Objective: To assess the epidemiologic evidence for the association between physical activity and endometrial cancer risk, taking into account the methodologic quality of each study.

Design: Systematic review, best evidence synthesis.

Data Sources: Studies were identified through a systematic review of literature available on PubMed through December 2006.

Review Methods: We included cohort and case-control studies that assessed total and/or leisure time and/or occupational activities in relation to the incidence of endometrial cancer. The methodologic quality of the studies was assessed with a comprehensive scoring system.

Results: The included cohort (n = 7) and case-control (n = 13) studies consistently show that physical activity is associated with a decreased risk of endometrial cancer. The best evidence synthesis showed that the majority (80%) of 10 high-quality studies found risk reductions of >20%. Pooling of seven high-quality cohort studies that measured total, leisure time, or occupational activity showed a significantly decreased risk of endometrial cancer (summary estimate: OR, 0.77; 95% CI, 0.70-0.85) for the most active women. Case control studies with relatively unfavorable quality scores reported divergent risk estimates, between 2-fold decreased and 2-fold increased risk. Effect modification by body mass index or menopausal status was not consistently observed. Evidence for an effect of physical activity during childhood or adolescence was limited.

Conclusions: Physical activity seems to be associated with a reduction in the risk of endometrial cancer, which is independent of body weight. Further studies, preferably prospective cohort studies, are needed to determine the magnitude of the risk reduction and to assess which aspects of physical activity contribute most strongly to the reduced risk and in which period of life physical activity is most effective. (Cancer Epidemiol Biomarkers Prev 2007;16(4):639–48)

Endometrial cancer is the eighth most common cancer in women worldwide. An estimated 200,000 cases occur yearly, accounting for 1.8% of all new cases of cancer worldwide and 4% to 8% in Western industrialized countries (1). Known risk factors for endometrial cancer include obesity, postmenopausal estrogen replacement, ovarian dysfunction, type II diabetes, infertility, nulliparity, and tamoxifen use (2, 3). Recently, physical inactivity has received increasing attention as a potential risk factor for endometrial cancer (4-6). Physical activity together with maintenance of a healthy body weight would provide women with a powerful strategy for the prevention of endometrial cancer and possibly other cancers as well (7).

The majority of studies on the association between physical activity and cancer have focused on breast cancer. About 50 observational studies have been conducted on total or leisure time activities, in which both null results and inverse associations between physical activity and breast cancer have been observed (8). By contrast, much fewer studies examined the association between physical activity and endometrial cancer, and the results seem to point rather uniformly to risk reduction from physical activity. By systematically reviewing all the evidence from observational epidemiologic studies, we aim to estimate the magnitude of the effect of physical activity on endometrial cancer risk and to examine the level of evidence, taking into account the methodologic quality of the studies including those on total, leisure time, and occupational activities. Because obesity is a strong risk factor for endometrial cancer, we have paid special attention to a possible role for body weight as a confounder, effect modifier, or intermediary factor in the association between physical activity and endometrial cancer.

Search and Selection of Literature

Studies were identified through a systematic review of published literature available on PubMed literature databases through December 2006. The databases were searched using the following terms: (“physical activity” OR “physical inactivity” OR “exercise” OR “sedentary lifestyle”) AND (“endometrial cancer” OR “cancer, endometrium” OR “neoplasms, endometrium” OR “cancer, corpus uteri” OR “neoplasms, corpus uteri” OR “cancer, uterus” OR “neoplasms, uterus”). From relevant publications, the bibliographic lists were hand searched for additional articles.

The criteria for inclusion of studies in the review were as follows: case-control or cohort studies investigating the association between physical activity and endometrial cancer; with incidence, prevalence, or mortality as end point; >10 cancer cases included in the analysis; published in English. We included studies assessing leisure time activity or total activity or occupational activity.

Data Extraction and Quality Assessment

The data extraction and study quality assessment were independently done by two reviewers (D.W.V. and E.M.M.). Any disagreement was resolved by consensus or by consultation with a third reviewer (F.E.v.L.). Details of the standardized data extraction are described elsewhere (8). We documented study size, characteristics of the study population, components of physical activity assessment, and methodologic characteristics.

A quality scoring system was developed that captured both generic methodologic issues and issues specific to our subject (see Appendix A; ref. 8). The items of the scoring system were categorized according to three important sources of error in observational studies (the major headings): selection bias, misclassification bias, and confounding bias. Criteria for physical activity assessment methods were partly adopted from Powell et al. (9). The quality scoring system contained 19 items (selection, 5; misclassification, 11; and confounding, 3). The members of the Task Force Physical Activity and Cancer assessed which aspects of quality are more important and therefore should be weighted more in the overall quality score. In this research area, the potential for confounding bias is judged less important. Studies that adequately adjusted for potential confounders show that the magnitude of the risk estimates does not materially change after adjustment, whereas biases due to selection or misclassification are expected to lead to larger effects on risk estimates. Thus, the major headings were weighted 2:2:1. The maximum attainable score is 105 (see Appendix A), and the quality score of the studies is presented as percentage of the maximum attainable score.

Analysis

We assessed statistical heterogeneity across studies using a formal test (10) and found statistical evidence for heterogeneity for total, leisure time, and occupational activities combined, both in cohort and case-control studies. Summary estimates were calculated using a general variance–based method using confidence intervals (11).

A qualitative summary of all studies was undertaken according to a best evidence synthesis, taking into account the methodologic quality of the studies and the consistency of the available evidence (see Appendix B). An inverse association between physical activity and endometrial cancer risk within a study was defined as a risk estimate for the highest versus the lowest level of activity of <0.8, irrespective of statistical significance. In our best evidence synthesis, the evidence for an inverse association was defined as “strong” if ≥75% of the high-quality studies reported an inverse association. Studies were categorized as high or low quality based on the median quality score of all studies combined. Graphical displays were used to investigate whether the risk estimates from studies with a relatively low methodologic quality differed systematically from those with relatively high quality. Possible publication bias was investigated by funnel plots.

We identified 20 relevant articles on physical activity and endometrial cancer risk. The main characteristics and results of the 7 cohort studies (4, 6, 12-16) and 13 case-control studies (5, 17-28) are summarized in Tables 1 and 2, respectively. All studies were published between 1993 and 2006. Two cohort studies and four case-control studies assessed total activity whereas the other studies reported only leisure time activities and/or occupational activities. The number of endometrial cancer cases ranged from 49 to 5,287 in the cohort studies and from 31 to 832 in the case-control studies. There was considerable variation among the studies with respect to age of the participants, physical activity assessment, and the length of follow-up (cohort design).

Table 1.

Characteristics and results of the cohort studies stratified by source of activity (total, leisure time, occupational)

