Am J Clin Nutr l997;66:837-44. Printed in USA. © 1997 American Society for Clinical Nutrition 837

Carrying the burden of cardiovascular risk in old age:associations of weight and weight change with prevalentcardiovascular disease, risk factors, and health status inthe Cardiovascular Health Study�3

Tamara B Harris, Peter J Savage, Grethe S Tell, Mary Haan, Shiriki Kumanyika, and James C Lynch

ABSTRACT Measured weight in old age, reported weight at

age 50 y, and weight change from age 50 y to old age were studiedin association with prevalent cardiovascular disease (CVD), CVDrisk factors, and health status in a population of 4954 men andwomen aged � 65 y in the Cardiovascular Health Study (CHS).Heavier weight (ie, generally weight in the fourth quartile for thecohort) at age 50 y was more closely associated with prevalentCVD than was current weight, with these associations stronger in

women than in men. Heavier current weight and heavier weight at

age 50 y were associated with cardiovascular risk factors, includ-

ing higher blood pressure, lower high-density-lipoprotein choles-terol, and higher fasting insulin. Heavier weight at both time pointswas related to mobility problems in both men and women and to

lower current physical activity levels; among women, strong as-

sociations were also seen with lower education and current in-come. Remaining within 10% of reported weight at age 50 y wasassociated with better health status as measured by reported health,

mobility difficulty, number of medications, and prevalent CVD in

men. Paradoxically, most cardiovascular risk factors were lowest

for weight losers despite an association of weight loss with poorerhealth. In this cohort of persons aged � 65 y, heavier weight wasassociated with CVD and CVD risk factors, suggesting that pre-vention of overweight may prove beneficial in improving cardio-vascular risk in older persons. Weight stability from age 50 y to old

age was associated with better health status than was weight gain

or loss. Am J Clin Nutr l997;66:837-44.

KEY WORDS Weight, aging, cardiovascular disease, cor-

onary artery disease, health status, obesity, Cardiovascular

Health Study, humans, risk factors, elderly

INTRODUCTION

Cardiovascular disease (CVD) is a major cause of morbidity,disability, and mortality in older persons (1, 2). There is a

continuing need to identify modifiable risk factors that canlessen this burden. Body weight is potentially an ideal modi-fiable risk factor in that weight tends to increase during the life

span through late middle age (3). Although there are fewstudies specific to older persons, “heavier weight” (ie, gener-ally a body mass index � 27) and increased waist circumfer-

ence have been linked to multiple other cardiovascular risk

factors common in old age, including elevated blood pressure,

lipid abnormalities (4), and glucose intolerance (5). Under-

standing the correlates of CVD risks related to overweight in

old age is important because the proportion of overweight

persons aged 60-74 y in the US population has increased from

25% (1976-1980) to 41% (1988-1991) in men and from 37%

to 41% in women (6). It has been suggested that weight gain

leading to overweight in old age might be regarded as “usual”

and may carry little risk (7).

The Cardiovascular Health Study (CHS) provides a unique

opportunity to assess correlates of weight and prior weight

change in a large, noninstitutionalized sample of men and

women aged � 65 y. This paper addresses three research

questions: 1) Are reported weight at age 50 y (� 15 y before

examination in the CHS) and current weight related to preva-

lent CVD and subclinical indicators of CVD?, 2) Do those

currently overweight and those who gained weight from age

50 y have higher levels of cardiovascular risk factors than

people who weigh less or gained less?, and 3) Are those who

remained within 10% of reported weight at age 50 y in better

health than those who gained or lost > 10% of their weight at

age 50 y?

I From the Epidemiology, Demography and Biometry Program, Na-tional Institute on Aging, Bethesda, MD; the Division ofEpidemiology and

Clinical Applications, National Heart, Lung and Blood Institute, Bethesda,

MD; the Department of Public Health and Primary Health Care, Universityof Bergen, Bergen, Norway; the Department of Medicine, School ofMedicine, University of California at Davis; the Department of HumanNutrition and Dietetics, University of Illinois at Chicago; and Preventive

and Social Medicine, University of Nebraska Medical Center, Lincoln.2 Supported by NHLBI contracts NO1-HC-87079, NO1-HC-87080,

NO1-HC-87081, NO1-HC-87082, NOl-HC-87083, NO-HC-87084, NO-

HC-87085, and NO-HC-87086.3 Address reprint requests to TB Harris, National Institute on Aging,

Epidemiology, Demography and Biometry Program, Gateway Building,

Room 3C-309, 7201 Wisconsin Avenue, Bethesda, MD 20892-9205. E-mail: TamaraHarris@nth.gov.

