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Research Articles

Adult Stature and Risk of Cancer at Different Anatomic Sites in a Cohort of Postmenopausal Women

Geoffrey C. Kabat, Matthew L. Anderson, Moonseong Heo, H. Dean Hosgood III, Victor Kamensky, Jennifer W. Bea, Lifang Hou, Dorothy S. Lane, Jean Wactawski-Wende, JoAnn E. Manson and Thomas E. Rohan
Geoffrey C. Kabat
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Matthew L. Anderson
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Moonseong Heo
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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H. Dean Hosgood III
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Victor Kamensky
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Jennifer W. Bea
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Lifang Hou
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Dorothy S. Lane
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Jean Wactawski-Wende
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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JoAnn E. Manson
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Thomas E. Rohan
1Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx; 2Department of Preventive Medicine, Stony Brook University, Stony Brook; 3Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York; 4Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas; 5Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6Department of Preventive Medicine, Northwestern University School of Medicine, Chicago, Illinois; and 7Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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DOI: 10.1158/1055-9965.EPI-13-0305 Published August 2013
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  • Figure 1.
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    Figure 1.

    Association of height with all cancer and cancer at 19 anatomic sites. HR4s are adjusted for covariates in footnote h in Table 3.

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    Figure 2.

    Association of height with risk of all cancers by level of potential effect modifiers. HR4s are adjusted for covariates in footnote h in Table 3.

Tables

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  • Table 1.

    Baseline characteristics by quintiles of height in the WHI

    Quintiles of height in cm
    <156.5156.5–<160.2160.2–<163.5163.5–<167.1≥167.1
    N28,53629,29129,18028,91228,782
    Mean person-years295,762312,015315,329314,447315,208
    Mean age (y)65.163.863.062.361.1
    Mean weight (kg)66.870.973.575.779.8
    Mean BMI (kg/m2)28.528.228.127.727.4
    Mean MET-h/wka11.411.811.912.012.2
    Mean pack-years of smoking8.29.29.89.910.5
    Mean servings of alcohol/wk1.72.12.42.62.9
    Education, % >16 y23.126.427.730.434.9
    Ethnicity
     White, %72.581.784.686.187.3
     Black, %7.49.09.39.710.3
     Hispanic, %9.44.93.22.11.0
     Other, %10.74.42.92.11.4
    Income ≥$75,00013.216.717.920.123.0
    Parity, % nulliparous10.910.611.011.214.4
    Age of menarche,% <12 y27.123.421.920.116.9
    Age at first birth,% ≥30 yb10.08.58.28.79.8
    Oral contraceptive use, % ever33.839.142.345.349.3
    Hormone therapy, % ever52.454.757.558.160.3
    Current smokers, %6.06.77.17.17.8
    Mammography screeningc81.982.783.384.084.5
    Pap screeningd86.388.488.689.590.0
    Colorectal cancer screeninge43.243.744.544.444.2
    • ↵aDefined as caloric need per kilogram of body weight per hour of activity divided by the caloric need per kilogram of body weight per hour of rest, per hour per week.

    • ↵bN parous women = 117,603.

    • ↵cHad mammogram within past 2 years.

    • ↵dHad Pap screening within past 3 years.

    • ↵eHad any screening in the year before year 1 visit: rectal exam, Hemoccult, or colonoscopy or sigmoidoscopy.

  • Table 2.

    Effect of adjustment for different potential confounding variables on the association of height with all cancer (per 10 cm increment) in the WHI

    HR95% CI
    Adjusted for age only1.151.12–1.17
    Additionally adjusted individually for
     Education years1.141.12–1.17
     Ethnicity1.131.11–1.16
     Smoking (pack-yrs)1.131.11–1.16
     Weight (kg)1.121.09–1.14
     BMI (kg/m2)1.171.14–1.19
     Alcohol intake (servings)1.141.12–1.17
     Physical activity (MET-hrs/wk)1.151.12–1.17
     Age at menarche1.161.13–1.18
     Oral contraceptive use (ever)1.151.12–1.17
     Hormone therapy (ever)1.151.12–1.17
     Hormone therapy (type)a1.151.12–1.17
     Parity1.151.12–1.17
     Age at menopause1.151.12–1.17
     Mammography in past 2 years1.151.13–1.18
     Pap screening in past 3 years1.151.12–1.19
    Adjusted for main covariatesb1.131.11–1.16
    • ↵aNever, estrogen alone, estrogen + progestin, both E and E + P.

