High Rates of Obesity and Chronic Disease Among United Methodist Clergy

We used self‐reported data from United Methodist clergy to assess the prevalence of obesity and having ever been told certain chronic disease diagnoses. Of all actively serving United Methodist clergy in North Carolina (NC) 95% (n = 1726) completed self‐report height and weight items and diagnosis questions from the Behavioral Risk Factor Surveillance Survey (BRFSS). We calculated BMI categories and diagnosis prevalence rates for the clergy and compared them to the NC population using BRFSS data. The obesity rate among clergy aged 35–64 years was 39.7%, 10.3% (95% CI = 8.5%, 12.1%) higher than their NC counterparts. Clergy also reported significantly higher rates of having ever been given diagnoses of diabetes, arthritis, high blood pressure, angina, and asthma compared to their NC peers. Health interventions that address obesity and chronic disease among clergy are urgently needed.     

The validity of obesity based on self-reported weight and height: Implications for population studies

Objective: To validate self‐reported information on weight and height in an adult population and to find a useful algorithm to assess the prevalence of obesity based on self‐reported information. Research Methods and Procedures: This was a cross‐sectional survey consisting of 1703 participants (860 men and 843 women, 30 to 75 years old) conducted in the community of Vara, Sweden, from 2001 to 2003. Self‐reported weight, height, and corresponding BMI were compared with measured data. Obesity was defined as measured BMI ≥ 30 kg/m². Information on education, self‐rated health, smoking habits, and physical activity during leisure time was collected by a self‐administered questionnaire. Results: Mean differences between measured and self‐reported weight were 1.6 kg (95% confidence interval, 1.4; 1.8) in men and 1.8 kg (1.6; 2.0) in women (measured higher), whereas corresponding differences in height were ?0.3 cm (?0.5; ?0.2) in men and ?0.4 cm (?0.5; ?0.2) in women (measured lower). Age and body size were important factors for misreporting height, weight, and BMI in both men and women. Obesity (measured) was found in 156 men (19%) and 184 women (25%) and with self‐reported data in 114 men (14%) and 153 women (20%). For self‐reported data, the sensitivity of obesity was 70% in men and 82% in women, and when adjusted for corrected self‐reported data and age, it increased to 81% and 90%, whereas the specificity decreased from 99% in both sexes to 97% in men and 98% in women. Discussion: The prevalence of obesity based on self‐reported BMI can be estimated more accurately when using an algorithm adjusted for variables that are predictive for misreporting.     

Underreporting of BMI in adults and its effect on obesity prevalence estimations in the period 1998 to 2001

Objective: To identify the determinants of underreporting BMI and to evaluate the possibilities of using self‐reported data for valid obesity prevalence rate estimations. Research Methods and Procedures: A cross‐sectional monitoring health survey was carried out between 1998 and 2002, and a review of published studies was performed. A total of 1809 men and 1882 women ages 20 to 59 years from The Netherlands were included. Body weight and height were reported and measured. Equations were calculated to estimate individuals’ BMI from reported data. These equations and equations from published studies were applied to the present data to evaluate whether using these equations led to valid estimations of the obesity prevalence rate. Also, size of underestimation of obesity prevalence rate was compared between studies. Results: The prevalence of obesity was underestimated by 26.1% and 30.0% among men and women, respectively, when based on reported data. The most important determinant of underreporting BMI was a high BMI. When equations to calculate individuals’ BMI from reported data were used, the obesity prevalence rate was still underestimated by 12.9% and 8.1% of the “true” obesity prevalence rate among men and women, respectively. The degree of underestimating the obesity prevalence was inconsistent across studies. Applying equations from published studies to the present data led to estimations of the obesity prevalence varying from a 7% overestimation to a 74% underestimation. Discussion: Valuable efforts for monitoring and evaluating prevention and treatment studies require direct measurements of body weight and height.     