Received February 28, 1997.Accepted for publication April 23, 1997.

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838 HARRIS ET AL

SUBJECTS AND METHODS

Study population

The CHS is a longitudinal, observational study designed to

examine risk factors for coronary artery disease (CAD) and

stroke in a population of 5201 men and women aged � 65 y.

Details of the study design and recruitment of the CHS cohort

were published previously (8, 9). Briefly, the study population

was drawn from a random sample of Medicare enrollees in four

communities: Forsyth County, NC; Sacramento County, CA;

Washington County, MD; and Pittsburgh. The protocol at each

study site had approval from its own Institutional Review

Board. Those who were institutionalized, those confined to awheelchair, those planning to move, and those undergoing

treatment for cancer were excluded. Eligible Medicare enroll-ees and other household members aged � 65 y were inter-

viewed in their homes and then scheduled for a clinic exami-

nation. For this study, we excluded persons who did not have

a reported weight at age 50 y (n 215) or a weight, height, or

waist circumference measurement at the baseline examination

(n 55) with some overlap in these categories. An additional

153 people were excluded because a pack-year history ofcigarette smoking, a critical confounder in studies of weight,

could not be computed. The final study population was 4800

persons, 2070 men and 2730 women, 4.5% African American

and < I % (n = 29) other ethnic groups. The mean age of the

men was 73.2 ± 5.7 y and that of the women was 72.3 ± 5.4 y.

Measurement of anthropometry and weight history

Weight was measured to the nearest 0.2 kg (0.5 lb) with a

balance-beam scale with subjects wearing underwear and an

examination gown or light clothing and no shoes. Standingheight was measured with a fixed stadiometer calibrated in

centimeters. Each participant, as part of a general health his-tory, was asked to recall his or her weight at age 50 y. Waist

circumference was also measured in the CHS; however, be-

cause waist circumference and current body weight yielded

similar results, analyses with waist circumference are not re-

ported. There was no indication of whether the change in

weight from age 50 y to the present weight was voluntary or

involuntary.

Prevalent cardiovascular disease

Methods for ascertainment of prevalent CVD in the CHS

based on hospital records, physicians’ reports, and baseline

examination data have been published (10). Disease measures

in this paper include CAD [defined as myocardial infarction

(including silent myocardial infarction from electrocardio-

gram) and angina pectoris (symptomatic and treated with ni-

trates), coronary bypass surgery, and coronary artery angio-plasty] and all CVD, which included CAD, congestive heart

failure, stroke, transient ischemic attack or carotid stenosis

� 50%, rheumatic disease, ankle-arm blood pressure ratio

� 0.9 (in mm Hg), antiarrhythmic drug or digitalis use, andreport of atrial fibrillation, pacemaker, or heart surgery. Weexamined the association with weight alone and then controlled

for risk factors measured with current weight, including sys-

tolic blood pressure, diabetic status, total cholesterol, and

education.

Subclinical indicators of cardiovascular disease

Indicators of subclinical CVD examined in this paper in-cluded an electrocardiographically derived quantitative evalu-

ation of left ventricular mass ( 1 1 ), sonographically measured

internal carotid artery wall thickness (12), and echocardio-

graphy-based quantitative assessment of left ventricular ejec-

tion fraction, dichotomized as normal or not normal ( 1 3). In

addition, ankle and arm blood pressure measurements were

made by Doppler and a ratio � 0.9 was used as an indicator ofperipheral arterial disease (14). Analysis of the association ofsubclincal disease with weight excluded those who had prey-

alent CVD.

Cardiovascular risk factors

Cardiovascular risk factors examined in this report includedsystolic blood pressure measurements taken seated at rest; the

percentage of subjects hypertensive at baseline based on mea-

sured blood pressure or treatment status; fasting insulin and

glucose concentrations; the percentage of diabetic subjects by

report or glucose-tolerance testing, as measured by standard

criteria (15); and lipids, including total cholesterol and high-

density-lipoprotein (HDL) cholesterol (16).

