Methods

A total of 15,524 patients (of whom 12,529 [81%] were men) with histories of CHD aged 45 to 74 years were screened from February 1990 to October 1992 for participation in the Bezafibrate Infarction Prevention (BIP) study. BIP was a placebo-controlled, secondary prevention randomized trial assessing the effect of bezafibrate on the risk for recurrent events and mortality. Institutional ethics committees at each of the participating centers and the central national committee approved the study.

Height and weight measurements were available for 12,466 men (99%) screened (including 2,851 of 2,854 patients who participated in the clinical trial ). Patients with total cholesterol ≤270 mg/dl (7.0 mmol/L), high-density lipoprotein (HDL) cholesterol ≤45 mg/dl (1.16 mmol/L), and triglycerides ≤300 mg/dl (3.39 mmol/L) on the first screening visit (9,170 men) received dietary consultation and were invited to the next screening visit. Long-term mortality data were obtained through July 2004 from the Israeli population registry (data were complete for 11,992 men [96.2%]). Data regarding diagnoses of cancer were obtained from the Israel National Cancer Registry, a population-based registry established in 1960. Since 1982, reporting to the registry has been mandatory by law and includes all medical facilities in the country.

Patients’ weight and height were measured during the first screening visit. BMI was calculated as the ratio between weight (in kilograms) and squared height (in meters). The definition of hypertension was based on self-report by patients and assessment by screening physicians. Diabetes was defined on the basis of self-report of the disease or treatment with hypoglycemic drugs. Patients who had quit smoking ≥1 month before screening were categorized as past smokers. Patients who smoked at the time of screening or had quit <1 before screening were categorized as smokers.

Functional capacity was classified according to the New York Heart Association classification. Metabolic syndrome was defined on the basis of the Adult Treatment Panel III report classification as ≥3 of the following: HDL cholesterol >40 mg/dl (1.04 mmol/L), triglycerides >150 mg/dl (1.69 mmol/L), blood pressure >135/85 mm Hg, and glucose >110 mg/dl (6.11 mmol/L), and replacing waist circumference criteria (not available) with BMI > 28 kg/m ² . BMI classification was based on World Health Organization criteria, with further division of the normal and overweight ranges. Because the study group included only 32 men with BMIs <18.5 kg/m ² , they were included in the lowest subgroup of the normal range (<20 kg/m ² ).

Glomerular filtration rate (ml/min/1.73 m ² ) was estimated using the formula derived by the Modification of Diet in Renal Disease (MDRD) study group and calculated as 186 × (serum creatinine [mg/dl] ^−1.154 ) × (age [years] ^−0.203 ) × 1.21 (if black). Serum creatinine was available for 6,279 men of 12,466, who were invited to the second screening visit.

For the purpose of multivariate hazard ratio estimation, the 23.00 to 24.99 kg/m ² BMI group was used as the reference group. This choice was based on previous reports from population studies that pointed to a BMI of about 25 kg/m ² as the nadir of the BMI-mortality risk association.

Blood samples, drawn after ≥12-hour fasting, were collected using standardized equipment and procedures. Serum analysis was carried out at a central laboratory using standard automated procedures with commercially available diagnostic kits (Boehringer-Mannheim GmbH, Mannheim, Germany). Accuracy and precision for lipid measurements were under periodic surveillance by the Centers for Disease Control and Prevention and National Heart, Lung, and Blood Institute’s Lipids Standardization Program and by the Wellcome-Murex Diagnostic Clinical Chemistry Quality Assessment Program. Internal quality control applied 2 levels of control sera (Precinor Lipid and Precipath Lipid; Boehringer-Mannheim) for lipids and lipoproteins. Internal quality control samples were run at the beginning of each shift, and ≥4 repeated runs were made during the analytic process.

Data were analyzed using SAS version 8.2 (SAS Institute Inc., Cary, North Carolina). Characteristics of patients are presented as frequencies or as mean ± SD unless otherwise specified, and were compared using chi-square tests for categorical variables and analysis of variance for normally distributed continuous variables. Triglyceride values, which were not normally distributed, are presented as geometric mean (95% confidence interval) and were compared using the nonparametric Kruskal-Wallis test.

Test of trend in mean was performed applying the CONTRAST statement with the SAS GLM procedure. For geometric means, the test was performed on the log-transformed values. Trend in proportions was assessed by the Mantel-Haenszel chi-square test. Direct adjustment using the entire group included in the analysis as the reference group was used for computation of age adjusted mortality rates per 1,000 patient-years by BMI groups.

The cumulative probability of mortality by BMI groups was calculated applying the Kaplan-Meier method. Curves were compared using the log-rank test.

