In a population of 4,576 Dutch women aged 49-70 years who participated in the European Prospective. Investigation into Cancer and Nutrition (EPIC) in ...
American Journal of Epidemiology Copyright © 1997 by The Johns Hopkins University School of Hygiene and Public Health All rights reserved
Vol. 146, No. 4 Printed in U.S.A
Physical Activity and Cardiovascular Disease Risk Profile in Women
Margreet A. Pols,1 Petra H. M. Peeters,1 Jos W. R. Twisk,2 Han C. G. Kemper,2 and Diederick E. Grobbee1
aged; blood pressure; cardiovascular diseases; exercise; heart rate; obesity; risk factors; women
Numerous studies have been conducted to investigate the relation between physical activity and cardiovascular disease. Powell et al. (1) extensively reviewed most studies performed up to 1985, and they concluded that, especially in the better designed studies, physical activity showed an inverse relation with the incidence of coronary heart disease. In a metaanalysis conducted by Berlin et al. (2) of the cohort studies described by Powell et al. and of more recent publications, the same pattern was found, with the better designed studies yielding higher relative risks for less active subjects compared with more active subjects. Physical activity may lower the risk of coronary heart disease through mediation of cardiovascular disease risk factors. Indeed, in the literature, physical activity has been associated with favorable levels of cardiovascular disease risk factors (3-5). Most of these studies, however, were performed in men (4, 5). For women, the relations could be different, because
sex-specific factors such as hormonal changes influence the risk of cardiovascular disease for women importantly (6). The aim of this study was to investigate whether an association between physical activity and cardiovascular disease risk factors is also present in a population of women aged 49-70 years, and whether different types of activity are differently related to systolic and diastolic blood pressure (7), heart rate, body mass index (8), waist/hip ratio (9), and waist circumference (10). MATERIALS AND METHODS
The European Prospective Investigation into Cancer and Nutrition (EPIC) is a large international cohort study investigating the relation of nutrition and other life-style factors with the development of chronic diseases (11). Apart from cancer, cardiovascular disease is one of the endpoints (EPIC-Heart Study). This study is being carried out in nine European countries (Denmark, France, Germany, Great Britain, Greece, Italy, the Netherlands, Spain, and Sweden). By the end of 1998, data from 400,000 subjects will have been collected. Half of the Dutch cohort consists of women aged 49-70 years and is known as the EPIC-Prospect Study. A dietary and a general questionnaire are completed, blood samples are taken, and anthropometric measurements are carried out. In the coming decades,
Received for publication August 29, 1996, and accepted for publication April 7, 1997. Abbreviation: EPIC, European Prospective Investigation into Cancer and Nutrition. 1 Department of Epidemiology, Faculty of Medicine, Utrecht University, Utrecht, the Netherlands. 2 EMGO-lnstitute, Faculty of Medicine, Vrije Universiteit, Amsterdam, the Netherlands.
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In a population of 4,576 Dutch women aged 49-70 years who participated in the European Prospective Investigation into Cancer and Nutrition (EPIC) in 1993-1995, the relation between physical activity and the presence of cardiovascular disease risk indicators was assessed cross-sectionally. Physical activity was determined from a self-administered questionnaire, while blood pressure, heart rate, body mass index, waist/hip ratio, and waist circumference were measured at the study center. Mean risk indicator levels were calculated for different activity categories. Blood pressure was most clearly associated with time spent in sports (mean systolic blood pressure, adjusted for age, level of education, and smoking, 128.9 mmHg in the highest sports tertile, and 132.1 mmHg in the lowest sports tertile; mean diastolic blood pressure, 77.8 mmHg and 79.0 mmHg, respectively). Body mass index, waist/hip ratio, and waist circumference showed an inverse relation with cycling, gardening, do-it-yourself-activities, and sports. In this population, leisure-time activity was inversely related to cardiovascular disease risk indicators, but work activity and housework were not. The authors conclude that if investigators wish to measure physical activity in women over age 50 years with the aim to identify high- and low-risk groups for cardiovascular disease, they should consider not only housework activity, but also leisure-time activities such as cycling, sports, and do-it-yourself activities. Am J Epidemiol 1997;146:322-8.