Other indicators of health status

In addition to prevalent and subclinical CVD and other risk

factor levels, we evaluated the association of the weight mea-

sures with other indicators of health status. These included self

reports of global health status (fair or poor compared with

others), the mean number of current medications recorded (17),

report of difficulty with mobility, and the means of two quan-

titative measures: time to walk 4.6 m (15 ft), and pulmonary

function expressed as forced expiratory volume in 1 s as apercentage of that predicted (FEV 1%) (18).

Potential mediators of associations with weight

We examined level of physical activity in reported energy

expended daily (19), cigarette smoking status (current, former,

or never), mean age at baseline examination, education (highschool graduate or not), income (< $12 000/y compared with

� $12 000/y), and past or present use of estrogen postmeno-

pausally (for women only). This group of variables has been

shown in younger populations to affect risk of overweight andmay therefore mediate the association of weight with cardio-vascular risk.

Statistical methods

We tested the relations among the weight variables, includ-

ing current weight at age 50 y and weight change using Pearson

correlation coefficients. Reported weight at age 50 y and cur-

rent measured weight were considered in relation to the mea-

surements detailed above in two ways: as continuous variables

and in sex-specific quartiles, with dummy variables for each

quartile. Linear-regression models were used to assess the

association of continuous variables with weight variables. Lo-

gistic regression was used to assess the association of dichot-

omous variables with the weight variables. Both linear-regres-sion and logistic-regression models were sex-specific and were

adjusted for age, race, height, and pack-years of cigarette

smoking. Persons missing values for specific variables were

omitted from that analysis only; thus, the analytic sample for

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Women

100 -

80 -

60 -

40 -

20 -

0-

Men

<70.3 � 78.5- a 86.278.4 86.1

Quartiles (in kg)

�_ Gain of > 10% Stable within10%

WEIGHT, WEIGHT CHANGE, AND CVD RISK FACTORS IN AGING 839

FIGURE 1. Weight change from age 50 y to old age in relation to weight in old age.

various measures may vary slightly in total number. Because

our interest was in the association of overweight with CVD,CVD risk factors, and health status, we present a categorized

analysis in this paper. For current weight and weight at age

50 y, the thinnest quartile was used as the reference group in

logistic regression.In our assessment of the relations of other variables with the

weight variables, we tested whether there was a statistically

significant difference among quartiles of weight or levels of

weight change (P < 0.0 1 ). If the overall effect was significantfor the weight quartiles, we tested whether there was a linearassociation for the quartiles of weight (P < 0.01) consistent

with the hypothesis that thinner weight would be most protec-

tive of risk and heavier weight the least protective.

Weight change from age 50 y was categorized as a gain of� 10%, stable within 10%, or loss of > 10%, with the weight-

stable group used as the reference in logistic-regression mod-

els. We also examined a weight change of 4.54 kg (10 Ib) and

absolute weight change as well. Because results from all threeanalyses of weight change were similar, we elected to show the

weight change by ± 10%. All analyses of weight change in theregression models were adjusted for confounding by age, race,height, pack-years of cigarette smoking, and weight at age 50 y

(20). If the overall effect was significant for the weight change

levels, we tested for a quadratic association because we had

hypothesized that both the weight-loss and weight-gain groupswould have worse risk-factor and health-status measures thanthe weight-stable group. If the quadratic association was not

significant for weight change we tested for a linear trendbecause it was also possible, for instance, that weight loss

might lead to lower levels of cardiovascular risk factors and

higher levels of weight gain.

SAS software (release 6.08; SAS Institute Inc, Cary, NC)was used for the statistical analyses.

/‘� r

<57.5 57.5- 64.9- �73.9

64.8 73.8

Quartiles (in kg)

RESULTS

Relations among weight variables

The final study population was 4953 persons, 2142 men and

281 1 women. The mean age of the men was 73.2 ± 5.7 y and

of the women was 72.3 ± 5.4 y. As expected, older women

weighed less than older men but a higher percentage of women

had gained � 10% of weight from age 50 y (35% of womenand 17% of men) (Figure 1). Weight change was not evenly

distributed by quartile of current weight. Twenty-three percent

of women (n = 166) and thirty-two percent of men (n = 163)in the lowest quartile of current weight had lost 10% of body

weight since age 50 y. This contrasts with the heaviest quartile,in which68% ofwomen(n = 48l)and4O% ofmen(n = 211)

had gained � 10% of body weight since age 50 y. Weight atage 50 y and current weight were significantly correlated inboth men and women (r = 0.74 in women and 0.73 in men).