Trends in pre-pregnancy obesity in nine states, 1993-2003

Objective: Pre‐pregnancy obesity poses risks to both pregnant women and their infants. This study used a large population‐based data source to examine trends, from 1993 through 2003, in the prevalence of pre‐pregnancy obesity among women who delivered live infants. Research Methods and Procedures: Data from the Pregnancy Risk Assessment Monitoring System in nine states were analyzed for trends in pre‐pregnancy obesity (BMI > 29.0 kg/m²) overall and by maternal demographic and behavioral characteristics. Pre‐pregnancy BMI was calculated from self‐reported weight and height on questionnaires administered after delivery, and demographic characteristics were taken from linked birth certificates. The sample of 66,221 births was weighted to adjust for survey design, non‐coverage, and non‐response, and it is representative of all women delivering a live birth in each particular state. The sampled births represented 18.5% of all births in the United States. Results: Pre‐pregnancy obesity increased 69.3% during the study period, from 13.0% in 1993 to 1994 to 22.0% in 2002 to 2003. The percentage increase ranged from 45% to 105% for individual states. Subgroups of women with the highest prevalence of obesity in 2002 to 2003 were those who were 20 to 29 years of age, black, had three or more children, had a high school education, enrolled in Women, Infants, and Children, or were non‐smokers. However, all subgroups of women examined experienced at least a 43% increase in pre‐pregnancy obesity over this time period. Discussion: The prevalence of pre‐pregnancy obesity is increasing among women in these nine states, and this trend has important implications for all stages of reproductive health care.     

Adult obesity does not predict 6-year weight gain in men: the Aerobics Center Longitudinal Study

Objective: To determine the longitudinal relation between history of adult obesity and the 6‐year trajectory of weight change in men. Research Methods and Procedures: Subjects were healthy, affluent men (n = 761) between the ages of 20 and 78 years who completed at least four comprehensive medical exams at the Cooper Clinic between 1987 and 2003. Maximum adult weight was reported, and current height was measured at baseline. Body weight and cardiorespiratory fitness were measured at all examinations. Adult obesity status was determined from self‐reported maximum weight and measured height at baseline as BMI ≥ 30 kg/m². Weight at all examinations was regressed on a history of adult obesity using linear mixed effects modeling. Results: At baseline, men reporting a history of adult obesity were significantly heavier than men reporting no such history (BMI 29.8 vs. 25.0 kg/m²; p < 0.05). However, the rate of weight gain among men with a history of obesity was slower than among men without a history of adult obesity (0.04 vs. 0.18 kg/yr; p = 0.09), although this difference was only marginally significant. Fitness modulated the relationship between history of obesity and weight change over time, and both higher levels of fitness and greater frequency of dieting were associated with attenuated weight gain. In contrast, chronic disease and depression were associated with accelerated weight gain. Discussion: Although a history of obesity was associated with higher weight, it did not seem to result in accelerated weight gain over time. Additionally, dieting and fitness were important for minimizing weight gain.     

The prevalence of obesity in ethnic admixture adults

Objective: To determine whether the prevalence of obesity in ethnic admixture adults varies systematically from the average of the prevalence estimates for the ethnic groups with whom they share a common ethnicity. Methods and Procedures: The sample included 215,000 adults who reported one or more ethnicities, height, weight, and other characteristics through a mailed survey. Results: The highest age‐adjusted prevalence of overweight (BMI ≥ 25) was in Hawaiian/Latino men (88%; n = 41) and black/Latina women (74.5%; n = 79), and highest obesity (BMI ≥ 30) rates were in Hawaiian/Latino men (53.7%; n = 41) and Hawaiian women (39.2%, n = 1,247). The prevalence estimates for most admixed groups were similar to or higher than the average of the prevalences for the ethnic groups with whom they shared common ethnicities. For instance, the prevalence of overweight/obesity in five ethnic admixtures—Asian/white, Hawaiian/white, Hawaiian/Asian, Latina/white, and Hawaiian/Asian/white ethnic admixtures—was significantly higher (P < 0.0001) than the average of the prevalence estimates for their component ethnic groups. Discussion: The identification of individuals who have a high‐risk ethnic admixture is important not only to the personal health and well‐being of such individuals, but could also be important to future efforts in order to control the epidemic of obesity in the United States.     