Physical Activity and Cardiovascular Disease Risk in Women
Physical activity
The EPIC physical activity questions concerned work and leisure-time activities. Subjects were asked to classify their paid or voluntary job into sedentary work, standing work, manual work, or heavy manual work. In the case of retirees, the question referred to the occupation longest held by the subject. Therefore, for retired women, reported work activity represented past occupational activity. For leisure-time activities, women estimated the amount of time spent in walking, cycling, gardening, do-it-yourself activities, sports, and housework in a normal week during the summer and winter of the past year. In the analyses, the mean number of hours of summer and winter was used. Time spent in total leisure-time activity was computed as the sum of time spent in walking, cycling, gardening, do-it-yourself activities, and sports. Furthermore, subjects were asked whether they perspired while carrying out the above-mentioned activities in a normal Am J Epidemiol
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TABLE 1. Characteristics of 4,576 Dutch women aged 49-70 years who participated in the European Prospective Investigation into Cancer and Nutrition, 1993-1995 Mean (SD*) or%
Variable
Age (years) Height (m) Body weight (kg) BMI* (kg/m2) Waist circumference (m) Hip circumference (m) Waist/hip ratio Mean systolic blood pressure (mmHg) Mean diastolic blood pressure (mmHg) Mean heart rate (beats/minute) Smoking (%) Yes No Level of education (%) Primary Lower vocational General secondary Senior secondary vocational or senior general secondary >3 years Higher vocational or university >3 years :
57.1 (5.8) 1.64(0.06) 69.3(10.7) 25.7 (3.8) 0.83(0.1) 1.05(0.08) 0.79 (0.06) 131 (19) 78 (10) 74(11) 23.4 76.6 23.1 25.8 24.5 13.8 12.8
SD, standard deviation; BMI, body mass index.
week (yes/no). Reproducibility and validity of the physical activity questions were estimated in a pilot study preceding the start of the EPIC-Prospect Study, and have been published separately (12). In brief, reproducibility was assessed with 5 and 11 months test-retest intervals, and Spearman correlation coefficients (13) ranged from 0.47 to 0.89 in men and from 0.49 to 0.81 in women for specific activity categories. Relative validity, using an activity diary as a reference method, ranged from 0.32 to 0.81 in men and from 0.28 to 0.72 in women (12). Blood pressure and heart rate
Blood pressure and heart rate were measured in sitting position with a BOSO Oscillomat (Bosch+Sohn GmbH u. Co., Jungingen, Germany). Two measurements were taken with a 5-10 minutes interval, and the mean was used in the analyses. Anthropometric measurements
Anthropometric measurements (height, weight, waist circumference, and hip circumference) were taken with the subjects wearing indoor clothes and no shoes. Body mass index was calculated as weight (kg)/height (m)2. Waist/hip ratio was computed as waist circumference/hip circumference. Both being overweight and having a predominantly abdominal fat distribution add to the risk of developing cardiovascular disease. A body mass index of &25 kg/m2 is
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endpoints will be collected and risk estimates can be made. In the Netherlands, all women are invited for breast cancer screening on a 2-yearly basis, starting in the calendar year they turn age 50 years, and repeated until they reach age 70 years. From November 1993 to April 1995, all women who were invited for the national breast cancer screening program in Utrecht and surrounding areas received an invitation to participate in the EPIC-Prospect Study. A total of 5,948 women aged 49-70 years (±35 percent of the invited women) agreed to take part. Participating women received a dietary questionnaire and a general questionnaire. The general questionnaire comprised sections on socioeconomic factors, reproductive history, menstruation and hormonal therapy (contraceptive or other), past and current physical activity, past and current use of tobacco and past use of alcohol, medical history, and family history. Subjects completed the questionnaires at home, and brought them along when they visited the study center. The questionnaires were checked by trained interviewers for completeness and inconsistencies. Women who reported that they suffered a myocardial infarction or a stroke were excluded from the analyses (n - 227). Data on current antihypertensive medication were not available. However, the subjects were asked if they had ever been treated for hypertension and, if so, in what year the treatment started. Because subjects who were ever treated and were now normotensive might be so with or without treatment, only subjects who reported no treatment for hypertension were included in the analyses. Table 1 shows the general characteristics of the 4,576 remaining subjects.
