Impact of weight gain on the evolution and regression of prediabetes: a quantitative analysis

Eur J Clin Nutr. 2017 Feb;71(2):206-211. doi: 10.1038/ejcn.2016.118. Epub 2016 Jul 13.

Abstract

Background/objectives: The quantitative impact of weight gain on prediabetic glucose dysregulation remains unknown; only one study quantitated the impact of weight loss. We quantified the impact of weight gain on the evolution and regression of prediabetes (PDM).

Subjects/methods: In 4234 subjects without diabetes, using logistic regression analysis with a 4.8-year follow-up period, we analyzed the relationship between (1) δBMI (BMIfollow-up-basal) and the progression from normal glucose regulation (NGR) to PDM or diabetes, and (2) δBMI and the regression from PDM to NGR.

Results: Mean (±s.d.) δBMI was 0.17 (±1.3) kg/m2 in subjects with NGR and δBMI was positively and independently related to progression (adjusted odds ratio (ORadj) (95% CI), 1.24 (1.15-1.34), P<0.01). Mean (±s.d.) δBMI was -0.03 (±1.25) kg/m2 in those with PDM and δBMI was negatively related to the regression (ORadj, 0.72 (0.65-0.80), P<0.01). The relation of δBMI to the progression was significant in men (ORadj, 1.42 (1.28-1.59), P<0.01) but not in women (ORadj, 1.05 (0.94-1.19), P=0.36). Also, the negative impact of δBMI on the regression was significant only in men (men, ORadj, 0.65 (0.57-0.75), P<0.01; women, ORadj, 0.94 (0.77-1.14), P=0.51).

Conclusions: In Japanese adults, an increase in the BMI by even 1 kg/m2 was related to 24% increase in the risk of development of PDM or diabetes in NGR subjects and was related to 28% reduction in the regression from PDM to NGR. In women, we did not note any significant impact of weight gain on the evolution or regression of PDM.

Publication types

  • Evaluation Study

MeSH terms

  • Adult
  • Blood Glucose / analysis
  • Blood Glucose / metabolism
  • Body Mass Index
  • Disease Progression*
  • Female
  • Follow-Up Studies
  • Glucose Tolerance Test
  • Humans
  • Logistic Models
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Odds Ratio
  • Prediabetic State / blood
  • Prediabetic State / physiopathology*
  • Retrospective Studies
  • Risk Factors
  • Sex Factors
  • Weight Gain*

Substances

  • Blood Glucose