State ranks of incident cancer burden due to overweight and obesity in the United States, 2003

Objective: Given links between obesity and cancer, we estimated incident cancer burden due to overweight and obesity at the state level in the United States. Methods and Procedures: Using state rankings by per capita burden of incident cancer cases diagnosed in 2003 that were related to overweight and obesity, we examined the frequency with which states ranked in the highest and lowest quintiles of weight‐related burden for cancers of the postmenopausal breast, endometrium, kidney, colon, and prostate. In this study, data from the Behavioral Risk Factor Surveillance System (BRFSS), US Census, US Mortality Public Use Data Tapes, and National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) Program were used. Results: Western states had the lowest weight‐related cancer burden for both sexes. Iowa, South Dakota, and West Virginia had the highest burden for all three types of male cancers. West Virginia is the only state that ranked in the quintile of highest weight‐related burden for all four cancers considered in women. Discussion: For certain cancers, including endometrial, postmenopausal breast, and colon cancers, states with high burdens clustered in geographic regions, warranting further inquiry. Although state ranks for the total cancer burden and the prevalence of overweight and obesity correlated with state ranks for weight‐related incident cancer burden, they often served poorly as its proxy. Such a finding cautions against simply targeting states with high overweight and obesity or high total burdens of cancers for which overweight and obesity are risk factors, as this approach may not reach areas of unrecognized burden.     

Ethnic Differences in Self‐reported and Measured Obesit

As use of self‐reported data to classify obesity continues, ethnic differences in reporting errors remain unclear. The objective of this study is to elucidate misreporting disparities between African Americans (AAs) and European Americans (EAs). The Pennington Center Longitudinal Study (PCLS) is an ongoing investigation of environmental, behavioral, and biological factors associated with obesity, diabetes, and other common diseases. Self‐reported and measured height and weight were collected during initial screening for eligibility in various studies by telephone and clinic visits. All ethnicity‐sex groups (15,656 adults aged 18–65 years, 53% obese, 34% AA, 37% men) misreported heights and weights increasingly as measured values increased (P < 0.0001). More AA vs. EA women (P < 0.001) misreported height and weight, but more EA vs. AA men misreported their weight (P < 0.02). Obesity was underestimated more in AA vs. EA women (self‐reported ? measured prevalence = ?4.0% (AA) vs. ?2.6% (EA), P < 0.0001), but less in AA vs. EA men (?3.2% (AA) vs. ?4.2% (EA), P < 0.0001)). With measured obesity prevalence equalized at 53% in all groups, the self‐reported obesity prevalence in women was 50.4% (AA) vs. 49.6% (EA), and in men 49.8% (AA) vs. 47.3 (EA). Underestimation in women was ?2.6% (AA) vs. ?3.4% (EA); in men it was ?3.2% (AA) vs. ?5.7% (EA), P < 0.003. Self‐reported height and weight portend underestimation of obesity prevalence and the effect varies by ethnicity and gender. However, comparisons depend on the true prevalence within ethnicity‐gender groups. After controlling for obesity prevalence, disparity in underestimation was greater in EA than in AA men (P < 0.003) but not women.     

Overweight and obesity in an ethnically diverse rural school district: the Healthy Kids Project

Objective: Data on Native American children and adolescents are rarely reported along with other racial and ethnic groups. The Healthy Kids Project is part of an effort to describe the prevalence of overweight and obesity in a racially mixed rural area where Native American, Hispanic, African American, and white children reside. Methods and Procedures: We measured height and weight of students in Anadarko, Oklahoma public schools (n = 1,980) in 2002–2003. All available students (95.7%) whose parents had not opted out of school health assessments were included. From these data, we calculated BMI (weight (kg) / height (m²)) and used the International Obesity Task Force reference to classify children into BMI categories. Results: Native American, Hispanic, African American, and white children who live and attend school in the same surroundings are at risk of overweight and obesity. White children had the lowest combined prevalence of overweight and obesity (37.6%), and Native American children had the highest (53.8%) followed closely by African American (51.7%) and Hispanic children (50.5%). Discussion: The childhood obesity epidemic includes all racial and ethnic groups to different degrees. In a rural public school, Native American, Hispanic, and African children had higher rates of overweight/obesity than white children.     

