1 Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway.
2 Department of Pathology, The Norwegian Radium Hospital, Oslo, Norway.
Received for publication July 2, 2002; accepted for publication September 12, 2002.
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ABSTRACT |
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adolescence; body mass index; cohort studies; mortality
Abbreviations: Abbreviations: BMI, body mass index; CDC, Centers for Disease Control and Prevention; NCHS, National Center for Health Statistics.
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INTRODUCTION |
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The Third Harvard Growth Study included height and weight measurements for 3,000 schoolchildren during 19221935. A total of 508 lean or overweight adolescents aged 1318 years were followed for more than 50 years with regard to death (3), and overweight in adolescence was associated with increased mortality. In a long-term follow-up of Dutch men aged 18 years, mortality 2030 years later was 50 percent higher among those whose BMI ((weight in kg)/(height in meters)2) was higher than 25 compared with men whose BMI was 19.019.9 (6). Hoffmans et al. (6) also found increased mortality among men whose BMI was less than 18, which they ascribed to impaired health status.
It is known that obesity in adolescence also has other negative effects (5). Adolescent obesity has been shown to be associated with early maturation, increased truncal deposition of fat (7), and lasting social effects on self-esteem and body image (5, 7, 8). Obesity in childhood/adolescence also seems to be an important predictor of adult obesity (5, 9), although research that includes long-term follow-up data is lacking (10).
BMI is not a perfect measure of adiposity in adolescents, but it has been shown to be a valid measure of fatness in adolescents (11). In addition, a workshop on childhood obesity convened by the International Obesity Task Force in 1997 concluded that BMI offers a reasonable measure of fatness in children and adolescents (12). Since height and weight measurements are simple and inexpensive to collect and often have been a routine part of health examinations, BMI can be calculated in many epidemiologic studies.
There is no international agreement on an appropriate definition of obesity for adolescents (2), who are growing and are in various stages of maturation. Hence, age- and sex-specific growth curves need to be used to define overweight and risk for overweight. On the basis of a proposal from the International Obesity Task Force workshop (13), Cole et al. (14) proposed age- and sex-specific cutoff points to define overweight and obesity in adolescents. These cutoff points were linked to the adult categories for overweight (BMI, 2530) and obesity (BMI >30) and may be used in international comparisons of the prevalence of overweight and obesity. In the United States, the Centers for Disease Control and Prevention (CDC; Atlanta, Georgia) at the National Center for Health Statistics (NCHS; Hyattsville, Maryland) has created growth charts for children and adolescents up to the age of 20 years based on data from US health examinations (15). The CDC/NCHS guidelines for adolescents suggest using age- and sex-specific BMI to identify adolescents at the upper end of the distribution as being "at risk for overweight" (BMI, 85th94th percentiles) and overweight (BMI 95th percentile). In addition to age- and sex-specific growth curves for the 85th and 95th percentiles, CDC/NCHS also provides growth curves for the 3rd, 5th, 10th, 25th, 50th, 75th, 90th, and 97th percentiles (16).
The aim of the present study was to explore the relation between BMI and total mortality in a cohort of more than 200,000 Norwegian boys and girls aged 1419 years at measurement.
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MATERIALS AND METHODS |
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In the present study, all persons measured at age 1419 years were included, except 2,333 for whom the measurements were not performed according to the protocol (for example, they were wearing shoes), persons who declined to be measured, persons who were disabled, or women who claimed to be pregnant. The first measurement for each person was included. Altogether, 227,048 persons were eligible for the analysis. BMI was defined as (weight in kg)/(height in meters)2. Information on covariates other than sex, age, time of measurement, and area of residence was not available.
All residents of Norway are assigned a unique 11-digit identification number. By linkage to the Death Registry at Statistics Norway, it was possible to follow almost all persons in the present study from date of measurement until emigration, death, or June 30, 2001. A relatively small number of persons (n = 29) was lost to follow-up. Furthermore, 16 were excluded because their measurements were taken after the end of follow-up (when day and month of measurement were missing, the date was set as June 30).
Statistical analysis
Multivariate Cox proportional hazards regression models, with time since measurement as the time variable, were fitted to obtain relative risk estimates of dying (20). It was assumed that the hazard function for a person with a covariate vector x = (x1, x2, ... ,xp)' could be expressed by h(t; x) = h0(t) x exp(x' x ß), where h0(t) represents the hazard function for a person with covariate values all equal to zero, and ß = (ß1, ß2, ... ,ßp)' is a vector of regression coefficients. The first measurement obtained at age 1419 years was used. In the analyses, the following three categorized variables were included:
1. Age at measurement: 1416 years, 1719 years
2. Year of birth: 19431949, 1950
3. BMI at baseline: followed the guidelines from CDC/NCHS (15, 16) by using percentiles in a US reference population: <3rd, 3rd4th, 5th9th, 10th24th, 25th74th, 75th84th, 85th94th, 95th
The proportionality assumption in the Cox model was assessed by inspecting log-minus-log plots, results from stratified analyses, and results from separate analyses for different time periods after measurement. The analyses were performed by using the statistical program package SPSS (21). Analyses were performed separately for each sex. Results were presented as relative risks, with 95 percent confidence intervals, of dying.
