Context As the prevalence of obesity increases in the United States, concern
over the association of body weight with excess mortality has also increased.
Objective To estimate deaths associated with underweight (body mass index [BMI]
<18.5), overweight (BMI 25 to <30), and obesity (BMI ≥30) in the
United States in 2000.
Design, Setting, and Participants We estimated relative risks of mortality associated with different levels
of BMI (calculated as weight in kilograms divided by the square of height
in meters) from the nationally representative National Health and Nutrition
Examination Survey (NHANES) I (1971-1975) and NHANES II (1976-1980), with
follow-up through 1992, and from NHANES III (1988-1994), with follow-up through
2000. These relative risks were applied to the distribution of BMI and other
covariates from NHANES 1999-2002 to estimate attributable fractions and number
of excess deaths, adjusted for confounding factors and for effect modification
by age.
Main Outcome Measures Number of excess deaths in 2000 associated with given BMI levels.
Results Relative to the normal weight category (BMI 18.5 to <25), obesity
(BMI ≥30) was associated with 111 909 excess deaths (95% confidence
interval [CI], 53 754-170 064) and underweight with 33 746
excess deaths (95% CI, 15 726-51 766). Overweight was not associated
with excess mortality (−86 094 deaths; 95% CI, −161 223
to −10 966). The relative risks of mortality associated with obesity
were lower in NHANES II and NHANES III than in NHANES I.
Conclusions Underweight and obesity, particularly higher levels of obesity, were
associated with increased mortality relative to the normal weight category.
The impact of obesity on mortality may have decreased over time, perhaps because
of improvements in public health and medical care. These findings are consistent
with the increases in life expectancy in the United States and the declining
mortality rates from ischemic heart disease.
As the prevalence of obesity increases in the United States,1,2 concern about the association of body
weight with excess mortality has also increased. However, estimating deaths
attributable to overweight and obesity in the US population raises complex
methodologic issues.3,4 In several
previous studies,5-7 relative
risk estimates from epidemiologic cohort studies were combined with estimates
of the prevalence of overweight and obesity from national surveys to calculate
the fraction of deaths attributable to overweight and obesity. It is important
to adjust relative risk estimates for confounding factors such as age and
smoking that are associated with obesity and mortality.8,9 When
relative risks are adjusted for confounding factors, the use of properly adjusted
estimators of attributable risk is necessary to avoid bias.8,9
Previous estimates5,7 of
deaths associated with obesity in the United States used adjusted relative
risks in an attributable fraction formula appropriate only for unadjusted
relative risks and thus only partially adjusted for confounding factors, did
not account for variation by age in the relation of body weight to mortality,
and did not include measures of uncertainty in the form of SEs or confidence
intervals (CIs). Previous estimates used data from a variety of studies to
estimate relative risks, but the studies had some limitations. Four of 6 included
only older data (2 studies ended follow-up in the 1970s and 2 in the 1980s),
3 had only self-reported weight and height, 3 had data only from small geographic
areas, and 1 study included only women. Only 1 data set, the National Health
and Nutrition Examination Survey (NHANES) I, was nationally representative.
The objective of this study was to estimate deaths associated with underweight,
overweight, and obesity in the United States in 2000 by using all available
mortality data from the NHANES and to offer an assessment of the uncertainty
of those estimates.
We used a different approach from that used previously. Our method was
derived from the methods used with theGail model10,11 for
predicting breast cancer risk. This method allows us to account for confounding
and effect modification, and we provide SEs for the estimates. We also use
only data from nationally representative samples with measured heights and
weights. We use this approach to make estimates of excess deaths associated
with different levels of body weight in the United States in 2000.
All data in this report come from the series of NHANES surveys conducted
by the National Center for Health Statistics. In each survey, a different
nationally representative cross-sectional sample of the US population was
interviewed and examined. To estimate relative risks, we used baseline data
from NHANES I (1971-1975), NHANES II (1976-1980), NHANES III (1988-1994),
and the subsequent mortality data through 1992 for NHANES I and NHANES II
and through 2000 for NHANES III.12-18 Data
from NHANES 1999-2002 were used to estimate the current distribution of body
mass index (BMI) and other covariates. In each survey, height and weight were
measured with standardized procedures. Body mass index was calculated as weight
in kilograms divided by the square of height in meters.