Author (reference)Cohort name and countryBaselineAge (y)Follow-up (y)Cohort sizeNo. casesActivity measure—life periodContrastRisk estimate (95% CI)*; trendQuality score (% of max)
Total activity           
    Colbert et al. (13) Breast Cancer Detection Demonstration Project (United States) 1987-1989 61 ± 8 8.2 23,369 253 postmeno MET—recent Highest activity quintile vs lowest HR, 0.8 (0.5-1.1) 75 
         Residual confounding: no  
    Friberg et al. (6) Swedish Mammography Cohort 1997 50-83 7.2 33,723 199 postmeno MET—recent Highest activity quintile vs lowest RR, 0.79 (0.53-1.17); trend: no (P = 0.27) 87 
         Residual confounding: partly  
Leisure time activity           
    Terry et al. (12) Swedish Twin Registry (Sweden) 1967 42-81 20.4 11,659 133 pre- and post-meno Subjective—recent Hard physical exercise vs none (4 cats) HR, 0.1 (0.04-0.6); trend: yes (P < 0.01) 61 
         Residual confounding: yes  
    Furberg and Thune (14) Norwegian Women Cohort (Norway) 1974-1981 45 ± 7 15.7 24,460 130 pre- and post-meno Subjective—recent Grade 3 + 4 (sports) vs grade 1 (sedentary) HR, 0.79 (0.43-1.45); trend: no (P = 0.39) 75 
         Residual confounding: yes  
    Schouten et al. (4) Netherlands Cohort Study on Diet and Cancer (Netherlands) 1986 55-69 9.3 62,573 226 postmeno Duration (h/wk)—recent Total nonoccupational activity; ≥90 min/d vs <30 min/d (4 cats) HR, 0.54 (0.34-0.85); trend: yes (P = 0.002) 68 
         Residual confounding: partly  
    Friberg et al. (6) Swedish Mammography Cohort 1997 50-83 7.2 33,723 199 postmeno Hours/d—recent High (≥20 min/d) vs low (<20 min/d) RR, 0.99 (0.73-1.32); trend: n.a. 87 
         Residual confounding: partly  
Occupational activity           
    Pukkala et al. (15) Teachers cohort (Finland) 1958-1973, 1984-1991 20-75+ 24 10,118 49 pre- and post-meno Subjective—lifetime Physical exercise teachers vs language teachers SIRPE/SIRL: 0.85; trend: n.a. 68 
         Residual confounding: partly  
    Moradi et al. (16) Swedish Cancer Environment Registry (Sweden) 1960-1970 16-95 19 989,270 5,287 post- and post-meno Subjective—1970 Sedentary vs high/very high (4 cats) RR, 1.32 (1.17-1.50); trend: yes (<0.001) 71 
         Residual confounding: yes  
    Furberg and Thune (14) Norwegian Women Cohort (Norway) 1974-1981 45 ± 7 15.7 24,460 130 pre- and post-meno Subjective—recent Grade 3 + 4 (manual) vs grade 1 (sedentary) HR, 0.61 (0.35-1.05); trend: no (P = 0.09) 75 
         Residual confounding: yes  
    Friberg et al. (6) Swedish Mammography Cohort 1997 50-83 7.2 33,723 199 postmeno MET—recent High (standing/manual) vs low (sedentary) RR, 1.01 (0.75-1.37); trend: n.a. 87 
         Residual confounding: partly  
Author (reference)Cohort name and countryBaselineAge (y)Follow-up (y)Cohort sizeNo. casesActivity measure—life periodContrastRisk estimate (95% CI)*; trendQuality score (% of max)
Total activity           
    Colbert et al. (13) Breast Cancer Detection Demonstration Project (United States) 1987-1989 61 ± 8 8.2 23,369 253 postmeno MET—recent Highest activity quintile vs lowest HR, 0.8 (0.5-1.1) 75 
         Residual confounding: no  
    Friberg et al. (6) Swedish Mammography Cohort 1997 50-83 7.2 33,723 199 postmeno MET—recent Highest activity quintile vs lowest RR, 0.79 (0.53-1.17); trend: no (P = 0.27) 87 
         Residual confounding: partly  
Leisure time activity           
    Terry et al. (12) Swedish Twin Registry (Sweden) 1967 42-81 20.4 11,659 133 pre- and post-meno Subjective—recent Hard physical exercise vs none (4 cats) HR, 0.1 (0.04-0.6); trend: yes (P < 0.01) 61 
         Residual confounding: yes  
    Furberg and Thune (14) Norwegian Women Cohort (Norway) 1974-1981 45 ± 7 15.7 24,460 130 pre- and post-meno Subjective—recent Grade 3 + 4 (sports) vs grade 1 (sedentary) HR, 0.79 (0.43-1.45); trend: no (P = 0.39) 75 
         Residual confounding: yes  
    Schouten et al. (4) Netherlands Cohort Study on Diet and Cancer (Netherlands) 1986 55-69 9.3 62,573 226 postmeno Duration (h/wk)—recent Total nonoccupational activity; ≥90 min/d vs <30 min/d (4 cats) HR, 0.54 (0.34-0.85); trend: yes (P = 0.002) 68 
         Residual confounding: partly  
    Friberg et al. (6) Swedish Mammography Cohort 1997 50-83 7.2 33,723 199 postmeno Hours/d—recent High (≥20 min/d) vs low (<20 min/d) RR, 0.99 (0.73-1.32); trend: n.a. 87 
         Residual confounding: partly  
Occupational activity           
    Pukkala et al. (15) Teachers cohort (Finland) 1958-1973, 1984-1991 20-75+ 24 10,118 49 pre- and post-meno Subjective—lifetime Physical exercise teachers vs language teachers SIRPE/SIRL: 0.85; trend: n.a. 68 
         Residual confounding: partly  
    Moradi et al. (16) Swedish Cancer Environment Registry (Sweden) 1960-1970 16-95 19 989,270 5,287 post- and post-meno Subjective—1970 Sedentary vs high/very high (4 cats) RR, 1.32 (1.17-1.50); trend: yes (<0.001) 71 
         Residual confounding: yes  
    Furberg and Thune (14) Norwegian Women Cohort (Norway) 1974-1981 45 ± 7 15.7 24,460 130 pre- and post-meno Subjective—recent Grade 3 + 4 (manual) vs grade 1 (sedentary) HR, 0.61 (0.35-1.05); trend: no (P = 0.09) 75 
         Residual confounding: yes  
    Friberg et al. (6) Swedish Mammography Cohort 1997 50-83 7.2 33,723 199 postmeno MET—recent High (standing/manual) vs low (sedentary) RR, 1.01 (0.75-1.37); trend: n.a. 87 
         Residual confounding: partly  
*

Printed in italic if contrast is low versus high activity levels.

Trend: subjective assessment (P value for trend test if available).

Table 2.

Characteristics and results of the case-control studies stratified by source of activity (total, leisure time, occupational)

