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Invited Review Articles

Impact of body mass index on growth hormone stimulation tests in children and adolescents: a systematic review and meta-analysis

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 576-595 | Received 09 Apr 2021, Accepted 13 Jul 2021, Published online: 25 Aug 2021
 

Abstract

Peak stimulated growth hormone (GH) levels are known to decrease with increasing body mass index (BMI), possibly leading to overdiagnosis of GH deficiency (GHD) in children with overweight and obesity. However, current guidelines do not guide how to interpret the peak GH values of these children. This systematic review and meta-analysis aimed to study the effect of the BMI standard deviation score (SDS) on stimulated peak GH values in children, to identify potential moderators of this association, and to quantify the extent to which peak GH values in children with obesity are decreased. This systematic review was performed by the PRISMA guidelines. Medline, Embase, Cochrane, Web of Science, and Google Scholar databases were searched for studies reporting the impact of weight status on peak GH in children. Where possible, individual participant data was extracted and/or obtained from authors. Quality and risk of bias were evaluated using the Scottish Intercollegiate Guidelines Network (SIGN) checklists. The primary outcome was the association between peak GH values and BMI SDS. The pooled correlation coefficient r, 95% confidence interval (CI), and heterogeneity statistic I2 were calculated under a multilevel, random-effects model. In addition, exploratory moderator analyses and meta-regressions were performed to investigate the effects of sex, pubertal status, presence of syndromic obesity, mean age and mean BMI SDS on the study level. For the individual participant dataset, linear mixed-models regression analysis was performed with BMI SDS as the predictor and ln(peak GH) as the outcome, accounting for the different studies and GH stimulation agents used. In total, 58 studies were included, providing data on n = 5135 children (576 with individual participant data). Thirty-six (62%) studies had high, 19 (33%) medium, and 3 (5%) low risks of bias. Across all studies, a pooled r of −0.32 (95% CI −0.41 to −0.23, n = 2434 patients from k = 29 subcohorts, I2 = 75.2%) was found. In meta-regressions, larger proportions of males included were associated with weaker negative correlations (p = 0.04). Pubertal status, presence of syndromic obesity, mean age, and mean BMI SDS did not moderate the pooled r (all p > 0.05). Individual participant data analysis revealed a beta of −0.123 (95% CI −0.160 to −0.086, p < 0.0001), i.e. per one-point increase in BMI SDS, peak GH decreases by 11.6% (95% CI 8.3–14.8%). To our knowledge, this is the first systematic review and meta-analysis to investigate the impact of BMI SDS on peak GH values in children. It showed a significant negative relationship. Importantly, this relationship was already present in the normal range of BMI SDS and could lead to overdiagnosis of GHD in children with overweight and obesity. With the ever-rising prevalence of pediatric obesity, there is a need for BMI (SDS)-specific cutoff values for GH stimulation tests in children. Based on the evidence from this meta-analysis, we suggest the following weight status-adjusted cutoffs for GH stimulation tests that have cutoffs for children with normal weight of 5, 7, 10, and 20 µg/L: for overweight children: 4.6, 6.5, 9.3, and 18.6 µg/L; and for children with obesity: 4.3, 6.0, 8.6, and 17.3 µg/L.

Acknowledgments

The authors would like to thank Dr. Chiara Guzzetti, Dr. Sandro Loche, Dr. Ji-Eun Lee, and Dr. Aram Yang for providing additional information on their manuscript, and Elise Krabbendam, medical information specialist, for her help with the systematic literature search.

Disclosure statement

The authors report no conflict of interest.

Data availability statement

All data supporting the analyses in this paper are provided in the manuscript, Supplementary Material 1, and Supplementary Material 2, Individual Participant Dataset.

Additional information

Funding

This work was supported by the Elisabeth Foundation, a non-profit foundation supporting academic research under Grant ObesEcare.