Journal of Cardiovascular Nursing:
High School Body Mass Index and Body Mass Index at Entry to a Cardiac Disease Risk Prevention Clinic and the Association to All-Cause Mortality and Coronary Heart Disease: A PreCIS Database Study
Gambino, Katherine K. MSN, CRNP; Zumpano, Julia RD; Brennan, Danielle M. MS; Hoogwerf, Byron J. MD
Katherine K. Gambino, MSN, CRNP Nurse Practitioner, Preventive Cardiology and Rehabilitation and Nurse Manager, Women's Cardiovascular Center, Cleveland Clinic, Ohio.
Julia Zumpano, RD Registered Dietician, Preventive Cardiology and Rehabilitation and Women's Cardiovascular Center, Cleveland Clinic, Ohio.
Danielle M. Brennan, MS Senior Biostatistician, Department of Cardiovascular Medicine, Cleveland Clinic, Ohio.
Byron J. Hoogwerf, MD Staff Emeritus, Preventive Cardiology and Rehabilitation and Women's Cardiovascular Center, Cleveland Clinic; Endocrinology, Diabetes and Metabolism, Cleveland Clinic, Ohio.
Corresponding author Katherine K. Gambino, MSN, CRNP, Cleveland Clinic, Preventive Cardiology and Rehabilitation, Desk Jb1, 9500 Euclid Ave, Cleveland, OH 44195 (firstname.lastname@example.org).
Objective: To investigate overweight/obese patients (body mass index [BMI], ≥25 kg/m2) at entry to a preventive cardiology clinic who had a high school (HS) BMI of 25 kg/m2 or greater versus those with a BMI of less than 25 kg/m2 to determine coronary heart disease (CHD) prevalence, all-cause mortality.
Methods: Patients (n = 4,597) who had a BMI of 25 kg/m2 or greater at the time of initial visit to the prevention clinic were asked to report their weight at graduation from HS. Patients with BMI of 25 kg/m2 or greater in HS (n = 1,285) were compared with patients (n = 3,312) with a BMI of less than 25 kg/m2 in HS. Prevalent CHD was assessed at entry. Patient mortality was assessed using the Social Security Death Index for a maximum of 7 years after the initial visit.
Results: Mean/median values for most CHD risk factors were higher in the group with an HS BMI of 25 kg/m2 or greater, with the exception of low-density lipoprotein level (120 vs 132 mg/dL; P < .001), Lipoprotein (a) level (16 vs 19 mg/dL; P = .003), and systolic blood pressure (126 vs 128. 3 mm Hg; P < .001). Patients with an HS BMI of 25 kg/m2 or greater had a higher mean BMI at initial visit (33.9 vs 30.1; P < .001) and hemoglobin A1c (6.8% vs 6.3%; P < .001) and glucose concentrations (93 vs 91 mg/dL; P = .004), with a lower mean high-density lipoprotein level (43.2 vs 46.5 mg/dL; P < .001) as well as greater prevalence of smoking (16.2% vs 11.4%; P < .001), diabetes mellitus (32.4% vs 21.8%; P < .001), CHD (47.1% vs 43%; P = .01), and specifically myocardial infarction (25.8% vs 21.1%; P = .001). Fibrinogen and urine albumin-to-creatinine levels were elevated. After adjusting for risk factors, an HS BMI of 25 kg/m2 or greater was associated with a 21% higher prevalence of CHD (odds ratio, 1.20; P = .027). However, an HS BMI of 25 kg/m2 or greater was not a significant predictor of 7-year mortality (hazard ratio, 1.03; P = .84).
Conclusion: Patients with an HS BMI of 25 kg/m2 or greater had more CHD risk factors compared with those with an HS BMI of less than 25 kg/m2. Prevalence of CHD was also significantly higher in this group. However, an HS BMI of 25 kg/m2 or greater was not a significant predictor of mortality.
The prevalence of obesity is increasing in the United States as well as worldwide.1-4 Several epidemiological studies have demonstrated that obesity is associated with increased mortality from coronary heart disease (CHD) as well as other diseases including malignancy.5 Obesity is associated with a cluster of well-known CHD risk factors including dyslipidemia, hypertension, and dysglycemia (impaired glucose tolerance and diabetes mellitus [DM]) as well as emerging risk factors such as cytokines, adhesion molecules, and adipokines (such as adiponectin).6 There are few data on whether the duration of obesity affects medical outcomes such as mortality.
