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Body Weight and Health Care Among Women in the General Population


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To examine the relation between body mass index ([BMI] calculated as weight in kilograms divided by the square of height in meters) and the use of medical care services among a nationally representative sample of women. Multistage cluster-area probability sampling survey. Data are from the Cancer Control and Health Insurance supplements of the 1992 National Health Interview Survey conducted by the National Center for Health Statistics. Respondents were 6981 women aged 18 years or older residing in the United States who self-reported sociodemographic information and the use of health care services. Interval (< or = 3 years vs > 3 years) since most recent mammography, clinical breast examination, gynecologic examination, and Papanicolaou smear and the number of physician visits in the year before the survey. When age, race, income, education, smoking, and health insurance status were adjusted for, the BMI was directly related to delaying clinical breast examinations, gynecologic examinations, and Papanicolaou smears. Obese women (BMI of 35) were more likely than nonobese women (BMI of 25) to delay clinical breast examinations (odds ratio, 1.26; 95% confidence interval, 1.00-1.58), gynecologic examinations (odds ratio, 1.39; 95% confidence interval, 1.15-1.69), and Papanicolaou smears (odds ratio, 1.29; 95% confidence interval, 1.04-1.58). The BMI was not significantly related to delays in mammography. It was also related to increased physician visits (P = .001). Among women, an increased BMI is associated with decreased preventive health care services, which may exacerbate or even account for some of the increased health risks of obesity.
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Body Weight and Health Care Among
Women in the General Population
Kevin R. Fontaine, PhD; Myles S. Faith, PhD; David B. Allison, PhD; Lawrence J. Cheskin, MD
Objective: To examine the relation between body mass
index ([BMI] calculated as weight in kilograms divided
by the square of height in meters) and the use of medi-
cal care services among a nationally representative sample
of women.
Design and Setting: Multistage cluster-area probabil-
ity sampling survey. Data are from the Cancer Control
and Health Insurance supplements of the 1992 National
Health Interview Survey conducted by the National Cen-
ter for Health Statistics. Respondents were 6981 women
aged 18 years or older residing in the United States who
self-reported sociodemographic information and the use
of health care services.
Main Outcome Measures: Interval (#3 years vs .3
years) since most recent mammography, clinical breast
examination, gynecologic examination, and Papanico-
laou smear and the number of physician visits in the year
before the survey.
Results: When age, race, income, education, smoking,
and health insurance status were adjusted for, the BMI
was directly related to delaying clinical breast examina-
tions, gynecologic examinations, and Papanicolaou
smears. Obese women (BMI of 35) were more likely than
nonobese women (BMI of 25) to delay clinical breast ex-
aminations (odds ratio, 1.26; 95% confidence interval,
1.00-1.58), gynecologic examinations (odds ratio, 1.39;
95% confidence interval, 1.15-1.69), and Papanicolaou
smears (odds ratio, 1.29; 95% confidence interval, 1.04-
1.58). The BMI was not significantly related to delays in
mammography. It was also related to increased physi-
cian visits (P = .001).
Conclusion: Among women, an increased BMI is asso-
ciated with decreased preventive health care services,
which may exacerbate or even account for some of the
increased health risks of obesity.
Arch Fam Med. 1998;7:381-384
BESITY IS a major public
health problem in the
United States, with ap-
proximately 35% of
American women classi-
fied as overweight.
These women are at an
increased risk for diseases of many organ
systems, including some forms of cancer.
Indeed, obese women (body mass index
[BMI], calculated as weight in kilograms di-
vided by the square of height in meters, of
$35) have been shown to have signifi-
cantly higher rates of cervical, endome-
trial, ovarian, gallbladder, and breast can-
cers than nonobese women.
Although the
association between weight and certain
forms of cancer among women is strong,
other factors (eg, family history, age, smok-
ing status, and body fat distribution) ap-
pear to play an important role in determin-
ing cancer risk.
Nonetheless, the increased
cancer risk associated with obesity under-
scores the importance of preventive health
care examinations for obese women.
The examinations that were investi-
gated in this study (eg, mammography,
breast clinical examination, gynecologic ex-
amination, and Papanicolaou [Pap] smear
test) are critical strategies for the early de-
tection and treatment of some forms of can-
cer among women and form an important
element of the national health promotion
and disease prevention objectives contained
in Healthy People 2000.
