Dietary Insulin Index and Insulin Load in Relation to Endometrial Cancer Risk in the Nurses' Health Study

Published OnlineFirst May 23, 2014; DOI: 10.1158/1055-9965.EPI-14-0157

Cancer Epidemiology, Research Article Biomarkers & Prevention

Jennifer Prescott1,3, Ying Bao1, Akila N. Viswanathan2, Edward L. Giovannucci1,4, Susan E. Hankinson1,5, and Immaculata De Vivo1,3

Abstract Background: Although unopposed estrogen exposure is considered the main driver of endometrial carcinogenesis, factors associated with states of insulin resistance and hyperinsulinemia are independently associated with endometrial cancer risk. We used dietary insulin load and insulin index scores to represent the estimated insulin demand of overall diets and assessed their association with endometrial cancer risk in the prospective Nurses’ Health Study. Methods: We estimated incidence rate ratios (RR) and 95% confidence intervals (CI) for risk of invasive endometrial cancer using Cox proportional hazards models. Between the baseline dietary questionnaire (1980) and 2010, we identified a total of 798 incident-invasive epithelial endometrial adenocarcinomas over 1,417,167 person-years of follow-up. Results: Dietary insulin scores were not associated with overall risk of endometrial cancer. Comparing women in the highest with the lowest quintile, the multivariable-adjusted RRs of endometrial cancer were 1.07 (95% CI, 0.84–1.35) for cumulative average dietary insulin load and 1.03 (95% CI, 0.82–1.31) for cumulative average dietary insulin index. Findings did not vary substantially by alcohol consumption, total dietary fiber P intake, or body mass index and/or physical activity ( heterogeneity 0.10). Conclusions: Intake of a diet predicted to stimulate a high postprandial insulin response was not associated with endometrial cancer risk in this large prospective study. Considering the complex interplay of diet, lifestyle, and genetic factors contributing to the hyperinsulinemic state, dietary measures alone may not sufficiently capture absolute long-term insulin exposure. Impact: This study is the first to investigate dietary insulin scores in relation to endometrial cancer risk. Cancer Epidemiol Biomarkers Prev; 23(8); 1512–20. 2014 AACR.

Introduction terone (1, 2). However, endometrial cancer risk factors Two major risk factors for endometrial cancer include such as polycystic ovarian syndrome, type 2 diabetes, and obesity and use of estrogen-only postmenopausal hor- the accumulation of visceral fat also are associated with mone therapy (HT). These established risk factors, in insulin resistance and hyperinsulinemia (3–8). Up to one addition to several others [e.g., parity, oral contraceptive third of non-diabetic endometrial cancer patients exhibit (OC) use, smoking], correspond with alterations in sex insulin resistance based on an assessment of basal insu- steroid hormones such that the predominant driver of linemia and glycemia (9). Epidemiologic evidence sug- endometrial carcinogenesis is thought to be a relative gests that individuals with higher levels of insulin or C- increase in exposure to estrogen unopposed by proges- peptide, a stable marker of insulin secretion (10, 11), and those with evidence of metabolic syndrome are at increased endometrial cancer risk (12–18). Factor analysis Authors' Affiliations: 1Channing Division of Network Medicine, Depart- of various prediagnostic plasma hormones, binding pro- ment of Medicine, Brigham and Women's Hospital and Harvard Medical teins, and cytokines identified an "insulin resistance/ 2 School; Department of Radiation Oncology, Brigham and Women's Hos- metabolic syndrome" component associated with post- pital/Dana-Farber Cancer Institute, Harvard Medical School; 3Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public menopausal endometrial cancer risk (19). Finally, insulin Health; 4Department of Nutrition and Epidemiology, Harvard School of induces proliferation of endometrial cancer cell lines in Public Health, Boston; and 5Division of Biostatistics and Epidemiology, vitro University of Massachusetts School of Public Health and Health Sciences, (20, 21), suggesting that increased insulin signaling Amherst, Massachusetts may promote endometrial cancer development and/or Corresponding Author: Jennifer Prescott, Brigham and Women's Hos- progression. pital, 181 Longwood Ave., 3rd floor, Boston, MA 02115. Phone: 617-525- Western diets, which consist of high-fat and highly 0344; Fax: 617-525-2008; E-mail: [email protected] processed carbohydrate-rich foods, are substantially doi: 10.1158/1055-9965.EPI-14-0157 more insulinogenic (i.e., greater insulin secretion per 2014 American Association for Cancer Research. gram of food) compared with traditional diets based on