    • ↵bAge (continuous), hormone therapy (yes, no), pack-years of smoking (continuous), alcohol intake (continuous), W/H1.7 (continuous), age at menarche (<12, 12, 13, >13), education (less than high school grad, high school grad/some college, college grad, post-college), ethnicity (White, Black, other), randomization to treatment arm of clinical trials (yes, control, placebo, not randomized).

  • Table 3.

    HRs and 95% CIs for the association of height (per 10 cm increase) with specific cancers in the WHI

    Cancer siteN casesHR195% CIHR295% CIHR395% CIHR495% CI
    Colorectuma1,9041.131.05–1.211.151.07–1.241.191.10–1.281.171.09–1.26
    Colonb1,5161.131.04–1.221.141.04–1.241.181.08–1.291.161.07–1.26
    Rectumb2571.221.00–1.481.261.03–1.551.371.10–1.701.251.02–1.53
    Breastc6,7981.141.10–1.181.111.07–1.161.141.09–1.181.131.08–1.17
    Endometriumd1,1091.181.07–1.291.101.00–1.221.191.08–1.311.161.07–1.26
    Ovarye6831.110.99–1.251.141.01–1.291.110.98–1.261.131.00–1.29f
    Cervixg831.300.93–1.831.410.99–2.011.420.99–2.021.380.96–1.99
    Kidneyh3691.181.00–1.381.231.03–1.451.261.06–1.501.231.05–1.43
    Bladderg4571.130.97–1.301.050.90–1.221.050.90–1.221.060.90–1.24
    Thyroidi2701.271.06–1.541.321.08–1.621.331.08–1.631.291.05–1.58
    Lung (NS)j2691.120.93–1.361.130.93–1.371.200.98–1.471.120.92–1.38
    Lung (ES)g1,4660.990.91–1.071.000.92–1.090.980.90–1.071.091.00–1.19
    Stomachg1520.980.77–1.261.010.78–1.311.020.79–1.331.050.82–1.35
    Pancreasg4591.030.90–1.191.030.89–1.201.030.89–1.211.030.89–1.20
    Melanomag1,1691.291.17–1.411.151.04–1.261.161.05–1.271.151.04–1.26
    Braing1761.261.00–1.591.281.00–1.631.281.00–1.651.260.99–1.62
    Leukemiag4471.090.94–1.261.040.89–1.211.040.89–1.221.050.90–1.22
    NHLg8881.111.00–1.231.111.00–1.241.111.00–1.241.110.99–1.23
    Multiple myelomag2821.291.07–1.561.301.07–1.571.281.06–1.561.291.06–1.57
    All cancersh20,9281.151.12–1.171.121.10–1.151.141.11–1.161.131.11–1.16

    NOTE: Shading indicates statistically significant associations. Women with a history of bilateral oophorectomy were excluded from the analysis of ovarian cancer, and women with a history of hysterectomy were excluded from the analysis of endometrial cancer.

    Abbreviations: HR1, age-adjusted; HR2, multivariable-adjusted but without weight or BMI; HR3, multivariable-adjusted + BMI; HR4, multivariable + site-specific scaling of W/HX; NS, never smoker; ES, ever smoker.

