0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Investigation |

Body Weight Patterns From 20 to 49 Years of Age and Subsequent Risk for Diabetes Mellitus:  The Johns Hopkins Precursors Study FREE

Frederick L. Brancati, MD, MHS; Nae-Yuh Wang, PhD; Lucy A. Mead, ScM; Kung-Yee Liang, PhD; Michael J. Klag, MD, MPH
[+] Author Affiliations

From the Departments of Medicine (Drs Brancati and Klag and Ms Mead), Epidemiology (Drs Brancati and Klag), Health Policy and Management (Dr Klag), and Biostatistics (Drs Wang and Liang), The Johns Hopkins Medical Institutions, Baltimore, Md.


Arch Intern Med. 1999;159(9):957-963. doi:10.1001/archinte.159.9.957.
Text Size: A A A
Published online

Background  Obesity in middle age is a well-known risk factor for the development of type 2 diabetes mellitus. However, the importance of weight and weight gain at younger ages is less certain.

Objective  To determine the relationship of body weight patterns from 20 to 49 years of age with the subsequent risk for type 2 diabetes mellitus.

Setting  An ongoing longitudinal study of former medical students.

Participants  Nine hundred sixteen white men without diabetes at 50 years of age.

Measurements  Weight and height measured in medical school, then assessed by mailed questionnaire to 49 years of age.

Main Outcome  Incident type 2 diabetes mellitus based on physician self-report.

Results  During 14,255 person-years of follow-up, there were 35 incident cases of type 2 diabetes mellitus (2.5 per 1000 person-years). After simultaneous adjustment for age, physical activity, lifetime maternal history of diabetes, and smoking, body mass indexes (BMIs; calculated as weight in kilograms divided by the square of height in meters) at 25, 35, and 45 years of age were all strongly associated with diabetes risk (relative risks for overweight [BMI ≥25.0] vs not overweight, >3.0; all Ps<.05), as were maximum and average BMI to 49 years of age. The relationship of BMI at 25 years of age to diabetes risk was substantially attenuated by adjustment for BMI at 45 years of age and average BMI, but was independent of weight change, weight variability, or maximum BMI.

Conclusion  In men, overweight at 25 years of age strongly predicts diabetes risk in middle age, largely through its association with overweight at 45 years of age and high average BMI to 49 years of age.

Figures in this Article

DIABETES MELLITUS imposes a substantial burden on public health in the United States, contributing annually to more than 300,000 deaths1 and more than $130 billion in direct and indirect costs.2 Overweight in middle age is a well-established, potentially modifiable risk factor for type 2 diabetes mellitus. About 90% of prevalent diabetes cases in the United States are classified as type 2. Since 1970, at least 28 prospective studies have confirmed this relationship.330 However, the relationship between weight and weight gain at younger ages and the risk for diabetes is less certain. Of the 28 studies, only 6 presented data regarding weight history before 40 years of age.15,17,25,2830 The 6 studies were also able to assess longitudinal features of body weight, such as weight gain,15,17,2830 weight variability,15,29 and duration of overweight,25 in addition to body mass index (BMI; calculated as weight in kilograms divided by the square of height in meters) at a single point in time. Unfortunately, these studies used retrospective data collection for body weight at young ages,15,17,28 lacked follow-up of sufficient length to characterize body weight patterns in young adulthood and middle age in the same individuals,30 or were limited to Pima Indians, a group at unusually high risk for obesity and diabetes compared with the general US population.25,29 Furthermore, no single study sought to compare the predictive value of various longitudinal features of body weight. A better understanding of the relationship of body weight in young adulthood with the risk for diabetes in middle age would guide public health and clinical efforts aimed at primary prevention of type 2 diabetes mellitus by weight control. The rising prevalence of overweight in adolescents and adults in the United States heightens the need for such information.31 With this in mind, we conducted a prospective cohort study with the following 2 aims: to determine the relationship between weight patterns from 20 to 49 years of age and the subsequent risk for type 2 diabetes mellitus and to compare the predictive value of these patterns.

SETTING AND COHORT COMPOSITION

The setting for the study was the Johns Hopkins Precursors Study, designed and initiated by Caroline Bedell Thomas, MD, in 1947 to identify precursors of cardiovascular disease. It is an ongoing longitudinal cohort study of 1337 former medical students at the Johns Hopkins University School of Medicine, Baltimore, Md, in the classes of 1948 to 1964. Since the number of women who enrolled during that interval was too small to investigate separately (n=121), we focused on the 1216 men. For the present analysis, we further excluded men who were unavailable for follow-up (n=73), who lacked complete BMI data to 49 years of age (n=162), or who died before 50 years of age (n=47). Of the remaining 934 men, we excluded 18 who had diabetes at baseline or in whom diabetes developed before 50 years of age. Thus, 916 men without diabetes by 50 years of age were the subject of our analysis. In multivariate models that adjusted for physical activity at enrollment, we excluded an additional 118 men who did not provide this information.