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Dietary Insulin Scores and Endometrial Cancer Risk

less refined foods (22). Type, amount, and digestibility of previous 2 years. We then sought permission to obtain the dietary carbohydrate intake have direct physiologic relevant medical records and pathology reports. Study effects on circulating insulin levels (22–24), which are physicians blinded to questionnaire data reviewed the highly correlated with postprandial blood glycemia (r documents to verify and establish the date of diagnosis. ¼ 0.70; P < 0.001; ref. 22). Given the putative link between As <10% of NHS endometrial cancer cases were diag- insulin signaling and endometrial tumor growth, frequent nosed with serous, clear cell, or other rare histologic types, consumption of foods associated with elevated insulin or we restricted our analysis to cases with invasive endo- blood glucose response has been hypothesized to increase metrial adenocarcinoma (stages IA–IV) diagnosed endometrial cancer risk. between return of the 1980 dietary questionnaire and June Epidemiologic studies have investigated dietary car- 1, 2010. Over 1,417,167 person-years of follow-up, we bohydrate quality (glycemic index, GI) and/or a mea- identified 798 incident invasive epithelial endometrial sure of both carbohydrate quality and quantity (glyce- adenocarcinomas. mic load, GL) as surrogates of insulin and blood glucose levels with respect to endometrial cancer risk. Except Dietary assessment for the Prostate, Lung, Colorectal, and Ovarian (PLCO) Dietary information was first assessed in 1980 when a 61 Cancer Screening Trial (25), prior studies observed semiquantitative food frequency questionnaire (FFQ) was nonsignificant elevations in endometrial cancer risk sent to participants. Expanded questionnaires inquiring among women in the highest category of GL compared about annual average intake of over 130 individual foods with the lowest. This translated into a modest, but and 22 beverages were sent in 1984, 1986, and every 4 significant approximately 20% elevation in risk associ- years thereafter. FFQs asked, on average, how often dur- ated with a high GL diet in a recent meta-analysis (26). ing the previous year participants consumed each food or However, although postprandial blood glycemia from beverage using standard portion sizes. Nine responses carbohydrate consumption is highly correlated with were possible, ranging from never or less than once per circulating insulin levels, protein and fat can induce month to 6 or more times per day. Nutrient intakes were insulin secretion without raising blood glucose (22). calculated by multiplying the portion size of a single Thus, quantifying the postprandial insulin response for serving of each food by its reported frequency of intake, various food items, including those with low or no then multiplying the amount consumed by the nutrient carbohydrate content, may address the insulin hypoth- content of the food, and summing the nutrient contribu- esis more directly. In this analysis, we used novel tions of all food items using the U.S. Department of dietary insulin index (II) and insulin load (IL) scores Agriculture food composition data (28). Reproducibility developed for the Nurses’ Health Study (NHS) cohort to of the FFQ has been reported elsewhere (29–31). investigate prospectively whether diets high in insuli- II values for individual food items were obtained from nogenic foods are associated with endometrial cancer published estimates (31 foods; refs. 22, 32) or provided by risk. Dr. Jennie Brand-Miller of the University of Sydney, Australia (73 foods). U.S. food samples were shipped to Materials and Methods the laboratory in Sydney for testing as previously Study population described (22). The food II value was calculated by divid- The NHS is an ongoing prospective cohort following ing the area under the insulin response curve for 1,000 121,700 female registered nurses ages 30 to 55 years from kilojoules of the reference food (glucose). The II value for 11 U.S. states at enrollment in 1976. At baseline and each test food represents the mean response of 11 to 13 biennially thereafter, participants completed self-admin- subjects. On the basis of these data, we built an II database istered questionnaires providing detailed information on for a large number of foods queried on our FFQs. II values anthropometric, lifestyle, menstrual, and reproductive for individual foods ranged from 2.0 (butter) to 120.0 (jelly factors. Participants also report their medical history from beans). For foods not directly tested, II values were either which newly diagnosed cancers and other diseases are assigned values from similar foods (meats, fish, poultry, identified. Follow-up of the cohort is high, with >90% of fats, and oils) or calculated using an adjustment based on total possible person-years. Vital status was ascertained percentage of carbohydrates/1,000 kilojoule (cereal through next-of-kin, the U.S. Postal Service, and the grains, baked goods, sweets and snack foods, beverages, National Death Index. These methods have identified an fruits, and dairy foods), an inverse water ratio (nonstarchy estimated 98% of deaths in the cohort (27). Completion of vegetables), or inverse dietary fiber content ratio (starchy the self-administered questionnaire was considered to vegetables). imply informed consent. The NHS protocol was approved We calculated the average dietary IL for each partici- by the Human Research Committee of Brigham and pant by multiplying the II value of each food and beverage Women’s Hospital (Boston, MA). by its energy content, and summing values for all items reported [S(food II kilocalories per serving servings Case ascertainment per day)]. Each unit of dietary IL represents the equivalent On each questionnaire, women reported whether they insulin response generated by 1 kilocalorie of glucose. The had been diagnosed with endometrial cancer during the dietary II for the overall diet, which is the weighted mean