Author (reference)CountryActivity assessmentAge (y)No. casesNo. controlsStudy base (cases/controls)Activity measure—life periodsContrastRisk estimate (95% CI)* trendQuality score (% of max)
Total activity           
    Sturgeon et al. (17) United States 1987-1990 20-74 405 pre- and post-meno 297 Hospital based/population based Subjective (global assessment)—recent Very inactive vs very active (5 cats) OR, 2.5 (0.7-8.7); trend: no (P = n.a.) 60 
         Residual confounding: no  
    Shu et al. (18) China 1988-1990 18-74 268 pre- and post-meno 268 Population based/population based Subjective—age 50-59 Very inactive vs very active (5 cats) OR, 2.1 (0.6-7.1); trend: no (P = n.a.) 80 
         Residual confounding: no  
    Levi et al. (19) Switzerland/Italy 1988-1991 31-75 274 pre- and post-meno 572 Hospital based/hospital based Subjective—age 55 Lowest vs highest (4 cats) OR, 8.6 (3.0-25.3); trend: no (P < 0.01) 42 
         Residual confounding: yes  
    Salazar-Martinez et al. (23) Mexico 1995-1997 85 pre- and post-meno 668 Hospital based/hospital based MET-h/wk—recent? leisure? ≥38 MET-h/wk vs ≤29 (3 cats) OR, 0.47 (0.26-0.86); trend: no (P = 0.01) 44 
         Residual confounding: yes  
Leisure time activity           
    Sturgeon et al. (17) United States 1987-1990 20-74 405 pre- and post-meno 297 Hospital based/population based Subjective—recent Lowest quintile vs highest OR, 1.2 (0.7-2.2); trend: no (P = n.a.) 60 
         Residual confounding: no  
    Shu et al. (18) China 1988-1990 18-74 268 pre- and post-meno 268 Population based/population based MET—age 50-59 Lowest quartile vs highest quartile OR, 1.0 (0.6-1.7); trend: no (P = n.a.) 80 
         Residual confounding: no  
    Levi et al. (19) Switzerland/Italy 1988-1991 31-75 274 pre- and post-meno 572 Hospital based/hospital based Subjective—recent Sporsts and leisure: lowest vs highest (4 cats) OR, 1.9 (0.9-4.0); trend: no (P < 0.01) 42 
         Residual confounding: yes  
    Hirose et al. (20) Japan 1988-1993 18-80+ 145 pre- and post-meno 26,751 Hospital based/hospital based Frequency—recent Exercise for health: ≥3-4×/wk vs no activity (3 cats) OR, 0.63 (0.34-1.11); trend: no (P = n.a.) 48 
         Residual confounding: yes  
    Olson et al. (21) United States 1986-1991 40-85 232 pre- and post-meno 631 Hospital based/population based Duration—recent Vigorous activity: ≥100 h/y vs none (3 cats) OR, 0.67 (0.42-1.09); trend: yes (P = 0.06) 47 
         Residual confounding: yes  
    Goodman et al. (22) Hawaii (United States) 1985-1993 18-84 332 pre- and post-meno 511 Population based/population based Duration (lifetime h)—lifetime Lifetime hours: >3,339 vs 0 h (4 quartiles) OR, 0.9 (CI incl 1); trend: no (P = 0.34) 55 
         Residual confounding: yes  
    Moradi et al. (24) Sweden 1994-1995 50-74 709 postmeno 3,368 Population based/population based Duration—recent Exercise/sports: 0 h/wk vs >2 h/wk OR, 1.3 (1.1-1.7); trend: yes (P = 0.01) 70 
         Residual confounding: partly  
    Littman et al. (25) United States 1985-1991 45-74 822 mostly postmeno? 1,111 Population based/population based Duration—recent Any recreational activity: >6 h/wk vs none (4 cats) OR, 0.83 (0.59-1.15); trend: no (P = 0.31) 58 
         Residual confounding: yes  
    Matthews et al. (5) China 1997-2001 30-69 832 pre- and post-meno 846 Population based/population based Calorie expenditure—lifetime (adult + adolescence) Highest quartile vs none (5 cats) OR, 0.60 (0.42-0.86); trend: yes (P < 0.01) 74 
         Residual confounding: no  
Occupational activity           
    Sturgeon et al. (17) United States 1987-1990 20-74 405 pre- and post-meno 297 Hospital based/population based Frequency—recent Rarely/never vs daily OR, 1.4 (1.0-2.1); trend: no 60 
         Residual confounding: no  
    Shu et al. (18) China 1988-1990 18-74 268 pre- and post-meno 268 Population based/population based Caloric expenditure—lifetime Lowest quartile vs highest quartile OR, 1.0 (0.6-1.7); trend: no 80 
         Residual confounding: no  
    Levi et al. (19) Switzerland/Italy 1988-1991 31-75 274 pre- and post-meno 572 Hospital based/hospital based Subjective—recent Very low vs high (4 cats) OR, 1.5 (1.0-2.2); trend: no (P < 0.05) 42 
         Residual confounding: yes  
    Zheng et al. (26) China 1980-1984 ≥30 452 pre- and post-meno Population based/population based Job category—recent High (>12 kJ/m) vs Low (<8 kJ/m) SIRhigh/SIRlow: 0.72; trend: yes 55 
         Residual confounding: yes  
    Dosemeci et al. (27) Turkey 1979-1984 all 31 pre- and post-meno 244 Hospital based/hospital based Job category—lifetime Sedentary (<8 kJ/m) vs active (>12 kJ/m) OR, 0.5 (0.0-9.3); trend: yes (P = 0.27) 33 
         Residual confounding: yes  
    Kalandidi et al. (28) Greece 1992-1994 all 145 pre- and post-meno 298 Hospital based/hospital based Job category—recent Manual vs nonmanual (3 cats) OR, 0.41 (0.18-0.91); trend: yes 45 
         Residual confounding: no  
    Olson et al. (21) United States 1986-1991 40-85 232 pre- and post-meno 631 Hospital based/population based Caloric expenditure—recent Highest vs lowest tertile OR, 1.19 (0.76-1.87); trend: no (P = 0.39) 47 
         Residual confounding: yes  
    Goodman et al. (22) Hawaii (United States) 1985-1993 18-84 332 pre- and post-meno 511 Population basedPopulation based Duration (lifetime hours)—lifetime Lifetime hours: >20,089 h vs 0 h (4 quartiles) OR, 0.7 (CI incl 1); trend: no (P = 0.08) 55 
         Residual confounding: yes  
    Moradi et al. (24) Sweden 1994-1995 50-74 709 postmeno 3,368 Population based/population based Job category—recent Sedentary vs high/very high OR, 1.3 (0.9-1.9); trend: no (P = 0.05) 70 
         Residual confounding: partly  
    Matthews et al. (5) China 1997-2001 30-69 832 pre- and post-meno 846 Population based/population based Calorie expenditure—lifetime Highest quartile vs none OR, 0.86 (0.63-1.18); trend: no (P = 0.70) 74 
         Residual confounding: no  
Author (reference)CountryActivity assessmentAge (y)No. casesNo. controlsStudy base (cases/controls)Activity measure—life periodsContrastRisk estimate (95% CI)* trendQuality score (% of max)
Total activity           
    Sturgeon et al. (17) United States 1987-1990 20-74 405 pre- and post-meno 297 Hospital based/population based Subjective (global assessment)—recent Very inactive vs very active (5 cats) OR, 2.5 (0.7-8.7); trend: no (P = n.a.) 60 
         Residual confounding: no  
    Shu et al. (18) China 1988-1990 18-74 268 pre- and post-meno 268 Population based/population based Subjective—age 50-59 Very inactive vs very active (5 cats) OR, 2.1 (0.6-7.1); trend: no (P = n.a.) 80 
         Residual confounding: no  
    Levi et al. (19) Switzerland/Italy 1988-1991 31-75 274 pre- and post-meno 572 Hospital based/hospital based Subjective—age 55 Lowest vs highest (4 cats) OR, 8.6 (3.0-25.3); trend: no (P < 0.01) 42 
         Residual confounding: yes  
    Salazar-Martinez et al. (23) Mexico 1995-1997 85 pre- and post-meno 668 Hospital based/hospital based MET-h/wk—recent? leisure? ≥38 MET-h/wk vs ≤29 (3 cats) OR, 0.47 (0.26-0.86); trend: no (P = 0.01) 44 
         Residual confounding: yes  
Leisure time activity           
    Sturgeon et al. (17) United States 1987-1990 20-74 405 pre- and post-meno 297 Hospital based/population based Subjective—recent Lowest quintile vs highest OR, 1.2 (0.7-2.2); trend: no (P = n.a.) 60 
         Residual confounding: no  
    Shu et al. (18) China 1988-1990 18-74 268 pre- and post-meno 268 Population based/population based MET—age 50-59 Lowest quartile vs highest quartile OR, 1.0 (0.6-1.7); trend: no (P = n.a.) 80 
         Residual confounding: no  
    Levi et al. (19) Switzerland/Italy 1988-1991 31-75 274 pre- and post-meno 572 Hospital based/hospital based Subjective—recent Sporsts and leisure: lowest vs highest (4 cats) OR, 1.9 (0.9-4.0); trend: no (P < 0.01) 42 
         Residual confounding: yes  
    Hirose et al. (20) Japan 1988-1993 18-80+ 145 pre- and post-meno 26,751 Hospital based/hospital based Frequency—recent Exercise for health: ≥3-4×/wk vs no activity (3 cats) OR, 0.63 (0.34-1.11); trend: no (P = n.a.) 48 
         Residual confounding: yes  
    Olson et al. (21) United States 1986-1991 40-85 232 pre- and post-meno 631 Hospital based/population based Duration—recent Vigorous activity: ≥100 h/y vs none (3 cats) OR, 0.67 (0.42-1.09); trend: yes (P = 0.06) 47 
         Residual confounding: yes  
    Goodman et al. (22) Hawaii (United States) 1985-1993 18-84 332 pre- and post-meno 511 Population based/population based Duration (lifetime h)—lifetime Lifetime hours: >3,339 vs 0 h (4 quartiles) OR, 0.9 (CI incl 1); trend: no (P = 0.34) 55 
         Residual confounding: yes  
    Moradi et al. (24) Sweden 1994-1995 50-74 709 postmeno 3,368 Population based/population based Duration—recent Exercise/sports: 0 h/wk vs >2 h/wk OR, 1.3 (1.1-1.7); trend: yes (P = 0.01) 70 
         Residual confounding: partly  
    Littman et al. (25) United States 1985-1991 45-74 822 mostly postmeno? 1,111 Population based/population based Duration—recent Any recreational activity: >6 h/wk vs none (4 cats) OR, 0.83 (0.59-1.15); trend: no (P = 0.31) 58 
         Residual confounding: yes  
    Matthews et al. (5) China 1997-2001 30-69 832 pre- and post-meno 846 Population based/population based Calorie expenditure—lifetime (adult + adolescence) Highest quartile vs none (5 cats) OR, 0.60 (0.42-0.86); trend: yes (P < 0.01) 74 
         Residual confounding: no  
Occupational activity           
    Sturgeon et al. (17) United States 1987-1990 20-74 405 pre- and post-meno 297 Hospital based/population based Frequency—recent Rarely/never vs daily OR, 1.4 (1.0-2.1); trend: no 60 
         Residual confounding: no  
    Shu et al. (18) China 1988-1990 18-74 268 pre- and post-meno 268 Population based/population based Caloric expenditure—lifetime Lowest quartile vs highest quartile OR, 1.0 (0.6-1.7); trend: no 80 
         Residual confounding: no  
    Levi et al. (19) Switzerland/Italy 1988-1991 31-75 274 pre- and post-meno 572 Hospital based/hospital based Subjective—recent Very low vs high (4 cats) OR, 1.5 (1.0-2.2); trend: no (P < 0.05) 42 
         Residual confounding: yes  
    Zheng et al. (26) China 1980-1984 ≥30 452 pre- and post-meno Population based/population based Job category—recent High (>12 kJ/m) vs Low (<8 kJ/m) SIRhigh/SIRlow: 0.72; trend: yes 55 
         Residual confounding: yes  
    Dosemeci et al. (27) Turkey 1979-1984 all 31 pre- and post-meno 244 Hospital based/hospital based Job category—lifetime Sedentary (<8 kJ/m) vs active (>12 kJ/m) OR, 0.5 (0.0-9.3); trend: yes (P = 0.27) 33 
         Residual confounding: yes  
    Kalandidi et al. (28) Greece 1992-1994 all 145 pre- and post-meno 298 Hospital based/hospital based Job category—recent Manual vs nonmanual (3 cats) OR, 0.41 (0.18-0.91); trend: yes 45 
         Residual confounding: no  
    Olson et al. (21) United States 1986-1991 40-85 232 pre- and post-meno 631 Hospital based/population based Caloric expenditure—recent Highest vs lowest tertile OR, 1.19 (0.76-1.87); trend: no (P = 0.39) 47 
         Residual confounding: yes  
    Goodman et al. (22) Hawaii (United States) 1985-1993 18-84 332 pre- and post-meno 511 Population basedPopulation based Duration (lifetime hours)—lifetime Lifetime hours: >20,089 h vs 0 h (4 quartiles) OR, 0.7 (CI incl 1); trend: no (P = 0.08) 55 
         Residual confounding: yes  
    Moradi et al. (24) Sweden 1994-1995 50-74 709 postmeno 3,368 Population based/population based Job category—recent Sedentary vs high/very high OR, 1.3 (0.9-1.9); trend: no (P = 0.05) 70 
         Residual confounding: partly  
    Matthews et al. (5) China 1997-2001 30-69 832 pre- and post-meno 846 Population based/population based Calorie expenditure—lifetime Highest quartile vs none OR, 0.86 (0.63-1.18); trend: no (P = 0.70) 74 
         Residual confounding: no  

