The geographic distribution of obesity in the US and the potential regional differences in misreporting of obesity

Objective: State‐level estimates of obesity based on self‐reported height and weight suggest a geographic pattern of greater obesity in the Southeastern US; however, the reliability of the ranking among these estimates assumes errors in self‐reporting of height and weight are unrelated to geographic region. Design and Methods: Regional and state‐level prevalence of obesity (body mass index ≥ 30 kg m^?2) for non‐Hispanic black and white participants aged 45 and over were estimated from multiple sources: ( 1 ) self‐reported from the behavioral risk factor surveillance system (BRFSS 2003‐2006) (n = 677,425), ( 2 ) self‐reported and direct measures from the National Health and Nutrition Examination Study (NHANES 2003‐2008) (n = 6,615 and 6,138, respectively), and ( 3 ) direct measures from the REasons for Geographic and Racial Differences in Stroke (REGARDS 2003‐2007) study (n = 30,239). Results: Data from BRFSS suggest that the highest prevalence of obesity is in the East South Central Census division; however, direct measures suggest higher prevalence in the West North Central and East North Central Census divisions. The regions relative ranking of obesity prevalence differs substantially between self‐reported and directly measured height and weight. Conclusions: Geographic patterns in the prevalence of obesity based on self‐reported height and weight may be misleading, and have implications for current policy proposals.     

The Bias in Self‐reported Obesity From 1976 to 2005: A Canada–US Comparison

The objective of this study was to determine whether the bias in self‐reported estimates of obesity has changed over time and followed different patterns in Canada and the United States. Using age‐standardized data from three waves of the National Health and Nutrition Examination Survey (NHANES) in the United States and the Canadian Community Health Survey (CCHS) and the Canadian Heart Health Survey (CHHS) in Canada, discrepancies were compared between reported and measured estimates of height, weight, and obesity (based on the BMI) from 1976 to 2005. Results indicated that obesity increased in both countries, but rates were higher in the United States. The discrepancy between self‐reported and measured obesity was small in the United States with reported data underestimating measured prevalence by about 3%; this stayed relatively constant over time. In Canada, the discrepancy was large and doubled in the past decade (from 4 to 8%). In the United States, self‐reported data may be more accurate in monitoring changes in obesity over time, as the estimates have consistently remained about 3% below the measured estimates, whereas in Canada, monitoring obesity based solely on self‐reported height and weight may produce inaccurate estimates because of the increasing discrepancy between self‐reported and measured data.     

Disability,Arthritis, and Body Weight among Adults 45 Years and Older

Objectives : To examine the association between body weight and disability among persons with and without self‐reported arthritis. Research Methods and Procedures : Data were analyzed for noninstitutionalized adults, 45 years or older, in states that participated in the Behavioral Risk Factor Surveillance System. Self‐reported BMI (kilograms per meter squared) was used to categorize participants into six BMI‐defined groups: underweight (<18.5), normal weight (18.5 to <25), overweight (25 to <30), obese, class 1 (30 to <35), obese, class 2 (35 to <40), and obese, class 3 (≥40). Results : Class 3 obesity (BMI ≥ 40) was significantly associated with disability among participants both with and without self‐reported arthritis. The adjusted odds ratio (AOR) for disability in participants with class 3 obesity was 2.75 [95% confidence interval (CI) = 2.22 to 3.40] among those with self‐reported arthritis and 1.77 (95% CI = 1.20 to 2.62) among those without self‐reported arthritis compared with those of normal weight (BMI 18.5 to <25). Persons with self‐reported arthritis who were obese, class 2 (BMI 35 to <40) and obese, class 1 (BMI 30 to <35) and women with self‐reported arthritis who were overweight (BMI 25 to <30) also had higher odds of disability compared with those of normal weight [AOR = 1.72 (95% CI = 1.47 to 2.00), AOR = 1.30 (95% CI = 1.17 to 1.44), and AOR = 1.18 (95% CI = 1.06 to 1.32), respectively]. Discussion : Our findings reveal that obesity is associated with disability. Preventing and controlling obesity may improve the quality of life for persons with and without self‐reported arthritis.     

