First nationwide survey of prevalence of overweight, underweight, and abdominal obesity in Iranian adults

Objective: The goal was to estimate the prevalence of overweight, obesity, underweight, and abdominal obesity among the adult population of Iran. Research Methods and Procedures: A nationwide cross‐sectional survey was conducted from December 2004 to February 2005. The selection was conducted by stratified probability cluster sampling through household family members in Iran. Weight, height, and waist circumference (WC) of 89,404 men and women 15 to 65 years of age (mean, 39.2 years) were measured. The criteria for underweight, normal‐weight, overweight, and Class I, II, and III obesity were BMI <18.5, 18.5 to 24.9, 25 to 29.9, 30 to 34.9, 35 to 39.9, and ≥40 (kg/m²), respectively. Abdominal obesity was defined as WC ≥102 cm in men and ≥88 cm in women. Results: The age‐adjusted means for BMI and WC were 24.6 kg/m² in men and 26.5 kg/m² in women and 86.6 cm in men and 89.6 cm in women, respectively. The age‐adjusted prevalence of overweight or obesity (BMI ≥25) was 42.8% in men and 57.0% in women; 11.1% of men and 25.2% of women were obese (BMI ≥30), while 6.3% of men and 5.2% of women were underweight. Age, low physical activity, low educational attainment, marriage, and residence in urban areas were strongly associated with obesity. Abdominal obesity was more common among women than men (54.5% vs. 12.9%) and greater with older age. Discussion: Excess body weight appears to be common in Iran. More women than men present with overweight and abdominal obesity. Prevention and treatment strategies are urgently needed to address the health burden of obesity.     

Trends in overweight and obesity in Chinese adults: between 1991 and 1999-2000

Objective: The aim of this study was to evaluate trends in BMI and the prevalence of overweight (BMI ≥ 25 kg/m²) and obesity (BMI ≥ 30 kg/m²) between 1991 and 1999–2000 among Chinese adults. Methods and Procedures: In this study, two population‐based samples of Chinese adults aged between 45 and 79 years (n = 7,858 during each period), and comparable in the distributions of age, gender, degree of urbanization, and region (North/South) were used. Height and weight were measured using identical procedures at each period, and BMI was calculated as weight (in kilogram) divided by height (in square meter). Results: From 1991 to 1999–2000, the mean BMI increased from 21.8 to 23.4 kg/m² among men and from 21.8 to 23.5 kg/m² among women (each P < 0.001). Among men, the prevalence of overweight and obesity increased from 9.6 and 0.6%, respectively, in 1991 to 20.0 and 3.0%, respectively, in 1999–2000 (each P < 0.001). Among women, the prevalence of overweight and obesity increased from 14.5 and 1.8%, respectively, in 1991 to 26.5 and 5.2%, respectively, in 1999–2000 (each P < 0.001). The prevalence of overweight and obesity increased in all age groups, in rural and urban areas, and in North and South China, with greater relative increases in obesity among older age groups, South China, and rural areas (P interaction < 0.05). Discussion: Overweight and obesity increased tremendously during the 1990s in China. These data underscore the need for national programs in weight maintenance and reduction, to prevent obesity‐related outcomes in China.     

Prevalence of Overweight and Obesity in Elderly People in Spain

Objective: To estimate the prevalence of obesity and overweight in the older adult population in Spain by sex, age, and educational level. Research Methods and Procedures: A cross‐sectional study was carried out in 2001 in a sample of 4009 persons representative of the noninstitutionalized population ≥60 years of age. Anthropometric measurements (BMI and waist circumference) were obtained using standardized techniques and equipment. Overweight was considered at a BMI of 25 to 29.9 kg/m² and obesity at a BMI of ≥30 kg/m². Central obesity was considered at a waist circumference of >102 cm in men and >88 cm in women. Results: The mean BMI was 28.2 kg/m² in men and 29.3 kg/m² in women. The prevalence of overweight and obesity in men was 49% and 31.5%, respectively. The corresponding percentages in women were 39.8% and 40.8%. The prevalence of obesity was higher in persons with no education than in those with third level education (i.e., university studies), especially among women (41.8% vs. 17.5%). The prevalence of central obesity was 48.4% in men and 78.4% in women. Differences by educational level were seen in only women, in whom the prevalence of central obesity was 80.9% in those with no education and 59% in those with third‐level education. Discussion: The prevalence of overweight and obesity in the Spanish adult elderly population is very high. Some other populations show similar prevalences, especially in Mediterranean countries. Socioeconomic conditions in Spain during the years these cohorts were born may partly explain the high‐frequency of obesity.     

