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. 2019 Aug 20;8(16):e013011.
doi: 10.1161/JAHA.119.013011. Epub 2019 Aug 8.

Refining the Association Between Body Mass Index and Atrial Fibrillation: G-Formula and Restricted Mean Survival Times

Affiliations

Refining the Association Between Body Mass Index and Atrial Fibrillation: G-Formula and Restricted Mean Survival Times

Sarah C Conner et al. J Am Heart Assoc. .

Abstract

Background Previous studies assessing the association between body mass index (BMI) and atrial fibrillation (AF) did not account for time-varying covariates, which may be affected by previous BMI. We illustrate how the g-formula can account for time-varying confounding. Methods and Results We included 4392 participants from the Framingham Heart Study who were AF free at ages 45 to 55 years, and followed them for up to 20 years. We estimated hazard ratios (HRs) comparing time-varying nonobese versus obese with Cox models. We used the g-formula to compare nonobese versus obese and 10% annual decrease in BMI (until normal weight is reached) versus natural course. We estimated HRs and differences in restricted mean survival times, the mean difference in time alive and AF free. We adjusted for sex, age, and time-varying risk factors. Cox models indicated that nonobese participants had a decreased rate of AF versus obese participants (HR, 0.83; 95% CI, 0.72-0.97). G-formula analyses comparing everyone had they been nonobese versus obese yielded stronger associations (HR, 0.73; 95% CI, 0.58-0.91). The restricted mean survival time was 19.22 years had everyone been nonobese and 19.03 years had everyone been obese (difference, 2.25 months; 95% CI, -0.66 to 5.16). When assessing a 10% annual decrease in BMI, the association was weaker (HR 0.96; 95% CI, 0.86-1.08). Conclusions Decreased BMI was associated with a lower rate of AF after accounting for time-varying covariates that depend on previous exposure using the g-formula, which Cox models cannot accommodate. Absolute measures like the restricted mean survival time difference offer context to relative measures of association.

Keywords: atrial fibrillation; body mass index; epidemiology; survival analysis; time‐varying covariate.

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Figures

Figure 1
Figure 1
Directed acyclic graph of body mass index, other time‐varying covariates, and atrial fibrillation. The directed acyclic graph displays repeated measures at years k−1 and k. BMI k denotes the exposure, body mass index (BMI), at year k. Lk denotes confounders at year k (eg, systolic blood pressure). AF denotes the outcome, new‐onset atrial fibrillation (AF). Arrows indicate associations (eg, the association of body mass index [BMI] and incident AF). Adjustment for intermediate variables Lk (red) in a Cox model will block the path between BMI k−1 and AF (green), which prevents us from observing the full association. However, g‐methods can accommodate this scenario. If BMI k−1 did not cause AF through Lk (the green arrows were not present), then Lk would not be an intermediate variable and adjustment for Lk would not block the association of BMI k−1 and AF.
Figure 2
Figure 2
Multiple imputation and interpolation process. X completely measured, ▲ incomplete covariates, ▼ unattended examination, ● covariates multiply imputed, ■ covariates linearly interpolated. Examinations took place approximately every 2 years in the Original cohort and every 4 to 8 years in the Offspring. Covariates of interest include body mass index, smoking, systolic blood pressure, diastolic blood pressure, antihypertensive treatment, diabetes mellitus, heart failure, and myocardial infarction. [Correction added on 12 August 2019, after first online publication: The bottom panel of Figure 2 was removed.]
Figure 3
Figure 3
Kaplan–Meier curves of g‐formula survival probabilities comparing simulated populations under body mass index (BMI) interventions. AF indicates atrial fibrillation.

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