Most studies examining the role of BMI on mortality in patients treated with percutaneous coronary intervention (PCI) have focused on the short-term effects,^6–10 while only a few studies examined the impact of BMI on long-term mortality.^11–14 While many studies have examined the obesity paradox, only a few studies explored the mechanisms of this phenomenon.^{4 15 16} A more aggressive lifestyle modification and optimisation of medical treatment may be a plausible reason for the enhanced survival in individuals who are obese at the time of coronary revascularisation.

Hence, the aims of this study were (1) to evaluate the effect of BMI on long-term mortality in a consecutive series of patients treated with PCI and (2) to determine whether a difference in the use of optimal medication at follow-up between the different BMI groups is a contributing factor for the obesity paradox.

The small size (n=35) of the underweight group precludes any reliable analyses and the group was therefore excluded. Patient baseline characteristics and clinical data according to the three BMI categories are shown in table 1. Obese patients tended to be younger, and although the overall population was predominantly comprised of men, gender was more equally represented in the obese group. Dyslipidaemia, hypertension and diabetes mellitus were more common in the obese group, while current smoking was more prevalent in the normal weight group.

The different types of medication used at follow-up according to the three BMI categories are shown in table 2. Obese patients tended to use more β blockers and ACE inhibitors compared with the normal weight group resulting in more optimal medical treatment at follow-up in the obese group.

Univariate and multivariate associations between BMI and long-term outcome are presented in table 3. Clinical characteristics that had a significant association on multivariate analysis were age, gender, diabetes mellitus, multivessel disease and LVEF. In univariate analyses, overweight and obese patients had more favourable long-term outcomes in terms of all-cause death (HR: 0.72, 95% CI 0.63 to 0.82 and HR: 0.61, 95% CI 0.51 to 0.74, respectively) and cardiac death (HR: 0.77, 95% CI 0.63 to 0.94 and HR: 0.73, 95% CI 0.56 to 0.95, respectively). (table 3, figure 1) Overweight patients also showed a lower risk for the composite end point of cardiac death and non-fatal MI (HR: 0.84, 95% CI 0.71 to 0.99). Most of these differences remained significant after multivariate adjustments for all baseline characteristics. However, the lower incidence of cardiac death in obese patients did not remain significant after multivariate analysis. Moreover, when adjusting for baseline characteristics and optimal medication at follow-up, overweight and obese patients had a equal long-term survival (HR: 0.90, 95% CI 0.72 to 1.12 and HR: 1.07, 95% CI 0.80 to 1.43, respectively) compared with the normal weight group.

In a model with BMI as a continuous variable, one unit increase in BMI showed HR 0.95 (95% CI 0.93 to 0.97), p<0.001, adjusted HR 0.96 (95% CI 0.95 to 0.98), p<0.001. When OMT was introduced in the model, the relation did not remain significant: HR 1.00 (95% CI 0.98 to 1.03), p=0.81.

For the whole population, OMT had HR 0.63, for the normal population 0.60, for the overweight 0.64 and for the obese 0.69.

In a landmark analysis at 2 years, multivariate predictors of late outcome included gender, BMI, age, hypercholesterolaemia, diabetes mellitus, family history of CAD, previous coronary artery bypass graft surgery and LVEF.

The introduction of OMT in the 2-year landmark Cox regression model also altered the significance of BMI from overweight versus normal (HR: 0.806, 95% CI 0.678 to 0.960, p=0.015) and obese versus normal (HR: 0.840, 95% CI 0.661 to 1.067, p=0.152) in the model without OMT to overweight versus normal (HR: 0.911, 95% CI 0.722 to 1.149, p=0.429) and obese versus normal (HR: 1.122, 95% CI 0.819 to 1.537, p=0.472) in the model with OMT.

In the current study, we found that the inverse relation between BMI and mortality persists during long-term follow-up of patients treated with PCI. The overweight and obese groups showed almost 30% lower mortality than patients with a normal BMI.

In this population, crude death rate was 17% during a mean follow-up of 6 years. Cardiac deaths were responsible for 43% of all deaths. As expected, comorbid conditions (eg, dyslipidaemia, hypertension and diabetes mellitus) were more prominent in the obese population.

Several other studies have shown a paradoxical effect of moderate obesity on outcome after PCI.^6–12 They also found significantly worse outcomes in patients with a BMI >30 or <20 kg/m². These results were echoed in a large meta-analysis by Romero-Corral et al²¹ who included studies with a total of 250 152 patients undergoing PCI or coronary artery bypass grafting. In fact, overweight and obese patients with coronary heart disease had a lower risk for total and cardiovascular mortality compared with underweight and normal weight patients with coronary heart disease. Our study results are in line with these findings; however, while the duration of the follow-up period in most of these studies was restricted to 1 year, that period was extended to 6 years in the current study.