We calculated relative risks (hazard ratios) using Cox proportional
hazard models with age as the time scale.19 Because
the proportional hazards assumption was not met across age, for each survey
we divided the data into 3 age strata: 25 to younger than 60 years, 60 to
younger than 70 years, and 70 years or older and fit models separately within
each age stratum. According to federal guidelines,20 a
normal weight for adults is defined as a BMI from 18.5 to less than 25, overweight
as a BMI 25 to less than 30, and obesity as a BMI of 30 or greater, divided
into grade 1 (BMI 30 to <35), grade 2 (35 to <40) and grade 3 (BMI 40
or greater) obesity. For analysis, we grouped BMI as follows: less than 18.5,
18.5 to less than 25 (reference category), 25 to less than 30, 30 to less
than 35, and 35 or greater. In this report, we use the term underweight for BMI less than 18.5. The final model included BMI categories,
sex (male, female), smoking status (never, former, current), race (white,
black, other), and alcohol consumption categories (0, <0.07, 0.07 to <0.35,
≥0.35 oz/d). Race and ethnicity were assessed by interviewer observation
or self-report in NHANES I and II and by self-report in NHANES III and NHANES
1999-2002. For NHANES 1999-2002, no separate race variable
was available, and for analytic purposes non-Hispanic whites, Mexican Americans,
and other Hispanics were grouped together as “white,” non-Hispanic
blacks were considered “black,” and all others, including multiracial
participants, were grouped as “other.”
To calculate the proportion of deaths in 2000 attributable to each BMI
level, we first calculated the relative risks from the NHANES I, NHANES II,
and NHANES III mortality studies and from a data set that combined data from
all 3 surveys. Estimates were made from the combined data to obtain more precision
and to represent the US population during the 20-year period covered by these
surveys. We then applied each set of relative risks in turn to the current
distribution of the covariates (BMI group, sex, smoking status, race, and
alcohol consumption) in the general population, which was estimated from the
NHANES 1999-2002 cross-sectional survey data.
Within each survey and age group, we calculated the relative risk ri corresponding to each combination, i, of BMI level and the levels of the other covariates.
From the NHANES 1999-2002 cross-sectional survey data, we estimated the corresponding
prevalence of the risk-factor combination, pi.
The mortality rate for a given age group is R = I∑ripi, where I is the population baseline mortality rate and the sum is over all
risk-factor combinations. We calculated ri*
as the “counterfactual” relative risk in which the BMI level is
set to the reference level but all other risk factors for each participant
are left unchanged. The hypothetical counterfactual mortality rate from moving
all participants to the reference-weight category is R* = I∑ri*pi. The proportion of deaths attributable to non–reference-weight
categories was calculated as (R−R*)/R . Because the factor I cancels out, the
attributable fraction depends only on the relative risks and prevalences of
the covariates. R and R* were
adjusted to represent the general population parameters by taking the sample
weighting into account. This approach accounts for confounding by all covariates
in the model.
The estimated number of excess deaths associated with a given BMI level
and age group was then calculated by multiplying the total number of deaths
for that age group in 2000 by the attributable fraction for that BMI level.
In 2000, there were 397 341 deaths in the 25- to 59-year-old group, 315 834
deaths in the 60- to 69-year-old group, and 1 618 086 deaths in
the 70 years and older group.21 Standard errors
for estimates of number of attributable deaths were calculated by applying
a delta method for complex sample designs.22,23 This
method takes into account uncertainties in the relative risks, the distribution
of BMI, the distribution of covariates, and the estimated effects of covariates
and accounts for the added variability caused by the complex sample designs
of the NHANES surveys. Two-sided 95% CIs were computed according to normal
theory approximation.