Morbidity and mortality risk associated with an overweight BMI in older men and women

Background: There is controversy as to whether older adults with a BMI in the overweight range (25 to 29.9 kg/m²) are at increased health risk and whether they should be encouraged to lose weight. The purpose of this study was to determine whether older adults with a BMI in the overweight range are at increased morbidity and mortality risk. Methods: Participants consisted of 4968 older (≥65 years) men and women from the Cardiovascular Health Study limited access dataset. Based on BMI (kg/m²), participants were grouped into normal‐weight (20 to 24.9 kg/m²), overweight (25 to 29.9 kg/m²), and obese (≥30 kg/m²) categories. Participants were followed for up to 9 years to determine if they developed 10 weight‐related health outcomes that are pertinent to older adults. Cox proportional hazards models were used to estimate the hazards ratios of morbidity and mortality after adjusting for age, sex, income, smoking, and physical activity. Results: Compared with the normal‐weight group, the risks of myocardial infarction, stroke, sleep apnea, urinary incontinence, cancer, and osteoporosis were not different in the overweight group (p > 0.05). The risks for arthritis and physical disability were modestly increased in the overweight group (p < 0.05), whereas the risk for type 2 diabetes was increased by 78% in the overweight group (p < 0.01). After adjusting for all relevant covariates, all‐cause mortality risk was 11% lower in the overweight group (p < 0.05). Conclusions: A BMI in the overweight range was associated with some modest disease risks but a slightly lower overall mortality rate. These findings suggest that a BMI cut‐off point of 25 kg/m² may be overly restrictive for the elderly.     

Associations of leukocyte telomere length with body anthropometric indices and weight change in chinese women

Objective: This study evaluated associations of telomere length with various anthropometric indices of general and abdominal obesity, as well as weight change. Design and Methods: The study included 2,912 Chinese women aged 40‐70 years. Monochrome multiplex quantitative polymerase chain reaction was applied to measure relative telomere length. Results: Telomere length was inversely associated with body mass index (BMI), waist circumference, waist‐to‐height ratio, weight, and hip circumference (P_trend = 0.005, 0.004, 0.004, 0.010, and 0.026, respectively), but not waist‐to‐hip ratio (P_trend = 0.116) or height (P_trend = 0.675). Weight change since age 50 was further evaluated among women over age 55. Women who maintained their weight within ±5% since age 50, particularly within a normal range (BMI = 18.5‐24.9 kg/m²), or reduced their weight from overweight (BMI = 25‐29.9 kg/m²) or obesity (BMI ≥30 kg/m²) to normal range, had a longer mean of current telomere length than women who gained weight since age 50 (P_trend = 0.025), particularly those who stayed in obesity or gained weight from normal range or overweight to obesity (P = 0.023). Conclusion: Our findings show that telomere shortening is associated with obesity and that maintaining body weight within a normal range helps maintain telomere length.     

Modeling the Impact of Adjustable Gastric Banding on Survival in Patients with Morbid Obesity

Objective: Morbid obesity is associated with premature death. Adjustable gastric banding may lead to substantial weight loss in patients with morbid obesity. Little is known about the impact of weight loss on survival after adjustable gastric banding. We therefore developed a mathematical model to estimate life expectancy in patients with a body mass index (BMI) ≥40 kg/m² undergoing bariatric surgery. Research Methods and Procedures: We developed a nonhomogeneous Markov chain consisting of five states: the absorbing state (“dead”) and the four recurrent states BMI ≥40 kg/m², BMI 36 to 39 kg/m², BMI 32 to 35 kg/m², and BMI 25 to 31 kg/m². Scenarios of weight loss and age‐ and sex‐dependent risk of death, as well as BMI‐dependent excess mortality were extracted from life tables and published literature. All patients entered the model through the state of BMI ≥40 kg/m². Results: In men aged either 18 or 65 years at the time of surgery, who moved from the state BMI ≥40 kg/m² to the next lower state of BMI 36 to 39 kg/m², life expectancy increased by 3 and 0.7 years, respectively. In women aged either 18 or 65 years at the time of surgery, who moved from the state BMI ≥40 kg/m² to the next lower state BMI 36 to 39 kg/m², life expectancy increased by 4.5 and 2.6 years, respectively. Weight loss to lower BMI strata resulted in further gains of life expectancy in both men and women. Discussion: Within the limitations of the modeling study, adjustable gastric banding in patients with morbid obesity may substantially increase life expectancy.     