It is estimated that
regular Pap smear tests followed by appro-
priate treatment could prevent nearly all
deaths from cervical cancer, and screening
mammography followed by timely treat-
ment could reduce the breast cancer mor-
tality by 30% for women aged 50 to 69
Some evidence exists, however, that
obese women delay or avoid medical and
preventive care services.
For editorial comment
see page 385
From the Division of
Gastroenterology, Department
of Medicine, The Johns Hopkins
University School of Medicine,
and The Johns Hopkins
Bayview Medical Center,
Baltimore, Md (Drs Fontaine
and Cheskin); and the Obesity
Research Center,
St Luke’s-Roosevelt Hospital,
Columbia University College
of Physicians and Surgeons,
New York, NY (Drs Faith
and Allison).
©1998 American Medical Association. All rights reserved.
at Johns Hopkins University, on October 27, 2008 www.archfammed.comDownloaded from
The purpose of this study was to examine the rela-
tion between the BMI and both the frequency of physi-
cian visits and the use of preventive health care services
among a nationally representative sample of women, ad-
justing for age, sociodemographic characteristics, smok-
ing, and health insurance status.
Selected characteristics of respondents are shown in Table
1. The mean age of the women was 46.2 years (median,
42 years), with a range of 18 to 97 years (3 women were
$99 years, but their actual age was not specified). The
mean number of physician visits in the 12 months be-
fore completing the survey was 5.35 (median, 2). Nearly
70% of the women reported having some form of health
Of the 3105 women who answered the question
regarding the interval since their last mammography,
2657 indicated that it had been less than 3 years, and
448 reported that it had been more than 3 years. Of
the 4926 women who answered the question about
clinical breast examination, 4162 reported having had
1 less than and 764 more than 3 years before the sur-
vey. For gynecologic examination, of the 5924 women
who answered the question, 4416 reported having had
1 less than and 1508 more than 3 years before the sur-
vey. Finally, of the 6314 women who answered the
question regarding the interval since last Pap smear,
5126 reported having had 1 less than and 1188 more
than 3 years before the survey.
In the linear regression analysis adjusted for age, race,
education, family income, smoking status, and health in-
surance status, the BMI was associated with increased phy-
sician visits in the 12 months before completing the sur-
vey (b = .063, P = .002). That is, for every 1-unit increase
in the BMI, there was, on average, a 0.063-unit increase
in visits to a physician.
The fully adjusted odds ratios for having delayed
mammography, clinical breast examination, gyneco-
logic examination, and Pap smear testing (each for .3
years) as a function of the BMI are shown in
Table 2.
The BMI was directly related with a reduced probability
of having had a clinical breast examination (P = .04), gy-
necologic examination (P = .001), and Pap smear (P = .02)
in the previous 3 years. The BMI was not significantly
related to delays in mammography (P = .20). No evi-
dence of a nonlinear effect for the BMI was seen (ie, the
The data sources used were the 1992 National Health In-
terview Survey (NHIS), Cancer Control and Health Insur-
ance supplements, conducted by the National Center for
Health Statistics of the Centers for Disease Control and Pre-
vention, Atlanta, Ga.
The NHIS is a continuing annual per-
sonal interview survey of approximately 49 000 house-
holds in the civilian noninstitutionalized US population aged
18 years or older selected through a multistage cluster-
area probability sampling design. Data are collected on per-
sonal, sociodemographic, and health-related information
of family members and unrelated persons living in these
The Cancer Control Supplement to the 1992 NHIS was
administered to a randomly selected subsample of 12 035
adult respondents. The response rate was 87%. The survey
ascertained information on health-related knowledge and at-
titudes, as well as the use of health care services. Because
our interest was in characteristics associated with delayed
preventive health care among women, analyses were re-
stricted to female respondents (N = 6981). To include health
insurance status as a covariate in the analyses, subjects’ re-
cords were linked with their corresponding responses in the
Health Insurance Supplement to the 1992 NHIS.
Self-reported weight and height data were used to com-
pute the BMI for each respondent. Self-reported weight is
highly correlated with measured weight.