Data were analyzed using the SAS System for Windows (release 9.1; SAS
Institute Inc, Cary, NC) and SUDAAN (release 9.0; Research Triangle Institute,
Research Triangle Park, NC) software programs. All analyses included sample
weights that account for the unequal probabilities of selection because of
oversampling and nonresponse. All variance calculations incorporate the sample
weights and account for the complex sample design. We replicated the main
analyses with 2 separate SAS programs written independently by 2 of us (K.M.F.,
B.I.G.). Variance calculations were checked using jackknife resampling.
Descriptive data for the 3 survey cohorts are shown in Table 1. The numbers of deaths in the 3 cohorts were 3923, 2133,
and 2793, for a total of 8849 deaths. Estimated relative risks are shown in Figure 1 by BMI category, age group, and survey,
and relative risks from the combined data set and their SEs are shown in Table 2. Obesity (BMI ≥30) was associated
with increased risk, particularly at the younger ages; the relative risks
were lower in the oldest group. The relative risk in the overweight category
(BMI 25 to <30) was low, often below 1. Relative risks in the underweight
category usually exceeded unity (1.00). Relative risks were generally modest,
in the range of 1 to 2 in most cases. The prevalence of BMI levels in NHANES
1999-2002 is shown in Table 3.
Estimated numbers of excess deaths in 2000 in the United States, relative
to the reference BMI category of 18.5 to less than 25, are shown by survey
and BMI category (Figure 2). All estimates
are based on the covariate distribution from NHANES 1999-2002 and the number
of deaths in 2000 from US vital statistics data.21
Estimates based on relative risks from each of the 3 surveys showed
a similar pattern, with excess deaths greater than zero for the underweight
category, less than zero for the overweight category, and increasing at higher
BMI levels. Although the prevalence of BMI 35 or greater is low (Table 3), that category accounted for the largest
absolute number of estimated excess deaths in 2000, regardless of which survey
served as the source of relative risks.
The estimates of excess deaths associated with obesity (BMI ≥30)
were calculated from the distribution of BMI and other covariates in NHANES
1999-2002; however, these estimates vary according to the source of the relative
risk estimates. Excess deaths associated with obesity (BMI ≥30) were calculated
as 298 808 according to the NHANES I relative risks, 26 917 according
to the NHANES II relative risks, or 43 650 according to the NHANES III
relative risks. In all 3 cases, however, the majority of deaths associated
with obesity were associated with BMI 35 and above: 186 498, 21 777,
or 57 515 deaths, respectively. (NHANES III relative risks produced a
negative estimate for BMI 30 to <35.) For overweight (BMI 25 to <30),
the data consistently suggested no excess deaths overall: −14 354,
−171 945, or −99 979 excess deaths according to the
relative risks from each of the 3 surveys. For underweight (BMI <18.5),
the relative risks from all surveys suggested a slight increase in risk. The
estimated excess deaths associated with underweight were 41 930, 19 618,
or 38 456.
Using relative risks from the combined survey data, we estimated that
111 909 excess deaths in 2000 (95% CI, 53 754 to 170 064) were
associated with obesity (BMI ≥30) (Figure 2). Of the excess deaths associated with obesity, the majority (82 066
deaths; 95% CI, 44 843 to 119 289) occurred in individuals with
BMI 35 or greater. Overweight was associated with a slight reduction in mortality
(−86 094 deaths; 95% CI, −161 223 to −10 966)
relative to the normal weight category. Thus, for overweight and obesity combined
(BMI ≥25), our estimate was 25 814 excess deaths (95% CI, −86 284
to 137 913) in 2000, arrived at by adding the estimate for obesity to
the estimate for overweight. Underweight was associated with 33 746 excess
deaths (95% CI, 15 726-51 766).
Of the 111 909 estimated excess deaths associated with obesity
(BMI ≥30), the majority, 84 145 excess deaths, occurred in individuals
younger than 70 years. In contrast, of the 33 746 estimated excess deaths
associated with underweight, the majority, 26 666 excess deaths, occurred
in individuals aged 70 years and older.