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commonly regarded as overweight (14) and has been found to be associated with an increased risk of coronary heart disease in women (8). A high waist/hip ratio (>0.80) corresponds with a pattern of abdominal fat distribution that increases the risk of cardiovascular disease (9). A recent study (10) suggests that a waist circumference of ^ 8 0 cm in women could be an even stronger cardiovascular disease risk factor than the waist/hip ratio.
TABLE 2. Physical activity variables (% of population for categorical variables; means (SD*) for continuous variables) for 4,576 Dutch women aged 49-70 years who participated in the European Prospective Investigation into Cancer and Nutrition, 1993-1995 %or mean (SD)
Variable
Work activity (%) Sedentary Standing Manual Heavy manual
32.5 32.7 19.5 15.4
Perspiring (%) Yes No
67.0 33.0
Type of activity (hours/week), mean (SD) Housework Walking Cycling Gardening Do-it-yourself Sports Total leisure-time activity
19.3(11.3) 8.0(9.1) 3.9 (4.7) 1.6(2.4) 1.0(2.9) 1.3(2.1) 15.8(12.5)
Data analysis
RESULTS
Measures of activity are summarized in table 2. In the study population, 50.3 percent still had a paid or voluntary job and 44.4 percent used to have a paid or voluntary job but did not work any more. Of the
* SD, standard deviation.
subjects who ever had a job, 32.5 percent had a sedentary job and 32.7 percent had a standing job. Housework was the activity most frequently reported in the EPIC hours/week question. Of the leisure-time activities, walking was performed the most frequently, followed by cycling. Perspiring while doing one of these activities was reported by 67 percent of the subjects. Mean levels of the cardiovascular disease risk indicators are presented in table 1. Twenty-six percent of the population had systolic hypertension ( a 140 mmHg) and 12 percent had diastolic hypertension (>90 mmHg). A heart rate of S75 beats/minute was measured in 43 percent of the women. Obesity (body mass index ^25 kg/m2) was found in 53 percent, and a waist/hip ratio of ^0.8 in 38 percent. Finally, a waist circumference of ^ 8 0 cm was measured in 59 percent of the population. Relations between inactivity and cardiovascular disease risk are shown in table 3. In this population, the cardiovascular disease risk indicators seemed to be positively related to work activity, and inversely related to leisure-time activities. Both systolic and diastolic blood pressure were highest in the women who performed heavy manual work. There was a similar relation between systolic blood pressure and housework: women in the lowest tertile of the time spent engaged in housework had lower blood pressures. Blood pressure was inversely related to the time spent in cycling or sports, and in all leisure-time activities together. Am J Epidemiol
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Categorical activity variables were treated as such (work activity: categories 1-4, and perspiring: yes/ no). Continuous variables were divided into tertiles. In case more than 33 percent of subjects reported that they did not engage in a specific activity at all, they were all classified in the lowest tertile for that activity (e.g., gardening, 35.4 percent; sports, 47.1 percent; and do-it-yourself-activities, 72.8 percent, resulting in two groups). A multiple linear regression model (15) was used to calculate mean levels of the risk indicators for categories or tertiles of the activity variables, adjusted for age, level of education, and current smoking status. Alcohol consumption was not included as a covariate, because data on alcohol consumption was only available for about 60 percent of the population and alcohol use in this population was very low (74 percent of the women consumed 0-1 alcoholic drinks per day). To assess whether less active women more frequently have multiple risk indicators, the cardiovascular disease risk indicators were dichotomized using boundaries derived from the literature. The mean number of positive risk indicators (above the cut-off point) was calculated for different levels of activity. For systolic and diastolic blood pressure, we used the criteria proposed in the fifth report of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure (JNC V) (7), i.e., 140 mmHg for systolic blood pressure and 90 mmHg for diastolic blood pressure. A high resting heart rate is considered as a sign of a poor physical condition, although there is no clearly defined threshold level. Therefore an arbitrary value of 75 beats/minute was chosen. The other cut-off points were: body mass index, 25 kg/m2; waist/hip ratio, 0.80; and waist circumference, 80 cm.