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of II values for each of the component foods, was calcu- BMI (N ¼ 138; these women could reenter the analysis lated by dividing dietary IL by total energy intake [IL/ in subsequent cycles once information on BMI was avail- S(kilocalories per serving servings per day)]. For sec- able) for a total analytic population of 67,969 women at ondary analyses, we calculated average dietary IL and II baseline. Person-time of follow-up for each eligible par- scores excluding the estimated insulin response to alco- ticipant started with the return date of the baseline ques- holic beverages (beer, wine, and liquor). tionnaire and ended with date of endometrial cancer Bao et al. assessed validity of dietary IL in predicting the diagnosis, diagnosis of another cancer (except nonmela- actual insulin response (33). Healthy participants (n ¼ 10 noma skin cancer), hysterectomy, pelvic irradiation, death or 11 for each meal) consumed 13 different isoenergetic from any cause, or end of follow-up (June 1, 2010), which- (2,000 kilojoules) mixed meals of varying macronutrient ever occurred first. content. Despite limited statistical power, dietary IL Cox proportional hazards regression models estimated strongly correlated with the observed postprandial insu- incidence rate ratios (RR) and 95% confidence intervals lin response (r ¼ 0.78, P ¼ 0.002), suggesting that dietary IL (CI) with age in months and 2-year questionnaire cycle as may be a valid measure of actual insulin response to the time scale. Average dietary II, dietary IL, dietary GI, composite meals. dietary GL, and total dietary fiber intake were energy- adjusted by the residual method (36). This addresses the Assessment of non-dietary factors question of whether the composition of the diet, indepen- On the questionnaire administered in 1976, women dent of total energy intake, is most relevant to endometrial reported current weight, height, smoking history, age at cancer risk. Participants were classified according to die- menarche, OC use, pregnancy history, menopausal status, tary insulin score tertiles or quintiles based on the distri- age at menopause, use of postmenopausal HT, and per- bution observed within the cohort. Women in the lowest sonal history of other diseases. OC use and parity were quantile of each score served as the reference group in asked on each questionnaire until 1984, whereas most analyses. other covariate data (except height and age at menarche) To assess the importance of timing, we analyzed dietary were updated on each biennial questionnaire. Type of insulin scores in three ways: (i) using 1980 baseline values postmenopausal hormone used (i.e., estrogen alone or to reflect past exposure, (ii) simple update, to assess most estrogen with progesterone) was first asked in 1978 and recent dietary exposure, and (iii) cumulatively updating on all subsequent questionnaires. Weight at age 18 was the average dietary insulin scores with each successive reported on the 1980 questionnaire. First-degree family questionnaire data to reflect long-term exposure. To illus- history of endometrial cancer was collected in 1996 and trate the cumulative average method, we used the average 2008. Family history of colorectal cancer was first collected of dietary IL from 1980 and 1984 to predict endometrial in 1982, updated in 1988 and biennially thereafter. Starting cancer risk from 1984 to 1986. Similarly, we averaged IL in 1980, participants were asked hours per week of overall scores from 1980, 1984, and 1986 to predict risk from 1986 moderate and vigorous physical activity. Hours spent on to 1988. Factors included in the final multivariable anal- specific leisure-time activities were first reported in 1986 yses are listed in table footnotes. We additionally assessed and updated every 2 to 4 years. From the frequency, dietary GI (quintiles), dietary GL (quintiles), total dietary duration, and intensity of reported activities, we calcu- fiber intake (quintiles), BMI at age 18 (continuous), phys- lated total metabolic equivalent (MET) hours of activity ical activity (<3, 3 to <9, 9 to <18, 18 to <27, 27þ METs/ per week (34, 35). Body mass index (BMI) was calculated week, unknown), alcohol consumption (none, <5, 5–14.9, as weight in kilograms divided by the square of height in 15þ grams/day), coffee consumption (continuous), caf- meters (kg/m2). Pack-years of smoking were calculated feine intake (quintiles), and personal history of diabetes by multiplying the duration and dose of smoking; 1 pack- (no, yes) as potential confounders. Because results year is equivalent to having smoked 20 cigarettes per day remained similar, these factors were not included in final for 1 year. models. We performed a number of sensitivity analyses. We used Statistical analysis the 1984 dietary questionnaire as baseline because the FFQ We used the 1980 dietary questionnaire as baseline. We included more food items than the 1980 FFQ. To minimize sequentially excluded women who did not respond to the the possibility that preclinical disease influenced dietary 1980 FFQ, left an extensive number of items blank (>10) or assessment, we examined associations after incorporating reported implausible total energy intake (<500 or >3,500 a 4-year time lag between exposure assessment and endo- kcal/day; N ¼ 29,232), had been diagnosed with cancer metrial cancer diagnosis (e.g., 1980 exposure to predict before 1980 (other than nonmelanoma skin cancer; N ¼ disease risk from 1984 to 1986). We repeated analyses in 3,678), were born before 1920 or had an unknown date of which the dietary insulin scores were not energy-adjusted birth (N ¼ 58), or had undergone hysterectomy with or by the residual method and with dietary insulin scores that without oophorectomy or experienced menopause due to excluded the alcohol component. We additionally con- pelvic irradiation as of the 1980 questionnaire (N ¼ ducted an analysis restricted to women who did not report 20,625). Because obesity is an important risk factor for a personal history of diabetes to reduce dietary changes endometrial cancer, we also excluded women missing occurring as a result of a diabetes diagnosis.