We explored the effect of using different models with additional terms
and interaction terms. Models with only sex, BMI, and smoking were fitted,
as were models that used, in addition, race, alcohol, educational level, and
height, as well as interactions of BMI group with sex, race, or smoking. Although
some of these terms had coefficients that were statistically significantly
different from zero within 1 or more subgroups, the effect on the parameter
of interest (excess deaths) was not large, and the broad pattern of results
did not change. The highest number of deaths associated with BMI 30 or greater
was 137 696 for the simplest model, which included only sex, BMI, and
smoking; the lowest number was 79 449 for a more complex model that included
all listed variables and an interaction of smoking with BMI group.
We chose to use the NHLBI “normal weight” category of 18.5
to less than 25 as the reference category. The effect of using other reference
BMI categories was also explored. Across the reference categories 18.5 to
less than 25, 21 to less than 25, and 23 to less than 25, the estimated number
of excess deaths associated with BMI 30 or greater was 111 909, 129 148,
and 164 836, respectively, and the number of excess deaths associated
with a BMI less than the reference category was 33 746, 45 784,
and 81 705. Thus, using a reference category of 23 to less than 25 rather
than the normal weight category would result in increased estimates of excess
deaths for low weight and for obesity.
We undertook additional analyses to examine whether our estimates of
excess deaths might have been affected by factors such as length of follow-up,
weight stability, weight loss caused by illness, or smoking status. The purpose
of these analyses was not to make statistical comparisons between relative
risks but to assess the direction and possible magnitude of any effects of
these factors on estimated excess deaths. To examine whether the higher relative
risks in NHANES I might be due to the longer follow-up in NHANES I, we compared
the relative risks from the first phase of NHANES I through the 1982-1984
follow-up with the relative risks from NHANES II and III. Thus, the follow-up
period was similar for all surveys (≈10 years for NHANES I, ≈14
years for NHANES II, ≈9 years for NHANES III). The NHANES I relative
risks over the first 10 years of follow-up were higher in almost every BMI-age
subgroup than were the relative risks from the other surveys (data not shown).
Thus, even after controlling for length of follow-up, NHANES I tended to have
higher relative risks than the other surveys.
In NHANES I, the relative risks through 1992 associated with weights
measured in the 1982-1984 follow-up were almost always lower (in 14 of 15
subgroups) than the relative risks from 1971-1975 through the 1982-1984 follow-up,
suggesting a possible decrease in relative risks over time, although the differences
were small (data not shown). To examine whether the increased relative risks
at lower BMI levels might be related to possible weight loss associated with
illness and increased mortality, which could also have decreased the relative
risks associated with overweight and obesity, we repeated analyses excluding
the first 3 or the first 5 years of deaths and found little change in the
relative risk estimates (data not shown). We also repeated analyses including
only individuals who never smoked and found that the elevated relative risks
for the lowest BMI category persisted and that other relative risks were not
systematically different (Table 2).
To assess the longer-term effects of a given weight, excluding possible
effects of major weight gains or losses, we repeated the NHANES I analyses
for a subgroup of participants whose weight had not changed by more than 2
kg between baseline (1971-1975) and 1982-1984, looking at mortality from the
1982-1984 follow-up through 1992. In these analyses, the relative risks did
not differ systematically from the whole group (6 higher and 6 lower) and
differences were slight (data not shown). Overweight (BMI 25 to <30) that
had persisted for at least 10 years was still associated with no excess risk,
and underweight was still associated with an increased relative risk. Taken
together, these analyses suggest that differences in length of follow-up,
weight loss because of underlying illness, or confounding by smoking status
did not have a major impact on our estimates of excess deaths.
Our results show increased mortality associated with underweight and
with obesity, particularly with higher levels of obesity, relative to the
normal weight category. Our results are lower than previous estimates.5,7 Differences in statistical methods
account for some of the differences. Our method of estimation accounts more
fully for confounding and for effect modification by age than the partially
adjusted method used in previous estimates. When applied either to NHANES
I data or to the combined data set, our method yielded results that were more
than 20% lower than when the partially adjusted method was applied to the
same data with the same reference category and the same covariates. However,
the largest difference is due to the inclusion of the mortality data from
NHANES II and NHANES III, which decreased estimates by 63% or more relative
to NHANES I mortality data alone. It would be useful to know whether similar
secular patterns are detectable in other cohorts that span recent decades.