Association of childhood sexual abuse with obesity in a community sample of lesbians

Objective: Our goal was to examine the association between childhood sexual abuse (CSA) and obesity in a community‐based sample of self‐identified lesbians. Research Methods and Procedures: A diverse sample of women who self‐identified as lesbian was recruited from the greater Chicago metropolitan area. Women (n = 416) were interviewed about sexual abuse experiences that occurred before the age of 18. Self‐reported height and weight were used to calculate BMI and categorize women as normal‐weight (<25.0 kg/m²), overweight (25.0 to 29.9 kg/m²), obese (30.0 to 39.9 kg/m²), or severely obese (≥40 kg/m²). The relationship between CSA and BMI was examined using multinomial logistic regression analysis. Results: Overall, 31% of women in the sample reported CSA, and 57% had BMI ≥25.0 kg/m². Mean BMI was 27.8 (±7.2) kg/m² and was significantly higher among women who reported CSA than among those who did not report CSA (29.4 vs. 27.1, p < 0.01). CSA was significantly related to weight status; 39% of women who reported CSA compared with 25% of women who did not report CSA were obese (p = 0.004). After adjusting for age, race/ethnicity, and education, women who reported CSA were more likely to be obese (odds ratio, 1.9; 95% confidence interval, 1.1–3.4) or severely obese (odds ratio, 2.3; 95% confidence interval, 1.1–5.2). Discussion: Our findings, in conjunction with the available literature, suggest that CSA may be an important risk factor for obesity. Understanding CSA as a factor that may contribute to weight gain or act as a barrier to weight loss or maintenance in lesbians, a high‐risk group for both CSA and obesity, is important for developing successful obesity interventions for this group of women.     

Comparison of self-reported and measured BMI as correlates of disease markers in US adults

Objective: The purpose of this study is to evaluate the validity of BMI based on self‐reported data by comparison with technician‐measured BMI and biomarkers of adiposity. Research Methods and Procedures: We analyzed data from 10,639 National Health and Nutrition Education Study III participants ≥20 years of age to compare BMI calculated from self‐reported weight and height with BMI from technician‐measured values and body fatness estimated from bioelectrical impedance analysis in relation to systolic blood pressure, fasting blood levels of glucose, high‐density lipoprotein‐cholesterol, triglycerides, C‐reactive protein, and leptin. Results: BMI based on self‐reported data (25.07 kg/m²) was lower than BMI based on technician measurements (25.52 kg/m²) because of underreporting weight (?0.56 kg; 95% confidence interval, ?0.71, ?0.41) and overreporting height (0.76 cm; 95% confidence interval, 0.64, 0.88). However, the correlations between self‐reported and measured BMI values were very high (0.95 for whites, 0.93 for blacks, and 0.90 for Mexican Americans). In terms of biomarkers, self‐reported and measured BMI values were equally correlated with fasting blood glucose (r = 0.43), high‐density lipoprotein‐cholesterol (r = ?0.53), and systolic blood pressure (r = 0.54). Similar correlations were observed for both measures of BMI with plasma concentrations of triglycerides and leptin. These correlations did not differ appreciably by age, sex, ethnicity, or obesity status. Correlations for percentage body fat estimated through bioelectrical impedance analysis with these biomarkers were similar to those for BMI. Discussion: The accuracy of self‐reported BMI is sufficient for epidemiological studies using disease biomarkers, although inappropriate for precise measures of obesity prevalence.     

BMI may overestimate the prevalence of obesity among women of lower socioeconomic status

Objective: Our objective was to examine gender differences in height and weight associated with socioeconomic status (SES) and the consequent effect on body mass index in a multiethnic society. Research Methods and Procedures: A cross‐sectional study, the First Israeli National Health and Nutrition Survey, was performed on a representative population sample of 3246 adults 25 to 64 years of age, between the years 1999 to 2001. Height and weight were measured, and BMI and other weight‐height indices were calculated. SES was assessed by income and education. Results: Age‐adjusted height was significantly lower at lower levels of SES among both women and men (p < 0.001). As opposed to men, women of lower SES were heavier than those of higher SES, and the mean age‐adjusted weight was 4.6 kg higher among those of lower SES (p < 0.001). Thus, using the standard index of BMI, the prevalence of obesity was significantly higher among shorter women. Discussion: In this group of Israeli adults, the unfavorable effect of low SES on BMI was evident among women, partly due to their decreased height combined with increased weight common in this socioeconomic sector. Since BMI is only partly independent of height, it may overestimate the prevalence of obesity among women of lower SES. Alternative measures for classifying obesity in the lower SES groups that put less emphasis on height may be considered and studied.     