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78.4 ± 0.25 78.3 ± 0.27 78.4 ± 0.25 78.7 ± 0.25 78.5 ± 0.26 78.0 ± 0.26
131.1 ±0.45 129.9 ± 0.50 130.6 ±0.45 131.1 ±0.46 131.2 ±0.47 129.4 ± 0.46*
± 0.30 ± 0.28 ± 0.37 ± 0.44
±0.10 ±0.10 ±0.12 ±0.15*
75.3 ± 0.29 74.1 ±0.28 73.2 ± 0.27* 74.6 ± 0.29 74.0 ± 0.20
78.9 ± 0.27 78.1 ±0.24 78.2 ± 0.25* 78.0 ± 0.25 78.6 ±0.18
131.4 ±0.49 130.3 ± 0.44 130.0 ± 0.46* 129.5 ± 0.46 131.1 ±0.33*
25.4 ± 0.09 25.9 ± 0.07*
25.9 ±0.10 25.6 ± 0.09 25.7 ± 0.09
25.9 ± 0.09 25.7 ±0.12 25.6 ± 0.09*
79.0 ± 0.22 78.0 ± 0.32 77.8 ± 0.25*
132.1 ±0.41 129.9 ± 0.59 128.9 ± 0.44*
75.1 ±0.24 74.4 ± 0.34 72.7 ± 0.28*
78.6 ±0.18 77.9 ± 0.27
25.8 ± 0.07 25.6 ±0.10
26.0 ±0.10 25.7 ± 0.09 25.5 ± 0.09*
26.0 ±0.10 25.7 ± 0.09 25.6 ± 0.09*
25.8 ± 0.09 25.8 ±0.10 25.6 ± 0.09
25.7 ± 0.09 25.8 ± 0.09 25.7 ±0.10
25.5 25.8 25.5 26.5
Mean ± SE
(kg/m2)
Body mass index
74.4 ±0.19 73.7 ± 0.30
74.5 ± 0.28 73.9 ± 0.27 74.2 ± 0.30
75.2 ± 0.28 74.2 ± 0.28 73.1 ±0.28*
74.3 ± 0.27 74.4 ± 0.30 73.9 ± 0.27
74.0 ± 0.27 74.3 ± 0.29 74.3 ± 0.29
74.2 74.1 73.6 74.5
Mean ± SE
Heart rate (beats/minute)
130.9 ± 0.32 129.9 ± 0.48
77.9 ± 0.25 78.7 ± 0.25 78.6 ± 0.26*
78.0 ± 0.25 79.0 ± 0.26 78.2 ± 0.26
129.2 ± 0.44 131.4 ±0.48 131.1 ±0.47*
129.7 ± 0.47 131.2 ±0.45 130.9 ± 0.47
78.3 ± 0.27 78.2 ± 0.26 77.9 ± 0.34 79.2 ± 0.40
Mean ± SE
Mean ± SE
130.4 ±0.48 129.8 ± 0.47 130.3 ± 0.63 132.9 ±0.76*
Dlastolic
±0.0015 ±0.0014 ±0.0019 ± 0.0022*
2.42 ± 0.036 2.30 ± 0.051 2.16 ±0.040* 2.44 ± 0.042 2.27 ± 0.040 2.22 ±0.041* 2.21 ±0.041 2.36 ± 0.029*
83.1 ±0.21 82.3 ± 0.28 81.9 ±0.22* 83.2 ± 0.25 82.3 ± 0.23 82.2 ± 0.22* 81.9 ±0.23 82.9 ±0.17*
0.787 ±0.0014 0.785 ±0.0014 0.784 ±0.0014 0.783 ±0.0014 0.786 ±0.0010
2.33 ± 0.041 2.33 ± 0.040 2.26 ± 0.042
83.2 ± 0.25 82.2 ± 0.22 82.2 ± 0.23*
0.788 ±0.0012 0.785 ±0.0017 0.783 ±0.0014*
2.44 ± 0.040 2.27 ± 0.041 2.20 ± 0.042*
83.5 ± 0.24 82.0 ± 0.23 82.0 ± 0.23*
2.35 ± 0.028 2.22 ± 0.045*
2.34 ± 0.039 2.33 ± 0.043 2.26 ± 0.041
± 0.043 ± 0.042 ± 0.056 ± 0.063*
82.8 ± 0.22 82.7 ± 0.25 82.2 ± 0.23
2.24 2.31 2.23 2.55
2.25 ± 0.040 2.35 ± 0.041 2.32 ± 0.042
±0.24 ± 0.24 ± 0.31 ± 0.38*
Mean ± SE
No. of risk factors
82.6 ± 0.23 82.7 ± 0.24 82.4 ± 0.23
81.9 82.6 82.0 84.3
Mean ± SE
Waist (cm)
82.7 ±0.16 82.1 ±0.25* 0.787 ±0.0010 0.782 ±0.0015*
0.788 ±0.0014 0.783 ±0.0013 0.784 ±0.0014*
0.790 ± 0.0014 0.782 ±0.0014 0.784 ±0.0014*
0.785 ±0.0013 0.785 ±0.0014 0.786 ±0.0014
0.786 ±0.0014 0.786 ±0.0014 0.783 ±0.0014
0.782 0.787 0.784 0.793
Mean ± SE
Waist/hip ratio
* Significant trend (three or four categories) or significant difference (two categories), after adjustment for age, smokinc), and level of education (p < 0.05). t Means are adjusted for age, smoking, and level of education.
Do-it-yourself (hours/week) 0 £!4 Sports (hours/week) 0 14-1 £114 Total leisure-time activity (hours/week) £814 9-1614 £17 Perspiring No Yes
• & .
14-1 Mt
0
£414 Gardening (hours/week)
2-4
*7VS> Cycling (hours/week)
Work activity Sedentary Standing Manual Heavy manual Housework (hours/week) 21314 14-2116 2:22 Walking (hours/week) £3 314-7
Activity and level
Systolic
Blood pressure (mmHg)
TABLE 3. Mean levelst * standard errors (SE) of the cardiovascular disease risk factors for categories or tertiles of physical activity among 4,576 Dutch women aged 49-70 years who participated in the European Prospective Investigation into Cancer and Nutrition, 1993-1995
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DISCUSSION