Geographic Variation in the Prevalence of Obesity,Diabetes, and Obesity‐Related Behaviors**

Objective: To examine the variation in the prevalences of obesity and type 2 diabetes in weight loss counseling by health providers and in other potential obesity‐related determinants in 100 metropolitan statistical areas in the United States. Research Methods and Procedures: We performed a cross‐sectional study using data from the 2000 Behavioral Risk Factor Surveillance System, the largest telephone survey of health behaviors in the United States, of age‐adjusted prevalence of obesity, type 2 diabetes, intake of ≥five servings of fruits and vegetables per day, participation in 150 minutes of leisure‐time physical activity per week, receipt of weight management advice, and reports of trying to lose or maintain weight among men and women more than 18 years old. Results: The age‐adjusted prevalence of obesity ranged from 13.1% to 30.0% and that of type 2 diabetes from 3.3% to 9.2%. Among participants who had visited a physician for a routine checkup in the previous 12 months, 13.1% to 27.1% of all participants recalled receiving advice from a health professional about their weight, and 11.7% to 34.6% of overweight or obese participants recalled receiving advice to maintain or lose weight. Discussion: Significant differences in the prevalence of obesity and self‐reported type 2 diabetes and in medical practice patterns regarding weight management advice exist among metropolitan statistical areas. These results suggest important opportunities to investigate reasons for these variations that could potentially be used to mitigate the current epidemic of obesity and to identify areas where obesity and diabetes prevention efforts may need to be targeted.     

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.     

Major Increase in Prevalence of Overweight and Obesity between 1987 and 2001 among Danish Adults

Objective: The aim of the study was to examine the secular trends in the prevalence of obesity (BMI ≥ 30.0 kg/m²) and overweight (25.0 ≤ BMI < 30.0 kg/m²) in Danish adults between 1987 and 2001. Research Methods and Procedures: The study included self‐reported weight and height of 10, 094 men and 9897 women 16 to 98 years old, collected in a series of seven independent cross‐sectional surveys. Prevalence and changes in prevalence of obesity and overweight stratified by sex and age groups were determined Results: The prevalence of obesity more than doubled between 1987 and 2001, in men from 5.6% to 11.8% [odds ratio (OR) = 2.3, 95% confidence interval (CI) = 1.9 to 2.8, p < 0.0001] and in women from 5.4% to 12.5% (OR = 2.6, 95% CI = 2.1 to 3.2, p < 0.0001), with the largest increase among the 16‐ to 29‐year‐old subjects (men, from 0.8% to 7.5%, OR = 10.2, 95% CI = 4.1 to 25.3, p < 0.0001; women, from 1.4% to 9.0% OR = 7.0, 95% CI = 3.5 to 14.1, p < 0.0001). Between 1987 and 2001, the prevalence of overweight increased from 34% to 40% in men and from 17% to 27% in women. Discussion: The prevalence of overweight and obesity in Denmark has increased substantially between 1987 and 2001, particularly among young adults, a development that resembles that of other countries. There is clearly a need for early preventive efforts in childhood to limit the number of obesity‐related complications in young adults.     

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.     

Prevalence of Obesity Among Children With Chronic Conditions

New evidence suggests that children with chronic conditions may be predisposed to overweight and obesity. This study provides prevalence estimate of obesity for children and adolescents with select chronic conditions. We analyzed reported height and weight and the corresponding BMI from 46,707 subjects aged 10–17 years collected by the National Survey of Children's Health (NSCH‐2003). Our main outcome measure was the prevalence of obesity (defined as ≥95th percentile of the sex‐specific BMI for age growth charts), adjusted for underlying demographic and socioeconomic factors. We found that the prevalence of obesity among children 10–17 years of age without a chronic condition was 12.2% (95% confidence interval (CI) 11.5–13.0); the prevalence of obesity for children with asthma was 19.7% (19.5–19.9); with a hearing/vision condition was 18.4% (18.2–18.5); with learning disability was 19.3% (19.2–19.4); with autism was 23.4% (23.2–23.6); and with attention‐deficit/hyperactivity disorder was 18.9% (18.7–19.0). Our findings suggest that children 10–17 years of age with select chronic conditions were at increased risk for obesity compared to their counterparts without a chronic condition.     

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.     

Association between Adverse Childhood Experiences and Diagnosis of Cancer

Objective

Adverse childhood experiences (ACEs) are linked to multiple adverse health outcomes. This study examined the association between ACEs and cancer diagnosis.