Abbreviation: n.a., not applicable; SIR, standard incidence ratio; PE, physical exercise teachers; L, language teachers; high: <12 kJ/m; low: <8 kJ/m.

*

Printed in italic if contrast is low versus high activity levels.

Trend: subjective assessment (P value for trend test if available).

Includes only postmenopausal women.

Quality Score

The total quality score, as a percentage of the maximum score, ranged between 61% and 87% (median, 71%) for the cohort studies and between 33% and 80% (median, 55%) for the case-control studies. The median quality score of all studies combined was 60.5%. All seven cohort studies and three case-control studies were thus categorized as high-quality studies (i.e., quality score above the median). Especially cohort studies scored very favorably on issues about selection bias (range, 83-100%; median, 100%) as compared with case-control studies (range, 26-90%; median, 71%). Case-control studies scored moderately on misclassification issues (range, 24-83%; median, 57%) and even less favorably on confounding (range, 0-100%; median, 19%). Cohort studies scored similarly, for misclassification between 43% and 78% (median, 60%) and for confounding between 19% and 76% (median, 38%). Among case-control studies, there was a tendency for larger studies (i.e., greater number of endometrial cancer cases) to have a more favorable quality score than smaller studies (Fig. 1).

Figure 1.

The relation between quality score and study size in cohort and case-control studies. One cohort study [Moradi et al. (16)] includes 5,287 cases, but is depicted at 2,000 for presentation purposes.

Figure 1.

The relation between quality score and study size in cohort and case-control studies. One cohort study [Moradi et al. (16)] includes 5,287 cases, but is depicted at 2,000 for presentation purposes.

Close modal

Magnitude of Risk and Strength of Evidence

Four cohort studies reported on leisure time activity, of which three found a decreased risk of endometrial cancer (based on our definition; see Methods) for women in the highest activity versus the lowest activity category (Table 1; Fig. 2; refs. 4, 12, 14). Risk reductions ranged between 20% and 90%, and two of three studies showed evidence for a dose-response effect (trend test, P < 0.01; refs. 4, 12). Terry et al. (12) found that the highest activity level (i.e., “hard physical training”) was associated with a very strong decrease in risk of endometrial cancer compared with having no leisure time activities [hazard ratio (HR), 0.1; 95% confidence interval (95% CI), 0.04-0.6]. However, this was based on only two cases in the most active group. Only one cohort study assessed total activity and found a 20% endometrial cancer risk reduction (HR, 0.8; 95% CI, 0.5-1.1; ref. 13). In two of four studies that assessed occupational activity, a decreased risk of endometrial cancer was found in women in the highest versus the lowest category of occupational activity (e.g., manual/standing work versus sedentary work; refs. 14, 16).

Figure 2.

Risk estimates of studies on physical activity and endometrial cancer risk, ordered according to study design and total quality score. A. Cohort studies. B. Case-control studies. ⧫, leisure time activity; ◊, total activity; occupational activity. Risk estimates from Sturgeon et al. (17), Shu et al. (18), and Levi et al. (19) were reported for inactive versus active group and have been converted for presentation purposes.

Figure 2.

Risk estimates of studies on physical activity and endometrial cancer risk, ordered according to study design and total quality score. A. Cohort studies. B. Case-control studies. ⧫, leisure time activity; ◊, total activity; occupational activity. Risk estimates from Sturgeon et al. (17), Shu et al. (18), and Levi et al. (19) were reported for inactive versus active group and have been converted for presentation purposes.