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Dietary Insulin Scores and Endometrial Cancer Risk

We used the Wald test to assess linear trends of dietary Because higher dietary fiber content lowers insulin insulin score variables assigned the median value for each response to foods (37), we stratified our analysis by total intake category. Likelihood ratio tests assessed heteroge- dietary fiber intake (above vs. below median intake). neity by BMI (<30 vs. 30 kg/m2) and total physical Cumulative average dietary insulin scores were not asso- activity (high vs. low, using the median as the cutpoint) ciated with endometrial cancer risk among women with P strata. We additionally assessed heterogeneity by alcohol higher total dietary fiber intake ( trend 0.10). Among intake (drinkers vs. nondrinkers) and total dietary fiber women who consumed less total dietary fiber, those in the intake (above vs. below the median). We tested the pro- highest tertiles of cumulative average dietary insulin portional hazards assumption by comparing the log like- scores had significant 35% to 40% increased risks of endo- P ¼ lihood of models with and without interaction terms metrial cancer ( trend 0.03) compared with women in the between age and the dietary insulin score trend variables. lowest tertiles. However, heterogeneity by total dietary P The proportional hazards assumption was not violated fiber intake was not significant ( heterogeneity 0.77). (P 0.14). P values were based on two-sided tests and Food intake among insulin-resistant individuals stimu- considered statistically significant at P < 0.05. All analyses lates greater insulin production to overcome the were conducted using SAS version 9.3 (SAS Institute Inc.). decreased responsiveness of target tissues (38). Obese or less active individuals are more likely to exhibit insulin Results resistance (39) and, therefore, may experience the greatest Characteristics of women according to selected quintiles detriment from a high insulinogenic diet. We examined of dietary IL and II at the midpoint of follow-up (1994) are whether the association with cumulative average dietary shown in Table 1. Women in higher categories of the insulin scores differed by BMI and total physical activity. dietary insulin scores were slightly older, had a higher We did not observe a positive association between cumu- intake of carbohydrates and total dietary fiber, but con- lative average dietary insulin scores and endometrial sumed less protein, total fat, alcohol, and caffeine, and cancer risk among obese women or among women who were less likely to have ever smoked or taken OCs. Among reported total physical activity less than the median of the women that had used OCs, duration of use was shorter study population. Likewise, no association was observed among those in the highest categories of the dietary insulin in the group of women expected to have the highest scores. Parity, menopausal status, BMI, total physical proportion of insulin-resistant individuals (obese and low activity, and family history of endometrial or colorectal physical activity; Table 3). We observed a marginal cancer did not differ by categories of the dietary insulin increased risk associated with the highest compared with scores. Cumulative average dietary insulin scores were lowest tertile of cumulative average dietary II among r ¼ highly correlated with each other ( s 0.96) and with nonobese women with high levels of physical activity r ¼ P ¼ P ¼ cumulative average dietary GL ( s 0.75 with dietary IL; (RR, 1.37; 95% CI, 0.99–1.90; trend 0.06; heterogeneity r ¼ s 0.73 with dietary II), but only modestly correlated with 0.26). However, the same trend was not observed using r ¼ cumulative average GI ( s 0.37 and 0.39, respectively). the 1984 FFQ as baseline or in the 4-year lagged analysis, Past, recent, and long-term measures of dietary insulin suggesting the observation is due to chance. Finally, scores were not associated with endometrial cancer risk in because postmenopausal HT use may alter insulin age- or multivariable-adjusted analyses. Women in the responsiveness (12, 40), we conducted an analysis restrict- highest quintile of cumulative average dietary IL had an ed to women who never used postmenopausal hormones. P ¼ RR of 1.07 (95% CI, 0.84–1.35; trend 0.51; Table 2) Cumulative average dietary insulin scores were not asso- compared with women in the lowest quintile after adjust- ciated with endometrial cancer risk among these women ing for established and suspected endometrial cancer risk (data not shown). factors. The comparable RR for cumulative average die- P ¼ Discussion tary II was 1.03 (95% CI, 0.81–1.31; trend 0.59). We observed similar associations using the 1984 FFQ as base- We used novel dietary insulin scores to assess the line. Results remained essentially unchanged after incor- impact of diets high in insulinogenic foods on endome- porating a 4-year time lag between exposure assessment trial cancer risk. We did not find evidence for increased and diagnosis. Dietary insulin scores were not associated endometrial cancer risk associated with dietary IL or II with endometrial cancer risk after additionally adjusting in this large cohort of U.S. women. Further, the scores for dietary GI, dietary GL, total dietary fiber intake, BMI at were not associated with elevated risk among heavy age 18, total physical activity, personal history of diabetes, and/or less active individuals, subgroups of women hypertension, caffeine intake, alcohol consumption, or who collectively experience greater postprandial insu- coffee consumption. Similar results were obtained when lin response due to a higher proportion of insulin- the dietary insulin scores were not energy-adjusted by the resistant individuals (39). residual method, when the alcohol component was Prior studies assessed endometrial cancer risk using removed from the scores, or when analyses were restrict- dietary GL and GI scores to reflect the postprandial ed to women without a personal history of diabetes (data glucose response of carbohydrate-containing foods and not shown). Estimates did not differ by alcohol drinking to act as surrogates of insulin response to different diets. P status ( heterogeneity 0.71). With the exception of PLCO, which observed significant

