Limits of body mass index to detect obesity and predict body composition

Frankenfield, David C.; Rowe, William A.; Cooney, Robert N.; Js, Smith; Becker, Dolores A.

doi:10.1016/s0899-9007(00)00471-8

Cited by 442 publications

(354 citation statements)

References 16 publications

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“…Some studies have shown that the BMI score may underestimate or overestimate overweight and obesity 5,8 , since despite its correlation with excess body fat, the index would only reflect body proportions without estimating adiposity and the distribution of body fat. 5 On the other hand, WC measurement has recently started to be used as a health risk indicator 4,9,14,22,27 .…”

Section: Discussionmentioning

confidence: 99%

“…However, this index has clear limitations when it comes to defining overweight/obesity according to the different categories of gender, age, race, and physical activity, and evaluating the nutritional risk for comorbidity 3,6,7 , as well as differentiating and quantifying body fat distribution 5,8 . Diabetes, arterial hypertension, and metabolic syndrome are risks known to be associated with the distribution of body fat and, more specifically, the increase of central fat 2,3,9,10 .…”

Section: Introductionmentioning

confidence: 99%

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Risco nutricional na população urbana de Ouro Preto, sudeste do Brasil: estudo de corações de Ouro Preto

Freitas¹,

Caiaffa²,

César³

et al. 2007

Arq. Bras. Cardiol.

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SummaryObjective: To estimate the prevalence of combined nutritional risk [body mass index (BMI) and waist circumference (WC)] according to sociodemographic and sedentarism characteristics of the urban population of Ouro Preto, state of Minas Gerais, Brazil.Methods: This cross-sectional study was conducted with a probability sampling of 768 subjects aged 15 years or older. Nutritional risk (NR) was defined according to the BMI and WC classification criteria adopted by the National Institutes 2 . Binary logistic regression and the Hosmer & Lemeshow test were used to construct and adjust these models.Results: INR was observed in several BMI categories for both women and men, with the following results: 19.1% and 1.4% among those with normal weight, 91.7% and 56% in overweight patients, and 98.5% and 80% in obese patients, respectively. Age and level of education were independently associated with the CNR. Odds ratios (OR) for CNR in women and men over 60 years of age were 9.94 and 14.35, respectively, when compared to younger patients. For women with < 4 years of schooling, the OR was 1.83 compared to patients with more than 4 years of school attendance, while among men with an average number of years of school attendance, the OR was 2.55 relative to those with more years of schooling.Conclusion: These findings show that age and education have an independent effect on the probability of CNR occurrence, and also that a joint analysis of BMI and WC is important in screening groups for nutritional risk.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risco nutricional na população urbana de Ouro Preto, sudeste do Brasil: estudo de corações de Ouro Preto

Freitas¹,

Caiaffa²,

César³

et al. 2007

Arq. Bras. Cardiol.

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“…Body weight was stable for at least 3 months prior to study in all subjects. By defining obesity as a BMI greater than 30 kg·m −2 , or a BMI greater than 27 kg·m −2 with body fat greater than 35% [31], 49 NGT, 30 IGT and 139 T2DM subjects were obese and 89 NGT, 19 IGT and 69 T2DM subjects were non-obese. The study protocol was approved by the Institutional Review Board of the University of Texas Health Science Center at San Antonio, and informed written consent was obtained from each subject prior to their participation.…”

Section: Subjectsmentioning

confidence: 99%

Beta-cell dysfunction and glucose intolerance: results from the San Antonio metabolism (SAM) study