We wished to investigate overweight/obese patients, body mass index (BMI) of 25 kg/m2 or greater at entry to a preventive cardiology clinic, to determine the effect of high school (HS) BMI of 25 kg/m2 or greater versus less than 25 kg/m2 on CHD prevalence, mortality, and traditional and nontraditional risk factors for CHD. We regularly ask about HS weight in our preventive cardiology clinic and have documented weight at the time of entry visits; the database from this clinic afforded an opportunity to address these questions.
In review of the literature, there is a well-known association of obesity at an early age with the presence of multiple risk factors and risk factors related to the metabolic syndrome.7-10 Increased prevalence of future cardiovascular disease (CVD) associated with higher BMI at a younger age has also been reported. Falkstedt et al11 followed BMI, smoking, and blood pressure in Swedish men starting at around age 18 years (years 1969-1970) at the time of entrance into military service to the year 2004. Body mass index was found to be an independent predictor of stroke and coronary artery disease before the age of 55 years, independent of other risk factors. One study assessed the relationship of elevated BMI as well as the change in BMI between adolescence into young adulthood and used common carotid intima-media thickness as a measure of cardiovascular risk.12 Those with the largest increase in BMI as well as those who remained chronically overweight had had the thickest carotid intima media measurement.
In the past literature, some research has shown elevated BMI at an early age to be a predictor of mortality. Other research has not consistently shown this relationship, or it has been present with only certain BMI groups or only with CVD mortality and not always with all-cause mortality.13 In a Norwegian study by Engeland et al,14 BMI was assessed starting in adolescence and followed for an average of 10 or more years. These investigators concluded that BMI in adolescence seemed to be predictive of both mortality and adult obesity. Jeffreys et al15 followed up 629 men in a cohort study from an average age of 22 years for 35 years. Cardiovascular disease mortality was strongly associated with BMI in young adulthood, but the association was weaker when looking at BMI in mid adulthood. Using data from the Nurses Health Study II, van Dam et al16 looked at more than 100,000 women, assessed HS weight by recall, and found an association between moderately elevated BMI at age 18 years and premature death in women of younger and middle age. In 2 large reviews, one of cohort studies and the other a meta-analysis of 26 observational studies, mortality from all causes including CVD was assessed, and certain BMI ranges associate with higher mortality. In the review of cohort studies, Romero-Corral et al17 found a BMI of less than 20 kg/m2 to be associated with higher rate of total mortality and cardiovascular mortality, and a BMI of greater than 35 kg/m2 associated with higher CVD mortality, but not all-cause mortality. Those with a BMI of between 25 and 29 kg/m2 actually had the lowest risk of both. McGee and the Diverse Populations Collaboration,18 in a meta-analysis, also found an increased mortality in the heaviest group of individuals; those having a BMI of greater than 30 kg/m2 had relative risks of 1.22 for total mortality, 1.57 for CHD death, and 1.48 for CVD mortality when compared with those with a BMI between 18.5 and 24.9 kg/m2. In an older nested case-control study of the Dutch 1932 birth cohort, mortality from coronary artery disease was assessed in relation to BMI.19 More than 78,000 men were followed up over 32 years. The mortality from CHD was found to be the highest in the group with the highest BMI. There is also a comment from Kiess et al20 in their discussion, "Clinical Aspects of Obesity in Childhood and Adolescence," stating, "An increased risk of death from CVD in adults has been found in subjects whose BMI had been greater than the 75th percentile as adolescence." Overall, the research related to increased BMI at an early age and mortality is not entirely consistent.
