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The Journal of Clinical Endocrinology & Metabolism Vol. 89, No. 4 1879-1884
Copyright © 2004 by The Endocrine Society

Metabolic, Anthropometric, and Nutritional Factors as Predictors of Circulating Insulin-Like Growth Factor Binding Protein-1 Levels in Middle-Aged and Elderly Men

Katarina Wolk, Susanna C. Larsson, Bengt Vessby, Alicja Wolk and Kerstin Brismar

Department of Medicine (K.W.), Karolinska Institutet, SE-17177 Stockholm; Division of Nutritional Epidemiology (S.C.L., A.W.), The National Institute of Environmental Medicine, Karolinska Institutet, SE-17177 Stockholm; Department of Public Health and Caring Sciences (B.V.), Unit of Clinical Nutrition, Uppsala University, SE-75125 Uppsala; and Department of Molecular Medicine (K.B.), Karolinska Institutet, SE-17176 Stockholm, Sweden

Address all correspondence and requests for reprints to: Katarina Wolk, Department of Medicine, Karolinska Institutet, P.O. Box 210, SE-171 77 Stockholm, Sweden. E-mail: katarina.wolk{at}ks.se.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Circulating IGF binding protein (IGFBP)-1 levels have been associated with insulin sensitivity, the metabolic syndrome, several cardiovascular risk factors, and possibly with cancer. We examined long-term nutrient intake and metabolic and anthropometric factors in relation to IGFBP-1 levels in 226 men, 42–76 yr old, who completed 14 24-h diet recall interviews. Spearman rank correlation coefficients were calculated. Serum IGFBP-1 levels were significantly inversely correlated with insulin, homeostasis model assessment-insulin resistance, and IGF-I and positively correlated with age. Furthermore, IGFBP-1 was inversely correlated with anthropometric measures reflecting obesity, somewhat stronger in middle-aged (<65 yr) than in older men. Serum IGFBP-1 increased with higher energy and carbohydrate intake but only in the younger age group. The difference in mean IGFBP-1 levels comparing men in the top quartile of carbohydrate intake with those in the bottom quartile was 45% in men of age 42–54 yr (P = 0.01). Insulin, body mass index, and carbohydrate intake together explained 39% of the variability in IGFBP-1 levels in men 42–54 yr of age, 27% in men 55–64 yr, and 6% in men 65 or more years old. Our data suggest that metabolic, anthropometric, and nutritional factors are important determinants of IGFBP-1 levels in healthy men.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
LOW LEVELS OF IGF binding protein (IGFBP)-1 have been associated with insulin resistance, the metabolic syndrome, obesity, and with several cardiovascular risk factors (1, 2, 3, 4, 5). A key function of IGFBP-1 is to regulate the bioavailability of circulating IGF-I (6), which is involved in cell growth, differentiation, and apoptosis (7). It has been suggested that IGFBP-1 facilitates the transport of IGF-I from plasma to tissues, thus potentially increasing the activity of IGF-I in the target tissues (8). High circulating IGFBP-1 levels have been reported to be associated with elevated risk of prostate cancer in one study (9) but not in two other studies (10, 11).

Serum IGFBP-1 levels vary considerably among healthy individuals (12, 13). A monozygotic twin study showed that nongenetic factors explained 64% of total variation in serum IGFBP-1 levels (14). Insulin and IGF-I explained 28% and 8%, respectively, of the nongenetic variation in IGFBP-1 (15). Hence, approximately 30% of the variation in IGFBP-1 levels remains unexplained, and this variation might be due to dietary and other lifestyle factors.

IGFBP-1 has been found to be inversely correlated with fasting levels of insulin and IGF-I as well as with body mass index (BMI) (4, 5, 14). Serum IGFBP-1 levels are sensitive to energy and nutrient intake. Whereas food intake markedly reduces serum IGFBP-1 levels, dietary protein restriction and fasting have an opposite effect (6, 16). A study among 292 women (meat-eaters, vegetarians, and vegans) showed that both serum IGFBP-1 and IGFBP-2 levels were 20–40% higher in vegan women compared with meat-eaters and vegetarians (17).