The BMI is largely
independent of height (r = 0.03), strongly related to weight
(r = 0.86), and a reasonable measure of body fatness.
The covariates examined in these analyses were those
that might influence the use of health care: age, race (non-
white or white), family income, education (years com-
pleted), smoking status (nonsmoker-former smoker or cur-
rent smoker), and health insurance status (not covered or
unknown or covered by private insurance, Medicare, or both).
The outcome measures were the number of physician
visits in the 12 months before completing the survey and the
interval since the most recent use of the following preven-
tive health care procedures: mammography, clinical breast
examination, gynecologic examination, and Pap smear. The
interval since the most recent procedure was defined by the
NHIS as follows: within the past year, 1 to 3 years ago, more
than 3 years ago, unknown specific interval (#3 years vs .3
years), not ascertained or don’t know, or unknown or re-
fused. These responses were recoded and treated as dichoto-
mous variables: 0 indicates 3 years or less; and 1, greater than
3 years. Responses coded as unknown or not ascertained were
treated as missing variables and excluded from the analysis.
Multiple linear regression analysis was used to exam-
ine the relation between the BMI and the number of physi-
cian visits in the 12 months before completing the survey,
adjusting for the previously mentioned covariates. Logistic
regression analyses were used to examine whether the BMI
was related to delaying each of the 4 preventive care proce-
dures after controlling for the influence of the covariates. Af-
ter testing for linear effects (on the logit level), tests for non-
linear effects were conducted by adding the BMI squared to
the model. Finally, because of the heterogeneous age range
of this sample (
Table 1), interactions between the BMI and
age for each outcome variable were also tested.
Data were also tested by treating the BMI categorically
(quintiles). These results did not differ substantially from
analyses that treated the BMI as a continuous variable. There-
fore, given the advantages of using continuous variables in
epidemiological studies,
we report analyses that treated the
BMI as continuous. Separate odds ratios were computed for
BMIs of 35 and 40 relative to a BMI of 25 (the sample mean)
to estimate the relative odds of delaying care by obese and
severely obese women, respectively. Variability in sam-
pling associated with the estimated odds ratios was
assessed by 2-sided 95% confidence intervals, with P,.05
(2-tailed) considered statistically significant.
©1998 American Medical Association. All rights reserved.
at Johns Hopkins University, on October 27, 2008 www.archfammed.comDownloaded from
BMI-squared term was not significant when it was added
to the models), and no significant interactions occurred
between the BMI and age for any of the outcome mea-
sures. Furthermore, there was no independent associa-
tion or trend between race and health care use.
These data support a direct relationship between the BMI
and an increased number of physician visits after age, race,
income, education, smoking status, and health insur-
ance status were taken into account. Thus, as the BMI
increased, the frequency of physician visits also in-
creased. Compared with women of average relative body
weight (BMI of 25), however, obese and severely obese
women were significantly more likely to delay clinical
breast examinations, gynecologic examinations, and Pap
smear testing, suggesting that body weight may play a
role in delaying these forms of preventive health care.
Thus, although obese women visit physicians more fre-
quently and, presumably, are prompted to undergo pre-
ventive services, they also appear to be the least likely to
use these services. Given their increased health risks, the
absolute decrease in preventive services is clearly inap-
propriate for this population.
Obesity may make women less likely to seek pre-
ventive health care, especially for procedures (eg, pelvic
examination) that involve disrobing and manual ma-
nipulation of their bodies.
This may explain why obe-
sity did not associate with delays in mammography, as
this procedure is less personally invasive and involves less
direct physical contact with a health care practitioner.
Delays in preventive health care might also occur be-
cause obesity may dissuade physicians from suggesting
or performing certain procedures, particularly pelvic ex-
Physicians may be dissuaded by the tech-
nical difficulties associated with performing gyneco-
logic examinations of obese women.
Apart from the
difficulties physicians encounter when performing gy-
necologic procedures on obese women, they are also less
likely to perform such procedures on reluctant pa-
Thus, the association between body weight and
reluctance to undergo preventive health care examina-
tions may be mediated by attitudes toward one’s appear-
ance, discomfort with the procedures themselves, or the
nature of the interaction with the clinician.
because obese women are more likely than nonobese
women to make physician visits, preventive services may
be of a lower priority for them.