Obesity and Quality of Life: Mediating Effects of Pain and Comorbidities

Objective: To estimate the association between body mass index (BMI) and health‐related quality of life (HRQL) and examine whether joint pain and obesity‐related comorbidities mediate the BMI‐HRQL association. Research Methods and Procedures: Population‐based survey data from the 1999 Behavioral Risk Factor Surveillance Survey. Adults (N = 155, 989) were classified according to BMI as underweight (<18.5 kg/m²), desirable weight (18.5 to 24.9 kg/m²), overweight (25 to 29.9 kg/m²), obese class I (30 to 34.9 kg/m²), obese class II (35 to 39.9 kg/m²), and obese class III (≥40 kg/m²). Data including general health status, unhealthy days in the past 30 caused by physical problems and mental problems, and total unhealthy days in the past 30 were collected. Results: After adjusting for age, sex, race, smoking, education, and income, we observed J‐shaped associations between BMI and HRQL. Compared with desirable weight adults, underweight, overweight, and obesity classes I, II, and III adults [odds ratio (OR) = 1.57, 1.19, 1.95, 2.72, and 4.36, respectively] were significantly (p < 0.001) more likely to report fair/poor general health status. For unhealthy days caused by physical problems, the corresponding ORs were 1.51, 1.15, 1.66, 2.27, and 3.61 (p < 0.001). For unhealthy days caused by mental problems, the ORs were 1.35, 1.14 1.43, 1.57, and 2.25 (p < 0.001). For total unhealthy days, the corresponding ORs were 1.27, 1.09, 1.37, 1.73, and 2.46 (p < 0.01). Adding joint pain and obesity‐related comorbidities into models attenuated BMI‐HRQL associations. Discussion: Associations between BMI and HRQL indices were J‐shaped. Joint pain and comorbidities may mediate BMI‐HRQL associations.     

BMI, obesity, and sickness absence in the Whitehall II study

Objective: To study BMI and change in BMI from age 25 as predictors of sickness absence. Research Methods and Procedures: Data were collected from 2564 women and 5853 men, who were British civil servants (35 to 55 years) on entry to the Whitehall II study (Phase 1, 1985 to 1988). Employer's records provided annual medically certified (long, >7 days) and self‐certified (short, 1 to 7 days) spells of sickness absence. BMI at age 25 and Phase 1 were examined in relation to absences from Phase 1 to the end of 1998 (mean follow‐up, 7.0 years). Results: After adjustment for employment grade, health‐related behaviors, and health status, overweight (BMI = 25.0 to 29.9 kg/m²) and obesity (BMI > 30.0 kg/m²) at Phase 1 were significant predictors of short and long absences in both sexes; rate ratios (95% confidence intervals) ranged from 1.13 (1.05 to 1.21) to 1.51 (1.30 to 1.76) compared with a BMI of 21.0 to 22.9 kg/m². Additionally, a BMI of 23.0 to 24.9 kg/m² at Phase 1 predicted long absences in women, and underweight (BMI < 21.0 kg/m²) predicted short absences in men. Obesity at age 25 predicted long absences, and obesity at Phase 1 predicted short and long absences in both sexes. Chronic obesity was a particularly strong predictor of long absences in men, with a rate ratio of 2.61 (1.88 to 3.63). Discussion: Findings from this well‐characterized cohort suggest that the obesity epidemic in industrialized countries may result in significant increases in sickness absence. Further research is needed to determine the underlying mechanisms. Policy to reduce sickness absence needs to tackle the problem of excess weight in the working population.     

