Nutrition and Cancer Early Diet and Later Cancer

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Early Diet and Later Cancer Risk: Prospective Associations of Dietary Patterns During Critical Periods of Childhood with the GH-IGF Axis, Insulin Resistance and Body Fatness in Younger Adulthood a

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Anke L. B. Günther , Matthias B. Schulze , Anja Kroke , Katharina Diethelm , Gesa c

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Joslowski , Danika Krupp , Stefan Wudy & Anette E. Buyken

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Department of Nutritional, Food and Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany b

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Department of Molecular Epidemiology, German Institute of Human Nutrition PotsdamRehbruecke, Nuthetal, Germany c

IEL–Nutritional Epidemiology, Rheinische Friedrich-Wilhelms-University Bonn, DONALD Study at the Research Institute of Child Nutrition, Dortmund, Germany d

Justus-Liebig-University of Giessen, Center of Child and Adolescent Medicine, Laboratory for Translational Hormone Analytics in Pediatric Endocrinology, Peptide Hormone Research Unit, Giessen, Germany Published online: 30 Jul 2015.

To cite this article: Anke L. B. Günther, Matthias B. Schulze, Anja Kroke, Katharina Diethelm, Gesa Joslowski, Danika Krupp, Stefan Wudy & Anette E. Buyken (2015) Early Diet and Later Cancer Risk: Prospective Associations of Dietary Patterns During Critical Periods of Childhood with the GH-IGF Axis, Insulin Resistance and Body Fatness in Younger Adulthood, Nutrition and Cancer, 67:6, 877-892, DOI: 10.1080/01635581.2015.1056313 To link to this article: http://dx.doi.org/10.1080/01635581.2015.1056313

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Nutrition and Cancer, 67(6), 877–892 Copyright Ó 2015, Taylor & Francis Group, LLC ISSN: 0163-5581 print / 1532-7914 online DOI: 10.1080/01635581.2015.1056313

Early Diet and Later Cancer Risk: Prospective Associations of Dietary Patterns During Critical Periods of Childhood with the GH-IGF Axis, Insulin Resistance and Body Fatness in Younger Adulthood Anke L. B. G€ unther Department of Nutritional, Food and Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany

Matthias B. Schulze

Downloaded by [Anette Buyken] at 03:39 25 August 2015

Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany

Anja Kroke Department of Nutritional, Food and Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany

Katharina Diethelm, Gesa Joslowski, and Danika Krupp IEL–Nutritional Epidemiology, Rheinische Friedrich-Wilhelms-University Bonn, DONALD Study at the Research Institute of Child Nutrition, Dortmund, Germany

Stefan Wudy Justus-Liebig-University of Giessen, Center of Child and Adolescent Medicine, Laboratory for Translational Hormone Analytics in Pediatric Endocrinology, Peptide Hormone Research Unit, Giessen, Germany

Anette E. Buyken IEL–Nutritional Epidemiology, Rheinische Friedrich-Wilhelms-University Bonn, DONALD Study at the Research Institute of Child Nutrition, Dortmund, Germany

Early life, adiposity rebound, and puberty represent critical growth periods when food choices could have long-term relevance for cancer risk. We aimed to relate dietary patterns during these periods to the growth hormone-insulin-like-growth-factor (GH-IGF) axis, insulin resistance, and body fatness in adulthood. Data from the Dortmund Nutritional and Anthropometric

Submitted 23 April 2014; accepted in final form 26 May 2015. Address correspondence to Anette E. Buyken, IEL–Nutritional Epidemiology, Rheinische Friedrich-Wilhelms-University Bonn, DONALD Study at the Research Institute of Child Nutrition, Heinstueck 11, 44225 Dortmund, Germany. Phone: +49 231 79 22 10 50. Fax: +49 231 71 15 81. E-mail: [email protected]

Longitudinally Designed (DONALD) Study participants with outcome data at 18–37 years, and 2 dietary records during early life (1–2 yr; n D 128), adiposity rebound (4–6 years, n D 179), or puberty (girls 9–14, boys 10–15 yr; n D 213) were used. Dietary patterns at these ages were derived by 1) reduced rank regression (RRR) to explain variation in adult IGF-I, IGF-binding protein-3 (IGFBP-3), homoeostasis model assessment for insulin resistance (HOMA-IR) and fat-mass index; 2) principal component analysis (PCA). Regarding RRR, the patterns “cake/canned fruit/cheese & eggs” (early life), “sweets & dairy” (adiposity rebound) and “high-fat foods” (pubertal boys) were independently associated with higher adult HOMA-IR. Furthermore, the patterns “favorable carbohydrate sources” (early life), “snack & convenience foods” (adiposity rebound), and “traditional & convenience carbohydrates” (pubertal boys) were related to adult IGFBP-3 (P trend < 0.01). PCA identified “healthy” patterns for

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all periods, but none was associated with the outcomes (P trend > 0.1). In conclusion, dietary patterns during sensitive growth periods may be of long-term relevance for adult insulin resistance and IGFBP-3.

