WHO Body Mass Index Categories Research Articles

Body Mass Index Is Associated with the Severity and All-Cause Mortality of Acute Kidney Injury in Critically Ill Patients: An Analysis of a Large Critical Care Database.

Background Acute kidney injury (AKI) is a common clinical syndrome carrying high morbidity and mortality. Body mass index (BMI) is a common health indicator, and a high BMI value-obesity has been shown to be associated with the outcomes of several diseases. However, the relationship between different BMI categories and mortality in all critically ill patients with AKI is unclear and needs further investigation. Therefore, we evaluated the ability of BMI to predict the severity and all-cause mortality of AKI in critically ill patients. Methods We extracted clinical data from the MIMIC-III v1.4 database. All adult patients with AKI were initially screened. The baseline data extracted within 24 hours after ICU admission were presented according to WHO BMI categories. Logistic regression models and the Cox proportional hazards models were, respectively, constructed to assess the relationship between BMI and the severity and all-cause mortality of AKI. The generalized additive model (GAM) was used to identify nonlinear relationships as BMI was a continuous variable. The subgroup analyses were performed to further analyze the stability of the association between BMI category and 365-day all-cause mortality of AKI. Result A total of 15,174 patients were extracted and were divided into four groups according to BMI. Obese patients were more likely to be young and male. In the fully adjusted logistic regression model, we found that overweight and obesity were significant predictors of AKI stage III (OR, 95 CI: 1.17, 1.05–1.30; 1.32, 1.18–1.47). In the fully adjusted Cox proportional hazards model, overweight and obesity were associated with significantly lower 30-day, 90-day, and 365-day all-cause mortality. The corresponding adjusted HRs (95 CIs) for overweight patients were 0.87 (0.77, 0.99), 0.84 (0.76, 0.93), and 0.80 (0.74, 0.88), and for obese patients, they were 0.87 (0.77, 0.98), 0.79 (0.71, 0.88), and 0.73 (0.66, 0.80), respectively. The subgroup analyses further presented a stable relationship between BMI category and 365-day all-cause mortality. Conclusions BMI was independently associated with the severity and all-cause mortality of AKI in critical illness. Overweight and obesity were associated with increased risk of AKI stage III; however, they were predictive of a relatively lower mortality risk in these patients.

Body Mass Index and Weight Change in Patients With HER2-Positive Early Breast Cancer: Exploratory Analysis of the ALTTO BIG 2-06 Trial

Background: The association between obesity and prognosis in HER2-positive early breast cancer remains unclear, with limited data available. This study aimed to determine the impact of body mass index (BMI) at baseline and weight change after 2 years on outcomes of patients with HER2-positive early breast cancer. Methods: ALTTO was a randomized phase III trial in patients with HER2-positive early breast cancer. BMI was collected at randomization and 2 years after. WHO BMI categories were used: underweight, <18.5 kg/m2; normal weight, 18.5 to <25 kg/m2; overweight, ≥25 to <30 kg/m2; and obese ≥30 kg/m2. A weight change from baseline of ≥5.0% and ≤5.0% was categorized as weight gain and weight loss. The impact of BMI at randomization and of weight change on disease-free survival (DFS), distant disease-free survival (DDFS), and overall survival (OS) were investigated with multivariate analyses, adjusting for baseline patients and tumor characteristics. Results: A total of 8,381 patients were included: 187 (2.2%), 3,797 (45.3%), 2,690 (32.1%), and 1,707 (20.4%) were underweight, normal weight, overweight, and obese at baseline, respectively. Compared with normal weight, being obese at randomization was associated with a significantly worse DDFS (adjusted hazard ratio [aHR], 1.25; 95% CI, 1.04–1.50) and OS (aHR, 1.27; 95% CI, 1.01–1.60), but no significant difference in DFS (aHR, 1.14; 95% CI, 0.97–1.32). Weight loss ≥5.0% at 2 years after randomization was associated with significantly poorer DFS (aHR, 1.34; 95% CI, 1.05–1.71), DDFS (aHR, 1.46; 95% CI, 1.07–1.98), and OS (aHR, 1.83; 95% CI, 1.18–2.84). Hormone receptor and menopausal status but not anti-HER2 treatment type influenced outcomes. Toxicities were more frequent in obese patients. Conclusions: In patients with HER2-positive early breast cancer, obesity at baseline is a poor prognostic factor. Weight loss during treatment and follow-up negatively impacts clinical outcomes. Dietary counseling should be part of survivorship care programs.