Characterization and heritability of obesity and associated risk factors in vervet monkeys

Objective: The objective was to determine the prevalence and heritability of obesity and risk factors associated with metabolic syndrome (MS) in a pedigreed colony of vervet monkeys. Design: A cross‐sectional study of plasma lipid and lipoprotein concentrations, glycemic indices, and morphometric measures with heritability calculated from pedigree analysis. A selected population of females was additionally assessed for insulin sensitivity and glucose tolerance. Subjects: All mature male (n = 98), pregnant (n = 40) and non‐pregnant female (n = 157) vervet monkeys were included in the study. Seven non‐pregnant females were selected on the basis of high or average glycated hemoglobin (GHb) for further characterization of carbohydrate metabolism. Measurements: Morphometric measurements included body weight, length, waist circumference, and calculated BMI. Plasma lipids [total cholesterol (TC), triglycerides (TG), high‐density lipoprotein cholesterol (HDL‐C)] and glycemic measures (fasting blood glucose, insulin, and GHb) were measured. A homeostasis model assessment index was further reported. Glucose tolerance testing and hyperinsulinemic‐euglycemic clamps were performed on 7 selected females. Conclusion: Vervet monkeys demonstrate obesity, insulin resistance, and associated changes in plasma lipids even while consuming a low‐fat (chow) diet. Furthermore, these parameters are heritable. Females are at particular risk for central obesity and an unfavorable lipid profile (higher TG, TC, and no estrogen‐related increase in HDL‐C). Selection of females by elevated GHb indicated impaired glucose tolerance and was associated with central obesity. This colony provides a unique opportunity to study the development of obesity‐related disorders, including both genetic and environmental influences, across all life stages.     

What Is the Accurate Prevalence of Obesity in Sweden in the 21st Century? Methodological Experiences From the Skaraborg Project

Objective: To examine the impact of non‐response to self‐reported body weight and height in health questionnaires for the estimation of obesity prevalence. Methods and Procedures: A cross‐sectional population‐based health survey in the community of Vara with 16,009 residents (in year 2002) in South‐western Sweden. Participants randomly selected in strata by sex and age among residents being 30–74 years old were consecutively invited to the local health care center for a health examination, including two visits. Self‐reported information on body weight and height were obtained by health questionnaires at the first visit, and measured information on both variables at the second visit. For this study 1,809 subjects (904 men and 905 women) completed both visits (participation rate 81%), and a nurse measured body weight and height of all at visit two. Participants not self‐reporting body weight and/or height at the first visit were defined as non‐responders. Results: Both male and female non‐responders were significantly older than responders. Female non‐responders had significantly higher BMI (29.8 ± 5.8 kg/m²) than female responders (26.6 ± 5.3 kg/m²), (P < 0.001). No similar findings were seen in men. Non‐responders were more likely to be obese than responders both in men (odds ratio (OR) 2.06, 95% confidence interval (CI) 1.03–4.11) and in women (OR 2.24, 95% CI 1.25–4.02). Discussion: Non‐responders to self‐reported body weight and height in health questionnaires contribute to the underestimation of obesity. Measured body weight and height are to prefer when describing the accurate prevalence of obesity in populations.     