Assessing the Validity of Body Mass Index Standards in Early Postmenopausal Women

Objective: To examine the relationship between percentage of total body fat (%Fat) and body mass index (BMI) in early postmenopausal women and to evaluate the validity of the BMI standards for obesity established by the NIH. Research Methods and Procedures: Three hundred seventeen healthy, sedentary, postmenopausal women (ages, 40 to 66 years; BMI, 18 to 35 kg/m²; 3 to 10 years postmenopausal) participated in the study. Height, weight, BMI, and %Fat, as assessed by DXA, were measured. Receiver operating characteristic analysis was performed to evaluate the ability of BMI to discriminate obesity from non‐obesity using 38%Fat as the criterion value. Results: A moderately high relationship was observed between BMI and %Fat (r = 0.81; y = 1.41x + 2.65) with a SE of estimate of 3.9%. Eighty‐one percent of other studies examined fell within 1 SE of estimate as derived from our study. Receiver operating characteristic analysis showed that BMI is a good diagnostic test for obesity. The cutoff for BMI corresponding to the criterion value of 38%Fat that maximized the sum of the sensitivity and specificity was 24.9 kg/m². The true‐positive (sensitivity) and false‐positive (1 ? specificity) rates were 84.4% and 14.6%, respectively. The area under the curve estimate for BMI was 0.914. Discussion: There is a strong association between %Fat and BMI in postmenopausal women. Current NIH BMI‐based classifications for obesity may be misleading based on currently proposed %Fat standards. BMI >25 kg/m² rather than BMI >30 kg/m² may be superior for diagnosing obesity in postmenopausal women.     

Overall and central obesity and risk of type 2 diabetes in U.S. black women

Objective: Obesity has risen to epidemic proportions in the United States, leading to an emerging epidemic of type 2 diabetes. African‐American women are disproportionately affected by both conditions. While an association of overall obesity with increasing risk of diabetes has been documented in black women, the effect of fat distribution, specifically abdominal obesity, has not been studied. We examined the association of BMI, abdominal obesity, and weight gain with risk of type 2 diabetes. Research Methods and Procedures: During eight years of follow‐up of 49,766 women from the Black Women's Health Study, 2472 incident cases of diabetes occurred. Cox proportional hazard models were used to estimate incidence rate ratios (IRRs), with control for age, physical activity, family history of diabetes, cigarette smoking, years of education, and time period of data collection. Results: Sixty‐one percent of participants had a BMI ≥25 kg/m² (WHO definition of overweight). Compared with a BMI of <23 kg/m², the IRR for a BMI of >45 kg/m² was 23 (95% confidence interval, 17.0 to 31.0). The IRR for the highest quintile of waist‐to‐hip ratio relative to the lowest was 2.3 (95% confidence interval, 2.0 to 2.7) after control for BMI. Furthermore, at every level of BMI, an increased risk was observed for high waist‐to‐hip ratio relative to low. Discussion: Central obesity, as well as overall obesity, is a strong risk factor for diabetes in African‐American women. Efforts to reduce the prevalence of obesity in African‐American women are of paramount importance.     

Overweight,Obesity, and Binge Eating in a Non‐clinical Sample of Five Brazilian Cities

Objective: To investigate the relationship between obesity/overweight and binge eating episodes (BEEs) in a large nonclinical population. Research Methods and Procedures: Consumers at shopping centers in five Brazilian cities (N = 2858) who participated in an overweight prevention program were interviewed and had weight and height measured to calculate BMI. Results: Prevalence of overweight (BMI = 25 to 29.9 kg/m²) was 46.6% for men and 36.6% for women. Obesity (BMI ≥ 30 kg/m²) was about two‐thirds of the prevalence of overweight. BEEs (subjects who binged one or more times per week over the last 3 months) in normal‐weight individuals was 1.4% for men and 3.9% for women, whereas in overweight/obese, these prevalences were 6.5% and 5.5%, respectively (p < 0.01). After adjustment for age, socioeconomic variables, and childhood obesity, those who reported BEEs had an odds ratio of being overweight/obese of 3.31 (95% confidence interval: 1.11 to 9.85) for men and 1.73 (95% confidence interval: 1.05 to 2.84) for women. Discussion: These findings indicate a strong association between episodes of binge eating and overweight/obesity, mainly among men.     