Close modal

Of the 13 case-control studies, 4 assessed total activity and 9 assessed leisure time activity (3 studies assessed both). Ten case-control studies included some assessment of occupational activities. Of the nine studies assessing leisure time activity, five observed a decreased risk of endometrial cancer (based on our definition; see Methods) for the most active group compared with the least active group (Table 2; Fig. 2; refs. 5, 19-21, 24). Three of these nine studies also showed evidence for a dose-response effect (P values between <0.01 and 0.06 for trend test; refs. 5, 21, 24) and one study reported a significant trend test although no obvious trend could be observed (19). All four studies that assessed total activity found a markedly decreased risk of endometrial cancer (HRs between 0.1 and 0.5) for the most active women compared with the least active women (17-19, 23). None of these studies clearly showed a dose-response effect, although a trend test suggested differently in two studies (trend test, P ≤ 0.01; refs. 19, 23). Six of 10 studies reporting on occupational activity found a decreased risk of endometrial cancer (based on our definition; see Methods; refs. 17, 19, 22, 24, 26, 28). Two of these studies also showed some evidence for a dose-response effect; however, no P values were reported (26, 28). Dosemeci et al. (27) reported on the only study to find a 2-fold increased risk of endometrial cancer for women with active jobs as compared with women with sedentary jobs. The reported odds ratio (OR) was not statistically significant, based on only 31 cases, and the study had an unfavorable quality score.

Based on our best evidence synthesis, there is strong evidence for an inverse association between physical activity and endometrial cancer risk. Eight of 10 high-quality studies reported a risk reduction of >20% for the highest category of total, leisure time, or occupational activity. Seven of eight (88%) high-quality studies reporting on total or leisure time activities found an inverse association with either of these physical activity assessments. Only 3 of 7 (43%) high-quality studies on occupational activity found a reduction in risk for women with active jobs as compared with women with inactive jobs.

Statistical Heterogeneity and Pooling

The effect estimates of eight case-control studies that investigated leisure time activities and reported 95% CIs were not found to be statistically heterogeneous. Pooling resulted in a summary estimate of a 27% decreased risk of endometrial cancer for the most active women compared with the least active women (summary OR, 0.73; 95% CI, 0.62-0.86). Similarly, effect estimates of eight case-control studies that reported on occupational activities and included 95% CIs were also not found to be statistically heterogeneous (summary OR, 0.80; 95% CI, 0.66-0.96). Pooling of all total, leisure time, and occupational activity effect estimates, irrespective of statistical heterogeneity, suggested an at least 20% decrease in endometrial cancer risk for the most active women compared with the least active women [cohort summary relative risk (RR), 0.77; 95% CI, 0.70-0.85; case-control summary OR, 0.71; 95% CI, 0.63-0.80; Fig. 2].

Effect Modification by Body Mass Index and Menopausal Status

Four of seven cohort studies assessed whether body mass index (BMI) had a modifying effect on the association between physical activity and endometrial cancer risk and did not find any statistical evidence for interaction (at the multiplicative level; refs. 4, 6, 13, 14). Of all case-control studies, six assessed effect modification by BMI. Four studies found no differences in stratum-specific risk estimates (5, 18, 24, 25). Sturgeon et al. (17) found that the decrease in risk found with leisure time activity was limited to those with a BMI >25. Levi et al. (19) also observed stronger associations with physical activity in those with a high BMI; however, these analyses were not adjusted for potential confounders. Most studies adjusted for BMI as a confounding factor but found only slightly attenuated risk estimates.

Very few studies specifically assessed whether the association between physical activity and endometrial cancer risk differed by menopausal status. Colbert et al. (13) found no significant interaction between menopausal status and total activity. Furberg and Thune (14) stratified by age and found that the effect of physical activity was stronger in women aged ≥50 years (not statistically significant). Of the case-control studies, only two studies examined effect modification by menopausal status. Both Sturgeon et al. (5) and Matthews et al. (17) found no significant difference in effect between premenopausal and postmenopausal women.

Association with Physical Activity in Different Life Periods

The association between endometrial cancer risk and physical activity in different periods of life was only assessed in five case-control studies (5, 18, 19, 21, 24). The association with physical activity levels in recent years of life (above age 50, or years before physical activity assessment) was generally somewhat stronger than the association with physical activity in adolescence or young adulthood (18, 19, 21, 24). None of these studies adjusted for physical activity levels in other periods of life. Matthews et al. (5) specifically studied physical activity patterns in adolescence and adulthood in relation to premenopausal and postmenopausal endometrial cancer risk. They reported that being physically active only in adulthood (i.e., nonactive during adolescence) was associated with a decrease in postmenopausal but not in premenopausal endometrial cancer risk. Higher levels of physical activity in adolescence were associated with a decreased risk of premenopausal endometrial cancer only. However, being physically active in adolescence only (i.e., nonactive during adulthood) was associated with marginally decreased risk of both premenopausal and postmenopausal endometrial cancer (not statistically significant).

Exploring Causes of Heterogeneity in Study Results

We next examined whether methodologic issues can explain heterogeneity in the magnitude of the estimated endometrial cancer risk. Substantial variation between studies was observed in exposure quantification and categorization. The reference category of leisure time activities varied from “none” to 2-3 h of (moderate) activity per week, whereas the highest activity category varied from 2 h of (vigorous) activities per week to >6 or even 9 h of moderate/vigorous activities per week. We did not observe a pattern or trend of studies with higher activity categories or a larger contrast finding stronger associations between physical activity and endometrial cancer risk (data not shown).

Besides these issues relating to exposure assessment, we also examined whether study quality could explain heterogeneity in magnitude of the risk estimates. In Fig. 2 studies are ordered according to total quality score, showing the relation between the total quality score and the magnitude of the estimate of the highest versus the lowest level of activity. Studies with an unfavorable total quality score tended to report more divergent risk estimates, ranging from a >2-fold decreased risk to a 2-fold increased risk. In particular, high variability in the magnitude of the risk estimates was found in case-control studies with a relatively unfavorable “selection bias score” (Fig. 3). In cohort studies, selection bias was not an issue as six of seven cohort studies attained the maximum score. The magnitude of the risk estimates in cohort and case-control studies did not correlate strongly with quality scores for “misclassification” or “confounding” (data not shown).

Figure 3.

Relation between selection bias score and magnitude of the association between physical activity and endometrial cancer risk.

Figure 3.

Relation between selection bias score and magnitude of the association between physical activity and endometrial cancer risk.

Close modal

Exploring Publication Bias

Figure 4 represents a funnel plot for cohort and case-control studies combined. The funnel plot shows that risk estimates of the larger studies cluster around a risk reduction of 20% to 50%, comparing the lowest and highest levels of physical activity, in both cohort and case-control studies. Studies with relatively small numbers of cases show a larger diversity in risk estimates, both strong risk reductions and some increased risks. These results suggest that no major bias has occurred by selective publication.

Figure 4.

Funnel plot of cohort and case-control studies, relating study size to magnitude of the risk estimate. One cohort study (Moradi et al.) includes 5,287 cases, but is depicted at 2,000 for presentation purposes.

Figure 4.

Funnel plot of cohort and case-control studies, relating study size to magnitude of the risk estimate. One cohort study (Moradi et al.) includes 5,287 cases, but is depicted at 2,000 for presentation purposes.

Close modal

This is the first systematic and standardized review of epidemiologic studies of the association between physical activity and endometrial cancer. Considerable variation among studies was observed with respect to design, exposure assessment, and study quality (scores ranging between 33% and 87% of the maximum attainable score). The best evidence synthesis showed that the majority of high-quality studies found strong evidence for an inverse association between physical activity and endometrial cancer risk. The pooled estimate of seven high-quality cohort studies showed a statistically significantly decreased risk of endometrial cancer (OR, 0.77; 95% CI, 0.70-0.85) for the most active women compared with the least active women. We found some evidence that study quality was inversely associated with the estimated magnitude of the risk reduction, particularly with regard to selection bias in case-control studies. Therefore, several more high-quality cohort studies are needed for a definitive conclusion on the association between physical activity and endometrial cancer risk.