DATA COLLECTION

During medical school, each participant underwent a detailed medical history and physical examination, including measurement of height with a stadiometer and weight with a balance-beam scale. At this baseline examination, the age range was 20 to 29 years. After medical school, follow-up data collection was performed using annual mailed questionnaires. From 1949 to 1985, questions about body weight were posed every 3 to 5 years; after 1985, questions about body weight were posed annually. During most years, questions were posed regarding the following items: cigarette smoking, medication use, and old and new medical conditions in participants and their parents. To assess the validity of self-reported weight, a substudy of 78 men was conducted in 1989.32 In this convenience sample, measured weight was highly correlated with reported weight (r=0.98) with no bias (β=1.015 [95% confidence interval {CI}, 0.975-1.056]; intercept, 0.261 [95% CI, −3.057-3.579]). Since 1964, participants were asked specifically whether they had diabetes mellitus and whether they were taking medications specifically for diabetes. In general, the yearly response rates have exceeded 70% and, during any 5-year interval, at least 85% of participants have responded at least once. In addition, ongoing mortality surveillance is conducted by review of alumni records and obituaries and by period National Death Index searches. A committee of internists reviews copies of the death certificates to assess cause of death and underlying medical conditions.

CHARACTERIZATION OF BODY WEIGHT BEFORE 50 YEARS OF AGE

Measured height at enrollment was assumed to be unchanged during the course of follow-up. Body mass index after enrollment was recalculated whenever updated self-report data were available. Variability in number of years since graduation and in individual response rates to annual questionnaires produced a distribution of weight updates before 50 years of age, with a median of 10 (range, 3-18) per participant. To facilitate comparisons of body weight across a 30-year age span, we focused on weight at the midpoint of the decade (ie, 25, 35, and 45 years of age). If weight updates were available in the midpoint year or in the midpoint year±1, we used these values directly (n=156, 665, and 808 for third, fourth, and fifth decades, respectively) If not (n=760, 251, and 108 for third, fourth, and fifth decades, respectively), we estimated weight at the midpoint using a random effects model that combined individual data from the remaining years of the decade with cohort-wide data on linear trends in weight change for that decade.33

In addition to BMI at decade midpoints, we defined 4 weight variables that characterized longitudinal features of body weight from 20 to 49 years of age. First, change in BMI was defined as the BMI at 45 years of age minus the BMI at 25 years of age. Second, maximum BMI was defined as the maximum of all values to 49 years of age, including interpolated and projected values from the random-effects model. Third, body mass fluctuation was defined as the sum of the squared distances between the reported BMI and the BMI predicted from the random-effects model at the same age, divided by the number of reported BMI values. Finally, to reflect duration and degree of obesity, we calculated average BMI, ie, the sum of BMI values for the 30 years from 20 to 49 years of age, divided by 30. For this calculation, changes in weight between reported values separated by more than 1 year were assumed to have occurred in a single step at the midpoint between values.

DEFINITION OF INCIDENT TYPE 2 DIABETES MELLITUS AFTER 50 YEARS OF AGE

Incident type 2 diabetes mellitus was defined by the occurrence of any 1 of the following conditions after 50 years of age: (1) report of pharmacologically treated diabetes on an annual mailed questionnaire; (2) report of nonpharmacologically treated diabetes on 2 or more annual mailed questionnaires; (3) physician diagnosis of diabetes in office or hospital records; (4) report of a fasting plasma glucose level of at least 7.8 mmol/L (≥140 mg/dL) or a nonfasting plasma glucose level of at least 11.1 mmol/L (≥200 mg/dL); and (5) diagnosis of diabetes as an underlying or other condition on a death certificate. (Individuals who met any of these conditions before 50 years of age were excluded from the present analysis.) Of the 35 incident cases that are the subject of this analysis, 8 (23%) were confirmed by medical records or death certificates and 25 (71%) by the completion of a supplemental diabetes questionnaire that confirmed symptoms at presentation, elevated fasting glucose or glycohemoglobin levels, and/or antidiabetic medication use and that ruled out a history of ketosis, immediate need for insulin therapy at diagnosis, or other features suggestive of type 1 diabetes mellitus. The earliest record of diabetes was taken as the event date.

DEFINITION OF COVARIATES

Physical activity at enrollment was classified by response to the following question: How much regular exercise have you had during the past month? (1) none, (2) little, (3) moderate, (4) much.

Cigarette smoking was defined by a time-dependent dichotomous smoking variable that reflected changes in smoking behavior during the entire follow-up. Parental history of diabetes mellitus was defined by the presence of participant report of diabetes in a parent on enrollment or at any point during follow-up or diagnosis of diabetes as an underlying or other condition of the death certificate of a participant's parent.

STATISTICAL ANALYSIS

At 50 years of age, men were characterized by various patterns of body weight during the preceding 30 years. To assess the interrelatedness of these continuous variables, we constructed a matrix of Pearson correlation coefficients. Next, we investigated their relationship with the risk for incident diabetes after 50 years of age using Kaplan-Meier analyses. In these analyses, BMI change, maximum BMI, BMI variability, and average BMI were categorized into quartiles. However, to faciliate comparisons and interpretability, absolute BMIs at 25, 35, and 45 years of age were handled differently. These variables were categorized into 4 groups based on set cut points derived from the distribution of BMI at 35 years of age, then rounded to the nearest whole BMI unit (<22.0, 22.0-23.9, 24.0-24.9, and ≥25.0). The cut point at 25.0 corresponds to the present National Institutes of Health definition of overweight. The log-rank test was used to determine the statistical significance of risk differences between quartiles. We used proportional hazards regression to estimate the relationship of individual weight history features with diabetes risk independent of baseline physical activity, time-dependent smoking, and cumulative maternal history of diabetes. In this cohort, cumulative paternal diabetes from enrollment through follow-up was not associated with incident diabetes risk (data not shown). The assumption of proportionality underlying these regression models was confirmed by examining log-log plots. Finally, we assessed the independent predictive value of BMI at 25 years of age relative to other body weight measures by constructing a series of proportional hazards regression models that included selected body weight measures in addition to aforementioned covariates. All tests of significance were 2-tailed.