Given the correlational nature of this study, it can-
not be presumed that the “causal” source of the ob-
served association lies with the women. The delay may
be initiated by the women, health care providers, or some
unmeasured covariate of obesity. For example, perhaps
associated disorders such as arthritis prohibit preven-
tive health care screening. Further investigations using
alternative designs will be fundamental in determining
possible causal pathways.
This study has some limitations. First, weights
and heights were not measured but were self-reported.
Second, respondents were asked to recall the number
of physician visits in the previous 12 months and the
intervals since their most recent use of health care ser-
vices. The accuracy of recall cannot be verified and
provides another possible source of bias. Furthermore,
the reasons for the physician visits are not known.
Finally, because these data were obtained from an
observational study, the associations observed could
be due to residual confounding or confounding from
unmeasured variables.
The effect of obesity on cervical, ovarian, endo-
metrial, and breast cancer mortality among women is
well documented.
If detected early, however, many
of these cancers might be successfully treated.
Therefore, screening tests for this high-risk population
are of particular importance. As this study illustrates,
although obese women visit physicians more often
than nonobese women, they appear less likely to use
preventive health care services. Delays in the use of
these services may account for some of the increased
risk of mortality from these cancers.
Table 1. Selected Characteristics of Respondents
Characteristic Respondents, No. Value*
Age, y 6981 46.2 ± 18.6
White race, % 6981 79.9
Weight, kg 6981 69.8 ± 26.5
Height, cm 6964 163.1 ± 7.1
Body mass index, weight (kg)/
[height (m)]
6805 25.1 ± 5.4
Physician visits 6947 5.3 ± 14.4
Married, % 6974 50.2
Education level, %
,12 y
12 y 6960 37.9
.12 y 38.7
Family income, %
,$20 000
$20 000-$40 000 5745 29.3
.$40 000 28.2
Smoking status, %
Former or nonsmoker
Current smoker 55.6
Health insurance, %
Not covered or unknown 32.2
Values are expressed as mean ± SD unless otherwise indicated.
Table 2. Adjusted Odds Ratio for Delaying
Mammography, Clinical Breast Examinations,
Gynecologic Examinations, and Papanicolaou Smears
According to Body Mass Index (BMI)*
Form of Preventive
Health Care
Obese (BMI of 35)
(n = 203)
Severely Obese
(BMI of 40) (n = 135)
Mammography 0.81 (0.59-1.12) 0.73 (0.45-1.19)
Clinical breast examination 1.26 (1.00-1.58)† 1.42 (1.00-1.99)†
Gynecologic examination 1.39 (1.15-1.69)† 1.63 (1.23-2.19)†
Papanicolaou smear 1.29 (1.04-1.58)† 1.46 (1.07-1.98)†
Data are given as odds ratio (95% confidence interval). Odds ratios are
relative to the average BMI, calculated as weight (kg)/[height (m)]
sample (25.1). Odds ratios have been adjusted for age, race, education,
income, smoking status, and health insurance status.
Significantly different from 1.00 (
©1998 American Medical Association. All rights reserved.
at Johns Hopkins University, on October 27, 2008 www.archfammed.comDownloaded from
An interesting finding was the discrepant results for
mammography vs breast examinations because these tests
are usually conducted in parallel. No clear answer ex-
ists why obesity was unrelated to delays in mammogra-
phy. Practice or referral services may underlie this dis-
sociation. Mammographies have traditionally only been
done when ordered by a physician. Perhaps once pa-
tients reach this stage of physician referral, their obesity
status no longer acts as a barrier to screening. More-
over, the incidence of patient self-referral for mammog-
raphy may be increasing in certain states. Perhaps re-
moving the physician from the referral process plays a
role in this nonsignificant finding. Further studies will
be needed to address such issues.
Given the association between the BMI and the num-
ber of physician visits, physicians may have a unique op-
portunity to present this information, alleviate fears about
the procedures, and encourage the use of preventive care
services. The already remarkably high prevalence of obe-
sity in the United States seems likely to continue or even
increase in the years to come.
Greater emphasis on pre-
ventive services has the potential to reduce the risk of a simi-
lar magnitude of increase in associated health problems.
