Standard Prediction Equations Research Articles

Challenges in obtaining accurate anthropometric measures for adults with severe obesity: A community-based study.

The number of people with severe obesity (BMI ⩾40 kg/m2) is increasing rapidly, but is poorly documented, partly as a result of inappropriate standard anthropometric measurement methods for community-based people. As part of a broader study, people receiving care services and with severe obesity were visited at home. The people were assessed for measurements using different weighing scales and a standard portable stadiometer. If the stadiometer could not be used, their half arm span and knee height were measured to estimate their height using standard predictive equations. Measurements were taken for 15 women and 10 men (n = 25) aged 40-87 years (mean 62 years). Weights ranged from 98.4 to 211.8 kg (mean 150 kg), with 16 participants requiring bariatric scales. For the six people who were unable to stand, we used wheelchair scales (n = 1), bed weighing scales (n = 2), routine weights from care home records (n = 2) or weight data from hospital records (n = 1). The standard portable stadiometer could only be used for one person; the others required alternative measures from which to estimate height. Large body habitus obscured bony landmarks, meaning alternative measures gave diverse heights. Fourteen participants had a ⩾8 cm difference in height between estimates from half arm span and knee height measurements. Standard practice commonly does not provide reliable measurements for people with severe obesity, particularly those with mobility difficulties. An inability to measure weight and height accurately can exclude people from appropriate care, obscuring the true numbers affected and the effectiveness of future service planning. Safe community care requires the availability of specialist scales and standardised methods for height estimation appropriate for older and disabled people with severe obesity.

A New Approach to Improve the Validity of Doubly Labeled Water to Assess CO2 Production during High-Energy Turnover.

Accurate measurement of energy expenditure (EE) using doubly labeled water depends on the estimate of total body water (TBW). The aims of this study were to 1) assess the accuracy of a new approach for estimating TBW and EE during high-energy turnover and 2) assess the accuracy of day-to-day assessment of EE with this new approach. EE was measured in six healthy subjects (three male) for 5 consecutive days using three doubly labeled water methods: 1) the plateau, 2) slope-intercept, and 3) overnight-slope method, with whole-room indirect calorimetry as reference method. Urine samples were collected every evening and morning. High EE (physical activity level of >2.5) was achieved by cycling 4 h·d-1. Physical activity level was 2.8 ± 0.1. TBW values were 41.9 ± 6.1, 38.4 ± 5.7, and 40.4 ± 5.8 L for the plateau, slope-intercept, and overnight-slope methods, respectively. The overnight-slope method showed the highest accuracy in estimated CO2 production, when compared with indirect calorimetry over the complete 5-d period (mean ± SD difference, 0.9% ± 1.6%). The plateau method significantly overestimated CO2 production by 4.7% ± 2.6%, whereas the slope-intercept method underestimated CO2 production (-3.4% ± 2.3%). When CO2 production was assessed per day, the overnight-slope method showed an average difference of 9.4% ± 4.5% to indirect calorimetry. The overnight-slope method resulted in a more accurate estimation of CO2 production and EE compared with the plateau or slope-intercept method over a 5-d period in high physical activity conditions. Day-to-day determination of EE using the overnight-slope method was more accurate than diet recall and several standard prediction equations in athletes.

Prognostic implications of differences in forced vital capacity in black and white US adults: Findings from NHANES III with long-term mortality follow-up.

BackgroundBecause Forced Vital Capacity (FVC) is reduced in Black relative to White Americans of the same age, sex, and height, standard lung function prediction equations assign a lower "normal" range for Black patients. The prognostic implications of this race correction are uncertain.MethodsWe analyzed 5,294 White and 3,743 Black participants age 20–80 in NHANES III, a nationally-representative US survey conducted 1988–94, which we linked to the National Death Index to assess mortality through December 31, 2015. We calculated the FVC-percent predicted among Black and White participants, first applying NHANES III White prediction equations to all persons, and then using standard race-specific prediction equations. We used Cox proportional hazard models to calculate the association between race and all-cause mortality without and with adjustment for FVC (using each FVC metric), smoking, socioeconomic factors, and comorbidities.FindingsBlack participants’ age- and sex-adjusted mortality was greater than White participants (HR 1.46; 95%CI:1.29, 1.65). With adjustment for FVC in liters (mean 3.7 L for Black participants, 4.3 L for White participants) or FVC percent-predicted using White equations for everyone, Black race was no longer independently predictive of higher mortality (HR∼1.0). When FVC-percent predicted was “corrected” for race, Black individuals again showed increased mortality hazard. Deaths attributed to chronic respiratory disease were infrequent for both Black and White individuals.InterpretationLower FVC in Black people is associated with elevated risk of all-cause mortality, challenging the standard assumption about race-based normal limits. Black-White disparities in FVC may reflect deleterious social/environmental exposures, not innate differences.FundingNo funding.