Optimal Gestational Weight Gain for Tibetans Based on Prepregnancy Body Mass Index

We aimed to estimate the optimal gestational weight gain (GWG) in Tibetan women and to evaluate the appropriateness of the Institute of Medicine (IOM) GWG recommendations for Tibetan women. We analyzed data from 1474 Tibetan women from a cross-sectional study conducted in 2019. According to the three different body mass index (BMI) classification criteria (WHO BMI categories, WHO Asian BMI categories, Chinese BMI categories), we estimated the association of GWG with pregnancy outcomes (neonate birthweight and mode of delivery) using a polynomial regression model, and the optimal GWG in each BMI group was calculated. The risk of adverse outcomes showed a U-shaped curve with increasing GWG. The optimal GWG of Tibetan women based on the WHO BMI categories was 17.2 kg (range, 13.3 to 20.9 kg) for underweight, 9.3 kg (5.8 to 12.9 kg) for normal weight, and 5.2 kg (1.3 to 9.1 kg) for overweight. Underweight Tibetan mothers may gain more gestational weight than recommend by the IOM guidelines. However, normal weight Tibetan mothers are likely to benefit from gaining less weight than that recommended by the IOM. The GWG recommendations based on the IOM guidelines might not be appropriate for Tibetan women, and ethnicity-specific recommendations for GWG should be properly addressed.

Increased body mass index linked to greater short- and long-term survival in sepsis patients: A retrospective analysis of a large clinical database

ObjectivesWe investigated the impact of obesity (proxied as body mass index (BMI)), on short- and long-term mortality in sepsis patients. MethodsWe conducted a retrospective analysis with adult sepsis ICU patients in a US medical institution from 2001 to 2012 in the MIMIC-III database. The WHO BMI categories were used. Multivariate logistic regression assessed the relationships between BMI and 30-day and 1-year mortality. ResultsIn total, 5563 patients were enrolled. Obese patients tended to be younger (P<0.001), to be female (P<0.001), to acquire worse SOFA scores (P<0.001), and to receive more aggressive treatment compared with their normal weight counterparts. Obese patients had notably longer mechanical ventilation periods and ICU and hospital lengths of stay (LOSs). In the final model, overweight and obese patients had lower 30-day (OR 0.77, 95% CI 0.66–0.91; OR 0.65, 95% CI 0.56–0.77, respectively) and 1-year (OR 0.83, 95% CI 0.71–0.96; OR 0.70, 95% CI 0.60–0.81, respectively) mortality risks than normal weight patients. In contrast, underweight patients had worse 30-day and 1-year outcomes compared with normal weight patients (P=0.01, P<0.001, respectively). In morbidly obese, severe sepsis and septic shock patients, obesity remained protective. ConclusionsObesity was correlated with short- and long-term survival advantages in sepsis patients.

Is body mass index associated with lowest mortality increasing over time?

It is debatable whether the body mass index (BMI) value that is associated with the lowest all-cause mortality has increased over time. Such an increase might indicate that the WHO BMI categories for normal weight and overweight need to be revised over time. This study assessed whether the BMI associated with the lowest all-cause mortality increased over time among US adults in the National Health Interview Survey. This survey with up to 25 years of follow-up included 901 197 participants, aged 20 to 79 years with baseline BMI between 18.5 and 39.9 kg m-2 and known mortality status between the original survey dates and 31 December 2011. The BMI values associated with the lowest mortality were estimated for different survey time periods: 1986-1989, 1990-1994, 1995-1999, 2000-2004 and 2000-2009. Among 901 197 participants, 130 495 died during over 14.5 million person-years of follow-up. There was a U-shaped BMI-mortality association in all the survey periods. When we used the original follow-up durations, the BMI associated with the lowest mortality increased monotonically from 23.9 kg m-2 in 1986-1989 to 28.6 kg m-2 in 2005-2009. When using a fixed follow-up duration of 5, 10, 15 or 20 years, we found no monotonic increasing pattern in the BMI associated with the lowest mortality. With duration of 15 years, the estimates of BMI associated with lowest mortality appeared to be relatively stable over time among both the general population and never smokers free from cardiovascular disease and cancer at baseline. With a fixed long-term follow-up duration, the BMI value associated with the lowest mortality remains relatively stable over time.

Inaccurate self-report of height and its impact on misclassification of body mass index in postmenopausal women.