To our knowledge, no previous study has examined the relation between IGFBP-1 levels and long-term nutrient intake in healthy men. Given the potential important role of IGFBP-1 on overall health, better knowledge about the associations of modifiable nutritional and anthropometric factors with circulating IGFBP-1 levels is needed. We therefore conducted a study to evaluate these associations in a general population of free-living middle-aged and elderly men.


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Study population

This study included healthy men, ages 42–76 yr, randomly selected from the population register of Uppsala (city) and Knutby (countryside) in central Sweden. The men were invited to participate in a validation study of a food-frequency questionnaire (18). A total of 469 men filled in the form; and among them, 308 participated in 14 24-h diet recall interviews performed during 1 yr (once per month). In this group, within 2 wk after completion of the last interview, we collected blood samples and data on weight, height, waist circumference, and sagittal measures for 237 men. We excluded from the analyses 11 subjects who had measurements 2 SDs below or above the mean of the reference population: nine with extremely high insulin values (>28.5 mU/liter), one with high IGFBP-1 value (149 µg/liter), and one with very high IGF-I value (358 µg/liter). These exclusions left 226 men for analyses. The study was approved by the ethical committees at Uppsala University Hospital and at Karolinska Institutet, Stockholm.

Blood collection and laboratory assays

Venous blood samples were drawn in the morning, after a 12-h overnight fast. Serum was separated by centrifugation at 1200 x g after coagulation of the blood during 2 h at room temperature. Samples were stored at –70 C until analyzed for insulin, glucose, IGFBP-1, and IGF-I. IGFBP-1 and IGF-I were analyzed after storage of up to 2 yr. IGFBP-1 was determined by RIA according to the method of Póvo et al. (19) The antibodies used were raised in rabbits against purified human amniotic protein, and the cross-reaction with IGFBP-2 and IGFBP-3 was less than 0.1%. The assay measures both phosphorylated and nonphosphorylated forms. The sensitivity of the assay was 3 µg/liter with within-assay and between-assay coefficients of variation of 3% and 10%, respectively.

IGF-I was assayed, within 1 yr after blood collection, by RIA after separation of IGFs from IGFBPs by acid-ethanol extraction (20). The sensitivity of the assay was 2 µg/liter, and the within-assay and between-assay coefficients of variation were 4% and 11%, respectively. There was no significant cross-reactivity between IGF-I, IGF-II, or other peptide hormones with IGF-I antiserum. No significant interference of IGFBPs was detected. Insulin was assayed by ELISA with reagents from Hoffman-La Roche LTD Diagnostic Division (Basel, Switzerland) immunodiagnostics for the ES 300. Plasma glucose was assayed by the glucose dehydrogenase method (Advia 1650, Bayer’s Business Group Diagnostics, Tarrytown, NY).

Assessment of nutrient intake

Long-term nutrient intake was estimated on the basis of the mean nutrient intake from 14 24-h dietary telephone interviews performed over 1 yr. The 24-h diet recall technique was completed with probing questions. An administrative program had been choosing random days for consecutive dietary interviews for each individual, covering all weekdays, including weekends. Portion sizes were described in household measures. The interviews were entered using personnel computer nutrient software package MATS (Rudans Lättdata, Västeras, Sweden) (21). For nutrient calculations, we used the Swedish Food Administration Food Database PC version 1992, which includes 1,593 foods and whole dishes (22). For dishes reported but not included in this database, the dietician obtained recipes from the participants and entered appropriate amounts of the component foods.

Anthropometric measurements

The waist was measured with the subjects in the supine position. The abdominal sagittal circumference was recorded at the umbilical level as the height of the abdomen measured from the examination couch when lying down with the legs straight. BMI was calculated by dividing body weight (in kilograms) by the square of height (in meters).