Accepted for publication August 15, 1997.
This study was supported in part by research grants
DK26687, DK51716-01, R29DK47256-01 A1, and
T32DK37352 from the National Institutes of Health, Na-
tional Institute of Diabetes, Digestive, and Kidney Dis-
eases, Bethesda, Md.
Moonseong Heo, PhD, provided statistical assistance.
Corresponding author: Kevin R. Fontaine, PhD, De-
partment of Medicine, The Johns Hopkins University School
of Medicine, 333 Cassell Dr, Suite 1640, Baltimore, MD
21224-6805 (e-mail:
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Background: The prevalence of overweight and obesity continues to rise and is associated with increased morbidity and mortality. Weight bias is common among physicians and medical students and limits the therapeutic alliance between providers and patients with overweight and obesity. Objective: The authors sought to explore the relationship between the gross anatomy course and medical student attitudes towards weight and obesity. Design: The authors employed a mixed-methods approach consisting of semi-structured interviews and anonymous web-based surveys of first-year medical students taking gross anatomy at one USA medical school. They analyzed transcripts of interviews and free-text survey responses using a grounded theory approach and performed tests of association to investigate the relationship between demographic information, responses to multiple-choice survey questions and weight bias. Results: A total of 319 (52%) first-year medical students (2015–2018) completed the survey and 33 participated in interviews. Of survey respondents, 71 (22%) responded that the course had changed how they felt about people with overweight/obesity. These respondents were also more likely to affirm that the course had affected their views toward their own bodies (p
We have all heard people say ‘Beauty is only skin-deep’, or ‘Beauty is in the eye of the beholder’: our culture promulgates a conception of beauty as subjective, superficial, and independent of other values like moral goodness or knowledge and understanding. Yet our taste in beauty affects many aspects of our lives, sometimes playing a decisive – and often detrimental – role in areas as wide-ranging as our identity and self-esteem, our morally salient decisions, and our relationship to the environment. This presents us with a choice: we can either ignore the facts – leaving our conception of beauty unchanged and allowing our taste to influence much in our lives while either not acknowledging such influence, or perhaps seeking to reprimand it; or we can take the power of beauty seriously and seek to harmonise our taste with our values. I argue for the latter option and propose a way of bringing beauty and taste in line with what matters to us using the notion of functional beauty. Adopting this strategy, I suggest, can have a powerful – and positive – impact on our self-esteem and wellbeing, our relationship to others, as well as our attitudes towards the environment.
Background Physicians may have biases toward overweight patients which likely influences clinical judgments and can lead to disparities in patient care. An increasing number of adults are considered overweight/obese, so it is important to address these biases in training future physicians.Methods Forty-five first-year medical students participated in art museum programs and physician presentations, or were part of the control group. Four validated measures Beliefs About Obese Persons Scale, Attitudes Toward Obese Persons Scale, Fat Phobia Scale, and the Harvard Implicit Association Test (IAT) and researcher-generated questions, measured levels of bias before and after study activities.ResultsAll participants demonstrated decreased bias. ANCOVA analysis did not reveal significant differences between the experimental and control groups. However, prior to the study 75% of participants had “preference for thin individuals.” Forty percent of those participating in study activities indicated a positive change by associating more positive traits with obese body shapes, compared to 29% of the control group. Study activities were rated positively.Discussion/Conclusion The art museum was an engaging/relaxing place for reflection on body types and biases. Physicians provided important instruction for normalization/de-stigmatization of patient care. Although there were no significant findings, the study has raised questions for continuing this work. What are most effective ways/times to address weight bias within the medical school curriculum? Could this work extend to other marginalized patient groups? The diversity in art and humanities creates a rich resource for discussing viewpoints and experiences. The small number of participants and the timing/lack of focus in museum sessions are noted as limitations.