Table 1 summarizes characteristics of the 916 men. The sample was predominantly white; the mean age at enrollment was about 23 years; by 50 years of age, fewer than 1 in 5 were current smokers; and about 25% reported diabetes in a parent during the full follow-up. By present standards, the men were lean, with a mean BMI of 23.2 at 25, 23.9 at 35, and 24.1 at 45 years of age. On average, the men gained 1 U BMI from 25 through 45 years of age. For a man of 1.8 m height (5 ft 11 in), this corresponds to a weight gain of 3.2 kg (7.1 lb). From 20 through 49 years of age, mean maximum BMI was 25.9, mean BMI variability was 2.3, and mean average BMI was 23.8.

Table Graphic Jump LocationTable 1. Selected Characteristics of 916 Men Without Diabetes by 50 Years of Age*

As expected, BMIs at 25, 35, and 45 years of age were strongly associated with each other, as well as with maximum and average BMI (all rs>0.50; all Ps<.001 [Table 2]). In contrast, BMI at 25 years of age was inversely associated with BMI change from 25 through 45 years of age (r=−0.38). Variability of BMI was not strongly associated with most other features of weight history (−0.20<r<0.20), except for maximum BMI (r=0.47).

Table Graphic Jump LocationTable 2. Correlations Among Selected Body Weight Patterns in 916 Men Without Diabetes by 50 Years of Age*

During an average of 15.6 years (range,1-30 years) of follow-up, after 50 years of age, there were 35 incident cases of type 2 diabetes mellitus, corresponding to an incidence rate of 2.5 per 1000 person-years. Figure 1 displays a Kaplan-Meier plot of incident diabetes after 50 years of age by BMI at 25 years of age. By 65 years of age, the cumulative incidence of diabetes was 7.2% in men with BMIs of 25.0 or greater compared with 4.5%, 1.9%, and 4.2% in the lower 3 BMI groups, from lowest to highest, respectively (P<.001). The relationships of BMI at 45 years of age and average BMI from 20 to 50 years of age with the cumulative incidence of diabetes after 50 years of age were also impressive (Figure 2 and Figure 3). To facilitate comparison of the predictive strength of different body weight measures before adjustment, we calculated the cumulative incidence of diabetes from 50 through 65 years of age from Kaplan-Meier plots for each of the 8 features (Table 3). For each feature, the cumulative incidence by quartile is presented, as well as the P value for a log-rank test across all 4 quartiles. In general, diabetes risk appeared to be clearly higher in the top quartiles compared with the lower 3 quartiles. The individual measures that emerged as strong predictors of diabetes after 50 years of age were BMI at 25, 35, and 45 years of age; BMI change from 25 to 45 years of age; maximum BMI from 20 to 49 years of age; and average BMI from 20 to 49 years of age. Variability of BMI before 50 years of age also predicted incident diabetes, but this relationship was only marginally significant.

Place holder to copy figure label and caption
Figure 1.

Cumulative incidence of type 2 diabetes mellitus after 50 years of age by body mass index (BMI) at 25 years of age in 916 former medical students. Quartile cut points were based on BMI distribution at 35 years of age, rounded to nearest BMI unit (<22.0, 22.0-23.9, 24.0-24.9, and ≥25.0). Cumulative incidence was significantly greater in men in the upper quartile of BMI compared with men in the lower 3 quartiles (P<.001 by log-rank test).

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Cumulative incidence of type 2 diabetes mellitus after 50 years of age by body mass index (BMI) at 45 years of age in 916 former medical students. Quartile cut points were based on BMI distribution at 35 years of age, rounded to nearest BMI unit (<22.0, 22.0-23.9, 24.0-24.9, and ≥25.0). Cumulative incidence was significantly greater in men in the upper quartile of BMI compared with men in the lower 3 quartiles (P<.001 by log-rank test).

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Cumulative incidence of type 2 diabetes mellitus after 50 years of age by quartiles of average body mass index (BMI) from 20 to 50 years of age in 916 former medical students. Cumulative incidence was significantly greater in men in the upper quartile of average BMI (≥25.0) compared with men in the lower 3 quartiles (<22.0, 22.0-23.9, and 24.0-24.9) (P<.001 by log-rank test).

