1 Department of Epidemiology, University of Washington, Seattle, WA.
2 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA.
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ABSTRACT |
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case-control studies; endometrial neoplasms; exercise; physical fitness; risk factors
Abbreviations: CI, confidence interval; MET, metabolic equivalent; OR, odds ratio
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INTRODUCTION |
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We used data from a population-based case-control study conducted in western Washington to examine the association between recreational physical activity and endometrial cancer risk, independent of obesity, exogenous hormones, diet, and other risk factors.
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MATERIALS AND METHODS |
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Controls were identified by random-digit dial telephone calls (14) within the three counties. A short screening questionnaire was used to identify women aged 4574 years as potential controls. If more than one eligible woman lived at the address, one was selected randomly. Controls were chosen with stratified sampling techniques, in such a way that the age and county distributions of controls were broadly similar to those of cases.
Of the 1,154 eligible cases, 833 (72 percent) completed the interview. Reasons for nonparticipation included death (n = 100), physician refusal (n = 63), or refusal by the woman herself (n = 158). One interview was lost before analysis, and 10 women did not complete the questions on physical activity, leaving 822 for analysis.
A total of 52,045 random digit calls were initially made to select controls from the population. Among these calls, 26,405 were found to be nonresidential and, in 2,113, residential status could not be determined. We were unable to determine whether there were any eligible women in 877 (3.7 percent) of the 23,527 households. Among the 2,620 women determined to be eligible (by age and county), 1,975 (75.4 percent) agreed to be interviewed. We excluded 861 control women because of prior hysterectomy (n = 860) or prior diagnosis of endometrial cancer (n = 1). Three women did not answer the questions on physical activity, leaving 1,111 for the analysis.
Cases and controls were assigned a reference date that served as the time frame before which questions in the interview referred. The reference date for the cases was the month and year of diagnosis. The reference years for the controls were chosen to approximate the distribution of reference years in the cases; reference months were chosen at random.
Data collection
Participants completed face-to-face interviews conducted by trained interviewers at the participant's home, except for 34 (3 percent) of the cases and 39 (5 percent) of the controls who completed the interview by telephone.
A detailed history of contraceptive and noncontraceptive hormone use was obtained using a calendar of life events and photographs of hormone preparations to assist recall. The interview also included questions on alcoholic beverage consumption, smoking habits, usual diet (via a food frequency questionnaire), family history of cancer, and other demographic, socioeconomic, and reproductive characteristics. The physical activity component of the interview was a modification of the Minnesota Leisure Time Physical Activity Questionnaire (15, 16
). All subjects were asked the following question: "During the two-year period prior to (reference date), did you do any strenuous physical activities, exercise or sports on a regular basis, that is, at least 24 times a year? Include walking for pleasure or to and from work/school, if at least 1 mile. Also include aerobics, dance, jogging, running, exercising, swimming, bicycling, and gardening. Include indoor and outdoor sports." Women who answered "yes" to this question were asked additional questions for each activity they did, including the number of months per year, times per week or month, and minutes and/or hours per episode. Women who exercised in the past but stopped exercising 2 or more years before their diagnosis or reference date were classified as nonexercisers.
Data analysis
We conducted analyses of physical activity in several ways. First, we estimated the relative risk (by means of the odds ratio) associated with any exercise compared with no exercise. Next, we calculated the weekly duration of exercise for each woman by multiplying the average duration of each episode of activity by the number of times per week and months per year. We summed the minutes per year for each activity and divided by 52 to calculate the minutes per week and subsequently divided by 60 to calculate the hours per week. To determine whether the association between endometrial cancer and physical activity was stronger among women who reported doing more activity per week than those who reported less, we divided the reported weekly duration into five groups (according to the distribution of the controls) and examined it for a trend of decreasing risk.
Next, we divided the activities into intensity categories and completed analyses similar to the ones described above. An activity's intensity was calculated as the ratio of the metabolic rate for the activity relative to the resting metabolic rate (1.0 kcal/kg/minute) and expressed in metabolic equivalents (METs) (17, 18
). Intensity codes for the activities reported ranged from 2.5 METs to 12.0 METs. Examples are provided in table 1. One MET is defined as the energy expenditure for sitting quietly. A three-MET activity requires three times the metabolic energy expenditure of sitting quietly. Activities that were grouped into a single code in our questionnaire that had different MET intensity codes were averaged. For example, water aerobics (4.0 METs) and swimming (7.0 METs) were grouped together, so the average METs for swimming/water aerobics were computed as 5.5 METs. We created categories according to the intensity level of reported activities by dividing those who exercised into three roughly equal groups: any high-intensity activities (MET
6, such as aerobics, hiking, jogging, and tennis); exclusively moderate- or low-intensity activities (MET < 6, such as gardening, dancing, bicycling, walking); and finally exclusively low-intensity activities (MET < 4, such as walking, bowling, or golf). Within each intensity level, we then compared any exercise at that level with no exercise. To determine whether more exercise was associated with a greater reduction in risk than was less exercise, we created three categories of duration (according to the distribution of the controls) within each intensity level and examined them for a trend. Finally, we calculated the total estimated energy expenditure for each person by multiplying the weekly duration of exercise for each activity by its intensity code and summing the estimated energy expenditures for all activities.