Statistical analyses

Because of the slightly positively skewed nature of the IGFBP-1 distribution in our dataset, we conducted a logarithmic transformation of this variable to improve normality. Homeostasis model assessment (HOMA)-insulin resistance was calculated according to the formula of Matthews et al. (23), i.e. HOMA: [fasting insulin (mU/liter) x fasting plasma glucose (mmol/liter)]/22.5. Spearman rank correlation coefficients and multivariate regression analyses (adjusted for age, insulin, IGF-I, and BMI) were used to estimate association of metabolic, anthropometric, and nutritional factors with IGFBP-1 levels. To evaluate how much of the variability in serum IGFBP-1 levels might be explained by anthropometric and nutritional factors, we calculated partial Spearman correlation coefficients controlled for age, insulin, IGF-I, and BMI. All statistical analyses were performed using SAS software (SAS Institute Inc., Cary, NS). Two-sided P values < 0.05 were considered statistically significant.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
Metabolic, anthropometric, and nutritional characteristics of the study subjects are presented in Table 1Go. The average age of the men was 60.5 yr (SD ± 10.1), and the range was from 42–76 yr of age. Age was positively correlated with serum levels of IGFBP-1 (Spearman r = 0.36; P = 0.0001) and insulin (r = 0.24; P = 0.0003) and inversely correlated with serum IGF-I levels (r = –0.44; P = 0.0001). BMI and waist circumference increased with age, whereas energy and nutrient intake showed the opposite trend.


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  		TABLE 1. Metabolic, anthropometric, and nutritional characteristics of 226 men of age 42–76 yr, by age groups

 
We first examined serum IGFBP-1 levels in relation to serum levels of IGF-I, insulin, glucose, and HOMA as well as with anthropometric factors. As shown in Table 2Go, IGFBP-1 was significantly inversely correlated with IGF-I in men of age 65 yr and older but not in younger men. By contrast, IGFBP-1 showed a strong inverse correlation with insulin and HOMA, but these correlations was confined to middle-aged men (<65 yr). We further observed that IGFBP-1 was significantly inversely correlated with BMI, weight, sagittal measure, and waist. With the exception for weight, these correlations were somewhat stronger in men less than 65 yr of age. In contrast, height was inversely correlated with IGFBP-1 only in men 65 yr and older.


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  		TABLE 2. Spearman correlation coefficients of serum levels of log IGFBP-1 with metabolic, anthropometric, and nutritional factors in 226 men by age groups

 
We next examined the relation between nutritional factors with serum IGFBP-1 levels (Table 2Go). Significant positive correlations were observed for intakes of energy, total fat, and carbohydrates, but these correlations were only significant in men younger than 65 yr. Inclusion of carbohydrates, fat, and protein in the same multivariate regression model (adjusted for age, insulin, IGF-I, and BMI) revealed that only carbohydrate intake was significantly positively associated with IGFBP-1 (P = 0.03). When we simultaneously entered monosaccharides, disaccharides, starch, and total fiber in a model adjusted for age, the only significant (positive) association was between starch and IGFBP-1 (P = 0.05). This association did not change appreciably after including in the model insulin and IGF-I (P = 0.08). However, further adjusting for BMI significantly attenuated the association between starch and IGFBP-1 (P = 0.16). There was no significant correlation between IGFBP-1 and alcohol consumption.

We calculated partial Spearman correlation coefficients to evaluate how much of the variability in serum IGFBP-1 levels might be explained by different metabolic, anthropometric, and nutritional factors (Table 3Go). In these analyses, we used BMI as a measure of body composition, because this was the anthropometric variable most strongly correlated with IGFBP-1 levels. BMI, insulin, and carbohydrate intake could together explain 39% of the variability in serum levels of IGFBP-1 in men of age 42–54 yr, with BMI being the strongest single determinant, explaining 21% of the variability. In men of age 55–64 yr, insulin was the strongest single predictor of IGFBP-1 levels. None of the single parameters explained more than 8% (IGF-I) of IGFBP-1 variability in men 65–76 yr of age. Regarding the macronutrients, carbohydrate was the most important determinant of IGFBP-1 levels in men of age 42–54 yr and 55–64 yr (explained 7% and 3%, respectively, of the variability), whereas total fat and protein appeared more important in men of age 65–76 yr, explaining 4% of the variability.