Most of the studies included in this review controlled for confounding factors to some extent. On the other hand, neither cohort nor case-control studies scored very favorably on study quality with respect to confounding. The incomplete assessment of confounders does not automatically imply, however, that the results of the included studies are biased. In those studies that adequately adjusted for potential confounders and reported both adjusted and unadjusted risk estimates, the magnitude of the risk estimates did not materially change by adjusting for confounding factors. An important issue with respect to confounding is the role of BMI. Body weight or BMI could be in the causal pathway between physical activity and endometrial cancer risk (i.e., hypothetically, the apparently protective effect from physical activity might be wholly due to a lower body weight in physically active women). If this is the case, adding BMI as a confounding factor to the regression models would strongly attenuate the effect of physical activity. Three of five cohort studies and 6 of 13 case-control studies specifically reported on the effect of adding BMI to the model adjusted for other confounding factors. Most studies found only slightly attenuated risk estimates, providing evidence that physical activity is associated with lower endometrial cancer risk independently of BMI. Furthermore, no convincing evidence was found for differences in the association between physical activity and endometrial cancer risk after stratification for BMI.

This review shows that only few studies assessed total physical activity. All four studies that assessed both total physical activity and leisure time activity found that the association with endometrial cancer risk was stronger for total than for leisure time activity. Overall, the evidence was less consistent for occupational activity than for total and leisure time activities. Most studies on occupational activity used crude methods for exposure assessment (i.e., job title) and a large number of women were not, or only shortly, engaged in paid employment. This may have resulted in errors in the measurement of physical activity and consequently risk estimation for risk of endometrial cancer. Although leisure time activity has become more important in Western countries and may reflect an individual's total physical activity level in most societies, this assumption does not hold for all populations. Therefore, future studies should aim at measuring both total and leisure time activities, and special attention should be paid to household activities.

Several issues have not received sufficient attention in the epidemiologic studies thus far. Some studies have used very rough assessments of physical activity, without specifically taking into account the frequency, duration, and intensity of physical activities, and the different periods in life during which activity patterns may have changed. In addition, the association of physical activity and premenopausal endometrial cancer risk has been insufficiently studied. Future epidemiologic studies will need to address these issues to specify the association between physical activity and endometrial cancer risk.

The mechanisms by which physical activity may protect against endometrial cancer are not fully understood. Obesity is one of the main risk factors for endometrial cancer and is estimated to account for ∼40% of endometrial cancer incidence in Europe (29). Although lack of physical activity is known to be associated with an increased risk of obesity (30, 31), the studies described in this systematic review show that physical activity is associated with a decreased risk of endometrial cancer in both normal weight and obese women. The combined effects of endogenous hormones, such as sex steroid hormones, insulin, and insulin-like growth factor-I, are also known to play an important role in the development of endometrial cancer, and may well relate to the mechanism underlying the effect of physical activity on endometrial cancer risk (32). Many of the effects of known risk factors for endometrial cancer can be explained by the unopposed estrogen hypothesis (2). This hypothesis proposes that endometrial cancer risk is increased in women who have high plasma bioavailable estrogens insufficiently counterbalanced by progesterone, which would result in stimulation of proliferation and induction of genetic damage in endometrial cells (2, 33). Both hormones also affect levels of insulin-like growth factor-I, possibly in opposite directions. Hyperinsulinemia is also associated with increased risk of endometrial cancer (34, 35). Although the effects of physical activity on insulin-like growth factor-I are unclear (36), physical activity is known to decrease the levels of serum estrogens (37) and serum insulin (38).

In conclusion, physical activity seems to be associated with a significant reduction in the risk of endometrial cancer. However, the number of high-quality prospective cohort studies is still limited. Based on 20 observational studies, evidence suggests that physical activity is associated with a 20% to 40% decreased risk of endometrial cancer. Further studies are needed to assess which aspects (i.e., frequency, intensity, duration) of physical activity are most strongly related to the risk of endometrial cancer; which amount of physical activity is necessary; and in which period of life physical activity contributes most to the risk reduction. Both observational epidemiologic studies, preferably prospective in design, and intervention studies should be designed to examine interactive effects of physical activity, diet, and body weight. Intervention studies should help elucidate the causal pathway through which these effects occur.

Methodologic quality score—cohort and case-control studies

CriteriaScoreComments
Selection bias   
    1a. Percentage loss to follow-up? Only applicable to cohort studies   
        >20% or unknown or unclassifiable The percentage is unclassifiable if the total eligible cohort is not clear. 
        5-20%  
        <5%  
    1b. Percentage response of the cases and controls? Only applicable to case-control studies   
        <75% or unknown or unclassifiable Response = [1 − (refusal of subject/physician, contact problems, death before interview) / eligible subjects) × 100. Judging the response of cases and controls, the lowest percentage counts. Unclassifiable if the complete eligible group is not clear. 
        75-90%  
        >90%  
    2. Was the absolute difference in percentage response <20% between cases and controls?   
        Not applicable (cohort study) 10  
        No or unknown  
        Yes  
    3. Percentage incident cases?   
        <75% Some studies include prevalent and/or fatal cases without information about the date of diagnosis, which may introduce bias, as physical activity may also be associated with survival. 
        75-99% or unknown  
        100%  
    4. Did the cases and controls originate from the same source population?   
        Not applicable (cohort study) 10  
        No or unknown  
        Yes 10  
    5. Were the same exclusion/inclusion criteria applied to cases and controls?   
        Not applicable (cohort study)  
        No or unknown  
        Yes  
    Maximal selection bias score 42  
Misclassification bias   
    Determination of physical activity   
        6. Was the measure of leisure time activities that was analyzed complete enough?   
            No Activity may have been assessed extensively whereas only few components where included in the analysis. Judgement of the item was based on reviewers' consensus. 
            Yes  
        7. Was total activity assessed?   
            No Total activity means leisure time activity and job/household activity. These should be combined in one effect measure. 
            Yes  
        8. Did the measure of physical activity include intensity, frequency and duration?   
            One component or unknown  
            Intensity + frequency/duration per week  
        9. Type of administration of physical activity questionnaire   
            By proxy By proxy means that physical activity is not individually assessed (e.g., a family member was asked); classification was based on college registration of athletics. 
            Self-administered  
            Interview-administered  
        10. Was the operationalization of the physical activity score understandable?   
            No or partly  
            Yes  
        11. Did the physical activity measure include past physical activity?   
            No, only recent A physical activity measure covering more periods of life is supposed to be more accurate. 
            Yes, more life periods  
        12. Did the authors consider changes over time in physical activity pattern in the analyses?   
            No Yes: e.g., when two measurements of physical activity several years apart were used to classify participants in consistently active or inactive. 
            Yes  
        13. Was the physical activity questionnaire validated or was reliability tested?   
            No or unknown  
            Yes  
        14. Was physical activity level assessed before endometrial cancer diagnosis?   
            No When physical activity is measured after the diagnosis of endometrial cancer, there is a possibility of recall bias. 
            No, but physical activity level was assessed the same way for cases and controls  
            Yes  
    Outcome   
        15. Was the case diagnosis valid?   
            No or unknown Endometrial cancer self-report may be valid, especially if confirmed by medical report. 
            Yes  
        16. Could benign endometrial disease (carcinoma in situ) in any way have influenced the results?   
            Yes or unknown Any influence seems unlikely if <5% of cases have carcinoma in situ and/or if separate analyses/exclusion did not result in different estimates. 
            No  
    Maximal misclassification bias score 42  
Confounding bias   
    17. Were confounders adjusted for in a correct way (statistically)?   
        No or unknown  
        Yes  
    18. Could residual confounding be a problem?   
        Yes Potential confounders: age, BMI, parity, age at menopause (and/or smoking), oral contraceptive use, hormone replacement therapy; Residual confounding could also be a problem when (a) continuous variables were crudely categorized or (b) BMI or hormone replacement therapy were not measured within 5 y of diagnosis. 
        Partly  
        No  
    19. Were the effects of leisure time activities adjusted for occupational/household activities?   
        No or unknown  
        Yes  
    Maximal confounding bias score 21  
   