Eligibility for Obesity Treatment and Risk of Mortality in Men

Objective: To evaluate the risk of all‐cause and cardiovascular disease (CVD) mortality associated with each outcome of the NIH obesity treatment algorithm and to examine the effects of cardiorespiratory fitness on the risk of mortality associated with these outcomes. Research Methods and Procedures: The NIH obesity treatment algorithm was applied to 18, 666 men (20 to 64 years of age) from the Aerobics Center Longitudinal Study in Dallas, TX, examined between 1979 and 1995. Risk of all‐cause and CVD mortality was assessed using Cox proportional hazards regression. Results: A total of 7029 men (37.7%) met the criteria for needing weight loss treatment [overweight (BMI = 25 to 29.9 kg/m² or WC > 102 cm) with ≥2 CVD risk factors or obese (BMI ≥ 30 kg/m²)]. Mortality surveillance through 1996 identified 435 deaths (151 from CVD) during 191, 364 man‐years of follow‐up. Compared with the normal weight reference group, the hazard ratios (95% confidence interval) for death from all causes were 0.63 (0.45 to 0.88), 1.23 (0.98 to 1.54), 1.05 (0.60 to 1.85), and 1.71 (1.64 to 2.31) for men who were overweight with <2 CVD risk factors, overweight with ≥2 CVD risk factors, obese with <2 CVD risk factors, and obese with ≥2 CVD risk factors, respectively. Corresponding hazard ratios for CVD mortality were 0.72 (0.38 to 1.37), 1.67 (1.12 to 2.50), 1.69 (0.67 to 4.30), and 3.31 (2.07 to 5.30). Including physical fitness as a covariate significantly attenuated all risk estimates. Discussion: The NIH obesity treatment algorithm is useful in identifying men at increased risk of premature mortality; however, including an assessment of fitness would help improve risk stratification among all groups of patients.     

Familial Risk of Overweight and Obesity in the Canadian Population using the WHO/NIH Criteria

Objective: To determine the familial risk of overweight and obesity in Canada. Research Methods and Procedures: The sample was comprised of 15,245 participants from 6377 families of the Canada Fitness Survey. The risk of overweight and obesity among spouses and first‐degree relatives of individuals classified as underweight, normal weight, pre‐obese, or obese (Class I and II) according to the WHO/NIH guidelines for body mass index (BMI) was determined using standardized risk ratios. Results: Spouses and first‐degree relatives of underweight individuals have a lower risk of overweight and obesity than the general population. On the other hand, the risk of Class I and Class II obesity (BMI 35 to 39.9 kg/m²) in relatives of Class I obese (BMI 30 to 34.9 kg/m²) individuals was 1.84 (95% CI: 1.27, 2.37) and 1.97 (95% CI: 0.67, 3.25), respectively, in spouses, and 1.44 (95% CI:1.10, 1.78) and 2.05 (95% CI: 1.37, 2.73), respectively in first‐degree relatives. Further, the risk of Class II obesity in spouses and first‐degree relatives of Class II obese individuals was 2.59 (95% CI: ?0.91, 6.09) and 7.07 (95% CI: 1.48, 12.66) times the general population risk, respectively. Discussion: There is significant familial risk of overweight and obesity in the Canadian population using the BMI as an indicator. Comparison of risks among spouses and first‐degree relatives suggests that genetic factors may play a role in obesity at more extreme levels (Class II obese) more so than in moderate obesity.     