INTRODUCTION Epidemiologic evidence suggests that cancer and other chronic diseases may have origins early in life. In particular, childhood diet has been proposed to exert sustained, perhaps lifelong influences during distinct critical growth periods, i.e. infancy, the period of “adiposity rebound” in mid-childhood and puberty (1,2). Because of the long latency period between exposure and cancer diagnosis, for prospective studies potential intermediate markers of disease risk are of special interest within this context. The growth-hormone insulin-like growth factor (GH-IGF) axis may represent such an intermediate factor. Elevated levels of IGF-I, a major regulator of human growth whose bioavailability is regulated by several binding proteins (BPs), has been linked to different types of cancer and is susceptible to nutritional influences (3–6). Importantly, it has been proposed that the GH-IGF axis can be programmed early in life, which may explain associations of early life factors with cancer (7,8) and could also unfavorably influence body fatness (9), itself an established cancer risk factor (6). Furthermore, IGFBP metabolism is linked to insulin sensitivity, which may also lie on the pathway between childhood diet and cancer (10,11). In particular, higher IGFBP-2 levels reflect higher long-term insulin sensitivity (12). However, data on early nutritional influences on the adult GH-IGF axis are currently limited. It has been suggested that the GH-IGF axis can be programmed by breastfeeding as well as protein and/or dairy intake in childhood, but the evidence is contradictory (9,13). Data from adult populations further suggest associations of other dietary factors with the GH-IGF axis [e.g., vegetable intake, zinc and calcium, lycopene (14,3), low-fat diets with high omega-3 fatty acids (15), dietary glycemic index (GI) (16) and glycemic load (GL) (17)]. It is conceivable that already during childhood, dietary patterns related to several of these factors simultaneously have a long-term impact on the adult GH-IGF axis. Dietary patterns consider the complexity of an individual’s diet as a whole, taking into account synergistic and/or antagonistic interactions between nutrients and acknowledge that single nutrients have different food sources (18). To date, however, no study has considered the relevance of dietary patterns during potentially critical periods in childhood for the adult GH-IGF axis. With respect to childhood dietary patterns and body composition or insulin metabolism, the few existing prospective studies also rarely followed participants up beyond adolescence (19,20). Our aim was to derive dietary patterns during three potentially critical periods of growth in childhood (early life, adiposity rebound in mid-childhood, puberty), and to examine

them for independent associations with the GH-IGF axis (IGFI, IGFBP-3, and IGFBP-2 reflecting long-term insulin sensitivity) (12), body fatness (fat-mass index, FMI), and insulin resistance (homeostatic model assessment for insulin resistance, HOMA-IR) in young adulthood.

MATERIALS AND METHODS Study Sample The Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study is an ongoing, open cohort study conducted at the Research Institute of Child Nutrition in Dortmund, Germany (21,22). Briefly, since recruitment began in 1985, detailed information on diet, growth, development, and metabolism between infancy and early adulthood has been collected from over 1500 children. Every year, 35–40 infants are newly recruited and first examined at 3 mo. Each child returns for 3 more visits in the first year, 2 in the second, and then once annually until early adulthood. The study was approved by the Ethics Committee of the University of Bonn, and all examinations are performed with parental and later the participants’ consent. The ages of the children who were initially recruited were quite variable; that is, information on the first years of life was not always available. In addition, many participants have not yet reached adulthood. For this analysis, 308 participants who were term 36–43 wk gestation) singletons with a birth weight 2500 g had provided 1 blood sample in which IGF-I and IGFBP-3 in young adulthood was measured (range 18– 37 years). With regards to puberty (girls: 9–14 yr, boys: 10– 15 yr), 2 plausible 3-day weighed dietary records (2–6 records per participant; mean D 5) were available for 222 of the 308 participants. The inclusion criterion of 2 records was chosen to better describe habitual dietary intake. Participants who had consistently underreported energy intake (i.e., all food records implausible or more implausible than plausible food records) were excluded from analyses (n D 18). A 3-day weighed dietary record was considered plausible when total energy intake was adequate in relation to the estimated BMR, using modified age-dependent cutoffs based on Goldberg et al. (23,24). Furthermore, participants had to provide anthropometric data both at the beginning of puberty (baseline) and in young adulthood, and information on relevant covariates such as early life and socioeconomic factors. This resulted in a final sample of 213 (55.4% females) for analyses on puberty. With regards to adiposity rebound (age 4–6 yr), the corresponding sample size was 179 (52.5% female). For early life (1–2 yr), data of 128 participants could be used (53.1% female). We did not further incorporate data from the first year of life because food intake was expected to differ considerably and would have complicated the definition of uniform food groups for dietary pattern analyses. Insulin and IGFBP-2 measurements were missing for a few individuals (see Tables 1–6).