Accuracy of Self‐reported Weight and Height in Binge Eating Disorder: Misreport Is Not Related to Psychological Factors

This study examined the degree of misreport in weight, height, and BMI among overweight adults (n = 392) with binge eating disorder (BED) and tested whether the degree of misreport was associated with eating disorder psychopathology and psychological variables. Male (n = 97) and female (n = 295) participants self‐reported height and weight, and were subsequently measured by clinic staff. Participants also completed a series of diagnostic interviews and self‐report assessments. Discrepancies between self‐reported and measured values were modest. The degree of misreport for weight, height, and BMI was not related to eating disorder features, depression, and self‐esteem. Overall, the errors in self‐reported weight and height by overweight patients with BED were very slight. The degree of discrepancy between self‐reported and measured values was not related to eating disorder or psychological features, suggesting that such data are not biased or systematically related to individual differences in overweight patients with BED.     

Modeling the potential public health impact of prepregnancy obesity on adverse fetal and infant outcomes

Objective: Approximately one‐third of US reproductive‐aged women are obese, and prepregnancy obesity is a strong risk factor for adverse fetal and infant outcomes. The annual number of preventable adverse fetal and infant outcomes associated with prepregnancy obesity in the US was estimated. Design and Methods: Adverse fetal and infant outcomes for which statistically significant associations with prepregnancy obesity had been reported by peer‐reviewed meta‐analyses, which included fetal deaths and nine different major birth defects, were assessed. The true prevalence of prepregnancy obesity was estimated by multiplying self‐reported prepregnancy obesity by a bias factor based on the difference between measured and self‐reported obesity in US adult women. A Monte Carlo simulation approach was used to model the attributable fraction and preventable number, accounting for uncertainty in the estimates for: 1 strength of the association with obesity, 2 obesity prevalence, and 3 outcome prevalence. Results: Eliminating the impact of prepregnancy obesity would potentially prevent the highest numbers of four outcomes: fetal deaths (6,990; uncertainty interval [UI] 4,110‐10,080), congenital heart defects (2,850; UI 1,035‐5,065), hydrocephalus (490; UI 150‐850), and spina bifida (405; UI 305‐505). If 10% of women with prepregnancy obesity achieved a healthy weight before pregnancy or otherwise mitigated the impact of obesity, nearly 300 congenital heart defects and 700 fetal deaths per year could potentially be prevented. Conclusion: This simulation suggests that effective prevention strategies to reduce prepregnancy obesity or the risk associated with obesity could have a measurable impact on infant health in the US.     

The perceived effectiveness of continuing care and group support in the long-term self-help treatment of obesity

Objective : Obesity is increasingly considered a chronic disease requiring continuing care, but professional long‐term treatment for most patients is not available. This study examined treatment recipients’ perception of the effectiveness of different components of a group self‐help, continuing‐care treatment program for obesity. Research Methods and Procedures : Members (n = 120) and volunteer leaders (n = 66) of a self‐help, continuing‐care treatment program of previously demonstrated effectiveness (mean treatment duration, 40.6 months; mean weight lost, 14.1 kg) rated how helpful and effective they found the various therapeutic strategies used by this program. The strategies examined were continuing care, group support, behavior therapy, motivational enhancement strategies involving positive reinforcement, and motivational enhancement strategies involving punishment. Results : The single most highly valued aspect of treatment was the provision of continuing care, followed by group support. Greater success at achieving one's goal weight was associated with perceptions of greater effectiveness of the program's strategies overall (r = 0.219, p < 0.005), of continuing care (r = 0.225, p < 0.005), and of positive reinforcement strategies (r = 0.223, p < 0.01). Participants who had successfully attained their goal weight perceived behavior therapy strategies as more effective than did participants who had not reached their goal weight [t (170) = 2.93, p < 0.005]. Discussion : The high ratings given to continuing care and group support strategies indicate the acceptability of supportive self‐help treatment for obesity administered over the long term. The findings suggest that continuing care and group support should be made available to participants in the self‐help treatment of obesity.     