The reason for the paradoxic U- or J-shaped relation between BMI and adverse outcome is not yet understood. Several explanations for this phenomenon have been suggested. Peripheral adiposity confers cardiovascular benefits due to the secretion of adiponectin, which has anti-inflammatory, insulin-sensitising and antiatherogenic effects. Also, these patients seem to have a lower total body fat content, which implies that subcutaneous body fat is relatively ‘inert’ in metabolic and inflammatory/mediation terms.²² Furthermore, it has been suggested that hypercholesterolaemia and high levels of serum low-density lipoproteins associated with obesity serve a scavenging action against unbound circulating lipopolysaccharides with consequent anti-inflammatory response and improved long-term outcome.²³

Studies of the BMI–mortality relationship may suffer from several sources of bias and confounding which can explain the U- or J-shaped relationship in some of these studies. Reverse causality can be present if thin people are disproportionately more susceptible to disease and suffer worse health outcomes than those with higher BMI levels. Another important consideration is potential overcontrolling by adjustment for cardiovascular risk factors associated with increased weight.^{24 25} If BMI contributes to the development of a risk factor, statistical adjustment for such risk factors could be misleading with regard to the contribution of BMI. Besides these methodological and conceptual issues, there are several potential modifiers of the BMI–mortality association. This association may vary according to variables such as sex, ethnicity, age and body fat distribution. Another major problem with BMI is that it is a surrogate, measuring total body mass. One explanation for a U-shaped relationship between BMI and mortality is that calculated BMI measures do not differentiate between fat and fat-free mass, which have opposite effects on health and longevity.²⁶

In this study, the impact of differences in optimal medication, one of the implicated mechanisms of the obesity paradox, was explored. Strikingly, we did notice that optimal medical treatment was more common in the high BMI groups, likely a reflection of the higher incidence of risk factors in these subgroups. Our study supports the hypothesis that part of the obesity paradox may be mediated by the earlier and more complete secondary preventive medical treatment in the high BMI groups who present for revascularisation at a younger age.

Aspirin, statin, β blocker and ACE inhibitor use have all shown significant reduction in mortality in previous studies.²⁷ In our study cohort, patients with a higher BMI were more often on β blocker and ACE inhibitor treatment when compared with subjects with normal weight. The positive effect on survival in the long-term of such drug treatment is an important contributor to the apparent survival advantage that is observed in patients with a high BMI. Thus, at least in part, OMT explains the obesity paradox. Moreover, our study highlights the importance of optimising medical treatment and encouraging compliance even in patients with good symptom control achieved after percutaneous revascularisation for CAD.

The beneficial effect of OMT in the higher BMI group may have been influenced by a change in lifestyle. The change in BMI over time and measures other than OMT such as exercise and dieting may have contributed to the improved long-term prognosis in these patients.

Baseline clinical characteristics of patients with a high BMI suggest that these patients have a higher risk profile compared with those with normal or low BMI. Clearly, patients with high BMI undergoing PCI have a more optimal medical treatment. Whether more active screening related to the obesity and cardiovascular risk factors is leading to a more timely and aggressive pharmacological and/or mechanical intervention in this population remains to be established.

In an era of stent implantation as a mainstream treatment for CAD, stent-related factors may also influence the impact of BMI on clinical outcome. Although in our study we were not interested in stent-related outcomes such as stent thrombosis and stent restenosis with target lesion revascularisation, these two may play a role in hard end points especially in the long term. Patients with a high BMI have been shown to have higher rates of target vessel revascularisation possibly reflecting more aggressive neointimal hyperplasia in the stent, progressive disease in the treated vessel or a combination of the two.¹⁴ The coexisting cardiovascular risk factors (hypertension, dyslipidaemia and particularly diabetes mellitus) in these patients are thought to play a major role in these mechanisms of target vessel failure. Stent thrombosis has an even more direct effect on hard end points since it causes an MI and sometimes sudden cardiac death even before presentation. Patients with a high BMI are thought to be at a higher risk possibly due to suboptimal dosing of dual antiplatelet treatment.¹⁴ Thus, although stent-related factors can potentially influence the relation of BMI and outcome, the mechanisms implicated do not support the obesity paradox that we observe.

The current study has a number of limitations that need to be highlighted. Data regarding waist circumference and waist/hip ratio that measures abdominal obesity were not routinely available. A more precise differentiation between peripheral adiposity and central compartment adiposity would have served to support the suggested hypothetical explanation about the role of a high BMI in prolonging survival in our patient population. Regarding the detection of our end points, a number of non-fatal and/or asymptomatic or silent MIs might have not been reported, especially if these occurred outside the hospital. Noting that in patients who have a contraindication to a treatment option (eg, β blockers), the lack of benefit from this treatment is not physician induced but determined by the patient's condition, which may itself put the latter in a higher risk category. This will in the future need to be addressed in a prospective study. Clinical measurement, rather than self-reported height and weight, would have provided a more accurate BMI data, eliminating any possible bias. OMT was defined according to patient medication at first time of contact but no information of duration or compliance of such treatment was available. Objective parameters of lifestyle modifications and risk factor control would shed light on the importance of such an intervention on clinical outcome.