Weight change was also significantly and strongly correlated

with current weight (r 0.60 in women and 0.49 in men)whereas the correlation with weight at age 50 y was much

smaller (r = -0.09 in women and -0.23 in men) (all corre-

lations were significant at P < .0001).

Relation of anthropometric variables with prevalentdisease

For women, weight at age 50 y was associated with currentprevalent CVD and CAD and CVD (Table 1). Women in the

heaviest quartile of weight at age 50 y were ‘�‘77% more likely

to have prevalent CAD compared with those in the lowestquartile whereas little or no association was found with current

weight. Neither past nor current weight showed consistent

associations with prevalent disease for men, although trends

were stronger for weight at age 50 y. Both weight loss andweight gain were associated with increased risk of CAD and

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840 HARRIS ET AL

TABLE 1Relation of past weight, current weight, and weight change to prevalent cardiovascular disease (CVD) and coronary artery disease (CAD)

Women Men

Weight Total CAD odds CVD odds Weight Total CAD odds CVD oddsrange n Cases ratio Cases ratio range n Cases ratio Cases ratio

kg kg

Reported weight at age 50 y’

Quartile 1 <55.4 681 114 1.00 262 1.00 <70.4 551 165 1.00 308 1.00

Quartile 2 55.4-61.2 730 150 1.39 315 1.23 70.4-77.0 447 114 0.88 252 1.13Quartile3 61.3-67.9 544 83 1.02 226 1.19 77.1-83.8 520 163 1.24 295 1.19

Quartile 4 � 68.0 775 180 1.77 775 1.57 � 83.9 552 164 1.23 322 1.36

Overall 2730 P < 0.012 p < 0.012 2070 P = 0.06 P = 0.16Current weight’

Quartile 1 < 57.5 682 134 1.00 293 1.00 < 70.3 498 160 1.00 307 1.00

Quartile 2 57.5-64.8 695 137 1.07 304 1.07 70.3-78.4 554 155 0.90 291 0.78Quartile 3 64.9-73.8 665 110 0.93 288 1.11 78.5-86.1 506 150 1.03 290 1.00

Quartile 4 � 73.9 668 146 1.33 286 1.08 � 86.2 512 141 0.96 289 1.00

Overall 2730 P = 0.06 P = 0.85 2070 P = 0.77 P = 0.78Weight change since age 50 y’

Loss of � 10% 264 70 1.18 149 1.30 261 107 1.69 192 1.89

Stable within 10% 1512 282 1.00 651 1.00 1444 384 1.00 772 1.00

Gain of � 10% 954 175 1.01 371 0.87 365 115 1.26 213 1.21

Overall 2730 P = 0.43 P = 0.02 2070 P < 0.0l� P < 0.0l�

‘ Adjusted for age, height, pack-years of smoking, and race.2 Linear trend.

3 Adjusted for age, height, pack-years of smoking, race, and weight at age 50 y.

4 Quadratic association.

CVD in men whereas in women there was a modest elevationin risk for CVD only for those who had a weight loss, and

weight gain was protective. Controlling for other cardiovascu-

lar risk factors such as systolic blood pressure, diabetic status,

total cholesterol, and education did not substantively change

these associations. Once those with prevalent disease wereexcluded from the analysis of subclinical indicators (46% ofthe women and 58% of the men), the only associations betweenpast and current weight were with left ventricular mass fromelectrocardiogram in both men and women, and of current

weight with carotid thickness in women. No consistent asso-ciations were noted for weight change (data not shown).

Cardiovascular risk factors

Most cardiovascular risk factors showed strong positive as-

sociations with past and current weight (Table 2). For women,all risk factors were significantly associated with current

weight and weight at age 50 y except for total cholesterol. Thesame was true for current weight in men. Greater fasting

insulin and glucose concentrations were associated withheavier weight for both men and women and those in thehighest quartile of weight were four to six times more likely to

be diabetic. Weight change showed the expected pattern in

terms of CVD risk factors. Women who gained weight from

age 50 y had higher mean levels of cardiovascular risk factorsthan those whose weight remained stable, whereas those who

had lost weight tended to have lower mean levels. The sametrends were seen for men.

