17 Jun WHAT INFLUENCE MIGHT THESE FINDINGS HAVE ON SOCIETAL PERCEPTIONS OF BODY IMAGE AND WEIGHT LOSS?
The calculation of Body Mass Index (BMI) is an important measurement tool for determining relative disease risk for preventable conditions like type 2 diabetes, hypertension, and heart disease. These conditions may be controlled and/or prevented by maintaining a healthy weight relative to height. For instance, the higher the BMI number above the normal range (18-25), the greater the degree of overweight. National indicators for obesity, as determined by the BMI report that women are more likely to have higher BMI’s in comparison to men. In addition, minority women including African Americans, Hispanics, and Asian Americans are more likely to have a higher BMI in comparison to white women. However, recent research suggests that current standards for measuring BMI may not be accurate for African American women. Read the article “Ethnic-Specific BMI and Waist Circumference Thresholds” and create a 4- to 5-page report in Microsoft Word document that covers the following: • Explain why the current BMI scale may not be an accurate measure of obesity for African American women. • How can these findings impact the manner in which physicians communicate with their female patients about weight loss and disease prevention? In your explanation, be sure to describe at least one positive and one negative implication that these findings might have on how physicians counsel their female patients regarding weight-loss. • What influence might these findings have on societal perceptions of body image and weight loss? • Explain how an accurate perception of body image is associated with appropriate weight-control behavior. • What social and cultural factors influence African American women’s risk of becoming obese? • What role do the media play in promoting healthy eating behaviors in women and girls? • What can be the implications for healthcare policy as a result of the findings of the study? Support your responses with examples. Cite any sources in APA format.
Reference Katzmarzyk, P. T., Bray, G. A., Greenway, F. L., Johnson, W. D., Newton, J., Robert L, Ravussin, E.. . Bouchard, C. (2011). Ethnic-specific BMI and waist circumference thresholds. Obesity, 19(6), 1272-1278. doi:10.1038/oby.2010.319
1272 VOLUME 19 NUMBER 6 | junE 2011 | www.obesityjournal.org
articles nature publishing group
Epidemiology
Introduction
The use of anthropometric measures such as BMI and waist
circumference (WC) to identify people who are at elevated
risk of developing obesity-related disorders and conditions is
currently a cornerstone of the clinical management of obesity
(1–3). The utility of BMI and WC in identifying patients at
increased obesity-related health risk is evidenced by their associations
with more direct measures of adiposity (4), chronic
disease risk factors (5–8), incidence of chronic disease (9–11),
and rates of premature mortality (12–15).
The most commonly used BMI thresholds in adults for defining
body weight status are 25 kg/m2 (overweight), and 30 kg/m2
(obesity) (1–3). Evidence that health risks accumulate at lower
levels of BMI among Asian populations has resulted in lower
clinical BMI thresholds for this group of 23 kg/m2 for moderate
to high risk and 27.5 kg/m2 for high to very high risk (16).
Formal recommendations for different BMI thresholds in
populations other than Asians have not been made; however,
levels of adiposity and obesity-related health risks may differ
by ethnicity at the same level of BMI (17–20).
Among populations of European descent, the WC thresholds
are 80 and 88 cm in women and 94 and 102 cm in men, to
indicate high and very high levels of obesity-related health risk,
respectively. These thresholds were developed based on the
association between WC and BMI (at 25 and 30 kg/m2, respectively),
rather than the association between WC and health risk
per se (21). At the same level of WC, there is great heterogeneity
across populations in sensitivity and specificity for identifying
people who are considered overweight (BMI ≥25 kg/m2) (22).
At present, there are no definitive WC thresholds proposed
for other populations, although some have been suggested for
Asian groups based on preliminary evidence (23).
The purpose of this study was to determine the optimal BMI
and WC thresholds for the identification of cardiometabolic
risk in a sample of white and African-American (AA) adults.