Methods

Data from the 2010 Behavioral Risk Factor Surveillance System (BRFSS) survey were used. The BRFSS is the largest ongoing telephone health survey, conducted in all US states, the District of Columbia, Puerto Rico, Guam and the U.S. Virgin Islands, and provides data on a variety of health issues among the non-institutionalized adult population. Principal component analysis (PCA) was used to derive components for ACEs. Multivariable logistic regression models were used to provide adjusted odds ratios (OR) and 95% confidence intervals (CI) for the association between ACE components and overall, childhood and adulthood cancer, adjusting for confounders such as age, gender, race/ethnicity, income, educational status, marital status, and insurance status.

Results

Approximately 62% of respondents reported being exposed to ACEs and about one in ten respondents reported ever having been diagnosed with cancer. Component 1, which had the sexual abuse variables with the highest weights, was significantly associated with adulthood cancer (adjusted OR: 1.21; 95% CI: 1.03–1.43).

Conclusion

The association between ACEs and adulthood cancer may be attributable to disease progression through association of ACEs with risk factors for other chronic diseases. More research should focus on the impact of sexual abuse ACEs and adverse health outcomes.     

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.     

Self‐Reported Body Mass Index and Health‐Related Quality of Life: Findings from the Behavioral Risk Factor Surveillance System

Objective: To examine the relationship between self‐reported body mass index (BMI) and health‐related quality of life in the general adult population in the United States. Research Methods and Procedures: Using data from 109,076 respondents in the 1996 Behavioral Risk Factor Surveillance System, we examined how self‐reported BMI is associated with five health‐related quality of life measures developed by the Centers for Disease Control and Prevention for population health surveillance. Results: After adjusting for age, gender, race or ethnicity, educational attainment, employment status, smoking status, and physical activity status, participants with a self‐reported BMI of <18.5 kg/m² and participants with a self‐reported BMI of ≥30 kg/m² reported impaired quality of life. Compared with persons with a self‐reported BMI of 18.5 to <25 kg/m², odds ratios (ORs) of poor or fair self‐rated health increased among persons with self‐reported BMIs of <18.5 (1.57, 95% confidence interval [CI]: 1.31 to 1.89), 25 to <30 kg/m² (1.12, 95% CI: 1.04 to 1.20), 30 to <35 kg/m² (1.65, 95% CI: 1.50 to 1.81), 35 to <40 kg/m² (2.58, 95% CI: 2.21 to 3.00), and ≥40 kg/m² (3.23, 95% CI: 2.63 to 3.95); ORs for reporting ≥14 days of poor physical health during the previous 30 days were 1.44 (95% CI: 1.21 to 1.72), 1.04 (95% CI: 0.96 to 1.14), 1.32 (95% CI: 1.19 to 1.47), 1.80 (95% CI: 1.52 to 2.13), and 2.37 (95% CI: 1.90 to 2.94), respectively; ORs for having ≥14 days of poor mental health during the previous 30 days were 1.18 (95% CI: 0.97 to 1.42), 1.02 (95% CI: 0.95 to 1.11), 1.22 (95% CI: 1.10 to 1.36), 1.68 (95% CI: 1.42 to 1.98), and 1.66 (95% CI: 1.32 to 2.09), respectively. Discussion: In the largest study to date, low and increased self‐reported BMI significantly impaired health‐related quality of life. Particularly, deviations from normal BMI affected physical functioning more strongly than mental functioning.     

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.     

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.     

Prevalence and Covariates of Obesity in Lebanon: Findings from the First Epidemiological Study

Objective: To estimate the prevalence of overweight and obesity and examine associated covariates in the Lebanese population. Research Methods and Procedures: A cross‐sectional survey of a representative sample of 2104 individuals, 3 years of age and older. Anthropometric measurements and dietary assessments were conducted following standard methods and techniques. Overweight and obesity (classes I to III) were defined according to internationally standardized criteria for classification of BMI. Results: For children 3 to 19 years of age, prevalence rates of overweight and obesity were higher overall for boys than girls (22.5% vs. 16.1% and 7.5% vs. 3.2%, respectively). For adult men and women (age ≥ 20 years), the prevalence of overweight was 57.7% and 49.4%, respectively. In contrast, obesity (BMI ≥ 30 kg/m²) was higher overall among women (18.8%) than men (14.3%), a trend that became more evident with increasing obesity class. BMI, percentage of body fat, and waist circumference increased to middle age and declined thereafter. Whereas lack of exercise associated significantly with obesity among children, obesity in older adults was more prevalent among the least educated, nonsmokers, and those reporting a family history of obesity. Discussion: The results from this national population‐based study in Lebanon show high prevalence rates of overweight and obesity comparable with those observed in developed countries such as the United States. While further studies are needed to examine the underlying social and cultural factors associated with lifestyle and nutritional habits, now is the time to institute multicomponent interventions promoting physical activity and weight control nationwide.     