In our study among 4,576 women aged 49-70 years, the relations between the activity parameters and cardiovascular disease risk indicators indicate that in general a higher activity level of work or housework is associated with a higher level of the risk indicators, which was not expected. On the other hand, the inverse relation between leisure-time activities and risk profile was in agreement with the hypothesis that physical activity lowers cardiovascular disease risk. The differences in risk indicator levels between the activity groups were rather small and their clinical relevance may be questioned. The fact that several differences still reached statistical significance reflects the large number of subjects included in the study. Because the positive association between work activity and the risk indicators and the inverse relation between leisure-time activity and the risk indicators was fairly consistent for most activities and most risk indicators, it is not likely that these results are a chance
finding. In a population of healthy women in a rather narrow age range, in which the variation in physical activity probably is quite small, one would not expect to find huge contrasts in risk indicator levels. The effects of activity pattern on cardiovascular disease found in this study can therefore be considered real and relevant, although they are admittedly of small magnitude. Participants in the study were women who agreed to complete two rather extensive questionnaires, to spend an hour extra at the breast cancer screening unit to have the questionnaires checked and the measurements taken, and to provide a blood sample. Probably these women are interested in health-related topics and recognize the importance of scientific investigations. Furthermore, women who have a busy job might be less inclined to participate. Therefore, the women in the study could have been a selected population. Data on non-responders are scarce. Van Leer et al. (16) studied blood pressure in a monitoring project on cardiovascular disease risk factors in the Netherlands between 1987 and 1991, and they reported a mean systolic blood pressure of 125 mmHg and a mean diastolic blood pressure of 79 mmHg in 5,278 women aged 50-59 years. Body mass index, waist/hip ratio, and waist circumference did not differ from those found by Den Tonkelaar et al. (17) in women who participated between 1984 and 1986 in the same breast cancer screening project from which the women in our study were recruited. From these data, it seems that selection does not play an important role in our study. The analyses presented in this paper are cross-sectional. This implies that no conclusion can be drawn regarding cause and effect. It might be possible that women who are more active in their leisure time as a result have lower blood pressure and are leaner, but on the other hand such women could be more active because they feel more fit. We recognize that one study limitation is that we did not have data on current use of antihypertensive medication, but only on "ever" use of such medication. The exclusion of subjects who were ever treated for hypertension resulted in a lower mean blood pressure for the whole population (systolic blood pressure, 130.6 vs. 133.6 mmHg; diastolic blood pressure, 78.4 vs. 79.7 mmHg). The relations with the activity variables, however, were similar to those in the whole population. Furthermore, no data on angina pectoris were available and the possible inclusion of women with angina may have confounded the results to some extent, because both level of physical activity and level of the risk indicators can be affected by the presence of coronary heart disease. Am J Epidemiol