The Preventive Cardiology Information Systems (PreCIS) database is composed of information from more than 5,000 patients referred or self-referred to the Cleveland Clinic Preventive Cardiology Program for primary or secondary prevention of arterial sclerotic CVD. This is a physician and nurse practitioner-run clinic. At the time of the baseline visit, demographic information, medical history, and laboratory data were obtained and physical examination was performed, and data were entered into an electronic medical record that downloads to the corresponding database. Baseline history included a query about HS weight. All laboratory values were obtained within 30 days of the initial visit and after a 12-hour fast. Waist circumference measurements were obtained in standardized fashion, according to the National Institutes of Health guidelines.21 Patients reporting a history of diabetes and/or use of glycemic medications were identified as having diabetes. Likewise, patients reporting a history of hypertension and/or blood pressure medication use were defined as having hypertension. Blood pressure values consist of an average between 3 blood pressure measurements taken at the time of the visit. Patients who were actively smoking at baseline visit were designated as smokers. Fasting low-density lipoprotein (LDL) values are routinely calculated using the Friedwald equation or direct determination if triglyceride levels are greater than 300 mg/dL.13
The PreCIS database is an extensive database that houses patient data for statistical analysis for research and quality purposes. The data contained include demographic data, laboratory values, risk factor information, CVD events, medical history, symptoms, medications, vital signs, and height, weight, and waist measurements. Data collected are reviewed and updated on an ongoing basis to stay current with new procedures, markers, and medications. All exported patient data are deidentified. The Cleveland Clinic institutional review board reviews and approves the PreCIS database annually.
Patients included in the study were seen for their entry visit between January 1, 1995, and September 25, 2006.
Patients with an entry BMI of 25 kg/m2 or greater were divided into 2 groups based on HS BMI of 25 kg/m2 or greater or HS BMI of less than 25 kg/m2. Demographic and baseline characteristics are presented as means (SDs) or medians and interquartile ranges for continuous variables, and as percentages for categorical variables. Comparisons between the patients with an HS BMI of 25 kg/m2 or greater versus less than 25 kg/m2 were made using Student t test for the continuous variables (or Wilcoxon rank sum for non-normally distributed data) and the χ2 test for categorical data.
Odds ratios and their 95% confidence intervals (CIs) were calculated using logistic regression to assess the relationship of HS BMI of 25 kg/m2 or greater versus less than 25 kg/m2 to the prevalence of CHD. The vital status of the patients in our cohort was determined using the Social Security Death Index. Mortality data were followed through 7 years for all time-to-event analyses. Kaplan-Meier methods were used to estimate 7-year mortality rates and log-rank P values were generated to test the estimates in the 2 HS BMI groups. Hazard ratios (HRs) and 95% CIs were generated from a multivariable model using Cox proportional hazards models to assess the risk of death in the patients with an HS BMI of 25 kg/m2 or greater versus less than 25 kg/m2. Variables used for adjustment in the multivariable models for the prevalence of CHD and death were selected from a bootstrap analysis in which 300 models were generated. The variables that entered the models more than 50% of the time were considered for the final model and remained if P < .05.
All analyses were performed using SAS 9.1 (SAS Inc, Cary, North Carolina). All P's ≤.05 were considered to be statistically significant.
Clinical characteristics of patients with HS BMIs of less than 25 kg/m2 and 25 kg/m2 or greater based on self-report of HS weight are shown in Table 1. The total number of patients with an HS BMI of less than 25 kg/m2 were slightly older, and more were male. Racial differences were seen between the 2 groups, with a majority of both groups being white. In the patients with an HS BMI of 25 kg/m2 or greater, history of DM was significantly greater.
Patients with an HS BMI of less than 25 kg/m2 had a higher systolic blood pressure and lower mean body weight, BMI, waist measurements, and percentage of smokers. Patients with an HS BMI of less than 25 kg/m2 had higher total cholesterol, high-density lipoprotein (HDL), LDL, and non-HDL levels and slightly lower triglyceride levels. In the patients with an HS BMI of 25 kg/m2 or greater, glucose and hemoglobin A1c were higher. These patients also had lower Lp(a) and a higher fibrinogen and urine albumin-to-creatinine ratio.
In those with an HS BMI of 25 kg/m2 or greater, there was a greater prevalence of myocardial infarction and CHD.
Prevalence of CHD
The patients with an HS BMI of 25 kg/m2 or greater were associated with a 18% greater prevalence of CHD than patients with an HS BMI of less than 25 kg/m2 (odds ratio, 1.18; 95% CI, 1.04-1.34; P =.013). After adjustment for other significant associations of CHD (age, sex, baseline weight, waist circumference, HDL, diastolic blood pressure, history of hypertension, lipid abnormality, CVD, and peripheral vascular disease, and education level), an HS BMI of 25 kg/m2 or greater was still associated with greater CHD prevalence (HR, 1.21; 95% CI, 1.02-1.42; P =.027; Table 2).