The Relationship between Body Weight and Health Care among German Women

Objective: To investigate the relationship between body weight and the use of health care services among women from southern Germany. Research Methods and Procedures: Data were drawn from the 1994 to 1995 Monitoring of Trends and Determinants in Cardiovascular Disease Augsburg survey, covering a population‐representative sample of women 25 to 74 years old (n = 2301). Logistic regression models were used to calculate odds ratios (ORs) for the use of medical services by women with overweight (BMI 25.0 to 29.9 kg/m²) or obesity (BMI ≥ 30 kg/m²) in comparison with normal‐weight women (BMI < 25.0 kg/m²). Results: In multivariable analysis, obese women 50 to 74 years old were more likely than normal‐weight women to delay cancer screening procedures, such as manual breast examination and Papanicolaou smear (OR 0.52, 95% confidence interval 0.37 to 0.74) in the previous 12 months. However, the relationship between obesity and cancer screening was not found to be significant in 25‐ to 49‐year‐old women (OR 0.92, 95% confidence interval 0.62 to 1.36). Neither in the 25‐ to 49‐year‐old age group nor in the 50‐ to 74‐year‐old age group were independent relationships between higher body weight and total physician visits, hospitalizations, or medication use observed. Discussion: Obese women tended to use medical services with greater frequency due to obesity‐related diseases. However, postmenopausal women with a BMI ≥ 30 kg/m² were more likely to delay routine cancer screening, putting them at a greater risk for death from breast, cervical, and endometrial cancer. Thus, obese postmenopausal women should be targeted for increased screening.     

Overweight and Obesity: Two Predictors for Worse Early Outcome in Total Hip Replacement?

Objective: Doctors and patients assume that overweight and obesity are negative predictors for good and excellent early outcome after total hip replacement. It was the purpose of this prospective investigation to assess whether overweight or obese patients have worse early postoperative outcome in comparison with normal‐weight patients. Research Methods and Procedures: Sixty‐seven consecutive patients receiving a total hip replacement were enrolled in the study. Patients were grouped into three samples according to BMI: normal‐weight (BMI < 25 kg/m², n = 11), overweight (BMI 25 to 29.9 kg/m², n = 36), and obese (BMI ≥30 kg/m², n = 20). At 10 days and at 3 months after surgery, the patient‐centered outcome was analyzed with a self‐administered assessment chart, the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index. Statistical analysis was performed with a multiple regression model that took into consideration further confounding parameters (age, sex, affected side, anchorage of the implant, duration of surgery, hospital length of stay, and prior pain, stiffness, and function). Results: No significant influence of individual BMI on subjective outcome according to the WOMAC questionnaire was observed at either 10 days or 3 months after surgery. Hospital length of stay was comparable, and WOMAC scores did not differ significantly preoperatively, at 10 days, or at 3 months postoperatively among patients with different BMI. Discussion: These data showed that the BMI of the patients in our study sample had no significant impact on early outcome or hospital length of stay after total hip replacement. Our data suggest, therefore, that body weight should not be a justification for withholding surgery from overweight or obese patients.     

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.     

Effect of obesity on inpatient rehabilitation outcomes after total hip arthroplasty

Objective: This study examined whether obesity affected inpatient rehabilitation outcomes after total hip arthroplasty (THA). Research Methods and Procedures: This was a retrospective, comparative study conducted using a computerized medical database derived from THA patients at a university‐affiliated rehabilitation hospital (data from 2002 to 2005). Patients were divided into four brackets based on BMI: non‐obese (<25 kg/m²), overweight (25 to 29.9 kg/m²), moderate obesity (30 to 39.9 kg/m²), and severe obesity (≥40 kg/m²). All patients completed an interdisciplinary inpatient rehabilitation program after THA. Functional independence measure (FIM) scores, length of stay (LOS), FIM efficiency scores (FIM/LOS), hospital charges, and discharge disposition location were collected. Results: FIM scores improved from admission to discharge similarly in all groups (25 to 29.5 points). However, FIM efficiency, LOS, and total charges were curvilinearly related with BMI (all p < 0.05). Total hospital charges were highest in the severely obese group compared with the overweight group (p < 0.05). Non‐homebound discharge disposition rates were lower in non‐obese (13.1%) and severely obese groups (10.5%). Discussion: Elevated BMI does not prevent FIM gains in THA patients during inpatient rehabilitation. However, BMI is related with FIM efficiency, LOS, and hospital charges in a curvilinear fashion. Severely obese patients can achieve physical improvements but at a lower efficiency and greater cost.     

