Insulin and BMI as Predictors of Adult Type 2 Diabetes Mellitus

Abstract

BACKGROUND AND OBJECTIVES: Fasting insulin concentrations are increasingly being used as a surrogate for insulin resistance and risk for type 2 diabetes (T2DM), although associations with adult outcomes are unclear. Our objective was to determine whether fasting insulin concentrations in childhood associate with later T2DM. METHODS:Fasting insulin values were available from 2478 participants in the longitudinal Cardiovascular Risk in Young Finns Study at baseline age 3 to 18 years, along with data on adult T2DM (N = 84, mean age = 39.6 years). RESULTS:Among 3-to 6-year-olds, a 1-SD increase in fasting insulin was associated with a relative risk (RR) of 2.04 (95% confidence interval [CI], 1.54-2.70) for later T2DM, which remained significant after we adjusted for BMI and parental history of T2DM. For those aged 9 to 18 years, a 1-SD increase in insulin was associated with an RR of 1.32 (95% CI, 1.06-1.65) for T2DM, but this became nonsignificant after we adjusted for BMI and parental history of T2DM. In the latter age group, a 1-SD increase in BMI was associated with an RR of 1.45 (95% CI, 1.21-1.73) for T2DM, with adjustment for insulin and parental history of T2DM not improving this association. BMI in younger children was not associated with later T2DM. In life course analyses, those with T2DM had higher fasting insulin levels in early childhood and later adulthood but not in peripubertal years.CONCLUSIONS: Elevated fasting insulin concentrations in early childhood, but not adolescence, are independently associated with an elevated risk of T2DM in adulthood. WHAT'S KNOWN ON THIS SUBJECT:Fasting insulin levels in childhood are increasingly being used as a surrogate for insulin resistance and risk of later type 2 diabetes, despite only a moderate correlation with whole-body insulin sensitivity and few data related to adult outcomes. WHAT THIS STUDY ADDS:Elevated insulin values between the ages of 3 and 6 years are associated with an elevated risk for later type 2 diabetes. In 9-to 18-year-olds, elevated BMI (but not insulin values) is associated with later type 2 diabetes. Drs Sabin and Magnussen contributed equally to the study. Dr Sabin conceptualized the study, analyzed the data, and drafted the initial manuscript; Drs Magnussen and Juonala analyzed the data and assisted in writing core aspects of the manuscript; Professor Shield provided critical analysis of the findings and interpretation; Drs Kähönen, Lehtimäki, Rönnemaa, Knip, and Hutri-Kähönen and Professor Viikari collected the study data; Dr Koskinen and Professor Dwyer provided critical analysis of the findings and interpretation; Dr Loo collected the study data and provided data related to the correction of insulin values over time; Professor Raitakari led the study and was involved in all aspects of the study including conceptualization, data collection, analysis, and interpretation; and all authors approved the final manuscript as submitted. With the high prevalence of childhood obesity, pediatricians are routinely encountering obese patie...

Childhood obesity: Current and novel approaches

“…The latter is exemplified by the fact that many practitioners routinely measure fasting insulin levels in overweight and obese children, as a postulated surrogate for insulin sensitivity and determination of risk of future type 2 diabetes and yet they are a poor surrogate measure for insulin sensitivity and high levels have not yet been shown to be associated with the development of later Type 2 diabetes [51]. In fact, we have recently shown that BMI is a better predictor of later type 2 diabetes in adolescence than measurement of fasting insulin levels [52].…”

Bayesian hierarchical piecewise regression models: a tool to detect trajectory divergence between groups in long-term observational studies

“…As mentioned above, previous research on this data set suggested BMI levels were not significantly different between the two groups in childhood [87]. Models C (i.e.…”

“…In a previously published work on the YFS cohort, elevated BMI in children between 9 and 18 years was associated with an increased risk of developing T2DM in adulthood [87]. Additionally, a sex- and insulin-adjusted mixed model incorporating participants ages as a categorical variable, suggested that differences in average BMI values between those who do and those who do not develop adult T2DM tended to emerge during adolescence, becoming marginally significant from the age of 15 years onwards.…”

“…all β cohort priors and β initialBMI  −  z  −  score ). To remain consistent with previous analyses of this data set [87], time-varying measures of fasting insulin were log-transformed and standardized before being included as a level-1 predictor in the Bayesian hierarchical models to improve right skewedness and to linearize its relationship with BMI About 17% of the insulin measures were not available in the data. The missing data mechanism for ‘insulin’ was considered non-informative, as we have no reason to believe that the probability of an individual insulin measure being missing depends on the true value of this missing insulin observation (although it may be related to other observed variables for that individual).…”

“…In this paper we illustrate the use of Bayesian hierarchical piecewise regression modeling to detect trajectory divergence between groups of participants using longitudinal BMI data from the Cardiovascular Risk in Young Finns (YFS) Study, a well phenotyped prospective cohort with measures from multiple time-points. Previously published work on this data, based on categorical mixed modeling, suggested that BMI levels became statistically different between those who develop T2DM in adulthood and those who did not from the age of 15 years [87]. We re-analyse this data set to demonstrate how the Bayesian method can be used to (1) model the BMI profiles to better understand the natural history of the BMI trajectories in those who do and do not develop T2DM in adulthood while controlling for potential cohort effects, and (2) obtain a refined estimate and confidence interval of the age at which the two groups start diverging from one another, translating into significantly different BMI from a certain age onwards.…”