Self-reported height is commonly used in population obesity research. Evidence has also shown a positive association between depression and obesity. We examined the extent of height misreporting and its impact on body mass index (BMI) calculations and classification, and explored whether depression is associated with height misreporting. The Buffalo Osteoporosis and Periodontal Disease Follow-up Study enrolled 1,015 postmenopausal women between 2002 and 2006. Participants self-reported their height on a questionnaire before stadiometer measurement at the clinical visit. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale. Odds ratios and 95% CI for association between depression and height misreporting were estimated using logistic regression. Overall, 446 women (43.9%) misreported height by greater than 1/2 inch, of which 296 (29.2%) underestimated and 150 (14.8%) overestimated their height. Height misreporting influenced BMI calculations by ≥1 unit in 12% of women, and influenced classification into WHO BMI categories in 8% of women. After adjusting for age, race, education, and measured BMI, women with significant depressive symptoms were more likely to misreport their height (odds ratio = 1.65, 95% CI, 1.04-2.61). Height misreporting was common in older women and significantly influenced BMI calculations and classification. Obtaining objective data is thus important for studies investigating obesity-disease associations in this population, especially in those with significant depressive symptoms.

FRI0099 Obese patients with rheumatoid arthritis have reduced response rates to biologic anti-rheumatic agents: a comparison between european and american ra patients

BackgroundObesity in RA patients has been associated with an increased risk of comorbidity, total joint replacement, pain, disability, high medical costs and impaired quality of life. One study has suggested...

Body mass index influences the response to infliximab in ankylosing spondylitis.

IntroductionThe excess of adipose tissue in obese individuals may have immunomodulating properties and pharmacokinetic consequences. The aim of this study was to determine whether body mass index (BMI) affects response to infliximab (IFX) in ankylosing spondylitis (AS) patients.MethodsIn 155 patients retrospectively included with active AS, the BMI was calculated before initiation of IFX treatment (5 mg/kg intravenously). After 6 months of treatment, changes from baseline in BASDAI, Visual Analogue Scale (VAS) pain, C-reactive protein (CRP) level, and total dose of nonsteroidal antiinflammatory drug (NSAID) were dichotomized with a threshold corresponding to a decrease of 50% of initial level of the measure, into binary variables assessing response to IFX (BASDAI50, VAS50, CRP50, NSAID50). Whether the BMI was predictive of the response to IFX therapy according to these definitions was assessed with logistic regression.ResultsMultivariate analysis found that a higher BMI was associated with a lower response for BASDAI50 (P = 0.0003; OR, 0.87; 95% CI (0.81 to 0.94)), VAS50 (P < 0.0001; OR, 0.87; 95% CI (0.80 to 0.93)); CRP50 (P = 0.0279; OR, 0.93; 95% CI (0.88 to 0.99)), and NSAID50 (P = 0.0077; OR, 0.91; 95% CI (0.85 to 0.97)), criteria. According to the three WHO BMI categories, similar results were found for BASDAI50 (77.6%, 48.9%, and 26.5%; P < 0.0001), VAS50 (72.6%, 40.4%, and 16.7%; P < 0.0001); CRP50 (87.5%, 65.7%, and 38.5%; P = 0.0001), and NSAID50 (63.2%, 51.5%, and 34.6%; P = 0.06).ConclusionsThis study provides the first evidence that a high BMI negatively influences the response to IFX in AS. Further prospective studies, including assessment of the fat mass, pharmacokinetics, and adipokines dosages are mandatory to elucidate the role of obesity in AS IFX response.

Incidence of pre-eclampsia analysed by body mass index category and parity

BackgroundHypertension in pregnancy is an important cause of pregnancy complications for both mother and baby in about 8% of pregnancies. Epidemiological reviews have reported an association between pre-eclampsia and maternal...

Physical activity, body mass index, and mammographic density in postmenopausal breast cancer survivors.

To investigate the association between physical activity, body mass index (BMI), and mammographic density in a racially/ethnically diverse population-based sample of 522 postmenopausal women diagnosed with stage 0-IIIA breast cancer and enrolled in the Health, Eating, Activity, and Lifestyle Study. We collected information on BMI and physical activity during a clinic visit 2 to 3 years after diagnosis. Weight and height were measured in a standard manner. Using an interview-administered questionnaire, participants recalled the type, duration, and frequency of physical activities they had performed in the last year. We estimated dense area and percentage density as a continuous measure using a computer-assisted software program from mammograms imaged approximately 1 to 2 years after diagnosis. Analysis of covariance methods were used to obtain mean density across WHO BMI categories and physical activity tertiles adjusted for confounders. We observed a statistically significant decline in percentage density (P for trend = .0001), and mammographic dense area (P for trend = .0052), with increasing level of BMI adjusted for potential covariates. We observed a statistically significant decline in mammographic dense area (P for trend = .036) with increasing level of sports/recreational physical activity in women with a BMI of at least 30 kg/m2. Conversely, in women with a BMI less than 25 kg/m2, we observed a non-statistically significant increase in mammographic dense area and percentage density with increasing level of sports/recreational physical activity. Increasing physical activity among obese postmenopausal breast cancer survivors may be a reasonable intervention approach to reduce mammographic density.