Graphic Jump Location
Table Graphic Jump LocationTable 3. Cumulative Incidence of Diabetes From 50 to 65 Years of Age by Quartile of Selected Body Weight Patterns in 916 Men Without Diabetes by 50 Years of Age*

Next, we constructed a series of proportional hazards models to estimate the predictive value of different features of weight history independent of age and physical activity at enrollment, maternal history of diabetes, and time-dependent cigarette smoking (Table 4). This analysis is limited to the 798 men who provided physical activity data at baseline. In light of the consistent risk patterns observed in Kaplan-Meier plots, these analyses collapse the lower 3 quartiles into a single reference group. Thus the estimates reflect the relative risk for diabetes among men in the top category vs men in the lower 3 categories. Once more, BMI at 25 years of age emerged as a strong predictor of diabetes. Compared with their leaner counterparts, diabetes was almost 4 times more likely to develop after 50 years of age in men with BMI of 25.0 or greater at 25 years of age. Body mass index at 35 and 45 years of age, maximum BMI, and average BMI also displayed strong predictive value (all relative risks, >3.0).

Table Graphic Jump LocationTable 4. Unadjusted and Adjusted Associations of Selected Body Weight Patterns With the Risk for Incident Diabetes (n = 35) in 798 Men Without Diabetes by 50 Years of Age*

Finally, to determine the predictive value of BMI at 25 years of age independent of other BMI patterns before 50 years of age, we constructed 5 additional proportional hazards models (Table 4). In addition to age and physical activity at enrollment, maternal history of diabetes, and time-dependent cigarette smoking, each model included BMI at 25 years of age along with 1 or 2 other body weight measures. As before, relative risks for men in the top vs the lower 3 categories are displayed. Adjustment for BMI at 35 and 45 years of age (model 1) attenuated the relative risk associated with BMI at 25 years of age substantially, as did adjustment for average BMI (model 5). In these models, there was some indication of residual risk associated with BMI at 25 years of age (adjusted relative risk, 1.6-2.0), but the study had limited power to detect such modest risk levels. Body mass index at 25 years of age did remain independently associated with diabetes risk after 50 years of age, after adjustment for BMI change from 25 to 45 years of age (model 2), maximum BMI from 20 to 49 years of age (model 3), and BMI variability from 20 to 49 years of age (model 4). In other multivariate models, neither BMI variability nor BMI change were significantly associated with diabetes risk after adjustment for BMI at 45 years of age (data not shown).

These data suggest that, among white men, overweight at 25 years of age is a strong predictor of incident type 2 diabetes mellitus in middle age. This association appears to be explained largely by subsequent tracking of BMI to 49 years of age. Differences in BMI below 25.0 at 25 years of age did not appear to predict incident diabetes. These data also suggest that overweight at 45 years of age and average BMI before 50 years of age are the weight patterns most strongly associated with diabetes risk in middle age, followed by BMI at 25 years of age. A unique strength of our study was its use of 3 decades of prospectively collected data on body weight to characterize body weight patterns in early adulthood up to 50 years of age.

Several limitations of our study also deserve comment. First, by design the sample is limited to physicians who, for historical reasons, were almost entirely white men. This group is at relatively low risk for obesity and type 2 diabetes mellitus. Our results are therefore not directly generalizable to women, to individuals of lower socioeconomic status, or to members of ethnic minority groups, especially with regard to absolute levels of risk. Second, with the exception of the baseline measurement, we relied on self-report to characterize body weight. In this cohort of former medical students, self-report was quite accurate. However, to the extent that there was random misclassification, or a bias toward underreporting at higher levels of weight, we may have underestimated the true association between higher body weight and diabetes risk in our cohort. Third, ascertainment of incident diabetes was based only on self-report of physician diagnosis; the wide national dispersion of the cohort precluded the collection of blood specimens that would have greatly enhanced the sensitivity of ascertainment. No doubt, suboptimal sensitivity reduced the precision of our results. More important is the theoretical concern that suboptimal sensitivity may have led to ascertainment bias insofar as overweight men were more likely to be screened for diabetes than their leaner counterparts. In fact, it seems unlikely that body weight patterns before 50 years of age might influence screening practice years or even decades later. Finally, the relatively small of number of incident diabetes cases (n=35) limited the study's statistical power and, therefore, the precision of its risk estimates.

Since 1970, at least 28 studies have confirmed a strong relationship between body weight and the risk for type 2 diabetes mellitus.330 In most of these studies, body weight was first assessed at 40 years of age and older; only 6 assessed body weight at younger ages.15,17,25,2830 Two studies based on the Pima Indians25,29 used prospectively collected biennial data on weight from as early as 15 years of age to examine the following 3 aspects of weight history: duration of obesity,25 weight gain,29 and weight fluctuation.29 In this population at unusually high risk for obesity and type 2 diabetes mellitus, duration of obesity was a strong predictor of type 2 diabetes mellitus in men and women,25 as was weight gain in nonoverweight individuals.29 In overweight Pima Indians, weight gain predicted diabetes in men, but not women.29 However, baseline overweight status was a strong predictor of diabetes risk independent of weight gain. In contrast, weight fluctuation was not associated with diabetes risk in either sex.29 Although these analyses did not explicitly address the relative predictive value of body weight in young adulthood vs middle age, they appear to be generally consistent with our results.