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Downloaded from cebp.aacrjournals.org on September 29, 2021. © 2014 American Association for Cancer Research. 1516 Downloaded from acrEieilBoakr rv 38 uut2014 August 23(8) Prev; Biomarkers Epidemiol Cancer rsote al. et Prescott Table 1. Age-standardized characteristics of NHS participants at the midpoint of follow-up (1994)

Dietary IL Dietary II Quintile 1 Quintile 3 Quintile 5 Quintile 1 Quintile 3 Quintile 5 (217–621; n ¼ 9,558) (668–706; n ¼ 9,556) (755–1,279; n ¼ 9,795) (13.9–38.8; n ¼ 9,448) (41.7–44.1; n ¼ 9,568) (47.0–80.9; n ¼ 9,729) a cebp.aacrjournals.org Age (y) 59.3 (6.9) 59.5 (7.2) 60.6 (7.3) 59.3 (6.9) 59.4 (7.1) 60.7 (7.3)

Age at menarche (y) 12.6 (1.4) 12.5 (1.4) 12.5 (1.3) 12.6 (1.4) 12.5 (1.4) 12.5 (1.3) Published OnlineFirstMay23,2014;DOI:10.1158/1055-9965.EPI-14-0157 Ever use of OCs, % 52 50 47 52 50 47 Duration of OC useb (mo) 53.8 (48.5) 51.4 (46.9) 50.0 (47.9) 53.7 (48.4) 51.3 (46.5) 50.0 (47.9) Parous, % 93 94 94 93 95 94 Number of pregnanciesc 3.1 (1.5) 3.2 (1.5) 3.1 (1.4) 3.1 (1.5) 3.2 (1.5) 3.1 (1.4) Postmenopausal, % 80 80 81 80 79 81 Age at menopaused (y) 49.9 (3.7) 50.1 (3.5) 50.1 (3.5) 49.9 (3.7) 50.0 (3.6) 50.1 (3.5) Ever use of postmenopausal 50 50 53 50 50 52 hormonesd,% on September 29, 2021. © 2014American Association for Cancer Research. Never smoker, % 30 45 50 29 45 50 Past smoker, % 46 41 40 47 41 40 Current smoker, % 24 14 10 23 14 10 BMI at age 18 (kg/m2) 21.1 (3.4) 21.2 (3.4) 21.1 (3.4) 21.2 (3.4) 21.2 (3.3) 21.2 (3.4) Current BMI (kg/m2) 26.1 (5.2) 26.6 (5.3) 26.0 (5.0) 26.0 (5.2) 26.6 (5.3) 26.1 (5.0) Total physical activity 19.7 (25.7) 19.3 (25.0) 20.1 (23.1) 19.9 (26.0) 19.2 (24.5) 19.7 (23.1) (METs/week) Dietary II 35.7 (3.2) 42.9 (1.1) 50.1 (3.4) 35.5 (3.1) 42.9 (0.7) 50.3 (3.2) Dietary IL 570 (48) 687 (11) 810 (57) 571 (50) 687 (18) 808 (58) GL 85.8 (17.5) 109 (14) 131 (18) 85.7 (17.4) 109 (14) 131 (17) GI 50.4 (3.8) 52.8 (2.9) 54.7 (3.5) 50.4 (3.7) 52.8 (2.9) 54.7 (3.5) Carbohydrates (grams/day) 175 (30) 210 (24) 241 (26) 175 (30) 211 (24) 241 (26) Protein (grams/day) 75.9 (15.4) 74.9 (11.9) 70.6 (12.4) 76.0 (15.4) 74.9 (12.0) 70.5 (12.4) acrEieilg,Boakr Prevention & Biomarkers Epidemiology, Cancer Total fat (grams/day) 59.7 (12.4) 52.3 (9.6) 42.7 (9.6) 59.5 (12.5) 52.3 (9.7) 42.6 (9.5) Total dietary ﬁber 17.7 (6.8) 18.8 (5.5) 19.5 (5.5) 17.6 (6.4) 18.9 (5.6) 19.5 (5.6) (grams/day) Alcohol intake (grams/day) 13.0 (15.4) 3.7 (6.0) 1.9 (4.0) 13.5 (15.4) 3.5 (5.6) 1.8 (3.7) Caffeine intake (mg/day) 309 (231) 266 (216) 223 (206) 303 (229) 267 (216) 228 (209) Caloric intake (kcal/day) 1,711 (550) 1,777 (524) 1,702 (508) 1,707 (546) 1,777 (524) 1,699 (507) Personal history of 664 6 6 4 diabetes, % Personal history of 35 33 33 35 33 33 hypertension, % Family history of endometrial 333 3 3 3 cancer, % Family history of colon 13 15 14 13 15 14 cancer, %