Methods and Procedures
Sample
The Pennington Center Longitudinal Study (PCLS) is an ongoing investigation
of the effects of obesity and lifestyle factors on the development
of chronic diseases such as type 2 diabetes, cardiovascular disease
(CVD), and cancer. The sample is composed of volunteers who have
participated in variety of clinical studies, including diet interventions,
weight loss, and other metabolic/physiologic studies conducted at the
Pennington Biomedical Research Center (PBRC) in Baton Rouge,
Ethnic-Specific BMI and Waist Circumference
Thresholds
Peter T. Katzmarzyk1, George A. Bray1, Frank L. Greenway1, William D. Johnson1, Robert L. Newton Jr1,
Eric Ravussin1, Donna H. Ryan1 and Claude Bouchard1
BMI and waist circumference (WC) are used to identify individuals with elevated obesity-related health risks. The
current thresholds were derived largely in populations of European origin. This study determined optimal BMI
and WC thresholds for the identification of cardiometabolic risk among white and African-American (AA) adults.
The sample included 2,096 white women, 1,789 AA women, 1,948 white men, and 643 AA men aged 18–64 years.
Elevated cardiometabolic risk was defined as ≥2 risk factors (blood pressure ≥130/85 mm Hg; glucose ≥100 mg/
dl; triglycerides ≥150 mg/dl; high-density lipoprotein-cholesterol <40 mg/dl (men) or <50 mg/dl (women)). Receiver Operating Characteristic (ROC) curves were used to identify optimal BMI and WC thresholds in each sex-by-ethnicity group. The optimal BMI thresholds were 30 kg/m2 in white women, 32.9 kg/m2 in AA women, 29.1 kg/m2 white men, and 30.4 kg/m2 in AA men, whereas optimal WC thresholds were 91.9 cm in white women, 96.8 cm in AA women, 99.4 in white men, and 99.1 cm in AA men. The sensitivities at the optimal thresholds ranged from 63.5 to 68.5% for BMI and 68.4 to 71.0% for WC and the specificities ranged from 64.2 to 68.8% for BMI and from 68.5 to 71.0% for WC, respectively. In general, the optimal BMI and WC thresholds approximated currently used thresholds in men and in white women. There are no apparent ethnic differences in men; however, in AA women the optimal BMI and WC values are ~3 kg/m2 and 5 cm higher than in white women. Obesity (2011) 19, 1272–1278. doi:10.1038/oby.2010.319 1Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, USA. Correspondence: Peter T. Katzmarzyk (Peter.Katzmarzyk@pbrc.edu) Received 16 July 2010; accepted 22 November 2010; published online 6 January 2011. doi:10.1038/oby.2010.319 obesity | VOLUME 19 NUMBER 6 | june 2011 1273 articles Epidemiology LA since 1992. The current cross-sectional study included 6,476 participants (2,096 white women, 1,789 African-American women, 1,948 white men, and 643 African-American men) 18–64 years of age. Each participant provided their written informed consent and all PCLS procedures, including this analysis were approved by the PBRC institutional review board. Anthropometry Standardized anthropometric measures were obtained on all participants. Height was measured using standard methods with a stadiometer. Participants were required to remove shoes and asked to hold an inhaled breath, while a nurse lightly applied traction to the patient’s head in order to maintain alignment with the frankfort plane. A second nurse then lowered the slide until it reached the vertex of the skull and recorded the reading from the indicator. This process was repeated, and the average of the two heights was used in analysis (a third measurement was obtained if the first two measurements was >0.5 cm apart).
Weight was measured in duplicate using a calibrated digital scale after
all outer clothing, heavy pocket items, and shoes were removed. Weight
was recorded to the nearest 0.1 kg. A third measurement was obtained
if the difference between the first two measurements was >0.5 kg. BMI
was calculated as the weight in kg divided by the height in m2 (kg/m2).
WC was measured at the midpoint between the inferior border of the
ribcage and the superior aspect of the iliac crest using an inelastic measuring
tape. This process was repeated, and the average of the two values
was used in analysis (a third measurement was obtained if the first two
measurements was >0.5 cm apart).