The hospital frailty risk score in patients with heart failure is strongly associated with outcomes but less so with pharmacotherapy.

Although frailty is known to be an important prognostic factor in heart failure (HF), HF risk-adjustment models do not incorporate frailty measures and the interplay between frailty, age and pharmacotherapy is unclear. To explore the relationships between frailty, pharmacotherapy and outcomes in heart failure (HF). Retrospective cohort study of all adults in Alberta, Canada hospitalized for the first time for HF between 2004 and 2016. Frailty was defined using the Hospital Frailty Risk Score (HFRS). In 26626 patients (mean age 77.4years), the 8887 (33.4%) defined as frail (HFRS≥5) were older, had higher Charlson scores and more prior emergency department visits or hospitalizations. The HFRS and the Charlson Score were only weakly correlated (r=0.35). Whilst more common in older patients (41.4% of patients 80 or older), frailty was present in 22.4% of patients younger than 65. Frail patients had longer lengths of stay and worse outcomes postdischarge, but adding the HFRS to age, sex and Charlson score did not improve prediction of events (c-statistics 0.69 for 30-day mortality after admission, and 0.54 for 30-day readmission/ED visit/or death after discharge). Frail patients younger than 65 were significantly more likely than nonfrail patients 80 or older to be prescribed high-dose evidence-based HF therapies (27.1% vs. 22.2%, P=0.003). Although the HFRS reflects aspects of frailty that patient age and Charlson scores do not, the addition of the HFRS to standard risk prediction equations provides little additional information. Prescribing practices correlate more with patient age than frailty status.

Equivalence Reliability and Convergent Validity of Percent Body Fat Prediction Equations

Background: The fitness professional may often benefit from the use of a simple equation in determining a health outcome for an individual in lieu of a more complicated or expensive procedure. Therefore, the purpose of this study was to examine the reliability and validity of several standard prediction equations for percent body fat (PBF). Methods: Data used for this study came from a body composition assessment of N = 131 college students. Five different PBF prediction equations were used, with body mass index (BMI), age, and sex as inputs for each (PBFEQ1 thru PBFEQ5). Additionally, PBF using a bioelectric impedance (BIA) handheld device (PBFHH) was measured for each participant. Equivalence reliability was examined across the five PBF prediction equations using different analysis of variance (ANOVA) models of the intraclass correlation coefficient (ICC). Convergent validity between the prediction equations and PBFHH was determined by examining Pearson correlation coefficients and Bland and Altman limits of agreement (LOA). Reliability and validity was also examined for obesity classification using the Kappa statistic. Results: Reliability across the five PBF prediction equations was excellent for all ICC models in both female (ICCs > .985) and male (ICCs > .976) analyses. PBFHH scores adequately converged with scores from each prediction equation in both female (rs > .913) and male (rs > .817) analyses. LOA between PBFHH and PBFEQ5 indicate small to moderate bias of 4.0 ± 5.1% and 4.7 ± 7.9% in female and male analyses, respectively. Finally, reliability and validity of the prediction equations to classify participants into obese and non-obese categories ranged from moderate to almost perfect. Conclusion: This study provides psychometric evidence supporting the use of PBF prediction equations in a college student population.

No consistent evidence of a disproportionately low resting energy expenditure in long-term successful weight-loss maintainers

Evidence in humans is equivocal in regards to whether resting energy expenditure (REE) decreases to a greater extent than predicted for the loss of body mass with weight loss, and whether this disproportionate decrease in REE persists with weight-loss maintenance. We aimed to1) determine if a lower-than-predicted REE is present in a sample of successful weight-loss maintainers (WLMs) and 2) determine if amount of weight loss or duration of weight-loss maintenance are correlated with a lower-than-predicted REE in WLMs. Participants (18-65 y old) were recruited in 3 groups: WLMs (maintaining ≥13.6 kg weight loss for ≥1 y, n=34), normal-weight controls [NCs, body mass index (BMI; in kg/m2) similar to current BMI of WLMs, n=35], and controls with overweight/obesity (OCs, BMI similar to pre-weight-loss maximum BMI of WLMs, n=33). REE was measured (REEm) with indirect calorimetry. Predicted REE (REEp) was determined via 1) a best-fit linear regression developed with the use of REEm, age, sex, fat-free mass, and fat mass from our control groups and 2) three standard predictive equations. REEm in WLMs was accurately predicted by equations developed from NCs and OCs (±1%) and by 3 standard predictive equations (±3%). In WLMs, individual differences between REEm and REEp ranged from -257 to +163 kcal/d. A lower REEm compared with REEp was correlated with amount of weight lost (r=0.36, P<0.05) but was not correlated with duration of weight-loss maintenance (r=0.04, P=0.81). We found no consistent evidence of a significantly lower REE than predicted in a sample of long-term WLMs based on predictive equations developed from NCs and OCs as well as 3 standard predictive equations. Results suggest that sustained weight loss may not always result in a substantial, disproportionately low REE. This trial was registered at clinicaltrials.gov as NCT03422380.