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In the results presented, each exposure was adjusted for the frequency-matching factors (age in 5-year categories and county of residence), as well as estrogen use unopposed by progestational agents (i.e., no unopposed estrogen use or use for <3 years in duration, use for 3 years and current user, use for
3 years and former user, missing) and income (five categories). We considered adjustment of the association between physical activity and endometrial cancer for other factors: race (White, non-White), education (three categories), number of pregnancies (0, 1, 2, 3,
4), smoking (never smoker, former/current smoker), and (on the subsample participants who completed the food frequency questionnaire) total energy (quintiles), fruit and vegetable intake (quintiles), average daily alcohol intake (quintiles), and dietary fat (percentage of energy from fat (quintiles)). These factors did not change the beta-coefficients appreciably (<10 percent) and were not included as confounders in logistic models (19
). Models with additional adjustment for body mass index are presented separately because of the possible role of obesity in the causal pathway between physical activity and endometrial cancer. Body mass index was adjusted for using a simple binary variable (lower three quartiles vs. fourth quartile, according to the distribution of controls). More complicated adjustments for body mass index such as continuous terms, categorical and continuous terms, and splines did not change our results appreciably. Therefore, this simple model of the variable was retained.
The study was approved by the Institutional Review Board of the University of Washington.
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RESULTS |
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Energy expenditure incorporates two aspects of activity: intensity (through the use of METs) and duration, and it is calculated by summing the product of weekly duration and intensity code for each activity (table 4). There was inconsistent evidence of a trend (p = 0.23) associated with increasing energy expenditure. The estimated energy expenditure and weekly hours of exercise were highly correlated in our population (r = 0.98), and the odds ratios for this measure were similar to those seen for duration alone (i.e., weekly hours of exercise, presented in table 3).
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DISCUSSION |
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We were unable to determine whether heavier women (i.e., women with higher body mass indexes) did not exercise because of their weight or whether physical inactivity led to higher body mass indexes. To the extent that a lower body mass index is a consequence of exercise, then it is inappropriate to control for it, and estimates from our first model, without adjustment for body mass index, should be considered more valid. However, if having a higher body mass index resulted in these women's inactivity, our findings would suggest that there was only slight confounding by body mass and that the observed associations were independent of body mass index and other known risk factors, including other lifestyle factors such as dietary fat intake or fruit and vegetable consumption (data not presented).
The strengths of this study include its size, use of population-based controls, and assessment of physical activity by a questionnaire similar to one that is a standard tool used in many other epidemiologic studies (16). In addition, our questionnaire on physical activity allowed for the reporting of a wide variety of activities. Detailed information on the type, frequency, and duration of each activity was recorded. An additional strength of our survey instrument is that it allowed women to report the number of months per year that they did an activity, which may have helped to decrease overreporting of activities done for only part of the year.
There are several limitations of this study that should be noted. Physical activity is a complex behavior, and measurement error is a concern in this study and other studies (20). Although our questionnaire was validated, the validation population was a group of men and women aged 2159 years, with a mean age of 38 years (16
). Because of this different age and sex distribution, the results from the validation study may not be generalizable to the population of middle- and older-aged women who participated in this study. Because physical activity was a secondary hypothesis in this study, a nested validation study using objective or uncorrelated measures of physical activity was not included. Furthermore, our assessment of physical activity did not evaluate occupational activity or nonrecreational activity such as stair climbing, cleaning, or child rearing. This might bias our results to the null if recreationally inactive women were more likely to be nonrecreationally active. Our inability to account for the intensity level at which a subject practiced a given activity may have also introduced measurement error. Moreover, although an equal proportion of cases and controls completed the interview, reasons for nonparticipation differed between the two groups. Refusal was the main reason for nonparticipation among the controls (25.6 percent), while death (8.7 percent) and physician refusal (5.5 percent), in addition to participant refusal (13.7 percent), were also important reasons for nonparticipation among the cases. If cases or controls who did not participate were different from those who did in terms of reporting physical activity, our results may not be valid.