Unlike the studies of the Pima Indians, 2 studies of predominantly white populations relied largely17,28 or exclusively15 on retrospective weight data before 40 years of age, asking participants in the fifth, sixth, and seventh decades to recall weight at 18 years of age. In 1989, Holbrook et al15 described 886 men and 1114 women aged 50 years and older in Rancho Bernardo, Calif. Neither self-perceived overweight nor recalled body weight at 18 years of age was associated with diabetes. Instead, self-perceived underweight at 18, weight gain from 18 to 40, and recalled weight gain and weight fluctuation from 40 to 60 years of age and recalled maximum lifetime weight were significantly associated with diabetes. However, since diabetes may have developed and been diagnosed before exposure assessment in many participants, the possibility of recall bias or reverse causality cannot be excluded.

Colditz and colleagues17,28 have presented 8- and 14-year follow-up results in more than 90,000 initially nondiabetic women aged 30 to 55 years in the Nurses Health Study who provided data on recalled weight at 18 years of age. In both analyses, BMI at 18 years of age was strongly associated with the development of diabetes after enrollment, as was weight gain from 18 years of age to enrollment. However, the relationship of BMI at 18 years of age with diabetes risk was completely dependent on BMI at enrollment.17 These findings are similar to ours.

Finally, Ford and colleagues30 recently published results from the National Health and Nutrition Examination Survey Epidemiologic Follow-up Study regarding the risk for diabetes related to body weight and weight gain in a biracial cohort of men and women, 3300 of whom were aged 18 to 39 years at baseline. In this national sample, BMI at baseline and weight gain during the first 10 years of follow-up were strong predictors of incident diabetes during the second 10 years of follow-up. Although the authors reported no interaction between age and weight or weight gain, the study lacked longitudinal data required to compare the predictive strength of body weight in young adulthood directly vs middle age within individuals.

Of the numerous studies of overweight and obesity in childhood, 2 have addressed diabetes in middle age as an outcome.34,35 In a sample of 716 residents of Hagerstown, Md, Abraham and colleagues34 found weak relationships of overweight at 9 to 13 years of age with fasting glucose levels and prevalent diabetes 30 to 40 years later, but these relationships were not statistically significant. Likewise, Mossberg35 observed a higher incidence of diabetes in 504 Swedes who had been hospitalized for obesity during childhood (7.4%), compared with a population-based reference group (2.3%), although the difference was not statistically significant. Both studies were limited by small numbers and relatively high numbers of patients unavailable for follow-up. Neither assessed the predictive value of childhood overweight independent of overweight in adulthood.

The possibility of some residual association of BMI at 25 years of age with diabetes risk after adjustment for BMI at 45 years of age and average BMI raises a question about biological mechanism. One possible explanation is that early adulthood marks the end of a critical period for the development of metabolism. For example, androgen-induced intra-abdominal fat deposition during adolescence may contribute to subsequent hepatic insulin resistance that, in turn, leads to glucose intolerance.36 Another possibility is that differences in body weight in early adulthood reflect genetic predisposition to a greater extent than differences in middle age.37 To the extent that diabetes and overweight share common genetic risk factors, overweight in young adulthood would appear to itself confer risk, while in fact merely serving as a phenotypic marker. However, were this hypothesis true, one might have predicted that adjustment for parental history of diabetes would have attenuated the association. In our study, this association appeared to be independent of parental diabetes history.

Finally, overweight in young adulthood may confer diabetes risk by adding to cumulative exposure. In most epidemiological studies of adults, body weight has been analyzed independent of time. The only study that specifically investigated duration of obesity found it to be a strong risk factor for type 2 diabetes mellitus.25 In our study, much of the predictive value of BMI at 25 years of age was mediated by its association with a time-weighted average of body mass, a characterization of exposure that combines duration and degree. It may be that measurements of BMI confined to early middle age simply miss an important early contribution to cumulative exposure, like beginning assessment for pack-years of cigarette smoking at 40 rather than at 20 years of age. If sustained for decades, the insulin resistance associated with high body weight could contribute to the exhaustion of the ability of islet cells to maintain compensatory hyperinsulinemia, and thereby hasten the onset of diabetes.

Our study has 3 main implications. First, it suggests that future research on the relationship between body weight and diabetes risk should consider body weight in young adulthood and its relationship to average body weight through early middle age. Second, it implies that interventions aimed at the primary prevention of type 2 diabetes mellitus via weight control and weight reduction might be targeted at overweight young adults as well as overweight middle-aged individuals. Finally, it suggests that, in the absence of effective prevention strategies, the rising prevalence of overweight in young adults today may accelerate the incidence of diabetes well into the next century.

Accepted for publication August 31, 1998.

This work was supported by grant RO1 AG01760 from the National Institutes of Health, Bethesda, Md, and a Career Development Award from the American Diabetes Association, Alexandria, Va (Dr Brancati).

Presented in part at the 56th Scientific Sessions of the American Diabetes Association, San Francisco, Calif, June 10, 1996.

Reprints: Frederick L. Brancati, MD, MHS, Welch Center for Prevention, Epidemiology, and Clinical Research, 2024 E Monument St, Suite 2-600, Baltimore, MD 21205 (e-mail: fbrancat@welchlink.welch.jhu.edu).