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RESULTS |
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DISCUSSION |
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Use of Cox proportional hazards regression models assumes that relative risks do not vary by time. In the present study, a markedly lower relative risk of dying was observed in the first 10 years after measurement than later for persons whose BMI was above the 85th percentile in the reference population. This finding violates the proportionality assumption in the Cox model. However, because of a low number of deaths during the first 10 years, the impact of the first 10 years on the overall relative risk of dying was minor when the whole period was analyzed. Excluding the first 10 years of observation led to a slightly higher relative risk of dying for persons with the highest baseline BMI.
One of the major strengths of this study is the large number of persons included, who were recruited from the general population. The subjects were recruited from the national tuberculosis screening program, which was compulsory for persons aged 15 years or older. The measurements were performed in a standardized way. Follow-up of the study subjects was almost complete until the end of follow-up; of the 227,048 persons eligible for the study, 97.8 percent were registered as either being alive by the end of follow-up or having died during follow-up. A total of 2.2 percent had emigrated, and only 33 (for four of them, the date on which they were lost was known) persons were lost to follow-up.
Obesity in childhood/adolescence has many negative health consequences, which have been divided into the categories of immediate physical and social, intermediate (cardiovascular risk factor levels, persistent obesity into adulthood), and long-term (adult morbidity and mortality) (5). In the present study, the impact of adolescent BMI on long-term mortality was explored.
Because mortality is low during adolescence as well as young and middle-aged adulthood, a very large number of persons and a long follow-up are necessary to observe a sufficiently large number of deaths to obtain precise estimates. Both conditions were met in the present study. However, although follow-up in the present study was up to 38 years, the oldest persons were only aged 58 years when exiting the study. Hence, the excess mortality we observed among persons with a high BMI in adolescence shows excess mortality at middle age.
Studies including BMI in adolescence have used different definitions of overweight and obesity (5). In the present study, we decided to use age- and sex-specific growth charts from CDC/NCHS to group the adolescents by BMI. Another alternative was to use the growth charts from Cole et al. (14). However, those growth charts correspond to BMI levels of 25 and 30 at age 18 years only. The CDC/NCHS growth charts made it possible to develop more detailed categories.
However, the present material was also analyzed by using the growth curves from Cole et al. (14). Mortality among boys whose BMI corresponded to an adult BMI of 2530 and to an adult BMI of more than 30 was 25 percent (95 percent confidence interval: 13, 38) and 125 percent (95 percent confidence interval: 79, 185), respectively, higher than among those whose BMI corresponded to an adult BMI of less than 25. The corresponding figures for girls were 27 percent (95 percent confidence interval: 12, 43) and 114 percent (95 percent confidence interval: 61, 182).
After 55 years of follow-up of 508 persons, Must et al. (3) observed excess mortality among males, but not females, who were overweight (BMI, >75th percentile in the US reference population) in adolescence compared with those who were lean (BMI, 25th49th percentiles in the reference population). The observed increased risk of death was independent of adult BMI. In the present study, excess mortality was found for both sexes among persons whose BMI in adolescence was above the 85th percentile in a US reference population compared with those whose BMI was lower (25th74th percentiles). Among persons whose BMI was above the 95th percentile in the reference population, the mortality rate was more than 80 percent and 100 percent higher among boys and girls, respectively, than among persons whose BMI was between the 25th and 75th percentiles.
A weakness of the present study was our lack of information on other potential confounders besides age, sex, and birth year regarding the association between BMI and mortality. Other potential confounders include smoking habits, social class, and physical activity. Inclusion of smoking status in the regression model did not significantly change the estimated relative risks in the study by Must et al. (3), but the overall impact of these factors on the association between BMI and mortality is unclear. However, smoking habits, social class, and physical activity in adulthood might be influenced by BMI in adolescence; hence, these factors might partially be intermediate variables.
In a cohort of Dutch men aged 18 years, Hoffmans et al. (6) found increased mortality among those whose BMI was 25 or higher compared with those whose BMI was lower. However, the increase in mortality was evident only after a follow-up of more than 20 years (6). The necessity of having a long follow-up period when studying the association between BMI and mortality was also made clear in the present study. The excess mortality among overweight adolescents was not apparent the first 10 years after measurement. However, both males and females whose BMI was above the 85th percentile in the US reference population during adolescence already evidenced excess mortality in their thirties compared with those whose BMI was between the 25th and 75th percentiles.
In adolescence and young adulthood, mortality is low, and a large proportion of the deaths are due to accidents or suicides. After age 30 years, a larger proportion of the deaths are due to illnesses that may be influenced by BMI. However, since no information on cause of death was available in this study, we could not perform analyses on different causes of death. It is also possible that adverse health effects of obesity during adolescence are connected to long-term obesity. We had no information on how old the study subjects were at onset of obesity.
In summary, this study showed that overweight adolescents have increased long-term mortality. The excess mortality is not clearly manifested before they reach their thirties. Even though BMI is not regarded as an ideal measure of adiposity in adolescents, it is predictive of adult mortality.
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NOTES |
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REFERENCES |
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