Current health status

Heavier weight, both current and past, was associated withpoorer health status more strongly in women than in men

(Table 3). Heavier persons had poorer self-reported health,

more mobility difficulty (both by self report and by signifi-cantly longer time to walk 4.6 m, or 15 ft), and were takingmore medications. Among women, pulmonary function tendedto be worst in the heaviest women. Men with the lowest past

weight had the poorest pulmonary function, but this trend was

not significant. Weight stability was associated with better

health status than were either weight gain or weight loss. Thiswas true for reported health status, mobility difficulty, number

of medications taken, pulmonary function, and timed walkingin women; results for men followed a similar pattern but were

not significant.

Explanatory variables

We examined several variables that could potentially mcdi-

ate an association between weight and cardiovascular riskfactors and disease. Of these, current patterns of physical

activity in old age showed the most consistent associations with

weight in both men and women (Table 4). Women and menwho were heaviest at both age 50 y and currently reported

lower energy expended daily although the trend for weight at

50 y in men was not significant. Women who were heavierwere more likely to have never smoked and to report lower

education and income and were slightly younger. They werealso less likely to have ever used estrogen. Among men, neversmoking tended to be associated with heavier past weight; men

who were thinner tended to be older. Weight change was not

consistently related to these variables except that those withweight loss were more likely to be older.

DISCUSSION

We showed that heavier weight in middle and old age was

positively associated with CVD and its risk factors, particularly

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WEIGHT, WEIGHT CHANGE, AND CVD RISK FACTORS IN AGING 841

TABLE 2Anthropometric variables in relation to selected cardiovascular risk factors in older women and men

.

Hypertension.

(odds ratio)

Systolic blood

pressure

(mm Hg)

Total

cholesterol(mmollL)

HDLcholesterol(mmol/L)

.

Insulin

(pmol/L)Glucose

(mmolIL)

.

Diabetes vs.

euglycemia

Women

Reported weight at age 50 y’Quartile 1 1.00 133 5.84 1.68 88 5.4 1.00

Quartile 2 1.49 135 5.77 1.55 104 5.8 1.60

Quartile 3 1.60 137 5.87 1.47 122 5.9 2.06

Quartile 4 2.72 139 5.77 1.37 162 6.7 4.61

Overall P < 0.012 P < 0.012 P = 0.07 P < 0.012 p < 0.012 p < 0.012 P < 0.012

Current weight’Quartile 1 1.00 134 5.72 1.68 75 5.4 1.00Quartile 2 1.28 135 5.79 1.58 108 5.8 1.81

Quartile 3 1.58 137 5.92 1.47 123 6.1 2.87Quartile 4 2.56 139 5.82 1.34 174 6.7 6.21

Overall P < 0.012 P < 0.012 P < 0.012 P < 0.012 P < 0.012 p < 0.012 P < 0.012

Weight change since age 50 y’

Loss of �l0% 1.20 135 5.59 1.66 95 5.8 1.37Stable within 10% 1.00 135 5.77 1.55 108 5.9 1.00

Gain of � 10% 1.44 138 5.92 1.45 146 6.2 2.07Overall P < 0.012 P = 0.01 P < 0.012 p < 0.012 P < 0.012 p < 0.012 P < 0.0l�

Men

Reported weight at age 50 y’Quartile 1 1.00 135 5.28 1.29 100 5.8 1.00

Quartile2 1.14 134 5.17 1.27 110 6.0 1.38

Quartile 3 1.19 135 5.22 1.22 131 6.4 2.39

Quartile4 1.63 136 5.15 1.14 153 6.9 3.80

Overall P < 0.012 P = 0.39 P = 0. 1 1 P < 0.012 P < 0.012 p < 0.012 P < 0.012

Current weight’Quartile I 1.00 133 5.09 1.32 85 5.8 1.00

Quartile2 1.09 133 5.22 1.24 116 6.1 1.86Quartile 3 1.59 136 5.28 1.19 123 6.3 2.41Quartile4 1.77 138 5.22 1.14 171 7.0 4.80

Overall P < 0.012 p < 0.012 p 0.05 P < 0.012 P < 0.012 p < 0.012 P < 0.012

Weight change since age 50 y’Loss of � 10% 0.98 133 4.97 1.29 103 6.3 0.98

Stable within 10% 1.00 134 5.22 1.24 1 19 6.2 1.00

Gain of � 10% 1.34 138 5.28 1.14 158 6.6 1.77

Overall P < 0.05 P < 0.012 p < 0.012 p < 0.012 p < 0.012 p < 0.0l� P < 0.012

‘ Adjusted for age, height, pack-years of smoking, and race.2 Linear trend.