Relative to NHANES I, the more recent data from NHANES II and NHANES
III suggest the possibility that improvements in medical care, particularly
for cardiovascular disease, the leading cause of death among the obese, and
its risk factors may have led to a decreased association of obesity with total
mortality. Cardiovascular risk factors have declined at all BMI levels in
the US population, but, except for diabetes, the decline appears to be greater
at higher BMI levels.24 These findings are
consistent with the increases in life expectancy in the United States and
with the declining mortality rates from ischemic heart disease. Life expectancy
increased from 73.7 years in 1980 to 75.4 years in 1990 to 77.0 years in 2000
and continues to increase.25 Age-adjusted death
rates (per 100 000 population) for ischemic heart disease declined from
345.2 in 1980 to 249.6 in 1990 to 186.6 in 2000 and continue to decline.25
The methods used in our study to estimate deaths attributable to obesity
have several strengths. Our method accounts for confounding by all factors
included in the Cox proportional hazards model, as well as for modification
by age of the effect of obesity on mortality. Moreover, the NHANES surveys
are nationally representative, and the heights and weights of cohort members
were measured, rather than based on self-reports. Our design-based survey
methods applied to the NHANES data yielded unbiased population estimates and
estimates of SEs.
Our approach for estimating the number of deaths attributable to obesity
has important limitations, however. Like earlier estimates, our estimates
are based on assumptions that may not hold in practice. The key assumption
is that relative risks calculated from past cohorts apply to the current population.
The measured values of weight and height in NHANES I, II, and III are more
accurate than the self-reported values in some other studies. Nonetheless,
our covariate data are subject to measurement error and faulty reporting.
Because of errors in confounder measurements, our estimates of relative risks
for BMI categories may be subject to residual confounding. As in most studies,
our data on smoking were based on self-reports and may be subject to error,
especially in NHANES I in which much of the smoking data were gathered retrospectively.26 Serum cotinine data from NHANES III, however, showed
that misclassification by self-reported smoking status was low in that survey.27 Bias may also result from failure to control for
unknown confounders that are associated with body weight and mortality.
We used the current federal definitions of overweight and obesity, which
are based only on BMI, not on body composition. Our estimates give numbers
of excess deaths associated with different levels of body weight, but the
associations are not necessarily causal. Even if body weights were reduced
to the reference level, risks might not return to the level of the reference
category. Other factors associated with body weight, such as physical activity,
body composition, visceral adiposity, physical fitness, or dietary intake,
might be responsible for some or all of the apparent associations of weight
with mortality. Additional investigation of the effects of body composition
and visceral adiposity on mortality would be of interest.
The attributable fraction is a nonlinear function of relative risk and
changes rapidly at low levels of relative risk. For example, in a hypothetical
population in which the prevalence of obesity (BMI ≥30) was 30% and there
were 2 million deaths per year, the attributable fraction for unadjusted relative
risks of 1.2, 1.4, or 1.6 would translate into 113 000, 214 000,
or 305 000 deaths per year, a difference of about 100 000 deaths
for a slight change in relative risk.
Obesity is associated with a modestly increased relative risk of mortality,
often in the range of 1 to 2. In this range, estimates of attributable fractions,
and thus numbers of deaths, are very sensitive to minor changes in relative
risk estimates.3 Thus, results are affected
by the precision and bias in relative risk estimates. Additional precision
might be gained from larger cohort studies, but bias because of nonrepresentative
samples and the use of self-reported weight and height could lead to less
accurate estimates. Because our goal is to estimate deaths associated with
obesity in the US population, rather than in a subgroup, nationally representative
data are preferable as a source of relative risk estimates appropriate for
the whole population.3
Some have argued that it takes 15 years or more for obesity to have
its full impact on cardiovascular mortality.28 We
did not examine cardiovascular mortality specifically. However, the relative
risks for total mortality in weight-stable individuals in the latter part
of the NHANES I follow-up were similar to relative risks in the earlier follow-up
period. There is some question as to the optimal length of follow-up: the
longer the follow-up, the longer the interval between the event and the BMI
measurement and the higher the probability of misclassification.29 Across
the 6 cohorts used by Allison et al,5 there
was no relation between the length of follow-up in a cohort and the relative
risks in that cohort. Thus, this issue requires further study.