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CHILDHOOD DIETARY PATTERNS AND LATER CANCER RISK

TABLE 1 Characteristics of the study samples during early life (1–2 yr), adiposity rebound (4–6 yr), and puberty (boys: 10–15 yr, girls: 9–14 yr) in the Dortmund Nutritional and Anthropometric Longitudinally Designed Study (n D 128–213) Puberty


Characteristics n (% female) Birth and infancy Birth year (min–max) Gestational age (wk) n (%) birth weight 2 wk. b Body mass index 25 kg/m2. c Missing values: n D 1–7.

Laboratory Measurements Venous blood samples were drawn after an overnight fast, immediately centrifuged, and stored 90% whole grain, muesli with fruit, nuts or chocolate Ready to eat-cereals, 90% whole grain, muesli with fruit, nuts or chocolate Flour, dough Rice and other grains Pasta Biscuits Cakes, pastries, sweet bread Fruit Fruit, canned or dried Vegetables, canned/dried Legumes Potatoes Potato products Nuts Dairy products, unsweetened Dairy products, sweetened, high-fat Dairy products, sweetened, low-fat Cheese Eggs Animal fat Fish Meat, high-fat Sausages, cold cut, highfat Sausages, cold cut, lowfat

Food group

Adiposity rebound

Boys

Girls

— — — — — — —

0.30 — ¡0.20 0.21 — — ¡0.30 —

— ¡0.28 — — — — — — —

— 0.21 0.23 — ¡0.22 — ¡0.23 ¡0.26

¡0.26

—

—

— — — — — ¡0.33 — —

—

— — — — — — — —

0.25 — — — — — — —

— 0.25 — — — — — —

— 0.34 0.42 — —

¡0.24 ¡ ¡ ¡ 0.24

0.23 — 0.34 — —

— — — — 0.39

— — — —

— — — 0.31

— — — —

¡0.26 — — —

—

— — — — — —

—

—

— — 0.21 — — 0.28

—

—

— 0.26 ¡0.26 — — ¡0.23 0.25 ¡0.26

¡0.24 — — — — 0.20 — — —

— —

— —

— — — —

¡0.38 — — — —

— — — ¡0.21

—

— — 0.22 — — —

—

—

¡0.22 — — — — — — —

— — — — 0.20

— ¡0.28 ¡0.21 ¡0.42

—

— — — — — —

¡0.28

—

— — — — 0.25 — — —

— — ¡0.41 — —

— — — 0.24

—

— — — — — —

—

—

—

— — — — — —

—

—

¡0.25 — — — — — — —

— — — — —

— 0.28 — —

(Continued on next page)

— — — ¡0.34 ¡0.27 — ¡0.32 —

— — — ¡0.26 —

¡0.22 — 0.34 —

“Cake, canned “Favorable “Snack and “Sweet bread/cake “Traditional & “White bread “Brown bread, fruit, cheese carbohydrate “Sweets & “Rice & convenience “High-fat & convenience convenience & convenience low-fat dairy & & eggs” sources” dairy” pasta” foods” foods” foods” carbohydrate” foods” light soft drinks”

Early life

Puberty

TABLE 3 Food groups with factor loadings j0.2j in the dietary patterns derived by reduced rank regression (RRR) during early life (1–2 yr), adiposity rebound (4–6 yr), and puberty (boys: 10–15 yr, girls: 9–14 yr) in the Dortmund Nutritional and Anthropometric Longitudinally Designed Study (n D 125–208)


882 Boys

Girls

¡0.26 ¡0.28 ¡0.29 — — —

— — NA —

4.0 6.1 3.0 24.5 9.4 2.3

— — — — — —

— — NA 0.28

11.0 3.5 18.2 14.1 11.7 2.1

4.9 12.9 8.7 3.3 7.4 1.8

0.26 0.22 NA —

— — — 0.24 — —

2.1 12.2 5.9 1.4 5.4 3.2

— — NA —

¡0.32 — NA —

18.9 0.02 2.5 6.1 6.9 2.5

0.25 — ¡0.26 — 0.23 0.26

¡0.32 — — — — —

26.4 10.3 6.9 6.1 12.5 2.2

—

—

18.3 0.1 13.0 29.2 17.6 2.1

0.31 —

— — — — — 0.26

— ¡0.22

— ¡0.22 —

0.22 —

6.2 34.6 4.0 0.1 11.2 2.3

— — ¡0.31 0.26

— 0.30 — — — 0.20

41.8 7.4 21.0 0.03 17.6 2.6

—

— —

— ¡0.25 — — — 0.31

IGF-1 D insulin-like growth-factor-1; IGFBP-3 D insulin-like-growth-factor binding protein-3; HOMA-IR D homoeostasis model assessment for insulin resistance; FMI D fat-mass index.

