care) retarded coronary artery disease pro-gression among subjects with a predominance of dense LDL(subclass pattern B) at baseline (0.008 vs. 0.054 mm/y, p 0.007). No benefit was observed among subjects with apredominance of buoyant LDL upon entry (0.038 vs. 0.0039mm/y) [26].

The present study shows a clear, additive influence of LDLsubclass pattern B on the dyslipidemia associated with in-creased adiposity. Trends were also present in this sampletoward multiplicative interactions, i.e., greater worsening of thelipid profile (HDL cholesterol and triglycerides) with increas-ing waist circumference or body mass index among womenwith LDL subclass pattern B, compared to those with pattern A.

The women studied were taking part in a clinical trial, andthe range of adiposity in the sample was restricted because atrial exclusion criterion prevented enrollment of women withbody mass index 31.5 kg/m 2 . Restriction of the range of adiposity would tend to reduce the power to detect non-paral-lelism in the regression lines. Therefore, it is likely that thefailure to detect a significant multiplicative interaction is due to

Table 4. Serum Lipid Values according to Anthropometric Indicators and LDL Subclass Distribution Pattern

Independent Variables

Anthropometric Variable Main Effects

Low High p Value

Waist or BMI p Value

LDL Pattern

LDL Cholesterol (mg/dL)Mean SEM

Waist 0.677 0.746Pattern A 155.6 3.7 154.2 4.2Pattern B 154.7 7.0 151.7 5.7

BMI 0.744 0.749Pattern A 153.9 4.0 155.6 3.9Pattern B 155.7 6.8 150.7 5.4

HDL Cholesterol (mg/dL)Mean SEM

Waist 0.007 0.001Pattern A 57.2 1.6 53.2 1.3Pattern B 50.8 2.6 44.5 1.5

BMI 0.001 0.001Pattern A 58.4 1.7 52.9 1.2

Pattern B 51.0 2.4 44.0 1.5Triglycerides (mg/dL)

Geometric Mean (95% CI)

Waist 0.004 0.001Pattern A 95.4 103.4

(88.2, 102.5) (95.6, 112.2)Pattern B 115.9 147.8

(97.2, 138.2) (131.6, 165.7)BMI 0.029 0.001

Pattern A 93.4 103.9(86.5, 101.5) (96.0, 112.3)

Pattern B 124.3 141.7(103.5, 148.4) (127.7, 157.6)

Abbreviations: BMI body mass index; HDL high-density lipoprotein; LDL low-density lipoprotein.


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insufficient statistical power. Additional research will beneeded covering a wider range of adiposity to more fullycharacterize the influence of LDL subclass pattern on thedyslipidemia associated with increased adiposity.

A secondary objective of the current study was to comparethe utility of waist circumference and body mass index forpredicting adiposity-related alterations in the serum lipid pro-file. Body mass index reflects total adiposity, whereas waistcircumference is a measure of both total and abdominal adi-posity. These two measures were strongly correlated in oursample (r 0.77, p 0.001), and both were significantly asso-ciated with increased triglyceride and depressed HDL choles-terol concentrations. Neither waist circumference nor bodymass index correlated significantly with the LDL cholesterollevel.

Our group has previously shown that the LDL cholesterolconcentration was directly related to measures of adiposity in agroup of younger (18 to 49 years) men, but that this relationshipwas absent in men 50 and older [27]. Most women in the

present sample were 50 years of age or older. Thus, adipositydoes not appear to be a determinant of the LDL cholesterollevel among older persons of either gender. Based on these datait might be anticipated that weight loss would not produce thesame degree of LDL cholesterol-lowering among older indi-viduals that it does in young adults. Indeed, a meta-analysis of trials investigating blood lipid responses to weight loss showedthat the mean LDL cholesterol response was larger for youngersubjects ( 25 mg/dL) than those middle-aged or older ( 8mg/dL) [28].

CONCLUSIONS

In the current study, LDL subclass pattern B and anthropo-metric indicators of adiposity (waist or body mass index) wereindependent predictors of HDL cholesterol and triglyceridelevels in postmenopausal women. However, no significant re-lationship was observed between LDL cholesterol and mea-sures of adiposity. Non-significant trends were present towardgreater worsening of HDL cholesterol and triglyceride levelswith increasing adiposity among women with LDL subclasspattern B, compared to those with pattern A. Body mass indexand waist circumference showed similar relationships to tri-

glyceride and HDL cholesterol concentrations, suggesting thateither measurement may be used for assessing the risk of adiposity-related dyslipidemia in postmenopausal women.

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Received June 1999; revision accepted November 1999.


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Low-Density Lipoprotein Subclass Distribution Pattern