3 Adjusted for age, height, pack-years of smoking, race, and weight at age 50 y.4 Quadratic association.

for women. Heavier weight at age 50 y was associated withprevalent CVD, particularly for women. Heavier past and cur-

rent weight were associated with electrocardiogram left yen-tricular hypertrophy even after those with prevalent CVD were

excluded, and heavier weight was associated with a poorer

cardiovascular risk-factor profile. Last, heavier weight wasassociated with poorer health status and with many of the samebehavioral characteristics associated with overweight in

younger persons, such as reduced energy expenditure (19).Although cross-sectional, these data did not support the sug-

gestion that overweight is a benign health state in old age.We also showed that weight change from middle to old age

is common and that the direction of change may have importantrelations with overall health and risk of CVD. Those gaining

and losing weight tended to have more prevalent CAD andCVD, especially the men. Those who had lost weight were

older and reported worse health status than weight-stable per-

sons. Despite this, weight loss was associated with the best

CVD risk-factor profile. The association of “good” risk factorswith poor health is problematic and because these analyses are

based on cross-sectional data, cause and effect are unclear.

Longitudinal follow-up of these trends may help to explainthese associations and will allow assessment of risks associatedwith weight change (21, 22).

Weight is more strongly related to CVD in older women thanin older men in our data. Trends in sex patterns for smokingmay help to explain this finding. Persons who are heavy

smokers tend to be thin and at high risk of heart disease (23),and this may be reflected in the lack of association of weight

and prevalent disease in men, even though our analyses wereadjusted for smoking. Reflecting this sex difference in smok-ing, lower past weight was associated with poorer pulmonary

function in men whereas heavier weight was associated with

poorer pulmonary function in women. Lower-weight men, who

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842 HARRIS ET AL

TABLE 3Anthropometric variables in relation t o selected health-status indicators in older women and men

Odds ratios Means

Report of fair or Reported mobility Number of Time to walk

poor health difficulty medications used 4.6 m (s) FEVI %‘

Women

Reported weight at age 50 y2

Quartile 1 1.00 1.00 1.99 5.64 89.08

Quartile 2 1.35 1.27 2.17 5.75 90.59

Quartile 3 1.25 1.52 2.38 5.85 90.86

Quartile 4 2.54 2.66 2.94 6.34 87.37

Overall P < 0.0l� P < 0.01’ P < 0.01’ P < 0.01’ P = 0.01

Current weight2Quartile 1 1.00 1.00 2.16 5.76 89.38

Quartile 2 0.94 1.05 2.28 5.79 90.26

Quartile 3 0.99 1.27 2.33 5.81 91.34

Quartile 4 1.67 2.61 2.77 6.29 86.50

Overall P < 0.0l� P < 0.01’ P < 0.01’ P < 0.01’ P < 0.01Weight change since age 50 y4

Loss of � 10% 1.80 1.57 2.80 6.45 86.57

Stable within 10% 1.00 1.00 2.29 5.76 90.36

Gain of � 10% 1.21 2.61 2.42 6.01 88.51

Overall P < 0.0l� P < 0.0l� P < 0.0l� P < 0.0l� P < 0.0l�

Men

Reported weight at age 50 y2

Quartile I 1.00 1.00 1.77 5.32 75.11

Quartile 2 0.83 1.27 1.93 5.31 77.85

Quartile 3 0.97 1.79 2.26 5.61 78.24

Quartile 4 1.32 2.50 2.52 5.71 78.73

Overall P 0.03 P < 0.0l� P < 0.01’ P < 0.01’ P = 0.36

Current weight2

Quartile 1 1.00 1.00 2.02 5.41 76.22Quartile 2 0.74 1.10 1.96 5.29 78.19

Quartile 3 0.87 1.54 2.32 5.63 77.14

Quartile 4 0.86 1.88 2.23 5.67 78.16

Overall P = 0.28 P < 0.01’ P 0.02 P = 0.01 P = 0.40

Weight change since age 50 y4Loss of � 10% 2.44 1.61 2.67 5.68 74.96

Stable within 10% 1.00 1.00 2.00 5.44 78.37

Gain of � 10% 1.42 1.89 2.23 5.57 75.55

Overall P < 0.0l� P < 0.0l� P < O.Oi� P = 0.19 P < 0.0l�

‘ Forced expiratory volume in ls as a percentage of that predicted.2 Adjusted for age, height, pack-years of smoking, and race.