Maximal total score: 105   
    Patients and controls are not from the same source populations when:   
   
    •hospital-based controls are used and it is unlikely that the controls would be referred to the same hospital in case of cancer;   
    •cases are recruited from a specialized cancer hospital (e.g., subgroup of patients with more advanced disease) and controls are population based and it is quite uncertain whether they would be referred to the same hospital if they had become a case;   
    •controls are not a random sample of the source population;   
    •cases and controls are selected from different areas/countries.   
CriteriaScoreComments
Selection bias   
    1a. Percentage loss to follow-up? Only applicable to cohort studies   
        >20% or unknown or unclassifiable The percentage is unclassifiable if the total eligible cohort is not clear. 
        5-20%  
        <5%  
    1b. Percentage response of the cases and controls? Only applicable to case-control studies   
        <75% or unknown or unclassifiable Response = [1 − (refusal of subject/physician, contact problems, death before interview) / eligible subjects) × 100. Judging the response of cases and controls, the lowest percentage counts. Unclassifiable if the complete eligible group is not clear. 
        75-90%  
        >90%  
    2. Was the absolute difference in percentage response <20% between cases and controls?   
        Not applicable (cohort study) 10  
        No or unknown  
        Yes  
    3. Percentage incident cases?   
        <75% Some studies include prevalent and/or fatal cases without information about the date of diagnosis, which may introduce bias, as physical activity may also be associated with survival. 
        75-99% or unknown  
        100%  
    4. Did the cases and controls originate from the same source population?   
        Not applicable (cohort study) 10  
        No or unknown  
        Yes 10  
    5. Were the same exclusion/inclusion criteria applied to cases and controls?   
        Not applicable (cohort study)  
        No or unknown  
        Yes  
    Maximal selection bias score 42  
Misclassification bias   
    Determination of physical activity   
        6. Was the measure of leisure time activities that was analyzed complete enough?   
            No Activity may have been assessed extensively whereas only few components where included in the analysis. Judgement of the item was based on reviewers' consensus. 
            Yes  
        7. Was total activity assessed?   
            No Total activity means leisure time activity and job/household activity. These should be combined in one effect measure. 
            Yes  
        8. Did the measure of physical activity include intensity, frequency and duration?   
            One component or unknown  
            Intensity + frequency/duration per week  
        9. Type of administration of physical activity questionnaire   
            By proxy By proxy means that physical activity is not individually assessed (e.g., a family member was asked); classification was based on college registration of athletics. 
            Self-administered  
            Interview-administered  
        10. Was the operationalization of the physical activity score understandable?   
            No or partly  
            Yes  
        11. Did the physical activity measure include past physical activity?   
            No, only recent A physical activity measure covering more periods of life is supposed to be more accurate. 
            Yes, more life periods  
        12. Did the authors consider changes over time in physical activity pattern in the analyses?   
            No Yes: e.g., when two measurements of physical activity several years apart were used to classify participants in consistently active or inactive. 
            Yes  
        13. Was the physical activity questionnaire validated or was reliability tested?   
            No or unknown  
            Yes  
        14. Was physical activity level assessed before endometrial cancer diagnosis?   
            No When physical activity is measured after the diagnosis of endometrial cancer, there is a possibility of recall bias. 
            No, but physical activity level was assessed the same way for cases and controls  
            Yes  
    Outcome   
        15. Was the case diagnosis valid?   
            No or unknown Endometrial cancer self-report may be valid, especially if confirmed by medical report. 
            Yes  
        16. Could benign endometrial disease (carcinoma in situ) in any way have influenced the results?   
            Yes or unknown Any influence seems unlikely if <5% of cases have carcinoma in situ and/or if separate analyses/exclusion did not result in different estimates. 
            No  
    Maximal misclassification bias score 42  
Confounding bias   
    17. Were confounders adjusted for in a correct way (statistically)?   
        No or unknown  
        Yes  
    18. Could residual confounding be a problem?   
        Yes Potential confounders: age, BMI, parity, age at menopause (and/or smoking), oral contraceptive use, hormone replacement therapy; Residual confounding could also be a problem when (a) continuous variables were crudely categorized or (b) BMI or hormone replacement therapy were not measured within 5 y of diagnosis. 
        Partly  
        No  
    19. Were the effects of leisure time activities adjusted for occupational/household activities?   
        No or unknown  
        Yes  
    Maximal confounding bias score 21  
   
Maximal total score: 105   
    Patients and controls are not from the same source populations when:   
   
    •hospital-based controls are used and it is unlikely that the controls would be referred to the same hospital in case of cancer;   
    •cases are recruited from a specialized cancer hospital (e.g., subgroup of patients with more advanced disease) and controls are population based and it is quite uncertain whether they would be referred to the same hospital if they had become a case;   
    •controls are not a random sample of the source population;   
    •cases and controls are selected from different areas/countries.   
Level of evidenceStudy results(a)
Strong evidence for an inverse association ≥75% of all high-quality studies(b) reporting a decreased risk,(c) or 
 ≥60-75% of all high-quality studies reporting a decreased risk and <10% of all high-quality studies reporting an increased risk(c) 
Moderate evidence for an inverse association ≥60-75% of high-quality studies reporting a decreased risk and <25% of all high-quality studies reporting an increased risk, or 
 ≥50-60% of all high-quality studies reporting a decreased risk and <10% of all high-quality studies reporting an increased risk 
Indecisive evidence inconsistent findings defined as all other findings not applicable to strong, moderate or no evidence for an inverse association, or there are <4 high-quality studies available 
Nil ≥60% of all high-quality studies reporting no association or an increased risk, or 
 ≥40% of all high-quality studies reporting an increased risk 
Level of evidenceStudy results(a)
Strong evidence for an inverse association ≥75% of all high-quality studies(b) reporting a decreased risk,(c) or 
 ≥60-75% of all high-quality studies reporting a decreased risk and <10% of all high-quality studies reporting an increased risk(c) 
Moderate evidence for an inverse association ≥60-75% of high-quality studies reporting a decreased risk and <25% of all high-quality studies reporting an increased risk, or 
 ≥50-60% of all high-quality studies reporting a decreased risk and <10% of all high-quality studies reporting an increased risk 
Indecisive evidence inconsistent findings defined as all other findings not applicable to strong, moderate or no evidence for an inverse association, or there are <4 high-quality studies available 
Nil ≥60% of all high-quality studies reporting no association or an increased risk, or 
 ≥40% of all high-quality studies reporting an increased risk 

(a) At least four studies are necessary to define the evidence as strong, moderate, or no evidence. When less than four studies are available, the evidence will be defined as inconclusive.

(b) A high-quality study was defined as a study with a total quality score above the median quality score of all studies (i.e., >60.5% of the maximal attainable score).

(c) A decreased risk was defined as a risk estimate of <0.80 for the highest versus the lowest level of activity; no association as a risk estimate between 0.8 and 1.25; and an increased risk as a risk estimate >1.25.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: This review was undertaken as part of the activities of the Task Force Physical Activity and Cancer of the Signalling Committee of the Dutch Cancer Society.