Figure 1 displays the Kaplan-Meier mortality curves for the HS BMI groups. There was no difference in 7-year death in patients with an HS BMI of 25 kg/m2 or greater compared with an HS BMI of less than 25 kg/m2 (8.9% vs 8.1%; P = .43). This result was confirmed in a multivariable model adjusting for predictors of mortality (age, sex, baseline weight, waist circumference, DM, hyperlipidemia, CVD, myocardial infarction, peripheral vascular disease, African American race, current smokers, LDL and log transformation of triglycerides). The adjusted HR for an HS BMI of 25 kg/m2 or greater compared with an HS BMI of less than 25 kg/m2 was 1.03 (95% CI, 0.75-1.42; P = .84; Table 3).
CHD, Diabetes Prevalence, and Mortality by Weight Gain
After the prespecified analyses were completed, we proposed and completed analyses of the effects of weight gain for each of the HS weight groups (Table 4). The HS BMI of less than 25 kg/m2 group had the highest prevalence of CHD (56.8%) in the patients with the lowest weight gain compared with the other 3 groups (not statistically significant). An HS BMI of 25 kg/m2 or greater also had the highest prevalence of CHD (56.8%) in the patients with the lowest weight gain (P = .003).
By contrast, DM prevalence was highest in the group with a weight gain of 25 kg or greater compared with the group with a weight gain of less than 5 kg for both the group with an HS BMI of less than 25 kg/m2 (22.4%; P < .001) and the group with an HS BMI of 25 kg/m2 or greater (32.6%; P = .003). In both HS BMI of less than 25 kg/m2 and HS BMI of 25 kg/m2 or greater, 7-year mortality was not different across the weight gain groups.
The prevalence of obesity and specifically obesity in adolescents has been increasing over the past 2 decades. Obesity at an early age has been shown in the past literature to be associated with the presence of multiple risk factors and risk factors related to the metabolic syndrome.7-10 This is consistent with our study where those with an HS BMI of 25 kg/m2 or greater were found to be a much higher-risk group (Table 1). Therefore, of interest is the association of HS weight with CHD prevalence and mortality. Our study addresses this concept, demonstrating a significant association between HS weight and CHD prevalence. This has also been demonstrated previously in the literature.11,12 Even after adjustment for traditional, known risk factors, this association remained. In our study, we did not find having an HS BMI of 25 kg/m2 or greater to be a direct predictor of all-cause mortality.
The analyses of the effects of weight gain on CHD prevalence and DM prevalence are most striking for the amount of weight gain from HS to clinic visit in both groups. In the HS BMI of less than 25 kg/m2, 79% of patients gained more than 15 kg, and similarly in the HS BMI of 25 kg/m2 or greater, 48% of patients gained more than 15 kg. In addition, CHD was found to be more prevalent in both HS BMI groups with minimal weight gain (<5kg). This observation is not easy to explain, although the number of patients in the group that had a weight gain of less than 5 kg is small and the differences in CHD prevalence across other weight gain groups are similar. The simplest interpretation of these data is that HS BMI of 25 kg/m2 or greater is associated with much greater risk for CHD than HS BMI of less than 25 kg/m2 (Table 2) and that marked weight gain (eg, >25 kg vs modest weight gain of 5-25 kg) over the next 3 decades does little to increase CHD prevalence. The observation of increased prevalence of CHD and DM in the group with a BMI of 25 kg/m2 or greater suggests that there would be a significant benefit to targeting risk factors especially in the presence of obesity and efforts to prevent obesity and maintain normal body weight throughout HS.
The following limitations to this study should be noted. The population was taken from a cardiac prevention clinic, in which patients are at a higher risk for CHD, presenting with multiple risk factors, or a large percentage (55%) already having a diagnosis of CVD. This limits the ability to generalize results to other observational cohort populations, but our study cohort is quite typical of many high-risk prevention clinics. This retrospective review used HS weight measurements that were self-reported and not measured. Although self-report data may not be entirely accurate, the magnitudes of weight change from HS to clinic entry likely mitigate reporting variation of a couple of kilograms.22,23 The height measurement taken at the initial prevention visit was used to determine HS BMI, with the assumption that height is unchanged since HS. Since we have a middle-aged population, height loss with aging is not a major concern. Weight measurements were taken at clinic visits, so the exact time of weight gain or changes in weight gain are not known. The population had a greater percentage of men at 61.5% than women, who accounted for 38.5%, which may provide skewed results in regard to sex.