NOTE: Values are mean (SD) or percentages and are standardized to the age distribution of the study population. aValue is not age standardized. bAmong ever OC users. cAmong parous women. dAmong postmenopausal women. Published OnlineFirst May 23, 2014; DOI: 10.1158/1055-9965.EPI-14-0157

Dietary Insulin Scores and Endometrial Cancer Risk

Table 2. RR and 95% CI of endometrial cancer by dietary IL and dietary II in the NHS, 1980 to 2010

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Ptrend Dietary IL, RR (95% CI) Baseline (1980) Cases, N 140 173 163 156 166 Person-years 280,015 285,065 289,085 285,454 277,547 Age-adjusted 1.00 (ref) 1.25 (1.00–1.57) 1.15 (0.92–1.45) 1.14 (0.90–1.43) 1.22 (0.97–1.53) 0.21 Multivariablea 1.00 (ref) 1.17 (0.93–1.47) 1.03 (0.82–1.30) 1.00 (0.79–1.26) 1.03 (0.82–1.30) 0.78 Simple update Cases, N 139 160 179 165 155 Person-years 282,179 283,090 285,420 284,570 281,908 Age-adjusted 1.00 (ref) 1.18 (0.94–1.48) 1.31 (1.05–1.63) 1.20 (0.95–1.50) 1.07 (0.85–1.35) 0.50 Multivariablea 1.00 (ref) 1.08 (0.86–1.36) 1.16 (0.93–1.46) 1.08 (0.86–1.36) 0.99 (0.79–1.26) 0.99 Cumulative average Cases, N 131 169 150 186 162 Person-years 275,154 285,596 289,088 288,057 279,272 Age-adjusted 1.00 (ref) 1.27 (1.01–1.60) 1.12 (0.88–1.41) 1.39 (1.11–1.74) 1.21 (0.96–1.52) 0.08 Multivariablea 1.00 (ref) 1.14 (0.90–1.43) 0.97 (0.76–1.23) 1.22 (0.97–1.54) 1.07 (0.84–1.35) 0.51 Dietary II, RR (95% CI) Baseline (1980) Cases, N 144 161 171 166 156 Person-years 276,530 285,550 287,460 287,715 279,912 Age-adjusted 1.00 (ref) 1.10 (0.88–1.38) 1.16 (0.92–1.44) 1.14 (0.91–1.43) 1.10 (0.87–1.38) 0.38 Multivariablea 1.00 (ref) 1.04 (0.83–1.31) 1.06 (0.85–1.33) 1.03 (0.82–1.29) 0.98 (0.77–1.23) 0.81 Simple update Cases, N 132 167 169 171 159 Person-years 280,524 282,222 284,101 286,213 284,108 Age-adjusted 1.00 (ref) 1.28 (1.02–1.61) 1.31 (1.04–1.65) 1.31 (1.04–1.64) 1.15 (0.91–1.45) 0.23 Multivariablea 1.00 (ref) 1.17 (0.93–1.47) 1.18 (0.93–1.49) 1.19 (0.94–1.50) 1.07 (0.84–1.35) 0.56 Cumulative average Cases, N 133 168 156 181 160 Person-years 271,761 285,369 287,736 287,945 284,357 Age-adjusted 1.00 (ref) 1.24 (0.99–1.56) 1.13 (0.90–1.43) 1.36 (1.08–1.70) 1.14 (0.90–1.44) 0.18 Multivariablea 1.00 (ref) 1.09 (0.86–1.37) 1.00 (0.79–1.26) 1.19 (0.94–1.50) 1.03 (0.81–1.31) 0.59