Geiss  LHerman  WSmith  P Mortality in non–insulin-dependent diabetes. National Diabetes Data Group.,Diabetes in America. 2nd ed. Bethesda, Md National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health1995;233- 257NIH publication 95-1468
American Diabetes Association, Economic consequences of diabetes mellitus in the US in 1997. Diabetes Care. 1998;21296- 309
Link to Article
Dunn  JPIpsen  JElsom  KOOhtani  M Risk factors in coronary artery disease, hypertension and diabetes. Am J Med Sci. 1970;259309- 322
Link to Article
Paffenbarger  RSJWing  AI Chronic disease in former college students. Am J Epidemiol. 1973;97314- 323
Medalie  JHPapier  CMGoldbourt  UHerman  JB Major factors in the development of diabetes mellitus in 10,000 men. Arch Intern Med. 1975;135811- 817
Link to Article
Wilson  PWMcGee  DLKannel  WB Obesity, very low density lipoproteins, and glucose intolerance over fourteen years: The Framingham Study. Am J Epidemiol. 1981;114697- 704
Butler  WJOstrander  LEJCarman  WJLamphiear  DE Diabetes mellitus in Tecumseh, Michigan. Am J Epidemiol. 1982;116971- 980
Beaty  THNell  JVFajans  SS Identifying risk factors for diabetes in first-degree relatives of non–insulin dependent diabetic patients. Am J Epidemiol. 1982;115380- 397
Jarrett  RJKeen  HMcCartney  P The Whitehall Study: ten-year follow-up report on men with impaired glucose tolerance with reference to worsening to diabetes and predictors of death. Diabet Med. 1984;1279- 283
Link to Article
Balkau  BKing  HZimmet  PRaper  LR Factors associated with the development of diabetes in the Micronesian population of Nauru. Am J Epidemiol. 1985;122594- 605
Ohlson  L-OLarsson  BSvardsudd  K  et al.  The influence of body fat distribution on the incidence of diabetes mellitus. Diabetes. 1985;341055- 1058
Link to Article
Wilson  PWAnderson  KMKannel  WB Epidemiology of diabetes mellitus in the elderly: The Framingham Study. Am J Med. 1986;803- 9
Link to Article
Sicree  RAZimmet  PZKing  HOMCoventry  JS Plasma insulin response among Nauruans. Diabetes. 1987;36179- 186
Link to Article
Feskens  EJMKronmholt  D Cardiovascular risk factors and the 25-year incidence of diabetes mellitus in middle-aged men. Am J Epidemiol. 1989;1301101- 1108
Holbrook  TLBarrett-Connor  EWingard  DL The association of lifetime weight and weight control patterns with diabetes among men and women in an adult community. Int J Obes Relat Metab Disord. 1989;13723- 729
Lundgren  HBengtsson  CBlohme  GLapidus  LSjostrom  L Adiposity and adipose tissue distribution in relation to incidence of diabetes in women: results from a prospective population study in Gothenburg, Sweden. Int J Obes Relat Metab Disord. 1989;13413- 423
Colditz  GAWillett  WCStampfer  MJ  et al.  Weight as a risk factor for clinical diabetes in women. Am J Epidemiol. 1990;132501- 513
Kaye  SAFolsom  ARSprafka  JMPrineas  RJWallace  RB Increased incidence of diabetes mellitus in relation to abdominal adiposity in older women. J Clin Epidemiol. 1991;44329- 334
Link to Article
Morris  RDRimm  AA Association of waist to hip ratio and family history with the prevalence of NIDDM among 25,272 adult, white females. Am J Public Health. 1991;81507- 509
Link to Article
Helmrich  SPRagland  DRLeung  RWPaffenbarger  RSJ Physical activity and reduced occurrence of non–insulin-dependent diabetes mellitus. N Engl J Med. 1991;325147- 152
Link to Article
Charles  MAFontbonne  AThibult  NWarnet  J-MRosselin  GEEschwege  E Risk factors for NIDDM in white population: Paris prospective study. Diabetes. 1991;40796- 799
Link to Article
Haffner  SMMitchell  BDHazuda  HPStern  MP Greater influence of central distribution of adipose tissue on incidence of non–insulin-dependent diabetes in women than men. Am J Clin Nutr. 1991;531312- 1317
Skarfors  ETSelinus  KILithell  HO Risk factors for developing non–insulin dependent diabetes: a 10-year follow up of men in Uppsala. BMJ. 1991;303755- 760
Link to Article
Manson  JENathan  DMKrolewski  ASStampfer  MJWillett  WCHennekens  CH A prospective study of exercise and incidence of diabetes among US male physicians. JAMA. 1992;26863- 67
Link to Article
Everhart  JPettit  DJBennett  PKnowler  WC Duration of obesity increases the incidence of NIDDM. Diabetes. 1992;41235- 240
Link to Article
Rimm  EBChan  JStampfer  MColditz  GAWillett  WC Prospective study of cigarette smoking, alcohol use, and the risk of diabetes in men. BMJ. 1995;310555- 559
Link to Article
Perry  IWannamethee  SWalker  MThomson  AWhincup  P Prospective study of risk factors for development of non–insulin dependent diabetes in middle-aged British men. BMJ. 1995;310560- 564
Link to Article
Colditz  GAWillett  WCRotnitzky  AManson  JAE Weight gain as a risk factor for clinical diabetes mellitus in women. Ann Intern Med. 1995;122481- 486
Link to Article
Hanson  RLNarayan  KMcCance  D  et al.  Rate of weight gain, weight fluctuation, and incidence of NIDDM. Diabetes. 1995;44261- 266
Link to Article
Ford  ESWilliamson  DFLiu  S Weight change and diabetes incidence: findings from a national cohort of US adults. Am J Epidemiol. 1997;146214- 222
Link to Article
Kuczmarski  RJFlegal  KMCampbell  SMJohnson  CL Increasing prevalence of overweight among US adults: the National Health and Nutrition Examination Surveys, 1960 to 1991. JAMA. 1994;272205- 211
Link to Article
Klag  MJHe  JMead  LAFord  DEPearson  TALevine  DM Validity of physicians' self-reports of cardiovascular disease risk factors. Ann Epidemiol. 1993;3442- 447
Link to Article
Laird  NWare  J Random-effects models for longitudinal data. Biometrics. 1982;38963- 974
Link to Article
Abraham  SCollins  GNordsieck  M Relationship of childhood weight status to morbidity in adults. Public Health Rep. 1971;86273- 284
Mossberg  H-O 40-year follow-up of overweight children. Lancet. 1989;2491- 493
Link to Article
Dietz  WH Critical periods in childhood for the development of obesity. Am J Clin Nutr. 1994;59955- 959
Stunkard  ASorensen  THanis  C  et al.  An adoption study of human obesity. N Engl J Med. 1986;314193- 198
Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.