1
Descriptive Epidemiology Group I. GLOBOCAN. 2002. CANCERMondial. Available from: http://www-dep.iarc.fr.
2
Akhmedkhanov A, Zeleniuch-Jacquotte A, Toniolo P. Role of exogenous and endogenous hormones in endometrial cancer: review of the evidence and research perspectives.
Ann N Y Acad Sci
2001
;
943
:
296
–315.
3
Amant F, Moerman P, Neven P, Timmerman D, Van Limbergen E, Vergote I. Endometrial cancer.
Lancet
2005
;
366
:
491
–505.
4
Schouten LJ, Goldbohm RA, van den Brandt PA. Anthropometry, physical activity, and endometrial cancer risk: results from the Netherlands Cohort Study.
J Natl Cancer Inst
2004
;
96
:
1635
–8.
5
Matthews CE, Xu WH, Zheng W, et al. Physical activity and risk of endometrial cancer: a report from the Shanghai endometrial cancer study.
Cancer Epidemiol Biomarkers Prev
2005
;
14
:
779
–85.
6
Friberg E, Mantzoros CS, Wolk A. Physical activity and risk of endometrial cancer: a population-based prospective cohort study.
Cancer Epidemiol Biomarkers Prev
2006
;
15
:
2136
–40.
7
IARC Working Group on the evaluation of Cancer-Preventive Strategies. Weight control and physical activity. Lyon (France): IARC Press; 2002.
8
Monninkhof EM, Elias SG, Vlems FA, et al. Physical activity and breast cancer, a systematic review of current evidence.
Epidemiology
2007
;
18
:
137
–57.
9
Powell KE, Thompson PD, Caspersen CJ, Kendrick JS. Physical activity and the incidence of coronary heart disease.
Annu Rev Public Health
1987
;
8
:
253
–87.
10
Petitti DB. Statistical methods in meta-analysis. In: Petitti DB, editor. Meta-analysis, decision analysis and cost-effectiveness analysis. Methods for quantitative synthesis in medicine. New York: Oxford University Press; 2000. p. 94–118.
11
Prentice RL, Thomas DB. On the epidemiology of oral contraceptives and disease.
Adv Cancer Res
1987
;
49
:
285
–401.
12
Terry P, Baron JA, Weiderpass E, Yuen J, Lichtenstein P, Nyren O. Lifestyle and endometrial cancer risk: a cohort study from the Swedish Twin Registry.
Int J Cancer
1999
;
82
:
38
–42.
13
Colbert LH, Lacey JV, Jr, Schairer C, Albert P, Schatzkin A, Albanes D. Physical activity and risk of endometrial cancer in a prospective cohort study (United States).
Cancer Causes Control
2003
;
14
:
559
–67.
14
Furberg AS, Thune I. Metabolic abnormalities (hypertension, hyperglycemia and overweight), lifestyle (high energy intake and physical inactivity) and endometrial cancer risk in a Norwegian cohort.
Int J Cancer
2003
;
104
:
669
–76.
15
Pukkala E, Poskiparta M, Apter D, Vihko V. Life-long physical activity and cancer risk among Finnish female teachers.
Eur J Cancer Prev
1993
;
2
:
369
–76.
16
Moradi T, Nyren O, Bergstrom R, et al. Risk for endometrial cancer in relation to occupational physical activity: a nationwide cohort study in Sweden.
Int J Cancer
1998
;
76
:
665
–70.
17
Sturgeon SR, Brinton LA, Berman ML, et al. Past and present physical activity and endometrial cancer risk.
Br J Cancer
1993
;
68
:
584
–9.
18
Shu XO, Hatch MC, Zheng W, Gao YT, Brinton LA. Physical activity and risk of endometrial cancer.
Epidemiology
1993
;
4
:
342
–9.
19
Levi F, La Vecchia C, Negri E, Franceschi S. Selected physical activities and the risk of endometrial cancer.
Br J Cancer
1993
;
67
:
846
–51.
20
Hirose K, Tajima K, Hamajima N, et al. Subsite (cervix/endometrium)-specific risk and protective factors in uterus cancer.
Jpn J Cancer Res
1996
;
87
:
1001
–9.
21
Olson SH, Vena JE, Dorn JP, et al. Exercise, occupational activity, and risk of endometrial cancer.
Ann Epidemiol
1997
;
7
:
46
–53.
22
Goodman MT, Hankin JH, Wilkens LR, et al. Diet, body size, physical activity, and the risk of endometrial cancer.
Cancer Res
1997
;
57
:
5077
–85.
23
Salazar-Martinez E, Lazcano-Ponce EC, Lira-Lira GG, et al. Case-control study of diabetes, obesity, physical activity and risk of endometrial cancer among Mexican women.
Cancer Causes Control
2000
;
11
:
707
–11.
24
Moradi T, Weiderpass E, Signorello LB, Persson I, Nyren O, Adami HO. Physical activity and postmenopausal endometrial cancer risk (Sweden).
Cancer Causes Control
2000
;
11
:
829
–37.
25
Littman AJ, Voigt LF, Beresford SA, Weiss NS. Recreational physical activity and endometrial cancer risk.
Am J Epidemiol
2001
;
154
:
924
–33.
26
Zheng W, Shu XO, McLaughlin JK, Chow WH, Gao YT, Blot WJ. Occupational physical activity and the incidence of cancer of the breast, corpus uteri, and ovary in Shanghai.
Cancer
1993
;
71
:
3620
–4.
27
Dosemeci M, Hayes RB, Vetter R, et al. Occupational physical activity, socioeconomic status, and risks of 15 cancer sites in Turkey.
Cancer Causes Control
1993
;
4
:
313
–21.
28
Kalandidi A, Tzonou A, Lipworth L, Gamatsi I, Filippa D, Trichopoulos D. A case-control study of endometrial cancer in relation to reproductive, somatometric, and life-style variables.
Oncology
1996
;
53
:
354
–9.
29
Bergstrom A, Pisani P, Tenet V, Wolk A, Adami HO. Overweight as an avoidable cause of cancer in Europe.
Int J Cancer
2001
;
91
:
421
–30.
30
Erlichman J, Kerbey AL, James WP. Physical activity and its impact on health outcomes. Paper 2. Prevention of unhealthy weight gain and obesity by physical activity: an analysis of the evidence.
Obes Rev
2002
;
3
:
273
–87.
31
Haslam DW, James WP. Obesity.
Lancet
2005
;
366
:
1197
–209.
32
Kaaks R, Lukanova A, Kurzer MS. Obesity, endogenous hormones, and endometrial cancer risk: a synthetic review.
Cancer Epidemiol Biomarkers Prev
2002
;
11
:
1531
–43.
33
Key TJ, Pike MC. The dose-effect relationship between “unopposed” oestrogens and endometrial mitotic rate: its central role in explaining and predicting endometrial cancer risk.
Br J Cancer
1988
;
57
:
205
–12.
34
Czyzyk A, Szczepanik Z. Diabetes mellitus and cancer.
Eur J Intern Med
2000
;
11
:
245
–52.
35
Strickler HD, Wylie-Rosett J, Rohan T, et al. The relation of type 2 diabetes and cancer.
Diabetes Technol Ther
2001
;
3
:
263
–74.
36
Kaaks R, Lukanova A. Energy balance and cancer: the role of insulin and insulin-like growth factor-I.
Proc Nutr Soc
2001
;
60
:
91
–106.
37
McTiernan A, Tworoger SS, Ulrich CM, et al. Effect of exercise on serum estrogens in postmenopausal women: a 12-month randomized clinical trial.
Cancer Res
2004
;
64
:
2923
–8.
38
Borghouts LB, Keizer HA. Exercise and insulin sensitivity: a review.
Int J Sports Med
2000
;
21
:
1
–12.