aMultivariable model adjusted for age at menarche (<12, 12, >12 years of age, unknown), age at last birth and number of pregnancies (nulliparous, <30 years and 1–2 children, 30þ years and 1–2 children, <30 years and 3–4 children, 30þ years and 3–4 children, 5 or more children), OC use (never use, <13, 13–36, 37–72, >72 months), age at menopause (<45, 45–46, 47–48, 49–50, 51–52, >52 years), menopause and HT use status (premenopausal, postmenopausal-never HT user, -past HT use, -current E only, -current E þ P use, unknown), smoking status and pack-years of smoking (never smoker, past/<20 pack-years, past/21–40 pack-years, past/>40 pack- years, current/<20 pack-years, current/21–40 pack-years, current/>40 pack-years, unknown), family history of colorectal cancer (no, yes), family history of endometrial cancer (no, yes), total caloric intake (continuous), hypertension (no, yes), and BMI (continuous). E refers to estrogen-only hormone therapy use; E þ P refers to estrogen plus progesterone hormone therapy use. reduced risk among women who consumed high GL diets GL diets was weaker (pooled OR, 1.14; 95% CI, 0.91–1.44) (RR, 0.63; 95% CI, 0.46–0.84 for highest vs. lowest quartile; compared with cohort studies (26). ref. 25), most studies report nonsigniﬁcant elevations in To address the insulin hypothesis more directly, we endometrial cancer risk with GL or GI (26). Cohort studies used novel dietary insulin scores to quantify the post- observed elevated risks of 15% to 36% with high GL diets prandial insulin response. The food II, on which the scores (pooled RR, 1.22; 95% CI, 1.09–1.37 for highest vs. lowest were based, was developed under highly standardized category), including the NHS (RR, 1.29; 95% CI, 0.99–1.67; conditions (22). Dietary IL accurately predicted insulin ref. 41), but not with GI (pooled RR, 1.00; 95% CI, 0.87–1.14; response to mixed meals in healthy volunteers, demon- ref. 26). In contrast, case–control studies observed signif- strating validity of the index (33). Moreover, in the NHS icant increased endometrial cancer risk with GI (pooled and Health Professionals Follow-up Study cohorts, die- OR, 1.56; 95% CI, 1.21–2.02), but the relationship with high tary insulin scores positively correlated with plasma

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– triglyceride levels, particularly among obese individuals þ

trend (42), conﬁrming the ability to predict an expected biologic P

45, 45 response associated with insulin resistance. Contrary to < our hypothesis, we did not ﬁnd evidence of increased endometrial cancer risk associated with the dietary insu- 40 pack-years, 2 children, 30 – – lin scores. Given that imprecise FFQ assessments may P use, unknown), 1.49)1.44) 0.15 0.71 1.56) 0.22 1.31)1.90) 0.96 0.06 1.18)1.83) 0.38 0.35 – – – – – – – þ have biased results toward the null, we examined long- term exposure using cumulative average dietary scores, which dampen variation due to measurement error. The scores remained unrelated to endometrial cancer risk. 30 years and 1

< Insulin resistance/metabolic syndrome is an emerging risk factor for endometrial cancer (14–19). Fasting insulin, a marker of insulin resistance (43), was associated with (95% CI) 72 months), age at menopause ( 1.33)1.46) 1.19 (0.95 1.06 (0.78 1.40) 1.19 (0.91 1.33)1.59) 1.01 (0.79 1.37 (0.99 1.28)1.89) 0.89 (0.67 1.22 (0.81 > a – – – – – – – 20 pack-years, current/21 overall endometrial cancer risk in a Canadian population- < RR 72, based case–control study (44), and in subgroups of non- – Dietary II (tertiles) HT users and/or overweight/obese women in a Swedish population-based case–control study (45) and the 36, 37 – Women’s Health Initiative Observational Study (12). Because excess energy is a major contributor to insulin 13, 13 <

12 3 resistance and sustained elevated insulin levels (39), we hypothesized that insulin-resistant individuals (obese/ 40 pack-years, current/ ed by BMI and physical activity P refers to estrogen plus progesterone hormone therapy use. inactive) who consume an insulinogenic diet would be at > ﬁ þ highest risk for endometrial cancer. However, we did not

trend observe signiﬁcant associations between dietary insulin P scores and endometrial cancer risk among these indivi- P P duals ( trend 0.17; heterogeneity 0.19). Our study beneﬁts from the large, prospective design in which dietary and risk factor information was updated 1.30)1.49) 0.82 0.57 1.00 1.00 1.06 (0.85 1.09 (0.81 1.40) 0.72 1.00 1.07 (0.81 1.59) 0.45 1.00 1.14 (0.81 1.28) 0.97 1.00 1.04 (0.81 2.05) 0.17 1.00 1.27 (0.86 1.09) 0.17 1.00 0.97 (0.74 – – – – – – – 40 pack-years, past/

– every 2 to 4 years over follow-up. The prospective nature and high follow-up rate minimized recall and selection biases, whereas repeated assessments reduced measurement error. Known and suspected risk factors were con- trolled to minimize residual confounding, although confounding by unmeasured or unknown exposures cannot be ruled out. Given our extensive data, we conducted a (95% CI) 4 children, 5 or more children), OC use (never use, 1.17)1.36) 1.04 (0.84 1.10 (0.81 1.16) 1.07 (0.82 1.41) 1.15 (0.83 1.29) 1.00 (0.77 2.01) 1.35 (0.88 1.06) 0.83 (0.63 a – – – – – – – – number of sensitivity analyses to rule out chance ﬁndings 20 pack-years, past/21 < RR or a potential effect of subclinical disease on dietary intake. 12 years of age, unknown), age at last birth and number of pregnancies (nulliparous, Dietary IL (tertiles)