et al. 2004

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Aims/hypothesis. Both insulin resistance and beta-cell dysfunction play a role in the transition from normal glucose tolerance (NGT) to Type 2 diabetes (T2DM) through impaired glucose tolerance (IGT). The aim of the study was to define the level of glycaemia at which beta-cell dysfunction becomes evident in the context of existing insulin resistance. Methods. Insulin response (OGTT) and insulin sensitivity (euglycaemic insulin clamp) were evaluated in 388 subjects in the San Antonio Metabolism (SAM) study (138 NGT, 49 IGT and 201 T2DM). In all subjects the insulin secretion/insulin resistance index (DeltaI/DeltaGdivided byIR) was calculated as the ratio of the increment in plasma insulin to the increment in plasma glucose during the OGTT divided by insulin resistance, as measured during the clamp. Results. In lean NGTs with a 2-h plasma glucose concentration (2-h PG) between 5.6 and 6.6 and between 6.7 and 7.7 mmol/l, there was a progressive decline in DeltaI/AGdivided byIR compared with NGTs with a 2-h PG less than 5.6 mmol/l. There was a further decline in DeltaI/DeltaGdivided byIR in IGTs with a 2-h PG between 7.8 and 9.3 and between 9.4 and 11.0 mmol/l, and in Type 2 diabetic patients with a 2-h PG greater than It. I mmol/l. Lean and obese subjects showed coincident patterns of relation of 2-h PG to DeltaI/DeltaGdivided byIR. Conclusion/interpreation. When the plasma insulin response to oral glucose is related to the glycaemic stimulus and severity of insulin resistance, there is a progressive decline in beta-cell function that begins in "normal" glucose tolerant individuals

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“…BMI and WC are frequently used by researchers and clinicians to assess nutritional status and estimate body fat (Lean, 2000). However, the accuracy of BMI to predict body fat content has been repeatedly questioned because of the confounding effect of ageing, FFM and racial differences (Frankefield et al, 2001;Prentice and Jebb, 2001) and also in view of the fact that WC could offer a better estimate of the abdominal adiposity (Lean, 2000). However, in spite of the potential weaknesses of the BIA method in measuring body composition of Gambian subjects, we did find WC having a better sensitivity than BMI for the assessment of body fat in comparison to BIA (data not shown).…”

Section: Urbanization and Obesity In The Gambiamentioning

confidence: 99%

Urbanization and obesity in The Gambia: a country in the early stages of the demographic transition

et al. 2005

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Objective: To investigate the distribution of overweight and obesity and its relationship with socio-economic and behavioural factors in a developing-country population undergoing rapid nutritional transition. Design: Cross-sectional house-to-house survey in urban Gambia. Subjects: Four groups of 50 subjects were sampled as follows: young men (YM, 14-25 years), young women (YW, 14-25 years), older men (OM, 35-50 years) and older women (OW,(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50). Measurements: Several socio-economic and behavioural factors were investigated. Composite indices for socio-economic status, education, healthy lifestyle and western influences were created. Body weight, height, waist and hip circumferences were measured and body mass index (BMI) was calculated. Body composition was assessed by leg-to-leg bioimpedance. Overweight was defined as BMI ¼ 25.0-29.9 kg/m 2 and obesity as BMIX30.0 kg/m 2 . Results: There were highly significant gender and age differences in overweight (YM ¼ 0%, YW ¼ 10%, OM ¼ 6% and OW ¼ 34%) and obesity (YM ¼ 0%, YW ¼ 4%, OM ¼ 6% and OW ¼ 50%). Only 16% of OW were neither overweight nor obese compared to 88% of OM. OW had a higher fat mass percent (38.4%) than other groups, while fat-free mass (kg) was significantly higher in males than females with YW having the lowest value. Young generations were more educated and more influenced by western ideals than OM and OW. Weight gain was not always associated with weight concern and many overweight/obese subjects did not perceive themselves as overweight. Conclusion: Social and behavioural changes are already creating a perceptible 'generational gap' among this population undergoing rapid transition. The improved education and current lean status of the younger adults offers opportunities for preventative interventions. These need to be specially targeted at women.

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Limits of body mass index to detect obesity and predict body composition

Cited by 442 publications

References 16 publications

Risco nutricional na população urbana de Ouro Preto, sudeste do Brasil: estudo de corações de Ouro Preto

Risco nutricional na população urbana de Ouro Preto, sudeste do Brasil: estudo de corações de Ouro Preto

Beta-cell dysfunction and glucose intolerance: results from the San Antonio metabolism (SAM) study

Urbanization and obesity in The Gambia: a country in the early stages of the demographic transition

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