Conclusion/Implications for Practice
The data from our study strongly suggest that efforts at weight control in HS may be important to reduce the prevalence of CHD and DM. In addition, using HS weight as a risk assessment tool may provide insight to a higher-risk population of patients who warrant more aggressive treatment.
No caption available...Image Tools
1. Ford ES, Giles WH, Mokdad AH. Increasing prevalence of the metabolic syndrome among u.s. Adults. Diabetes Care
2. Mokdad AH, Ford ES, Bowman BA, et al. Diabetes trends in the U.S.: 1990-1998 [see comment]. Diabetes Care
3. Mokdad AH, Bowman BA, Ford ES, Vinicor F, Marks JS, Koplan JP. The continuing epidemics of obesity and diabetes in the United States. JAMA
4. Mokdad AH, Ford ES, Bowman BA, et al. The continuing increase of diabetes in the US.[comment]. Diabetes Care
5. Pischon T, Nothlings U, Boeing H. Obesity and cancer. Proc Nutr Soc
6. Mokdad AH, Ford ES, Bowman BA, et al. Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA
7. Hulanicka B, Lipowicz A, Koziel S, Kowalisko A. Relationship between early puberty and the risk of hypertension/overweight at age 50: evidence for a modified Barker hypothesis among Polish youth. Econ Hum Biol
8. Hulman S, Kushner H, Katz S, Falkner B. Can cardiovascular risk be predicted by newborn, childhood, and adolescent body size? An examination of longitudinal data in urban African Americans. J Pediatr
9. Sinaiko AR, Donahue RP, Jacobs DR Jr, Prineas RJ. Relation of weight and rate of increase in weight during childhood and adolescence to body size, blood pressure, fasting insulin, and lipids in young adults. The Minneapolis Children's Blood Pressure Study. Circulation
10. Srinivasan SR, Myers L, Berenson GS. Changes in metabolic syndrome variables since childhood in prehypertensive and hypertensive subjects: the Bogalusa Heart Study [see comment]. Hypertension
11. Falkstedt D, Hemmingsson T, Rasmussen F, Lundberg I. Body mass index in late adolescence and its association with coronary heart disease and stroke in middle age among Swedish men. Int J Obes
12. Oren A, Vos LE, Uiterwaal CS, Gorissen WH, Grobbee DE, Bots ML. Change in body mass index from adolescence to young adulthood and increased carotid intima-media thickness at 28 years of age: the Atherosclerosis Risk in Young Adults study. Int J Obes Relat Metab Disord
13. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem
14. Engeland A, Bjorge T, Tverdal A, Sogaard AJ. Obesity in adolescence and adulthood and the risk of adult mortality. Epidemiology
15. Jeffreys M, McCarron P, Gunnell D, McEwen J, Smith GD. Body mass index in early and mid-adulthood, and subsequent mortality: a historical cohort study. Int J Obes Relat Metab Disord
16. van Dam RM, Willett WC, Manson JE, Hu FB. The relationship between overweight in adolescence and premature death in women [see comment] [summary for patients in Ann Intern Med
. 2006;145(2):I34; PMID: 16847287]. Ann Intern Med
17. Romero-Corral A, Montori VM, Somers VK, et al. Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systematic review of cohort studies [see comment]. Lancet
18. McGee DL and the Diverse Populations Collaboration. Body mass index and mortality: a meta-analysis based on person-level data from twenty-six observational studies. Ann Epidemiol
19. Hoffmans MD, Kromhout D, Coulander CD. Body mass index at the age of 18 and its effects on 32-year-mortality from coronary heart disease and cancer. A nested case-control study among the entire 1932 Dutch male birth cohort. J Clin Epidemiol
20. Kiess W, Galler A, Reich A, et al. Clinical aspects of obesity in childhood and adolescence. Obes Rev
22. Bolton-Smith C, Woodward M, Tunstall-Pedoe H, Morrison C. Accuracy of the estimated prevalence of obesity from self reported height and weight in an adult Scottish population. J Epidemiol Community Health
23. Tsigilis N. Can secondary school students' self-reported measures of height and weight be trusted? An effect size approach. Eur J Public Health
coronary heart disease risk; high school weight; mortality; obesity
© 2010 Lippincott Williams & Wilkins, Inc.
Highlight selected keywords in the article text.