> We recognize that our study has several limitations. Although dietary insulin scores were developed to assess years and 3 total postprandial insulin response to food intake, the þ 12, 12, 0.10. E refers to estrogen-only hormone therapy use; E < scores do not account for overall composition or frequency of food intake, which may affect insulin response. In 12 3 1.00 0.88 (0.67 1.001.00 0.94 (0.75 1.01 (0.75 1.00 1.01 (0.73 1.00 1.34 (0.89 1.00 0.81 (0.61 1.00 1.01 (0.79 developing the database, acute postprandial insulin responses were measured in young lean individuals 4 children, 30

– (22), which may not reﬂect the absolute response in N heavier, middle-aged women. However, the method is valid if the relative insulin response to each food is 500 298 Cases, comparable between the two groups. It is important to values for interaction 52 years), menopause and HT use status (premenopausal, postmenopausal-never HT user, -past HT use, -current E only, -current E P

> consider that in addition to dietary factors that inﬂuence 30 years and 3

< insulin secretion acutely, elevated insulin levels are deter- 52, – mined by a host of factors including anthropometric 2 characteristics throughout the lifecourse, physical activ- 50, 51 2 – ity, dietary factors that influence insulin resistance, and 2 children, Cumulative average dietary IL, dietary II, and risk of endometrial cancer strati – genetic predisposition (39, 46–50). Thus, the acute post- 30 kg/m 40 pack-years, unknown), family history of colorectal cancer (no, yes), family history of endometrial cancer (no, yes), total caloric intake (continuous), hypertension (no, yes), > 48, 49 30 and low PA 182 ¼ 30 and high PA 244 prandial insulin response alone may not sufficiently – 30 kg/m < > < reflect absolute exposure to insulin levels. Finally, our Multivariable model adjusted for age at menarche ( Table 3. BMI a years and 1 46, 47 BMI High physical activity 341 smoking status and pack-years of smoking (never smoker, past/ Low physical activity 414 current/ and BMI (continuous). All BMI Intermediate group 329 BMI Abbreviation: PA, physical activity. cohort is not representative of the general U.S. population. By design, the target population was chosen to maximize

1518 Cancer Epidemiol Biomarkers Prev; 23(8) August 2014 Cancer Epidemiology, Biomarkers & Prevention

Dietary Insulin Scores and Endometrial Cancer Risk

internal validity through enhanced reporting of expo- Development of methodology: Y. Bao, E.L. Giovannucci, I. De Vivo Acquisition of data (provided animals, acquired and managed patients, sures and health outcomes. As underlying biology is provided facilities, etc.): S.E. Hankinson, I. De Vivo likely very similar across ethnic groups and social class, Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J. Prescott, Y. Bao, A.N. Viswanathan, E.L. observations made in our cohort may apply more broadly. Giovannucci, S.E. Hankinson, I. De Vivo In summary, our results do not support an association Writing, review, and/or revision of the manuscript: J. Prescott, Y. Bao, A. between dietary factors specifically related to the post- N. Viswanathan, E.L. Giovannucci, S.E. Hankinson, I. De Vivo Study supervision: I. De Vivo prandial insulin response and endometrial cancer risk. An integrated surrogate measure of hyperinsulinemia that Acknowledgments incorporates dietary, lifestyle, and genetic factors may The authors thank the NHS participants and cohort staff for their provide a more useful indicator for studies investigating valuable contributions as well as the following state registries: AL, AZ, the insulin hypothesis in disease risk. AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. This study was approved by the Human Investigations Committee of the DPH. Disclosure of Potential Conflicts of Interest No potential conflicts of interest were disclosed. Grant Support The NHS project, E.L. Giovannucci, and S.E. Hankinson are supported Disclaimer by the NIH (P01 CA87969). I. De Vivo (R01 CA082838) and J. Prescott (U54 The opinions or assertions contained in this work are the private views CA155626) were supported by funds from the NIH. of the authors and are not considered as official or reflecting the views of The costs of publication of this article were defrayed in part by the the NIH. Certain data used in this publication were obtained from the payment of page charges. This article must therefore be hereby marked Connecticut Department of Public Health (DPH). The authors assume full advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate responsibility for analyses and interpretation of these data. this fact.

Authors' Contributions Received February 14, 2014; revised May 1, 2014; accepted May 6, 2014; Conception and design: J. Prescott, I. De Vivo published OnlineFirst May 23, 2014.

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1520 Cancer Epidemiol Biomarkers Prev; 23(8) August 2014 Cancer Epidemiology, Biomarkers & Prevention

Dietary Insulin Index and Insulin Load in Relation to Endometrial Cancer Risk in the Nurses' Health Study

Jennifer Prescott, Ying Bao, Akila N. Viswanathan, et al.

Cancer Epidemiol Biomarkers Prev 2014;23:1512-1520. Published OnlineFirst May 23, 2014.

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