The age- and multivariate-adjusted mortality hazard associated with each BMI stratum, compared with the 23.0 to 24.99 kg/m ² group, was estimated using a Cox proportional-hazards model. A fixed set of variables selected on the basis of previous knowledge was introduced into models. Variables included in the models were age, history of myocardial infarction, diabetes, peripheral vascular disease, smoking, chronic obstructive pulmonary disease (COPD), HDL cholesterol level (continuous), non-HDL cholesterol level (continuous), and systolic blood pressure. Participation in the clinical trial was also included in the model to account for possible differences due to the selection of patients for participation in the BIP study. To study possible interactions between risk factors and BMI, we ran the models separately for patients with or without the risk factor tested (omitting the stratification risk factor from the variable list included in the model). The significance of possible interaction was tested by running a model with interaction product terms of risk factor existence and BMI group in the model in addition to the variables listed previously. The predictive discrimination ability of each model was evaluated using a C-statistic corresponding to the area under a receiver-operating characteristic curve. C-statistics ranged from 0.63 to 0.68 for all models.

The validity of the proportional-hazards assumption was tested by running a model including BMI groups and time-dependent explanatory variables for each group to test the assumption of no time-dependent effect. No significant deviation from the proportional-hazards assumption was detected.

Results

Most of the 12,466 men with CHD included in the analysis had BMIs ranging from 23.0 to 29.99 kg/m ² (23.0 to 24.99 kg/m ² : 22%; 25.0 to 26.99 kg/m ² : 26%; and 27.0 to 29.99 kg/m ² : 26%). Ten percent had BMIs of 20.0 to 22.99 kg/m ² , and 14% were obese, with BMIs ≥30 kg/m ² . Only 148 men (1%) had BMIs <20 kg/m ² (32 had BMIs <18 kg/m ² ).

The characteristics of patients by BMI group are listed in Tables 1 and 2 . The mean age was 59.4 years in lean patients (BMI <20 kg/m ² ), 60.1 years in those with BMIs of 20 to 24.9 kg/m ² , and decreased linearly thereafter with increasing BMI (p for linear trend = 0.001). A number of risk factors were progressively more frequent in patients with higher BMIs. The increase in the prevalence of hypertension (p for trend <0.0001) was paralleled in measured blood pressure (systolic and diastolic), and the increasing frequency of diabetes (p for trend <0.0001) was paralleled by glucose level, ranging from 103 mg/dl (5.72 mmol/L) in lean patients to 124 mg/dl (6.88 mmol/L) in obese patients ( Table 2 ). Past smokers were monotonically more prevalent with higher BMI. Similar linear relations with BMI were noted for total cholesterol, triglycerides, and HDL cholesterol (inverse) ( Table 2 ). The proportion of patients with metabolic syndrome increased with increasing BMI alongside the trends noted for its components ( Table 1 ).

The median number of components of the metabolic syndrome ranged from 1 in patients with BMIs <20 kg/m ² (interquartile range 1 to 2) to 4 in obese patients. Other risk factors, particularly COPD, stroke history, and smoking at the time of screening, were most likely to be found in lean patients, followed by obese patients, than in patients in the middle BMI range (a J-shaped association).

No significant differences between subgroups were noted for history of previous atherosclerotic disease (myocardial infarction or stroke). However, although patients with BMIs <25 kg/m ² were as likely to be functionally impaired (New York Heart Association class ≥II), the frequency of functional impairment increased thereafter with increasing BMI. The frequency of cancer diagnosis before or within 6 months of screening was slightly higher in patients with BMIs <23.0 kg/m ² compared to those with BMIs ≥23.0 kg/m ² ( Table 1 ).

Patients were followed for a median period of 12 years (interquartile range 9.9 to 13.2), corresponding to a total of 128,995 patient-years. Figures 1 and 2 depict age-adjusted mortality rates per 1,000 patient-years for the entire group and by the existence of risk factors and BMI category, respectively. Age-adjusted rates in the entire group of men followed a U-shaped pattern, with the highest rates observed in lean and obese patients and the lowest risk in those with BMIs of 23.0 to 24.99 kg/m ² . The corresponding adjusted hazards in patients with BMIs of 20.0 to 22.99 or 25.0 to 26.99 kg/m ² were similar to the low-risk reference category ( Table 3 ). Further adjustment for additional possible confounders had little impact on these results, with only a slight attenuation of risk in the highest 2 BMI categories. After multivariate adjustment, the cumulative mortality risk was similar in all subgroups studied, in patients with BMIs of 20.0 to 29.99 kg/m ² ( Figure 3 ). Men with BMIs <23 kg/m ² had the worst survival probability over most of the follow-up period. Men who were obese at baseline (BMI ≥30 kg/m ² ) had similar survival to those with BMIs of 23 to 29.99 kg/m ² over the first years of follow-up but had an increasing disadvantage later on (hazard ratio for 12 years 1.28, 95% confidence interval 1.15 to 1.42).

Age-adjusted mortality rate per 1,000 patient-years (PY) by BMI class in 12,466 men with CHD.

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