Recall bias and inappropriate timing of the reference period are also concerns. On average, there was a shorter time interval between the interview date and the reference year for the cases than for the controls (median, 21 months for cases and 26 months for controls). To determine whether this may have influenced our findings, we examined the relation between physical activity and endometrial cancer stratified on time between the reference date and the interview; risk estimates were similar within each stratum. Recall of low- and moderate-intensity physical activities tends to be poorer than recall of more vigorous activities (16, 21
, 22
). It is possible that the lower activity level reported among cases reflected a change in response to overt disease or that preclinical symptoms prompted cases to reduce their activity level. However, endometrial cancer is typically diagnosed at an early stage, so existence of overt disease during this time period is unlikely. In addition, evaluation of physical activity in the 2-year period prior to diagnosis can be justified on both practical and scientific grounds. First, recall of activities in the recent past is likely to be more accurate than is recall of activities in the more distant past. Moreover, the risk of endometrial cancer is strongly related to recent use of unopposed estrogen (23
). If physical activity is associated with endometrial cancer and is mediated through a hormonal pathway, then assessment of physical activity patterns in the several years prior to diagnosis might be the most etiologically relevant time period. In any case, it is likely that current physical activity levels are highly correlated with past physical activity.
Other epidemiologic studies of the association between physical activity and endometrial cancer have also suggested an inverse association between the two. Measures used to assess physical activity have varied widely, including job title alone (1, 5
, 11
), general self-evaluation on a relative scale of activity level (2
, 4
, 6
, 7
, 9
, 10
), relative frequency for a limited number of activities (6
, 8
, 10
), and detailed quantitative reporting for all recreational and some nonrecreational activities (3
). The strengths and weaknesses of various assessment methods have been discussed elsewhere (20
) and should be considered when evaluating the evidence for a causal association.
Table 5 includes details from selected studies that examined the association between recreational physical activity and endometrial cancer and provided some information about physical activity assessment methods. In the three studies in which assessment of recreational physical activity was based solely on a single question, a higher reported level of activity was associated with a decreased risk of endometrial cancer. Using four fixed response categories of duration, Moradi et al. (7) observed a greater risk of endometrial cancer among those who reported never exercising compared with those who reported doing 2 or more hours per week (OR = 1.3, 95 percent CI: 1.0, 1.7; p for trend = 0.01). Using a four-point relative measurement scale, Terry et al. (2
) found an inverse association for the highest level usual recreational physical activity relative to the lowest (OR = 0.1, 95 percent CI: 0.04, 0.6; p for trend < 0.01). A Japanese case-control study (4
) observed a reduced risk among women who exercised
34 times per week compared with those who did not exercise (OR = 0.60, 95 percent CI: 0.38, 0.93).
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Olson et al. (8) observed a reduced risk of endometrial cancer associated with vigorous activity (exercising long enough to sweat) 2 years prior to the interview (OR = 0.7, 95 percent CI: 0.4, 1.1). Conversely, there was little evidence of a trend with increasing duration of vigorous activity, and there was no apparent association among women who reported walking for exercise, pleasure, or transportation as of 2 years prior to the interview (
4 miles (6.44 km) per week compared with none: OR = 1.0, 95 percent CI: 0.7, 1.6). Occupational activity was not related to endometrial cancer risk (8
).
The assessment methods used by Goodman et al. (3) were most similar to ours. They found that women with occupations and other nonrecreational physical activities that were more physically demanding were at reduced risk of endometrial cancer compared with women who were sedentary (highest fourth compared with lowest: OR = 0.7 (p > 0.05), p for trend = 0.08). However, little association was observed for recreational physical activity (highest fourth compared with lowest: OR = 0.9 (p > 0.05), p for trend = 0.34) (3
).
If physical activity truly protected against the incidence of endometrial cancer in some women, there are several plausible means by which it might do so. 1) Physical activity may lead to weight reduction, resulting in reduced extragonadal aromatization of estrogen in adipose tissue, the major source of endogenous estrogen exposure after menopause (24). Physical activity, perhaps in part due to weight loss, has been associated with a decrease in insulin levels (25
). Insulin can stimulate androgen synthesis, decrease levels of sex hormone binding globulin, and increase levels of estrone, resulting in higher levels of bioavailable estrogens (26
). 2) Women who exercise may have lower levels of serum estradiol and estrone, even after controlling for body mass index (12
). 3) Active women may produce relatively less potent metabolites of estradiol (27
). Finally, 4) physical activity may also influence the amount and type of food consumed, which in turn may affect endometrial cancer risk (25
).
In summary, although our results provide support for an association between recent physical activity and endometrial cancer, the lack of a difference by duration or intensity level and the inconsistent results from other studies leave room for some skepticism. It is possible that the pursuit of any regular physical activity is more important in relation to risk than the actual time spent exercising or the intensity level, indicating a potential threshold effect. It is also possible that our assessment methods are simply too crude, or recall too poor, to determine the nature of this association precisely. A third possibility is that confounding, bias, or other noncausal mechanisms can explain our results and those of others. Studies that support or contradict these findings using improved physical activity assessment methods will provide additional insight into the nature of this relation.
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ACKNOWLEDGMENTS |
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NOTES |
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REFERENCES |
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