All sporting competitions took place on Wednesday afternoons at approximately the same time of day. Blood spot collection took place weekly on Tuesdays and Thursday between 2—4 pm, approximately 24 h before or after a competition. Measuring IGF-1 from dried blood spots on filter paper is both practical and reliable [ 44 ]. All samples were extracted and measured in one single assay to avoid inter-assay variation. The intra-assay coefficient of variation of this RIA was 1.
IGF-1 values derived from dried blood are reported here; conversion to serum IGF-1 values requires multiplication by 4.
Descriptive statistics for age, height, weight, pre-game and post-game IGF-1 are given in Table 1 for men and Table 2 for women. Box plots of averaged pre-game and post-game IGF-1 values by type of sport are presented in Figure 1. Multiple regression was performed to see if pre-game IGF-1 levels the dependent variable were associated with Age, Sex, Height, Weight or type of Sport independent variables.
Results are given in Table 3. Age and Sex are significantly associated with pre-game IGF Younger participants and women have higher IGF-1 values than older participants and men. The age effect is expected in our 18—25 year old participants, as younger adolescents and adults in this age range tend to have higher IGF-1 levels than older individuals. The women participants are, on average, younger than the men, and this accounts for some of the Sex effect. It is possible that selection bias also is a factor.
Elite women athletes are a highly selected group and may have high testosterone production, which leads to higher GH and IGF-1 levels [ 22 , 39 , 41 ]. When the multiple regression analysis was performed by sex, then Age was significant for the men, but not significant for the women.
There was no association between Age and type of Sport, so we were able to combine IGF-1 data for all sports. Due to the significant Sex effect, all tests of our hypotheses were conducted separately for men and women. Our first specific hypothesis is that sport players who will win their sporting competition will have higher IGF-1 values before the game is played. We found possible support for this hypothesis. A one-sided t -test was chosen as we hypothesised a priori that winners would have higher IGF-1 values than losers.
Comparisons of post-game IGF-1 values for winners vs. Another way to test for the effect of winning vs. In this statistical test, the winners had a combined mean IGF-1 value of This finding suggests that the eventual winners had higher IGF-1 values both 24 h before and 24 h after the sporting competition. Testing by sex found similar trends, but a smaller absolute difference between winners and losers and no significance.
Our second hypothesis is that changes in social status based on winning or losing important sporting competitions will be associated with changes in IGF-1 serum concentration in the players. There was no support for this hypothesis.
Using a dependent t -test, we found no significant difference between pre-game and post-game mean values for IGF-1 for men, for women, or for both sexes combined. For individual participants there was no pattern of increase or decrease in IGF-1 values from pre- to post-game related to winning or losing.
Our third hypothesis is that IGF-1 levels of participants within a sport team will be more similar than between sport teams, that is, within a social network of players who know each other well.
As may be seen in Figure 1 , for each sex the range of IGF-1 values by sport is large relative to the differences in mean IGF-1 values. The relationship between insulin-like growth factor-1 IGF-1 , assessed via finger-prick dried blood spot, and elite level sport competition outcome was analysed for a sample of undergraduate men and women attending a British university.
There was a statistically significant difference between the mean values of the combined pre- and post-game IGF-1 for all winners vs. Winners, as a group, had a 4. We did not predict this specific finding, but it is generally supportive of our hypothesis 1 which we proposed this type of difference as our proxy for social dominance.
The biological impact of this difference for the participants of this study is not known, but the existing research reports strong positive associations between greater IGF-1 and greater body skeletal growth, physical performance, emotional status and physical and mental energy [ 12 , 46 , 47 ].
Other research finds that a 1. Higher cognitive performance is a key to both sporting success and social dominance [ 49 , 50 , 51 ]. We found no evidence that winners increased, or decreased, in IGF-1 levels over losers hypothesis 2.
It seems that winners already have, on average, higher IGF-1 values the day before the game and that this difference is maintained for at least 48 h.