Cardiometabolic risk factors
Blood pressure. All blood pressure measurements were taken manually
using a stethoscope and standard sphygmomanometer or in some
cases using a validated Omron automatic measuring device. Resting
blood pressure measurements were obtained after a 5-min rest, with
the participant in a semirecumbent position in a quiet room. Each
measurement
was taken twice. The nurse waited 1–2 min before
repeating
the measurement and the average of the two measurements
was recorded. Participants were not allowed to engage in vigorous exercise,
ingest food or caffeine, or smoke within 30 min of measurement.
Upper-arm length and circumferences of the right arm were measured
in order to establish the appropriate cuff size. The Korotkoff sounds
were used to establish the first and 5th phases and all measurements
were recorded in mm Hg. High blood pressure was defined as systolic
blood pressure ≥130 mm Hg or diastolic blood pressure ≥85 mm Hg, or
reported treated hypertension.
Fasting blood lipid and glucose panel. Serum triglycerides, highdensity
lipoprotein-cholesterol, and plasma glucose were obtained
from a 12-h fasting blood draw. Participants were asked to refrain from
consuming alcohol or engaging in vigorous exercise at least 24 h before
blood withdrawal. Samples were analyzed on a Beckman Coulter Chemistry
Analyzer (Beckman Coulter, Brea, CA). High glucose was defined
as fasting plasma glucose ≥100 mg/dl, or reported diabetes. High triglycerides
were defined as ≥150 mg/dl. Low high-density lipoprotein-cholesterol
was defined as <40 mg/dl for men or <50 mg/dl for women. Covariates Participant age was computed from birth and observation dates. Smoking status was self-reported during the screening process, and participants were classified as “nonsmokers,” “current smokers,” or “former smokers.” Menopausal status (premenopausal/postmenopausal) was determined in women from their age and responses to questions regarding their reproductive history. Women aged 55+ years of age or those who indicated that they can no longer have children because of achieving menopause were considered to be postmenopausal. Statistical analysis Logistic regression models were used to determine the odds of having abnormal risk factors and the presence of two or more cardiometabolic risk factors (systolic/diastolic blood pressure ≥130/85 mm Hg, fasting glucose ≥100 mg/dl, triglycerides ≥150 mg/dl, high-density Table 1 D escriptive characteristics of the sample Women Men White African American White African American Number of subjects 2,096 1,789 1,948 643 Age, years 41.8 (12.8) 39.0 (11.8) 37.0 (13.3) 34.9 (12.4) BMI (kg/m2) 29.6 (6.7) 32.6 (6.7) 29.2 (5.5) 29.8 (5.8) Waist circumference (cm) 89.9 (16.3) 95.7 (15.7) 98.8 (15.4) 96.6 (16.5) Systolic blood pressure (mm Hg) 116.4 (14.0) 120.6 (15.7) 120.2 (12.2) 121.2 (12.4) Diastolic blood pressure (mm Hg) 74.5 (8.5) 77.4 (9.7) 77.3 (9.2) 77.6 (9.4) Triglycerides (mg/dl) 122.2 (69.9) 90.7 (50.2) 137.5 (80.4) 96.7 (55.0) HDL-cholesterol (mg/dl) 56.9 (13.9) 56.5 (13.2) 45.2 (11.0) 49.5 (11.7) Glucose (mg/dl) 98.8 (21.0) 104.0 (32.2) 103.7 (25.8) 102.1 (27.6) High blood pressure (%) 26.3 39.9 32.6 38.3 High blood glucose (%) 31.1 37.2 41.1 36.4 High triglycerides (%) 28.0 11.1 35.0 13.8 Low HDL-cholesterol 34.4 32.3 33.4 21.8 2+ Risk factors 33.6 36.6 43.0 33.1 Current smoking (%) 3.4 4.0 2.6 6.8 Postmenopausal (%) 23.7 12.1 –.– –.– Mean values for continuous variables are presented as mean (s.d.) and categorical variables are presented as a percentage (%). High blood pressure ≥130/85 mm Hg or reported treated hypertension; high blood glucose ≥100 mg/dl or reported type 2 diabetes; high triglycerides ≥150 mg/dl; low HDL-cholesterol <40 mg/dl in men; <50 mg/dl in women. HDL, high-density lipoprotein. 