Weight stigma is pervasive and has a range of deleterious effects. Among the most promising approaches for modifying this form of stigma are cognitive dissonance and social consensus. Due to their theoretical connection, this study tested the effects of an experimental manipulation of cognitive dissonance blended with social consensus for targeting weight stigma. It also added to research investigating the effects of cognitive dissonance on weight stigma by investigating a broader range of stigma measures. Participants were university students aged 18–35 years (N = 98) who were randomly allocated to one of four experimental conditions: blended cognitive dissonance, standard cognitive dissonance, blended control or standard control. Stigma measures included the perceived characteristics of, affective reactions towards, social avoidance of, and blameworthiness attributed to a higher-weight individual, and general weight stigma. Results showed that those in the cognitive dissonance conditions reported significantly lower weight stigma than those in the non-dissonance, control conditions. Moreover, those in the blended cognitive dissonance condition with higher in-group identification reported less negative affective reactions than those with lower in-group identification. The results provide consistent support for cognitive dissonance as an approach for reducing weight stigma and some additive support for an integrated cognitive dissonance and social consensus approach.
This chapter introduces the Health at Every Size® (HAES) paradigm and highlights evidence to support a shift away from a weight-centered approach to nutrition counseling. It addresses common misconceptions about the HAES approach, summarizes some of the negative health consequences of weight stigma, and explores the accessibility of a HAES-based approach to all people. Included at the end of the chapter are practical tools for implementing a HAES-based approach as a certified nutrition professional, a case study to showcase the opportunities and challenges when implementing a HAES-based approach during an outpatient nutrition visit, and recommended HAES resources for providers and patients.
All women over age 40 should receive an annual clinical breast examination. Mammography every one to two years is recommended for all women beginning at age 50 and concluding at approximately age 75 unless pathology has been detected. It may be prudent to begin mammography at an earlier age for women at high risk of breast cancer. Although the teaching of breast self-examination is not specifically recommended at this time, there is insufficient evidence to recommend any change in current breast self-examination practices.
In the analysis of data from case-control studies, quantitative exposure variables are frequently categorized into qualitative exposure variables, such as quarters. The qualitative exposure variables may be scalar variables that take the median values of each quantile interval, or they may be vectors of indicator variables that represent each quantile interval. In a qualitative analysis, the scalar variables may be used to test the dose-response relation, while the indicator variables may be used to estimate odds ratios for each higher quantile interval versus the lowest. Qualitative analysis, implicitly and explicitly documented by many epidemiologists and biostatisticians, has several desirable advantages (including simple interpretation and robustness in the presence of a misspecified model or outlier values). In a quantitative analysis, the quantitative exposure variables may be directly regressed to test the dose-response relation, as well as to estimate odds ratios of interest. As this paper demonstrates, quantitative analysis is generally more efficient than qualitative analysis. Through a Monte Carlo simulation study, the authors estimated the loss of efficiency that results from categorizing a quantitative exposure variable by quartiles in case-control studies with a total of 200 cases and 200 controls. In the analysis of the dose-response relation, this loss is about 30% or more; the percentage may reach about 50% when the odds ratio for the fourth quartile interval versus the lowest is around 4. In estimating odds ratios, the loss of efficiency for the second, third, and fourth quartile intervals versus the lowest is around 90%, 75%, and 40%, respectively. The authors consider the pros and cons of each analytic approach, and they recommend that 1) qualitative analysis be used initially to estimate the odds ratios for each higher quantile interval versus the lowest to examine the dose-response relation and determine the appropriateness of the assumed underlying model; and 2) quantitative analysis be used to test the dose-response relation under a plausible log odds ratio model.
Since the prevalence of several risk factors for cervix uteri cancer, such as sexual activity patterns, cigarette smoking, and contraceptive use, has changed over time, the authors analyzed US trends for this cancer during the 1970s to 1980s to search for corresponding variations. Invasive cervical cancer incidence and mortality rates continued to decrease among blacks and whites, although declines are moderating or plateauing among young whites. Carcinoma in situ rates have not changed greatly or have declined, more so among blacks than whites. Excess risks among blacks are less evident among younger than older age groups. Increasing trends were seen only among whites in certain age groups or with certain histologic types. Declining trends in cervical cancer appear related to the widespread use of cervical cytologic screening programs, which have counteracted increases anticipated from changes in risk factor prevalence. Continued surveillance is warranted, however, with special attention to the trends in cervical adenocarcinoma.