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Heart rate showed no association with work or housework. On the other hand, cycling, sports, and total leisure-time activities were all inversely associated with heart rate. The relations between work activity and body mass index, waist/hip ratio, and waist circumference all showed a similar pattern, with the women who reported that they did heavy manual work having the highest levels of the risk indicators. No relation was found with housework. The three obesity parameters were in general inversely associated with the leisuretime activities, especially with cycling, gardening, and sports. The general pattern present for individual risk indicators was also found if we considered clustering of risk indicators (occurrence of multiple risk factors), i.e., we observed a positive relation with work and housework, and an inverse one with the leisure-time activities. Again, the strongest associations were seen for cycling, do-it-yourself activities, sports, and time spent in all leisure-time activities combined. Relations between reported perspiring and risk indicators were very weak, and, if seen at all, were not in the expected direction. However, after we separated the "perspirers" (n = 1,503) from the "non-perspirers" (n — 3,044), we found that perspirers spent significantly more time in leisure-time activities (16.9 vs. 13.7 hours/week, p < 0.001) than did the non-perspirers. Among the non-perspirers, a relation between total leisure-time activity and the risk indicators was observed only for heart rate, whereas among the perspirers, a relation was found for every risk indicator except body mass index.
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identify women with a lower risk for cardiovascular disease. The risk indicators were inversely related to most leisure-time activities, as has been reported previously for men (4). For blood pressure, the relation was most prominent for sports and total leisure-time activity. The exclusion of subjects who were ever treated for hypertension might have weakened the associations because more women with a relatively high blood pressure were excluded. Time spent in cycling, sports, and all leisure-time activities did show the strongest influence on heart rate, probably because these activities are of higher intensity than, for example, walking or gardening. The anthropometric parameters (body mass index, waist/hip ratio, and waist circumference) were inversely related to all leisure-time activities except walking. In this population of women aged 49-70 years, a higher level of participation in leisure-time activities was generally associated with a more favorable level of cardiovascular disease risk indicators, especially indicators of being overweight. However, by contrast, work activity and housework were positively or not at all associated with the level of most risk indicators. We therefore recommend that investigators who study physical activity in women aged over 50 years in order to identify high- and low-risk groups for cardiovascular disease should consider all aspects of activity— work and housework activity, as well as such leisuretime activities as cycling, sports, and do-it-yourself activities.