1274 VOLUME 19 NUMBER 6 | junE 2011 | www.obesityjournal.org articles Epidemiology lipoprotein- cholesterol <40 mg/dl (men), or <50 mg/dl (women)) in each sex-by-ethnicity group separately. Odds ratios with 95% confidence intervals were calculated to assess the odds of the risk factor abnormality with elevated BMI or WC relative to the odds without the elevation. All odds ratios are expressed per s.d. of BMI or WC. Age, smoking status, and menopausal status (in women) were included as covariates in the logistic regression models. Receiver Operating Characteristic (ROC) curves were used to select the optimal anthropometric thresholds that identified individuals with abnormal risk factor levels and risk factor clustering in each sex-by-ethnicity group. Because the area under the curve is considered as a measure of the utility of BMI or WC and represents the tradeoff between the correct identification of high-risk individuals (sensitivity) and the correct identification of low-risk individuals (specificity), the optimal threshold was considered to be the point of convergence between sensitivity and specificity. In order to investigate the effects of age on the optimal thresholds, the sample was divided into three age groups (18–34 years, 35–49 years, 50–64 years). SAS version 9.0 was used for data management and preliminary analyses, and PASW version 18.0 was used to perform the ROC analyses. The level of significance was set at P ≤ 0.05. Results The descriptive characteristics of the sample are presented in Table 1. The sample was composed of 60% women and 38% AA volunteers. The average age of the volunteers was 38.9 years (s.d. 12.9 years), and the prevalence of two or more cardiometabolic risk factors was 37.2%, ranging from 34% in white women to 43% in white men. Both BMI and WC were strongly associated with the presence of two or more cardiometabolic risk factors as well as individual cardiometabolic risk factors (Table 2). The odds ratios for having two or more cardiometabolic risk factors per s.d. of BMI ranged from 2.6 in white women to 2.0 in African-American women, and the odds ratios per s.d. of WC were 3.1 in white women and 2.4 in all other groups. These results indicate that for every s.d. higher BMI (~6 kg/m2) or WC (~16 cm), the odds of having two or more cardiometabolic risk factors was two to three times higher than someone with a correspondingly lower level of BMI or WC, respectively. In general, the strength of the associations between BMI and WC and cardiometabolic risk factors was similar across all sex-byethnicity groups. The sex- and ethnic-specific ROC curves are presented in Figure 1 for the clinical utility of BMI (panel A) and WC (panel B) in predicting two or more cardiometabolic risk factors. The areas under the curve were significantly >0.5 in all
sex-by-ethnicity groups (Table 3), ranging from 0.697 to 0.755
for BMI and from 0.752 to 0.783 for WC. The optimal BMI
thresholds were 30 kg/m2 in white women, 32.9 kg/m2 in AA
women, 29.1 kg/m2 white men, and 30.4 kg/m2 in AA men,
whereas optimal WC thresholds were 91.9 cm in white women,
96.8 cm in AA women, 99.4 cm in white men, and 99.1 cm in
AA men. The sensitivities at the optimal thresholds ranged
from 63.5 to 68.5% for BMI and 68.4 to 71.0% for WC and the
specificities ranged from 64.2 to 68.8% for BMI and from 68.5
to 71.0% for WC, respectively.
Table 3 also presents the results of the age-specific analyses.
In women, there were no appreciable effects of age on the
optimal BMI thresholds, which ranged from 29.5 to 30.5 kg/m2
in white women and from 32.7 to 33.3 kg/m2 in AA women
across the three age groups. The optimal WC thresholds tended
to be lower in 18–34-year-old group vs. the older age groups in
Table 2 R esults of logistic regression analysis (odds ratios (95% confidence interval)) for BMI and waist circumference predicting
individual risk factors and the presence of two or more cardiometabolic risk factors
Women Men
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