Accounting for time-varying exposures and covariates in the relationship between obesity and diabetes: analysis using parametric g-formula.

Abstract

Background: Previous studies investigating the association between obesity and diabetes often did not consider the role of time-varying covariates affected by previous obesity status. This study quantified the association between obesity and diabetes using parametric g-formula.

Methods: We included 8924 participants without diabetes from the Korean Genome and Epidemiology Study-Ansan and Ansung study(2001-2002)-with up to the seventh biennial follow-up data from 2015 to 2016. Obesity status was categorised as normal (body mass index (BMI) <23.5 kg/m²), overweight (23.5-24.9 kg/m²), obese 1 (25.0-27.4 kg/m²) and obese 2 (≥27.5 kg/m²). Hazard ratios (HRs) comparing baseline or time-varying obesity status were estimated using Cox models, whereas risk ratio (RR) was estimated using g-formula.

Results: The Cox model for baseline obesity status demonstrated an increased risk of diabetes in overweight (HR 1.85; 95% CI=1.48-2.31), obese 1 (2.40; 1.97-2.93) and obese 2 (3.65; 2.98-4.47) statuses than that in normal weight status. Obesity as a time-varying exposure with time-varying covariates had HRs of 1.31 (1.07-1.60), 1.55 (1.29-1.86) and 2.58 (2.14-3.12) for overweight, obese 1 and obese 2 statuses. Parametric g-formula comparing if everyone had been in each obesity category versus normal over 15 years showed increased associations of RRs of 1.37 (1.34-1.40), 1.78 (1.76-1.80) and 2.42 (2.34-2.50).

Conclusions: Higher BMI classification category was associated with increased risk of diabetes after accounting for time-varying covariates using g-formula. The results from g-formula were smaller than when considering baseline obesity status only but comparable with the results from time-varying Cox model.