    • ↵aHR2 adjusted for age (continuous), servings of alcohol per week (continuous), pack-years of smoking (continuous), hormone therapy (ever, never), age at menarche (<12, 12, 13, >13), family history of colorectal cancer (yes, no, missing), physical activity (MET-hrs/wk—continuous), red meat intake (medium servings per day—continuous), folate intake (μg/day—continuous), aspirin use (yes, no), diabetes (yes, no), education (less than high school graduate, high school graduate/some college, college graduate, post-college), ethnicity (White, Black, other), randomization status in each of the clinical trials (dummy variables for treatment, control, placebo, not randomized).

    • ↵bHR2 adjusted for age, alcohol, pack-years, hormone therapy, family history of colorectal cancer, physical activity, red meat intake, folate intake, aspirin use, diabetes, education, ethnicity, randomization status.

    • ↵cHR2 adjusted for age, alcohol, pack-years, hormone therapy, parity (continuous), age at menarche, age at first birth (<20, 20–29, ≥30, missing), age at menopause (<45, 45–54, ≥55, missing), family history of breast cancer in a first degree relative (yes, no, missing), history of breast biopsy (ever, never, missing), education, ethnicity, randomization status in clinical trials.

    • ↵dHR2 adjusted for age, alcohol, pack-years, hormone therapy, parity, oral contraceptive use (ever, never), education, ethnicity, randomization status.

    • ↵eHR2 adjusted for age, alcohol, pack-years, hormone therapy, oral contraceptive use (ever, never), education, ethnicity, and randomization status.

    • ↵fLower confidence limit = 1.001.

    • ↵gHR2 adjusted for age, alcohol, pack-years, hormone therapy, education, ethnicity, and randomization status.

    • ↵hHR2 adjusted for age, alcohol, pack-years, hormone therapy, age at menarche, education, ethnicity, and randomization status.

    • ↵iHR2 adjusted for age, alcohol, pack-years, hormone therapy, history of thyroid nodules, history of goiter, education, ethnicity, and randomization status.

    • ↵jHR2 adjusted for age, alcohol, hormone therapy, education, ethnicity, and randomization status.

Additional Files

  • Figures
  • Tables
  • Supplementary Data

    Files in this Data Supplement:

    • Supplementary Figure Legend - PDF - 22KB, Legends for supplementary figures 1-5.
    • Supplementary Figure 1 - PDF - 68KB, Association of height with risk of breast cancer by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 3 in Table 3.
    • Supplementary Figure 2 - PDF - 68KB, Association of height with risk of colorectal cancer by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 1 in Table 3.
    • Supplementary Figure 3 - PDF - 69KB, Association of height with risk of melanoma cancer by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 6 in Table 3.
    • Supplementary Figure 4 - PDF - 67KB, Association of height with risk of lung cancer in ever smokers by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 6 in Table 3.
    • Supplementary Figure 5 - PDF - 68KB, Association of height with risk of endometrial cancer by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 4 in Table 3.
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Cancer Epidemiology Biomarkers & Prevention: 22 (8)
August 2013
Volume 22, Issue 8
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Adult Stature and Risk of Cancer at Different Anatomic Sites in a Cohort of Postmenopausal Women
Geoffrey C. Kabat, Matthew L. Anderson, Moonseong Heo, H. Dean Hosgood III, Victor Kamensky, Jennifer W. Bea, Lifang Hou, Dorothy S. Lane, Jean Wactawski-Wende, JoAnn E. Manson and Thomas E. Rohan
Cancer Epidemiol Biomarkers Prev August 1 2013 (22) (8) 1353-1363; DOI: 10.1158/1055-9965.EPI-13-0305

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Adult Stature and Risk of Cancer at Different Anatomic Sites in a Cohort of Postmenopausal Women
Geoffrey C. Kabat, Matthew L. Anderson, Moonseong Heo, H. Dean Hosgood III, Victor Kamensky, Jennifer W. Bea, Lifang Hou, Dorothy S. Lane, Jean Wactawski-Wende, JoAnn E. Manson and Thomas E. Rohan
Cancer Epidemiol Biomarkers Prev August 1 2013 (22) (8) 1353-1363; DOI: 10.1158/1055-9965.EPI-13-0305
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