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  		TABLE 3. The proportion of the variability in serum IGFBP-1 levels that might be explained by age and metabolic, anthropometric, and nutritional factors—partial Spearman correlation coefficients

 
Table 4Go shows the association between serum IGFBP-1 levels across categories of serum insulin levels, BMI, and carbohydrate intake. We observed inverse associations of IGFBP-1 levels with insulin and BMI. Serum IGFBP-1 levels tended to increase with increasing carbohydrate intake in middle-aged men; the difference in mean IGFBP-1 levels, comparing men in the top quartile of carbohydrate intake with those in the bottom quartile, was 45% in men of age 42–54 yr (P = 0.01). No significant association between IGFBP-1 and carbohydrate intake was noted in men of age 55–64 yr and in men 65 yr of age and older.


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  		TABLE 4. Mean serum levels of IGFBP-1 (µg/liter) by category of insulin levels, BMI, and carbohydrate intake in 226 men, stratified by age groups

 

   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
In this population-based study of well-nourished middle-aged and older men, we observed that energy and carbohydrate intake was positively correlated with serum IGFBP-1 levels in men younger than 65 yr of age. We further found inverse correlations between IGFBP-1 and such anthropometric factors as BMI, weight, and waist in both middle-aged and elderly men. Height was inversely related to IGFBP-1 only in men 65 yr of age and older.

In men less than 65 yr of age, BMI, insulin, and carbohydrate intake explained most of the variability in IGFBP-1 levels; whereas in men 65 yr and older, IGF-I, independent of insulin, appeared to be the major determinant. The lower explanatory power of metabolic, anthropometric, and nutritional factors in the elderly men suggests that with advancing age, genetics or other factors not measured by us might have an increasing role in explaining IGFBP-1 levels.

Our finding of an inverse correlation between IGFBP-1 and IGF-I is consistent with previous investigations (4, 12, 13, 24, 25). Benbassat et al. (13) reported that IGFBP-1 and IGF-I levels were related in older men but not in younger, which is in accordance with our study. This observation might suggest that the relation between IGFBP-1 and IGF-I is strongest when the secretion of GH is limited, as in older age. Because no IGF-I receptors have been detected in the liver (26, 27), the inverse correlation between IGFBP-1 and IGF-I in older men is unlikely due to a suppressing effect of IGF-I on liver IGFBP-1 production. Instead, one can speculate that IGF-I might increase the clearance of IGFBP-1.

Numerous investigations have confirmed that insulin, through inhibition of IGFBP-1 transcription, is the primary determinant of IGFBP-1 expression both in vitro and in vivo (28). Similarly to other studies (3, 4, 13, 24, 29, 30), we found that IGFBP-1 was strongly inversely related to insulin levels. However, in our data, this correlation was confined to middle-aged men (42–65 yr).

This study further confirms previous findings of a positive relation between IGFBP-1 and age in men (12, 13, 29, 31). The positive correlation between IGFBP-1 and age might be caused by higher production rates or slower clearance of IGFBP-1 from plasma in older men.

We found that BMI was strongly inversely correlated with IGFBP-1 levels, which is in agreement with earlier studies (3, 4, 24, 25, 29, 32). In our study, anthropometric factors reflecting abdominal obesity (waist and sagittal measure) were more strongly inversely related to IGFBP-1 in men less than 65 yr of age than in the elderly men, with the exception for weight, which showed the same correlation in both age groups.