Cumulative incidence of type 2 diabetes mellitus after 50 years of age by body mass index (BMI) at 25 years of age in 916 former medical students. Quartile cut points were based on BMI distribution at 35 years of age, rounded to nearest BMI unit (<22.0, 22.0-23.9, 24.0-24.9, and ≥25.0). Cumulative incidence was significantly greater in men in the upper quartile of BMI compared with men in the lower 3 quartiles (P<.001 by log-rank test).

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Cumulative incidence of type 2 diabetes mellitus after 50 years of age by body mass index (BMI) at 45 years of age in 916 former medical students. Quartile cut points were based on BMI distribution at 35 years of age, rounded to nearest BMI unit (<22.0, 22.0-23.9, 24.0-24.9, and ≥25.0). Cumulative incidence was significantly greater in men in the upper quartile of BMI compared with men in the lower 3 quartiles (P<.001 by log-rank test).

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Cumulative incidence of type 2 diabetes mellitus after 50 years of age by quartiles of average body mass index (BMI) from 20 to 50 years of age in 916 former medical students. Cumulative incidence was significantly greater in men in the upper quartile of average BMI (≥25.0) compared with men in the lower 3 quartiles (<22.0, 22.0-23.9, and 24.0-24.9) (P<.001 by log-rank test).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Selected Characteristics of 916 Men Without Diabetes by 50 Years of Age*
Table Graphic Jump LocationTable 2. Correlations Among Selected Body Weight Patterns in 916 Men Without Diabetes by 50 Years of Age*
Table Graphic Jump LocationTable 3. Cumulative Incidence of Diabetes From 50 to 65 Years of Age by Quartile of Selected Body Weight Patterns in 916 Men Without Diabetes by 50 Years of Age*
Table Graphic Jump LocationTable 4. Unadjusted and Adjusted Associations of Selected Body Weight Patterns With the Risk for Incident Diabetes (n = 35) in 798 Men Without Diabetes by 50 Years of Age*