We found no evidence that members of the same team were more similar in IGF-1 levels than they were to players from other teams hypothesis 3. A possible explanation for the hypothesis 3 results is that despite being on different teams, all of these elite student-athletes from the same university were actually part of the same social network.
Future studies of this type should measure the degree of interaction in terms of training and social activities of the participants. The support comes from the possibility that the higher total pre-game and post-game IGF-1 of the winners was due to their persistent social dominance over the losers.
A hierarchy of social dominance results when members of a social group vary in their ability to compete for resources or attention. Social dominance is usually measured via contests between two or more individuals, with winners ranked as dominant and losers ranked as subordinate [ 52 , 53 ]. Ethological research with non-human and human species has revised older notions that dominance is only achieved via coercive or aggressive behaviours.
Dominant individuals or social groups may be prosocial as well as coercive toward subordinates. The very large and diverse literature on the endocrinology of dominance is mostly focused on the hypothalamic-pituitary-adrenal HPA axis and its hormonal end-products, such as cortisol [ 54 , 55 ]. In the Introduction to this article we reviewed the limited literature related to social dominance and IGF Sporting contests between elite athletes is a justifiable model system to study social dominance and its associations with IGF Elite level sport requires a rare combination of talent, hard work and the right psychological profile, often a mixture of confidence, anxiety, and motivation [ 51 ].
Research comparing elite level team handball players with lower level players finds that the elites are, on average, significantly different in terms of being physically larger in both height and muscle mass, faster and more agile, possess superior skills in game performance and tactics, are more emotionally resilient, more team oriented, come from higher socioeconomic status families and have greater ego motivational orientation [ 50 ].
The associations of greater height, socioeconomic status and ego motivation in sporting success are also predicted components of the community effects in height hypothesis. Similarly, it is not possible to completely segregate causes and effects in the regulation of growth in height. Simple cause and effect relationships may not be the appropriate perspective to adopt in sport competition or in human height growth.
Both sport results and growth in height are the outcome of many biological, nutritional, social, economic, political and psychological effects and interactions [ 2 , 5 , 31 , 49 , 51 , 58 , 59 , 60 ]. Interpretation of the findings of our study is also limited by other factors. We did ask participants to list all performance supplements taken and a few admitted to creatine, which can enhance IGF-1 production [ 63 ]. The senior author asked the students who collected the data for this study about creatine usage.
These students, all of whom were themselves athletes, disclosed that they and all their team-mates used creatine and protein supplements. This included both the men and the women. If this is true, then the creatine effect on IFG-1 levels was virtually equalized for all participants. Finally, we did not measure dietary intake, including alcohol, before or after the competition.
It is unlikely that our participants fasted at any time. Chronic alcohol abuse is known to decrease IGF-1 production due to ethanol-induced liver injury [ 64 ], but again it is unlikely that our participants were liver injured or chronic alcohol abusers. Our findings offer some support for further investigation of the community effect in height hypothesis.
In essence, this hypothesis posits that there are influences on the attainment of final height which arise from the bio-social-psychological proximity of members within a social network. A next step in testing this hypothesis is validation of the findings by repeating the study with larger samples.
Such validation may warrant new analyses of longitudinal studies of IGF-1 levels of children and youth according to their social networks. GH secretion itself is regulated by endogenous signals coming from the central nervous system e. In addition, the immune system may be involved and, when activated, it causes suppression of IGF-1… In the event that one of these major regulators is missing GH or nutrients or activated immune system , there is resistance against the other factors with respect to IGF-1 production.
That is, IGF-1 transmits integrated information at the cellular level on the nutritional status, the GH secretory status, and the immune status of the organism. Generally speaking, IGF-1 provides information to the cells on the well-being of the organism. Thus, the rate of cellular activities such as proliferation, differentiation, or the synthesis of cell-specific products is adapted to the situation.
As succinctly stated in the above quote, many types of biological, social, economic, political, and emotional networks influence human growth. This serves to emphasise why human growth in height serves as a sensitive indicator of well-being by researchers in environmental epidemiology and public health. Several students collected the data used in the analysis.