ACKNOWLEDGMENTS
This study was supported by the Commission of European Communities contract no. Soc 95 200500 05F02.
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Few data have been reported on the relation between occupational activity and risk indicators in female populations. Albanes (18) compared body mass index for low, moderate, and high levels of non-recreational activity, and found inverse relations for both men and women in the second National Health and Nutrition Examination Survey (NHANES II). Stender et al. (5) reported a higher body mass index in men with higher levels of job activity compared with that in inactive men. Among 628 Shanghai women aged 35-64 years, Hong et al. (19) found inverse relations between weekly frequency of periods of activity that caused shortness of breath, increase in pulse rate, and perspiration on the one hand, and systolic and diastolic blood pressure, body mass index, and heart rate on the other hand. Hong et al. did not, however, discriminate between occupational and leisure-time activity. Few studies have been published that have compared different types of leisure-time activity with levels of cardiovascular disease risk indicators in female populations. Among 7,722 German females aged 25-69 years (20), leisure-time physical activity was inversely associated with systolic and diastolic blood pressure, and with body mass index. The differences in risk indicator levels between activity groups were of the same order of magnitude as those observed in our study. Bijnen et al. (4) studied the relation between various types of activity and cardiovascular disease risk indicators in a population of 1,402 men aged 69-90 years from Finland, Italy, and the Netherlands, and they reported no relation between physical activity and body mass index or blood pressure, but generally favorable associations between total weekly physical activity on the one hand and resting heart rate and high density lipoprotein (HDL) cholesterol on the other hand. These results point in the same direction as our results regarding leisure-time activity. Work activity and time spent on housework showed a similar pattern in the relation with cardiovascular disease risk profile: both were either positively or not at all related with the risk indicators. The positive relation between work and housework activity and risk indicators could not be explained by the theory that women who were involved in heavy jobs were less active during leisure time. On the contrary, a positive linear association was seen in total leisure-time activity for increasing levels of occupational activity. The women who performed heavy work or who spent a lot of time on housework might be a selected group. For example, the results could reflect a remaining effect of socioeconomic status, although the phenomenon remained after adjustment for level of education. In this population, the amount of time spent on housework was large, but it obviously is not suitable to
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London: Edward Arnold, 1991: chapter 1. 14. World Health Organization. Measuring obesity— classification and description of anthropometric data. Copenhagen: Regional Office for Europe, 1989. 15. Kleinbaum DG, Kupper LL, Muller KE. Applied regression analysis and other multivariable methods. 2nd ed. Belmont, CA: Wadsworth Publishing Co, 1988: chapter 8. 16. Leer EM van, Seidell JC, Kromhout D. Levels and trends in blood pressure and prevalence, and treatment of hypertension in the Netherlands, 1987-1991. Am J Prev Med 1994;10: 194-9. 17. Tonkelaar I den, Seidell JC, Noord PA van, et al. Fat distribution in relation to age, degree of obesity, smoking habits, parity and estrogen use: a cross-sectional study in 11,825 Dutch women participating in the DOM-project. Int J Obes 1990; 14:753-61. 18. Albanes D. Potential for confounding of physical activity risk assessment by body weight and fatness. Am J Epidemiol 1987;125:745-6. 19. Hong Y, Bots ML, Pan X, et al. Physical activity and cardiovascular risk factors in rural Shanghai, China. Int J Epidemiol 1994;23:1154-8. 20. Helmert U, Herman B, Shea S. Moderate and vigorous leisuretime physical activity and cardiovascular disease risk factors in West Germany, 1984-1991. Int J Epidemiol 1994;23: 285-92. Downloaded from aje.oxfordjournals.org by guest on July 13, 2011
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