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Identification of Direct and Indirect Social Network Effects in the Pathophysiology of Insulin Resistance in Obese Human Subjects
Authors:Christian H C A Henning  Nana Zarnekow  Johannes Hedtrich  Sascha Stark  Kathrin Türk  Matthias Laudes
Institution:1. Institute of Agricultural Economics, University of Kiel, Kiel, Germany.; 2. Department of Internal Medicine 1, University of Kiel, Kiel, Germany.; University of Bremen, Germany,
Abstract:

Objective

The aim of the present study was to examine to what extent different social network mechanisms are involved in the pathogenesis of obesity and insulin-resistance.

Design

We used nonparametric and parametric regression models to analyse whether individual BMI and HOMA-IR are determined by social network characteristics.

Subjects and Methods

A total of 677 probands (EGO) and 3033 social network partners (ALTER) were included in the study. Data gathered from the probands include anthropometric measures, HOMA-IR index, health attitudes, behavioural and socio-economic variables and social network data.

Results

We found significant treatment effects for ALTERs frequent dieting (p<0.001) and ALTERs health oriented nutritional attitudes (p<0.001) on EGO''s BMI, establishing a significant indirect network effect also on EGO''s insulin resistance. Most importantly, we also found significant direct social network effects on EGO''s insulin resistance, evidenced by an effect of ALTERs frequent dieting (p = 0.033) and ALTERs sport activities (p = 0.041) to decrease EGO''s HOMA-IR index independently of EGO''s BMI.

Conclusions

Social network phenomena appear not only to be relevant for the spread of obesity, but also for the spread of insulin resistance as the basis for type 2 diabetes. Attitudes and behaviour of peer groups influence EGO''s health status not only via social mechanisms, but also via socio-biological mechanisms, i.e. higher brain areas might be influenced not only by biological signals from the own organism, but also by behaviour and knowledge from different human individuals. Our approach allows the identification of peer group influence controlling for potential homophily even when using cross-sectional observational data.
Keywords:
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