Maike Schaefer performed all the IGF-1 radioimmunoassays and we thank her for this. Michael Hermanussen and Barry Bogin had the original idea for the study.
All co-authors contributed to the design. Bogin and his students were responsible for organizing the recruitment, follow-up of study participants and for data cleaning. Werner Blum was responsible for the IGF-1 assays and their interpretation.
Bogin drafted the manuscript, which was revised by all authors. All authors read and approved the final manuscript. National Center for Biotechnology Information , U. Published online May 4. Werner F. Paul B. Tchounwou, Academic Editor. Author information Article notes Copyright and License information Disclaimer. Received Mar 16; Accepted Apr This article has been cited by other articles in PMC. Abstract We test the hypothesis that differences in social status between groups of people within a population may induce variation in insulin-like growth factor-1 IGF-1 levels and, by extension, growth in height.
Introduction Human growth in height, weight and other body dimensions are widely used as indicators of well-being in environmental epidemiology and public health research [ 1 , 2 , 3 , 4 , 5 ]. Theoretical Background and Literature Review We build our hypothesis on research into social networks, which are known to shape human behaviour and biology [ 25 ]. Open in a separate window. Figure 1. Hypotheses Our general hypothesis is that changes in social status within a well-defined social network will have an association with serum concentrations of IGF Methods and Materials 4.
Participants The participants of this study were elite level sport players from undergraduate student teams. Variables Measured In the variables included age, sex, type of sport, a finger prick blood spot 24 h before a sport competition and another blood spot 24 h after the competition. Ethical Clearance All participants were informed about the requirements and potential risks involved with participating and gave informed written consent.
IGF-1 Sampling and Analysis A finger-prick blood spot was taken from participants approximately 24 h before a competitive sporting event and then again approximately 24 h after the event.
Results Descriptive statistics for age, height, weight, pre-game and post-game IGF-1 are given in Table 1 for men and Table 2 for women. Table 1 Descriptive statistics for men. Table 2 Descriptive statistics for women. Table 3 Wilkes multivariate tests of significance from multiple regression. Value F; DFs p Intercept 0. The questionnaire included questions related to the family income and living conditions as well as relevant medical history for each child and recording of parental height and weight.
At the day of the study, research team visited the schools, collected the questionnaires and consent forms filled and signed by the parents and performed the anthropometric measurements and blood sampling. The subjects were stratified into three groups of low, middle and high income. All subjects had their standing height measured by the same investigator using the same portable wall stadiometer SECA to the nearest 0.
Weight was measured on a digital scale with a precision of 0. BMI was calculated as weight kilograms divided by height meters squared. All samples were assayed within 2 months of sampling. Significant results were investigated further by Bonfferoni post hoc test. Homogeneity of group variances was tested by the Levene statistic. Correlation between variables was investigated by Pearson r. A relationship between more than two variables was analyzed using General Linear Models.
Low income group included boys and girls, middle income group included boys and girls, high income group included 95 boys and 91 girls. Because in the models, we analyzed, none of the group variances was significantly different from others, we do not report the Levene statistic in the following paragraphs. We examined the effect of ES for boys and girls separately for two reasons: first, analyzing boys and girls separately is physiologically sounder because of differences in growth patterns, onset and tempo of puberty, differences in IGF and IGFBP-3 levels between genders.
Consequently, analyzing genders separately allow better identification of associated factors in research related to growth. Taking into consideration relatively small effect sizes of the main effects, it would probably require much larger sample size to prove these interactions significant. Thus, despite of the fact that interactions were significant only in two models, we analyzed all main variables separately for each gender.
BMI SDSs tended to be higher in higher income groups but differences were not statistically significant. Height SDS in low plain , middle slanted line pattern and high criss-cross pattern income groups in girls and boys.