Ice cream Sugar, candy Sweet parfait Dressings, dips, gravy Savoury snacks Convenience foods (based on grain, vegetables, meat or fish) Water Light soft drinks Alcohol Miscellaneous Explained variance in response variables (%) IGF-I IGFBP-3 HOMA-IR FMI Total Explained variance in food group intake (%)

Food group

Adiposity rebound

4.3 9.2 20.6 28.1 15.5 2.7

— 0.41 — —

— — — — — —

“Cake, canned “Favorable “Snack and “Sweet bread/cake “Traditional & “White bread “Brown bread, fruit, cheese carbohydrate “Sweets & “Rice & convenience “High-fat & convenience convenience & convenience low-fat dairy & & eggs” sources” dairy” pasta” foods” foods” foods” carbohydrate” foods” light soft drinks”

Early life

Puberty

TABLE 3 Food groups with factor loadings j0.2j in the dietary patterns derived by reduced rank regression (RRR) during early life (1–2 yr), adiposity rebound (4–6 yr), and puberty (boys: 10–15 yr, girls: 9–14 yr) in the Dortmund Nutritional and Anthropometric Longitudinally Designed Study (n D 125–208) (Continued)


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CHILDHOOD DIETARY PATTERNS AND LATER CANCER RISK

TABLE 4 Association of the dietary patterns derived by reduced rank regression (RRR) during early life (1–2 yr) and IGF-I, IGFBP-2, IGFBP-3, HOMA-IR, and FMI in young adulthood (n D 125–128) Tertiles of pattern scores


Outcome

T1

Pattern 1: “Cake, canned fruit, cheese & eggs” IGF-I (g/L) Model 1a 267 (237; 297) Model 2b 266 (235; 296) IGFBP-2 (mg/L) Model 1 198 (170; 229) Model 2 191 (161; 223) IGFBP-3 (mg/L) Model 1 3.3 (3.1; 3.5) Model 2 3.3 (3.0; 3.5) HOMA-IR Model 1 2.3 (2.1; 2.6) Model 2 2.3 (2.1; 2.6) FMI (kg/m2) Model 1 4.6 (4.2; 5.2) Model 2 5.0 (4.5; 5.6) Pattern 2: “Favorable carbohydrate sources” IGF-I (g/L) Model 1a 280 (250; 311) Model 2b 284 (253; 314) IGFBP-2 (mg/L) Model 1 164 (137; 193) Model 2 156 (128; 187) IGFBP-3 (mg/L) Model 1 3.2 (3.0; 3.4) Model 2 3.2 (3.0; 3.4) HOMA-IR Model 1 2.7 (2.4; 3.0) Model 2 2.7 (2.4; 3.0) FMI (kg/m2) Model 1 5.4 (4.8; 6.0) Model 2 5.8 (5.2; 6.4)

T2

T3

Ptrend

296 (266; 325) 294 (264; 323)

307 (277; 337) 305 (275; 334)

0.03 0.03

151 (127; 178) 148 (123; 175)

140 (116; 166) 137 (112; 164)

0.003 0.01

3.4 (3.2; 3.7) 3.4 (3.2; 3.7)

3.6 (3.3; 3.8) 3.6 (3.4; 3.9)

0.04 0.02

2.7 (2.4; 3.0) 2.7 (2.4; 3.0)

3.2 (2.8; 3.5) 3.2 (2.8; 3.5)

0.0003 0.0003

5.1 (4.6; 5.7) 5.4 (4.9; 6.0)

5.8 (5.2; 6.4) 6.2 (5.6; 6.9)

0.01 0.02

300 (270; 330) 296 (266; 326)

291 (260; 321) 287 (256; 317)

0.5 0.7

160 (134; 189) 158 (132; 187)

161 (134; 191) 160 (132; 190)

0.7 0.9

3.6 (3.4; 3.8) 3.6 (3.4; 3.9)

3.5 (3.3; 3.8) 3.5 (3.3; 3.8)

0.002 0.003

2.5 (2.3; 2.8) 2.5 (2.2; 2.8)

3.0 (2.6; 3.3) 3.0 (2.6; 3.3)

0.13 0.14

5.4 (4.9; 6.0) 5.8 (5.2; 6.4)

4.7 (4.2; 5.2) 5.1 (4.6; 5.7)

0.006 0.01

Numbers are adjusted means (95% confidence interval), n D 128. For insulin-like-growth-factor binding protein-2 (IGFBP-2): n D 126, for HOMA-IR: n D 125. IGF D insulin-like growth factor; BP D binding protein; HOMA-IR D homoeostasis model assessment for insulin resistance; FMI D fat-mass index. a Adjusted for sex and age at outcome assessment. b IGF-I: additionally adjusted for high maternal education (yes/no), birth weight