Neither analyses of weight-stable participants nor analyses excluding
early mortality suggest that illness-induced weight loss had an important
impact on estimates of excess deaths. Estimates of relative risks for BMI
categories were little changed by such exclusions, and, in particular, there
was little change in the relative risk associated with the underweight and
overweight categories. More studies are needed to explore the possible impact
of baseline health status and other possible confounders.
In our analysis, we did not find overweight (BMI 25 to <30) to be
associated with increased mortality in any of the 3 surveys. Our results are
similar to those of a previous analysis of NHANES I and II data that found
little effect of overweight on life expectancy.30 Our
finding is consistent with other results reported in the literature, although
methodologic differences often preclude exact comparisons. In many studies,
a plot of the relative risk of mortality against BMI follows a U-shaped curve,
with the minimum mortality close to a BMI of 25; mortality increases both
as BMI increases above 25 and as BMI decreases below 25,31 which
may explain why risks in the overweight category are not much different from
those in the normal weight category. Some studies have found that overweight
was associated with a slightly increased risk of total mortality compared
with the normal weight category.32-34 Other
studies have suggested that overweight (BMI 25 to <30) is associated with
no excess mortality, particularly in older age groups.35-37,39 Further
investigation of the effects of overweight on mortality, particularly in the
elderly, and of the possible role of confounding would be of interest.
We did not examine other health problems caused by obesity. A recent
population-based study has found that overweight and obesity have a strong
and deleterious impact on important components of health status, including
morbidity, disability, and quality of life, and this impact is disproportionately
borne by younger adults.40 Nor did we examine
cause-specific mortality. Overweight and obesity may be more strongly associated
with cardiovascular mortality than with total mortality.41
The differences between NHANES I and the later surveys suggest that
the association of obesity with total mortality may have decreased over time,
perhaps because of improvements in public health or medical care for obesity-related
conditions. However, such speculation should be tempered by the awareness
that these differences between surveys may simply represent chance variation
and that small differences in relative risk translate into large differences
in the numbers of deaths.
Corresponding Author: Katherine M. Flegal,
PhD, National Center for Health Statistics, Centers for Disease Control and
Prevention, 3311 Toledo Rd, Room 4311, Hyattsville, MD 20782 (kflegal@cdc.gov).
Author Contributions: Dr Flegal had
full access to all of the data in the study and takes responsibility for the
integrity of the data and the accuracy of the data analysis.
Study concept and design: Flegal, Williamson.
Acquisition of data: Flegal, Graubard.
Analysis and interpretation of data: Flegal,
Graubard, Williamson, Gail.
Drafting of the manuscript: Flegal, Graubard,
Williamson, Gail.
Critical revision of the manuscript for important
intellectual content: Flegal, Graubard, Williamson, Gail.
Statistical analysis: Graubard, Gail.
Financial Disclosures: None reported.
Funding/Support: Partial salary suport for
Dr Flegal was provided by the US Army Research Institute of Environmental
Medicine.
Role of the Sponsor: All data used in this
study were collected by the National Center for Health Statistics, Centers
for Disease Control and Prevention. The Centers for Disease Control and Prevention
and the National Cancer Institute reviewed and approved this report before
submission. The US Army Research Institute of Environmental Medicine had no
role in this study.
Acknowledgment: We acknowledge Christine S.
Cox, MA, for her assistance with the NHANES III mortality data and Cheryl
Fryar, MSPH, for her capable programming assistance.
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