Body Mass Index Cutoffs for Underweight,Overweight, and Obesity in South Korean Schoolgirls

Objectives: To establish BMI percentiles and cutoffs for underweight, overweight, and obesity in South Korean schoolgirls. Research Methods and Procedures: A total of 1229 South Korean schoolgirls aged 8 to 18 years were randomly selected to complete a self‐administered questionnaire. BMI charts and cutoffs were constructed after analyzing data from 1107 subjects. Percentile curves were established by the modified LMS method. Results: The percentiles for underweight, overweight, and obesity corresponding to BMI of 18.5, 23.0, and 25.0 kg/m² at age 18 were the 13.0th percentile, the 77.8th percentile, and the 91.2nd percentile, respectively. The corresponding prevalences of underweight, overweight, and obesity were 12.1, 12.5, and 9.8%, respectively. Discussion: We established for the first time, to our knowledge, new BMI cutoffs for ages 8 to 18 that corresponded to BMIs of 18.5, 23.0, and 25.0 kg/m² for Asian adults designated by the International Obesity Task Force. These newly established BMI cutoffs might help to estimate the prevalence of overweight and obesity in Asian children.     

Hypocretin Deficiency in Narcoleptic Humans Is Associated with Abdominal Obesity

Objective: To determine the prevalence of obesity among patients with narcolepsy, to estimate associated long‐term health risks on the basis of waist circumference, and to distinguish the impact of hypocretin deficiency from that of increased daytime sleepiness (i.e., reduced physical activity) on these anthropometric measures. Research Methods and Procedures: A cross‐sectional, case‐control study was conducted. Patients with narcolepsy (n = 138) or idiopathic hypersomnia (IH) (n = 33) were included. Age‐matched, healthy members of the Dutch population (Monitoring Project on Risk Factors for Chronic Diseases and Doetinchem Project; n = 10, 526) were used as controls. BMI and waist circumference were determined. Results: Obesity (BMI ≥ 30 kg/m²) and overweight (BMI 25 to 30 kg/m²) occurred more often among narcolepsy patients [prevalence: 33% (narcoleptics) vs. 12.5% (controls) and 43% (narcoleptics) vs. 36% (controls), respectively; both p < 0.05]. Narcoleptics had a larger waist circumference (mean difference 5 ± 1.4 cm, p < 0.001). The BMI of patients with IH was significantly lower than that of narcolepsy patients (25.6 ± 3.6 vs. 28.5 ± 5.4 kg/m²; p = 0.004). Discussion: Overweight and obesity occur frequently in patients with narcolepsy. Moreover, these patients have an increased waist circumference, indicating excess fat storage in abdominal depots. The fact that patients with IH had a lower BMI than narcoleptics supports the notion that excessive daytime sleepiness (i.e., inactivity) cannot account for excess body fat in narcoleptic patients.     

Air Displacement Plethysmography: Validation in Overweight and Obese Subjects

Objective: Patients with moderate and severe obesity, because of their physical size, often cannot be evaluated with conventional body composition measurement systems. The BOD POD air displacement plethysmography (ADP) system can accommodate a large body volume and may provide an opportunity for measuring body density (D_b) in obese subjects. D_b can be used in two‐ or three‐compartment body composition models for estimating total body fat in patients with severe obesity. The purpose of this study was to compare D_b measured by ADP to D_b measured by underwater weighing (UWW) in subjects ranging from normal weight to severely obese. Research Methods and Procedures: D_b was measured with UWW and BOD POD in 123 subjects (89 men and 34 women; age, 46.5 ± 16.9 years; BMI, 31.5 ± 7.3 kg/m²); 15, 70, and 10 subjects were overweight (25 ≤ BMI < 30 kg/m²), obese (30 ≤ BMI < 40 kg/m²), and severely obese (BMI ≥ 40 kg/m²), respectively. Results: There was a strong correlation between D_b(kilograms per liter) measured by UWW and ADP (r = 0.94, standard error of the estimate = 0.0073 kg/L, p < 0.001). Similarly, percent fat estimates from UWW and ADP using the two‐compartment Siri equation were highly correlated (r = 0.94, standard error of the estimate = 3.58%, p < 0.001). Bland‐Altman analysis showed no significant bias between D_b measured by UWW and ADP. After controlling for D_b measured by ADP, no additional between‐subject variation in D_b by UWW was accounted for by subject age, sex, or BMI. Discussion: Body density, an important physical property used in human body composition models, can be accurately measured by ADP in overweight and obese subjects.