References

Geiss  LHerman  WSmith  P Mortality in non–insulin-dependent diabetes. National Diabetes Data Group.,Diabetes in America. 2nd ed. Bethesda, Md National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health1995;233- 257NIH publication 95-1468
American Diabetes Association, Economic consequences of diabetes mellitus in the US in 1997. Diabetes Care. 1998;21296- 309
Link to Article
Dunn  JPIpsen  JElsom  KOOhtani  M Risk factors in coronary artery disease, hypertension and diabetes. Am J Med Sci. 1970;259309- 322
Link to Article
Paffenbarger  RSJWing  AI Chronic disease in former college students. Am J Epidemiol. 1973;97314- 323
Medalie  JHPapier  CMGoldbourt  UHerman  JB Major factors in the development of diabetes mellitus in 10,000 men. Arch Intern Med. 1975;135811- 817
Link to Article
Wilson  PWMcGee  DLKannel  WB Obesity, very low density lipoproteins, and glucose intolerance over fourteen years: The Framingham Study. Am J Epidemiol. 1981;114697- 704
Butler  WJOstrander  LEJCarman  WJLamphiear  DE Diabetes mellitus in Tecumseh, Michigan. Am J Epidemiol. 1982;116971- 980
Beaty  THNell  JVFajans  SS Identifying risk factors for diabetes in first-degree relatives of non–insulin dependent diabetic patients. Am J Epidemiol. 1982;115380- 397
Jarrett  RJKeen  HMcCartney  P The Whitehall Study: ten-year follow-up report on men with impaired glucose tolerance with reference to worsening to diabetes and predictors of death. Diabet Med. 1984;1279- 283
Link to Article
Balkau  BKing  HZimmet  PRaper  LR Factors associated with the development of diabetes in the Micronesian population of Nauru. Am J Epidemiol. 1985;122594- 605
Ohlson  L-OLarsson  BSvardsudd  K  et al.  The influence of body fat distribution on the incidence of diabetes mellitus. Diabetes. 1985;341055- 1058
Link to Article
Wilson  PWAnderson  KMKannel  WB Epidemiology of diabetes mellitus in the elderly: The Framingham Study. Am J Med. 1986;803- 9
Link to Article
Sicree  RAZimmet  PZKing  HOMCoventry  JS Plasma insulin response among Nauruans. Diabetes. 1987;36179- 186
Link to Article
Feskens  EJMKronmholt  D Cardiovascular risk factors and the 25-year incidence of diabetes mellitus in middle-aged men. Am J Epidemiol. 1989;1301101- 1108
Holbrook  TLBarrett-Connor  EWingard  DL The association of lifetime weight and weight control patterns with diabetes among men and women in an adult community. Int J Obes Relat Metab Disord. 1989;13723- 729
Lundgren  HBengtsson  CBlohme  GLapidus  LSjostrom  L Adiposity and adipose tissue distribution in relation to incidence of diabetes in women: results from a prospective population study in Gothenburg, Sweden. Int J Obes Relat Metab Disord. 1989;13413- 423
Colditz  GAWillett  WCStampfer  MJ  et al.  Weight as a risk factor for clinical diabetes in women. Am J Epidemiol. 1990;132501- 513
Kaye  SAFolsom  ARSprafka  JMPrineas  RJWallace  RB Increased incidence of diabetes mellitus in relation to abdominal adiposity in older women. J Clin Epidemiol. 1991;44329- 334
Link to Article
Morris  RDRimm  AA Association of waist to hip ratio and family history with the prevalence of NIDDM among 25,272 adult, white females. Am J Public Health. 1991;81507- 509
Link to Article
Helmrich  SPRagland  DRLeung  RWPaffenbarger  RSJ Physical activity and reduced occurrence of non–insulin-dependent diabetes mellitus. N Engl J Med. 1991;325147- 152
Link to Article
Charles  MAFontbonne  AThibult  NWarnet  J-MRosselin  GEEschwege  E Risk factors for NIDDM in white population: Paris prospective study. Diabetes. 1991;40796- 799
Link to Article
Haffner  SMMitchell  BDHazuda  HPStern  MP Greater influence of central distribution of adipose tissue on incidence of non–insulin-dependent diabetes in women than men. Am J Clin Nutr. 1991;531312- 1317
Skarfors  ETSelinus  KILithell  HO Risk factors for developing non–insulin dependent diabetes: a 10-year follow up of men in Uppsala. BMJ. 1991;303755- 760
Link to Article
Manson  JENathan  DMKrolewski  ASStampfer  MJWillett  WCHennekens  CH A prospective study of exercise and incidence of diabetes among US male physicians. JAMA. 1992;26863- 67
Link to Article
Everhart  JPettit  DJBennett  PKnowler  WC Duration of obesity increases the incidence of NIDDM. Diabetes. 1992;41235- 240
Link to Article
Rimm  EBChan  JStampfer  MColditz  GAWillett  WC Prospective study of cigarette smoking, alcohol use, and the risk of diabetes in men. BMJ. 1995;310555- 559
Link to Article
Perry  IWannamethee  SWalker  MThomson  AWhincup  P Prospective study of risk factors for development of non–insulin dependent diabetes in middle-aged British men. BMJ. 1995;310560- 564
Link to Article
Colditz  GAWillett  WCRotnitzky  AManson  JAE Weight gain as a risk factor for clinical diabetes mellitus in women. Ann Intern Med. 1995;122481- 486
Link to Article
Hanson  RLNarayan  KMcCance  D  et al.  Rate of weight gain, weight fluctuation, and incidence of NIDDM. Diabetes. 1995;44261- 266
Link to Article
Ford  ESWilliamson  DFLiu  S Weight change and diabetes incidence: findings from a national cohort of US adults. Am J Epidemiol. 1997;146214- 222
Link to Article
Kuczmarski  RJFlegal  KMCampbell  SMJohnson  CL Increasing prevalence of overweight among US adults: the National Health and Nutrition Examination Surveys, 1960 to 1991. JAMA. 1994;272205- 211
Link to Article
Klag  MJHe  JMead  LAFord  DEPearson  TALevine  DM Validity of physicians' self-reports of cardiovascular disease risk factors. Ann Epidemiol. 1993;3442- 447
Link to Article
Laird  NWare  J Random-effects models for longitudinal data. Biometrics. 1982;38963- 974
Link to Article
Abraham  SCollins  GNordsieck  M Relationship of childhood weight status to morbidity in adults. Public Health Rep. 1971;86273- 284
Mossberg  H-O 40-year follow-up of overweight children. Lancet. 1989;2491- 493
Link to Article
Dietz  WH Critical periods in childhood for the development of obesity. Am J Clin Nutr. 1994;59955- 959
Stunkard  ASorensen  THanis  C  et al.  An adoption study of human obesity. N Engl J Med. 1986;314193- 198
Link to Article

Correspondence

CME
Also Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
Please click the checkbox indicating that you have read the full article in order to submit your answers.
Your answers have been saved for later.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 56

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
PubMed Articles
JAMAevidence.com