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.     

Obesity and Smoking: Comparing Cessation Treatment Seekers With the General Smoking Population

Obesity and smoking represent the leading preventable causes of morbidity and mortality in the United States. This study compared the prevalence of obesity among smokers seeking cessation treatment (n = 1,428) vs. a general population (n = 4,081) of never smokers, former smoker, and current smokers. Data from treatment‐seeking smokers in the Wisconsin Smokers' Health Study (WSHS) and individuals who completed the National Health and Nutrition Examination Survey (NHANES) 2005–2006 were pooled and obesity rates and other health characteristics were compared. The prevalence of obesity was significantly higher among WSHS treatment‐seeking smokers (36.8%) vs. NHANES current smokers (29.6%), but the obesity rates of WSHS treatment‐seeking smokers did not differ from NHANES former smokers (36.5%) or never smokers (36.5%). Treatment‐seeking smokers were more likely to be female and to have higher educational attainment compared to NHANES participants. Analysis of health characteristics revealed that treatment‐seeking smokers had higher levels of dietary fiber and vitamin C and lower blood levels of total cholesterol, triglycerides, and fasting glucose compared to NHANES current smokers. Results suggest that treatment‐seeking smokers may have a different health profile than current smokers in the general population. Health care providers should be aware of underlying heath issues, particularly obesity, in patients seeking smoking cessation treatment.     

Immigration and obesity among lower income blacks

Objective: Our objective was to examine the associations of nativity, immigrant generation, and language acculturation with obesity among lower income black adult men and women. Research Methods and Procedures: Data from 551 black adult men and women were collected from participants in the Healthy Directions‐Health Centers Study. Race/ethnicity and nativity were self‐reported. Language acculturation was defined using participants’ first language, preferred reading language, and language spoken at home. Mixed model logistic regression models were estimated to account for within‐health center clustering. Results: Foreign‐born blacks had a lower obesity risk, compared with all U.S.‐born participants, in multivariable analyses [odds ratio (OR) = 0.57, 95% confidence interval (CI), 0.38, 0.84]. Among U.S.‐born participants, those with foreign‐born parents were significantly less likely to be obese than individuals with U.S.‐born parents (OR = 0.54; 95% CI, 0.37, 0.80). Low‐moderate language acculturation also decreased the odds of being obese (OR = 0.45; 95% CI, 0.23, 0.88). Discussion: Our findings suggest a protective effect of foreign‐born status and low‐moderate language acculturation on obesity risk among lower income black immigrants. These data highlight the importance of more frequently examining nativity in obesity‐related research conducted among blacks.     

Prevalence of obese patients in a primary care setting

Objective: Previous research has addressed the relationship between BMI and chronic disease in primary care; however, little has been done with regard to the association between obesity and depression in primary care. The purpose of this paper is to assess the relationship between obesity and chronic conditions including depression. Research Methods and Procedures : Data from primary care patients seen at a university‐based family medicine clinic in the southeastern United States were extracted for the time between January 1, 1999 and January 1, 2002. Data extracted included most recent height and weight, age, ethnicity, pregnancy status, number of office visits, blood pressure, cholesterol, hemoglobin A_1C, current diagnoses, and medications. Results : A total of 8197 patients were included in the analysis. Sixty‐nine percent of patients seen in a 3‐year period were either overweight or obese. Comparing blood pressure, cholesterol, diagnoses, and medications between BMI groups found differences in virtually all categories. Diagnoses of high cholesterol, hypertension, diabetes, and depression significantly increased for obese patients. Discussion : Obese patients are over‐represented in primary care, and this over‐representation of obesity correlates with several diagnoses, including depression. Depression is a chronic disease that may interfere with health‐related behaviors and must be addressed within the health care system.     

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.