Correlates of BMI misreporting among apparently healthy individuals: the ATTICA study

Objective: The aim of this study was to investigate correlates of misreporting in BMI, based on self‐reported weight and height, in a randomly selected population sample of Greek adults and to evaluate the effect of obesity status misclassification on the associations between obesity and disease. Research Methods and Procedures: During 2001 to 2002, we randomly enrolled 1514 men (18 to 87 years old) and 1528 women (18 to 89 years old) from the Attica area, Greece; the sampling was stratified by the age‐sex distribution of the region. Various sociodemographic, clinical, and psychological characteristics were self‐reported, and weight and height were measured and recorded in all participants. Results: The proportions of true positives and true negatives for correct obesity status identification were 62% and 97%, respectively. Women were 9 times more likely to be under‐reporters than men, whereas men were 7.5 times more likely to be over‐reporters. A 10‐year increase in age was associated with a 48% higher likelihood of being an under‐reporter and 26% lower likelihood of being an over‐reporter, irrespective of sex and other characteristics of the participants. Clinical status, such as the presence of hypertension and diabetes, was associated with under‐reporting of body weight. Furthermore, the use of self‐reported data may substantially exaggerate associations between obesity and obesity‐related diseases, such as diabetes, hypercholesterolemia, and hypertension. Discussion: The study indicates that, apart from age and sex, disease status may be another factor that influences misreporting of obesity status, with diabetic and hypertensive people to be more likely to under‐report their overweight. Use of self‐reported data may bias obesity—disease associations.     

Pediatricians’ Own Weight: Self‐perception,Misclassification, and Ease of Counseling

Objectives: Pediatricians underdiagnose overweight and feel ineffective at counseling. Given the relationship between physicians’ health and health habits and counseling behaviors, we sought to determine the 1) percentage of pediatricians who are overweight; 2) accuracy of pediatricians’ own weight status classification; and 3) relationship between weight self‐perception and perceived ease of obesity counseling. Research Methods and Procedures: This study was a cross‐sectional, mail survey of North Carolina pediatricians that queried about their weight status and ease of counseling. Accuracy of pediatricians’ self‐classification of weight status was compared with BMIs derived from self‐reported height and weight. Using logistic regression, controlling for potential confounding variables, we examined the association between weight perception and ease of counseling. Results: The unadjusted response rate was 62%, and the adjusted response rate was 71% (n = 355). Nearly one‐half (49%) of overweight pediatricians did not identify themselves as such. Men had greater adjusted odds of misclassifying overweight than women [odds ratio (OR), 3.61; 95% confidence interval (CI) = 1.81, 7.21]. Self‐classified “thin” pediatricians had nearly six times the odds of reporting more counseling difficulty as a result of their weight than “average” weight pediatricians (OR = 5.69; 95% CI = 2.30, 14.1), and self‐identified “overweight” pediatricians reported nearly four times as great counseling difficulty as “average” weight physicians (OR = 3.84; 95% CI = 1.11, 13.3), after adjustment for self‐reported BMI weight status and other potential confounders. Discussion: The roles that physician weight misclassification and self‐perception potentially play in influencing rates of obesity counseling warrant further research.     

Self-reported comorbidities among self-described overweight African-American and Hispanic adults in the United States: results of a national survey

Objective: To examine the concordance between self‐described weight status and BMI, the prevalence of self‐reported comorbidities, and the association between comorbidities and self‐rated health among overweight African‐American and Hispanic US adults. Methods and Procedures: A nationally representative sample of 537 African‐American and 526 Hispanic adults who were identified using a combination of random digit dialing and listed household sampling and self‐described as being slightly or very overweight participated in a telephone interview. Self‐reported height and weight were used to calculate BMI. Results: More than half of African Americans (56%) and one‐third of Hispanics (34%) who self‐described as “slightly” overweight would be classified as obese based on BMI. One‐third (33%) of African Americans reported high blood pressure, followed by arthritis (20%), high cholesterol (18%), and diabetes (15%). Among Hispanics, high cholesterol was the most frequently reported comorbidity (17%), followed by high blood pressure (15%), and difficulty sleeping (12%). Almost three‐quarters of African Americans surveyed (72%) reported that their overall health was good to excellent compared to 62% for Hispanics. Discussion: Self‐reported rates of obesity‐related comorbidities fall below what would be expected based on prevalence data derived from physiologic measures, suggesting a lack of awareness of actual risk. Despite the greater self‐reported prevalence of certain risk factors for poor health, African Americans have a more optimistic view of their overall health and weight status compared to Hispanics. Physicians have an important opportunity to communicate to their minority patients the serious health consequences associated with excess weight.