To our knowledge we, for the first time, addressed the association between long-term nutrient intake and serum IGFBP-1 levels in middle-aged and older men. Moreover, this is the first study to investigate how much of the variability in IGFBP-1 levels might be explained by nutritional factors. We found that intakes of energy and carbohydrates were positively correlated with IGFBP-1. Given that IGFBP-1 was inversely correlated with HOMA (a measure of whole-body insulin resistance), one can speculate that nutritional factors that increase insulin sensitivity and thus reduce insulin levels are associated with higher IGFBP-I levels. Indeed, Lemne and Brismar (5) reported that men with insulin resistance had lower IGFBP-I levels than men without insulin resistance. Furthermore, studies in healthy children (33) and adults with normal glucose homeostasis (1) and in individuals with type 2 diabetes (30) have shown that IGFBP-1 is positively correlated with insulin sensitivity. Recently, Frystyk et al. (34) reported that glucose infusion during a 24-h period in healthy nonobese individuals resulted in increased insulin sensitivity. We found that intake of carbohydrates or more specifically starch, which is broken down into glucose, was positively correlated with IGFBP-1 levels. Thus, a potential explanation for this finding might be that a high carbohydrate diet leads to increased insulin sensitivity. Alternatively, one might speculate that a long-term high carbohydrate diet may induce hepatic insulin resistance and increased IGFBP-1 levels.

IGFBP-1 is highly sensitive to short-term nutritional status; its serum levels decrease rapidly after a meal and increase markedly after a few hours of fasting (35). Plasma and hepatic mRNA levels of IGFBP-1 increased in rats restricted of protein (36). Smith et al. (37) examined the influence of energy restriction (50% reduction of intake) for 6 d in eight pubertal children and eight adults. Energy restriction resulted in a significant increase in IGFBP-1 levels in adults but not in children. In another study, 16 healthy obese adult women were followed for 14 d of energy restriction (fasting or a hypocaloric diet enriched in protein, fat, or carbohydrate) (38). Although, IGFBP-1 levels increased during energy restriction in all groups, the increment was significantly lower on the high carbohydrate diet. However, these results are difficult to translate to our findings because the men in our study were generally well-nourished and because our results were based on long-term nutrient intake.

Major strengths of our study include its population-based design, relatively large sample size, and the extensive information on nutrient intake collected over 1 yr. Serum levels of IGFBP-1, IGF-I, and insulin were analyzed by experienced laboratory personnel, and all anthropometric measures were taken by a well-trained nurse from the metabolic clinic. However, this study was limited by its cross-sectional nature; the analyses were based on only one blood sample collected in the fasting stage. Nonetheless, it has been found that fasting IGFBP-1 levels correlate well with the 24-h mean serum IGFBP-1 levels. Kaaks et al. (39) demonstrated that the Spearman correlation coefficient for measurements of IGFBP-1 levels between two serum samples 1 yr apart was 0.63.

In conclusion, this study corroborates and extends previous findings of an inverse correlation between serum IGFBP-1 levels and anthropometric factors reflecting obesity. IGFBP-1 levels were significantly inversely correlated with whole-body insulin resistance, as measured using HOMA. We have showed that intakes of energy and carbohydrates were positively correlated with IGFBP-1 in well-nourished middle-aged men. A large proportion of the variability in IGFBP-1 levels might be explained by metabolic, anthropometric, and nutritional factors. These results suggest that factors such as metabolic, anthropometric, and nutritional are important determinants of IGFBP-1 levels in healthy men.


   Footnotes
 
This work was supported by grants from the Swedish Cancer Foundation and the Swedish Research Council/Medicine.

Abbreviations: BMI, Body mass index; HOMA, homeostasis model assessment; IGFBP, IGF binding protein.

Received August 27, 2003.

Accepted January 8, 2004.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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M. Shimizu, B. R Beckman, A. Hara, and W. W Dickhoff
Measurement of circulating salmon IGF binding protein-1: assay development, response to feeding ration and temperature, and relation to growth parameters
J. Endocrinol., January 1, 2006; 188(1): 101 - 110.
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S. C Larsson, K. Wolk, K. Brismar, and A. Wolk
Association of diet with serum insulin-like growth factor I in middle-aged and elderly men
Am. J. Clinical Nutrition, May 1, 2005; 81(5): 1163 - 1167.
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