3 Linear trend.

4 Adjusted for age, height, pack-years of smoking, race, and weight at age 50 y.5 Quadratic association.

formed the reference group, may have an increased risk of

CAD, which would tend to reduce rate ratios for heavier men.The data for assessment of weight history are limited, re-

flecting only two points in time with one direct measurement.

However, self-reported weight history has reasonable validity

in comparison with measured past weight, even in older per-sons (24-26). It is unclear which periods during the lifetimemight be most important in terms of weight-related healthoutcomes in old age. In longitudinal studies, weight tends topeak in late middle age and a simple weight history may miss

maximum weight or periods of weight cycling that may affecthealth outcomes (27). Because of these changes over the life

span, weight at age 50 y, the average age at menopause, may bemore predictive for women than for men, which may alsoexplain the greater strength of the associations in women.

This study indicated the complexity of analysis of data onweight in old age. In addition to methodologic problems iden-

tified, which are important in all populations (23), the associ-

ation of heavier weight with many risk factors and subclinicaldisease may make it difficult to show an independent contri-bution to risk from overweight. For instance, of those in this

study who were currently heavy, 79% were either hypertensive,diabetic, or had a ratio of total to HDL cholesterol � 4.5,

contrasted with 57% of thinner persons. Controlling for these

risk factors, which are thought be a result, rather than a cause

of overweight, could only diminish the strength of associationswith weight and may be especially problematic in older

persons.The sizable proportion of older persons gaining and losing

weight further complicates the analyses. Thinner persons, who

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WEIGHT, WEIGHT CHANGE, AND CVD RISK FACTORS IN AGING 843

TABLE 4Potential explanatory variables for the association of anthropometric variables and cardiovascular risk factors

Means Odds ratios

Never Low Low EstrogenPhysical Age at

activity baseline smokers education income use ever

kcat/d’ y

Women

Reported weight at age 50 y2

Quartile 1 1956 72.1 1.00 1.00 1.00 1.00

Quartile 2 1699 72.6 1.1 1 1.07 1.00 0.93Quartile 3 1656 72.4 1.48 1.49 1.17 0.71Quartile 4 1382 72.1 1.91 2.38 1.89 0.52Overall P < 0.0l� P = 0.20 P < 0.01’ P < 0.0l� P < 0.01’ P < 0.0l�

Current weight�

Quartile 1 1869 73.3 1.00 1.00 1.00 1.00

Quartile 2 1743 72.7 1.07 1 . 15 0.69 0.96Quartile 3 1629 72.1 1.29 1.16 0.92 0.77Quartile 4 1416 71.2 1.43 2.09 1.49 0.55

Overall P < 0.0i� P < 0.0l� P < 0.O1� P < 0.01� P < 0.01’ P < 0.0l�Weight change since age 50 y4

Loss of � 10% 1639 75.4 1.07 1.27 1.50 0.79Stable within 10% 1719 72.3 1.00 1.00 1.00 1.00

Gain of � 10% 1584 71.4 0.82 1.18 1.22 1.01Overall P = 0.26 P < 0.0i3 P = 0.04 P = 0.10 P = 0.01 P = 0.34

Men

Reported weight at age 50 y�

Quartile 1 2123 74.1 1.00 1.00 1.00Quartile 2 2102 73.3 1.25 1.05 1.02Quartile 3 2066 73.1 1.33 0.84 0.66Quartile4 1915 72.3 1.43 1.15 0.89Overall P = 0.46 P < 0.0l� P 0.07 P = 0. 18 P = 0.11

Current weight�Quartile 1 2173 75.2 1.00 1.00 1.00Quartile 2 21 16 73.3 0.88 0.89 0.79Quartile 3 2161 72.5 0.98 1.18 0.75