The relationships of relative weight to energy intake and to physical activity were studied among 141 females aged 34-59 y. As observed in previous studies Quetelet index (wt/ht2) was inversely related to energy intake (r = -0.11). However, obese women tended to be older (r = 0.16), exercise less (r = -0.30), and drink less alcohol (r = -0.16) than nonobese women. Older women had lower energy intake (r = -0.23) and exercised less (r = -0.12) than younger women. Energy intake and physical activity were positively related (r = 0.23). After adjustment for age, physical activity, alcohol, and smoking, the inverse correlation between relative weight and energy intake was significantly reduced (p = 0.04) from r = -0.11 to r = -0.02. Obese women reported higher intakes of total fat, and relative weight was significantly correlated with intakes of total fat (r = 0.20) and saturated fatty acids (r = 0.16). These data highlight the importance of considering factors that may confound the relationship between energy intake and obesity, and they suggest that fat intake may play a role in obesity that is independent of total energy intake.
In a prospective study, mortality ratios were computed in relation to overweight, cancer, and other diseases. The study included 750 000 men and women followed for 12 years. Each person was given a weight index. Death rates for overweight and underweight persons were compared with rates for persons of average weight. Men who were 40% or more overweight had a mortality ratio for cancer of 1.33; women, 1.55. This ratio was much lower than that for coronary heart disease (men, 1.95; and women, 2.07); diabetes (5.19 and 7.90), and digestive diseases (3.99 and 2.29). Overweight men had significantly higher mortality ratios for colorectal and prostate cancer; overweight women had much higher rates for cancer of the endometrium, gall bladder, and cervix; and also significantly higher rates for ovary and breast cancer.
Screening data from the Hypertension Detection and Follow-up Program in Minneapolis, MN, 1973-1974, provided an opportunity to evaluate the accuracy of self-report of height and weight. It was found that both were reported, on the average, with small but systematic errors. Large errors were found in certain population subgroups. Also, men and women differed somewhat in their pattern of misreporting. Weight was understated by 1.6% by men and 3.1% by women, whereas height was overstated by 1.3% by men and 0.6% by women. As in previous studies, it was found that the most important correlates of the amount of error were the actual measurements of height and weight. An interesting finding was that misreporting of both height and weight in men was correlated with both aspects of body size, whereas for women, it was related mainly to the characteristic in question. Certain other demographic variables, such as age and educational level, were also found to have some importance as factors influencing misreporting.
The relation between body weight and overall mortality remains controversial despite considerable investigation. We examined the association between body-mass index (defined as the weight in kilograms divided by the square of the height in meters) and both overall mortality and mortality from specific causes in a cohort of 115,195 U.S. women enrolled in the prospective Nurses' Health Study. These women were 30 to 55 years of age and free of known cardiovascular disease and cancer in 1976. During 16 years of follow-up, we documented 4726 deaths, of which 881 were from cardiovascular disease, 2586 from cancer, and 1259 from other causes. In analyses adjusted only for age, we observed a J-shaped relation between body-mass index and overall mortality. When women who had never smoked were examined separately, no increase in risk was observed among the leaner women, and a more direct relation between weight and mortality emerged (P for trend < 0.001). In multivariate analyses of women who had never smoked and had recently had stable weight, in which the first four years of follow-up were excluded, the relative risks of death from all causes for increasing categories of body-mass index were as follows: body-mass index < 19.0 (the reference category), relative risk = 1.0; 19.0 to 21.9, relative risk = 1.2; 22.0 to 24.9, relative risk = 1.2; 25.0 to 26.9, relative risk = 1.3; 27.0 to 28.9, relative risk = 1.6; 29.0 to 31.9, relative risk = 2.1; and > or = 32.0, relative risk = 2.2 (P for trend < 0.001). Among women with a body-mass index of 32.0 or higher who had never smoked, the relative risk of death from cardiovascular disease was 4.1 (95 percent confidence interval, 2.1 to 7.7), and that of death from cancer was 2.1 (95 percent confidence interval, 1.4 to 3.2), as compared with the risk among women with a body-mass index below 19.0. A weight gain of 10 kg (22 lb) or more since the age of 18 was associated with increased mortality in middle adulthood. Body weight and mortality from all causes were directly related among these middle-aged women. Lean women did not have excess mortality. The lowest mortality rate was observed among women who weighed at least 15 percent less than the U.S. average for women of similar age and among those whose weight had been stable since early adulthood.