MPH SDS in low plain , middle slanted line pattern and high criss-cross pattern income groups in girls and boys. The schools, children attended to, were not selected randomly and some of them had no representatives of all income levels. Accordingly, we did not assign them a random factor status. To ensure that school selection did not affect our results, we analyzed them as a random factor within each income level. For both genders and for each income levels, the effect of schools was not significant.
Both effects were approximately the same as in the simple models. Postnatal growth is regulated by genetic, environmental and hormonal factors. Main determinant of height is known to be the genetic height potential as estimated by MPH. However, nutrition and hormonal milieu should be optimal to reach this genetic height potential. A secular trend towards higher final height and earlier pubertal maturation is seen in countries with favorable socioeconomic development.
Height of healthy children of the same age and ethnic origin is influenced by the socioeconomic factors Gross et al. However, malnutrition, diarrhea and parasitic infestations are mostly responsible for the different heights observed among different socioeconomic groups in the previous studies from developing countries Gross et al. In the present study, we analyzed only healthy children with the normal height and weight. Our results demonstrate that even in the group of normal and healthy children, height, weight and IGF axis can be affected by economic conditions in a country of favorable development.
These results indicate that the genetic height potential MPH is the strongest parameter that determines height in healthy children. ES proved to have a limited impact only on boys. Height and weight SDS of children in low ES group were significantly lower than middle and high socioeconomic groups in boys but not in girls. The reason s for the small 0.
Similar to our findings, Ulukanligil and Seyrek a have demonstrated that underweight rates were significantly associated with the sex of the children in shantytown schools in that the boys had a significantly higher underweight rate than girls, but this rate did not differ between sexes in apartment schools where the socioeconomic level was higher. In the same population, boys had lower height SDSs than girls in shantytown schools Ulukanligil and Seyrek, b.
Similarly, in Pakistani children the rate of underweight was significantly higher in low income level among children and adolescents in males, but not in females Hakeem, Lack of significant difference in growth of girls from different ESs could be because of sexual dimorphism in metabolic adaptation during shortage of nutrients.
Taken together with no significant difference in height SDS in girls of different ES, these results suggest that secular trend is no longer in effect in girls but still valid in boys from low income families. The secular trend in height 0. Meyer and Selmer reported that the difference between highest and lowest income group is 3.
These numbers are similar to our data showing 0. Another reason of lower MPH in lower income groups might be that being short is a disadvantage in obtaining a well-paid employment. It has been shown that height at age 1 and 3 year is a strong predictor of income at adulthood Miller et al. In the Newcastle study, short stature at age 3 years predicted lower intelligence at age 11 years Miller et al.
Furthermore, short length at 1 year similarly predicted poor educational achievement in later childhood Barker et al. Thus, it is also possible to link early childhood growth with higher intelligence and educational achievement leading to better income later on.
Although MPH might simply reflect improved environmental and nutritional factors extending from parents to their offspring rather than being a good marker of genetic potential, our results show that the effect of MPH SDS on height SDS in the complex model was independent of the ES.
Previous studies reporting low IGF-I values in lower socioeconomic populations were performed in under-developed countries where subjects with malnutrition, diarrhea or short stature were included Lopez-Jaramillo et al.
In our analyses, children with pathological short stature, malnutrition, chronic diseases and low birth weight, conditions known to influence IGF axis, were excluded from the study. In addition to total calories, the quality of nutrients is also related to serum IGF-I levels.
Serum IGF-I is positively associated with consumption of red meats, fats and oils. Serum IGF-I is also positively associated with the fraction of energy intake derived from fat, whereas that derived from carbohydrates has a negative effect on serum IGF-I Heaney et al.
Although we did not have a quantitative analysis of nutritional intake of our study population, we think that energy requirement is mostly covered by high carbohydrate and low protein in the group of lower ES because of high cost of protein rich nutrients. IGFBP-3 correlated with anthropometric measurements in boys but not in girls, suggesting sexual dimorphism. In conclusion, our findings demonstrate that MPH is the most powerful predictor of height in children.
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