Quartile 4 1743 71.9 1.04 1.18 0.83Overall P < 0.0l� P < 0.01’ P = 0.62 P 0.16 P = 0.43

Weight change since age 50 y4Loss of � 10% 2037 76.3 0.91 1.15 1.27Stable within 10% 2086 72.8 1.00 1.00 1.00Gain of � 10% 1910 72.7 0.66 1.43 1.26Overall P = 0.39 P < 0.0l� P < 0.01’ P = 0.02 P = 0.23

�7To convert kcal/d to kJ/d, multiply by 4.184.2 Adjusted for age, height, pack-years of smoking, and race.

3 Linear trend.

4 Adjusted for age, height, pack-years of smoking, race, weight at age 50 y.

are often used as the reference category, may include a groupof weight losers, who tend to have poorer health status thanthinner weight-stable persons whereas the heavier persons in-dude those with a long duration of excess weight as well as agroup of relatively more recent gainers. Future analyses exam-iing risk associated with weight or weight-related health fac-

tors will need to take both short- and longer-term weight

change into account. Efforts should be directed to understand-

ing the factors responsible for both sustained weight loss andweight gain and to see whether weight gain specifically in old

age confers the risk seen for weight gain in younger life (28).

Our data show that heavier weight in middle age is associ-ated with poorer health status in old age, and that heavierweight in old age is associated with most known cardiovascularrisk factors. Given the prevalence of overweight in old age,

prevention of weight gain throughout life has been suggested to

be the most appropriate strategy to minimize cardiovascular

risk in old age. Among overweight older persons, research isneeded to delineate which groups of older persons might ben-

efit most from weight reduction as well as to identify effectivemethods by which overweight older persons can lose weight

effectively. A

The following institutions and principal staff participated in the Cardio-vascular Health Study. Forsyth County, NC-Bowman Gray School of

Medicine of Wake Forest University: GL Burke, A Elster, WH Ettinger,

CD Furberg, E Haponik, G Heiss, D Kilzman, HS Klopfenstein, M Lamb,DS Lefkowitz, MF Lyles, MB Mittelmark, C Nunn, W Riley, GS Tell, JF

Toole, and B Tucker; Sacramento County, CA-University of California,

Davis: W Bommer, C Bernick, A Duxbury, M Ham, C Hirsch, P Keller-man, L Laslett, M Lee, V Poirier, J Robbins, and M Schenker; Washington

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844 HARRIS ET AL

County, MD-The Johns Hopkins University: Mi Busby-Whitehead, RNBryan, ii Bush, J Chabot, GW Comstock, LP Fried, PS German, JG Hill,SJ Kittner, S Kumanyika, D Levine, JA Lima, NR Powe, TR Price, R

Rock, M Szklo, and M Tockman; Allegheny County, PA-University of

Pittsburgh: DO Ives, CA Jungreis, L Knepper, LH Kuller, RH McDonaldJr, E Meilahn, P Meyer, A Newman, T Orchard, R Schulz, VE Smith, and

SK Wolfson; Echocardiography Reading Center (baseline)-University of

California, Irvine: H Anton-Culver, JM Gadin, M Knoll, T Kurosaki, and

N Wong; Echocardiography Reading Center (follow-up)-Georgetown Uni-versity Hospital, Washington, DC: J Gottdiener, E Hausner, G Hecht, S

Kraus, S Livengood, A Notargiacomo, and R Webb; Ultrasound Reading

Center-Geisinger Medical Center: DH O’Leary, JF Polak, L Funk, and WFWoodruff; Central Blood Analysis Laboratory-University of Vermont: E

Bovill, E Cornell, and RP Tracy; Respiratory Sciences-University of

Arizona, Tucson: P Enright; Electrocardiography Reading Center-Univer-sity of Alberta, Edmonton: K Calhoun, H Calhoun, F Rautahaju, PRautaharju, and L Robertson; Coordinating Center-University of Wash-ington, Seattle: A Arnold, AL Fitzpatrick, BK Lind, RA Kronmal, BM

Psaty, DS Siscovick, L Shemanski, L Fisher, W Longstreth, T Ragunathan,

PW Wahl, and D Yanez; and the NHLBI Project Office: DK Bild, TAManolio, PJ Savage, and P Smith.

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