Resting energy expenditure in male athletes with a spinal cord injury

Objective: To investigate whether there are differences in the resting energy expenditure (REE) and body composition of athletes with a spinal cord injury (SCI) compared to active able-bodied controls.Design: In this cross sectional study, male athletes with a SCI were compared to active able-bodied controls matched for age, stretch stature and body mass. In addition, the accuracy of standard REE prediction equations in estimating REE was assessed.Participants: Seven male wheelchair athletes with a SCI and six matched active able-bodied controls volunteered to participate.Outcome measures: REE was measured using indirect calorimetry and estimated using population-specific prediction equations. Body composition (lean tissue mass, fat mass and bone mineral content) was measured by dual energy X-ray absorptiometry (DXA).Results: While absolute and adjusted REE in the athletes with SCI was lower than controls, this difference was not significant (P = 0.259). When adjusted for lean tissue mass (LTM), REE was significantly higher (P = 0.038) in the athletes with SCI compared to the controls (146 ± 29kJ/kg LTM vs. 125 ± 8kJ/kg LTM). LTM was significantly lower in the athletes with SCI (44.35 ± 6.98 kg) compared to the able-bodied controls (56.02 ± 4.93 kg; P < 0.01). The differences between predicted and measured REE in the athletes with SCI were not statistically significant (except for the Owen equation), however there was no significant correlation between the measures.Conclusion: This suggests that existing prediction equations used to estimate energy requirements may require modification for athletes with SCI.

High resting metabolic rate among Amazonian forager‐horticulturalists experiencing high pathogen burden

Resting metabolic rate (RMR) reflects energetic costs of homeostasis and accounts for 60 to 75% of total energy expenditure (TEE). Lean mass and physical activity account for much RMR variability, but the impact of prolonged immune activation from infection on human RMR is unclear in naturalistic settings. We evaluate the effects of infection on mass-corrected RMR among Bolivian forager-horticulturalists, and assess whether RMR declines more slowly with age than in hygienic sedentary populations, as might be expected if older adults experience high pathogen burden. RMR was measured by indirect calorimetry (Fitmate MED, Cosmed) in 1,300 adults aged 20 to 90 and TEE was measured using doubly labeled water (n = 40). Immune biomarkers, clinical diagnoses, and anthropometrics were collected by the Tsimane Health and Life History Project. Tsimane have higher RMR and TEE than people in sedentary industrialized populations. Tsimane RMR is 18 to 47% (women) and 22 to 40% (men) higher than expected using six standard prediction equations. Tsimane mass-corrected TEE is similarly elevated compared to Westerners. Elevated leukocytes and helminths are associated with excess RMR in multivariate regressions, and jointly result in a predicted excess RMR of 10 to 15%. After age 40, RMR declines by 69 kcal/decade (p < .0001). Controlling for lean mass and height accounts for 71% of age-related RMR decline, and adding indicators of infection minimally affects the age slope. The residual level of age-related decline from age 40 is 1.2% per decade. High pathogen burden may lead to higher metabolic costs, which may be offset by smaller body mass or other energy-sparing mechanisms.

Validity of Physical Activity Monitors for Estimating Energy Expenditure During Wheelchair Propulsion.

It is unknown if activity monitors can detect the increased energy expenditure (EE) of wheelchair propulsion at different speeds or on different surfaces. Individuals who used manual wheelchairs (n = 14) performed 5 wheeling activities: on a level surface at 3 speeds, on a rubberized track at 1 fixed speed and on a sidewalk course at a self-selected speed. EE was measured using a portable indirect calorimetry system and estimated by an Actical (AC) worn on the wrist and a SenseWear (SW) activity monitor worn on the upper arm. Repeated- measures ANOVA was used to compare measured EE to the estimates from the standard AC prediction equation and SW using 2 different equations. Repeated-measures ANOVA demonstrated a significant main effect between measured EE and estimated EE. There were no differences between the criterion method and the AC across the 5 activities. The SW overestimated EE when wheeling at 3 speeds on a level surface, and during sidewalk wheeling. The wheelchair-specific SW equation improved the EE prediction during low intensity activities, but error progressively increased during higher intensity activities. During manual wheelchair propulsion, the wrist-mounted AC provided valid estimates of EE, whereas the SW tended to overestimate EE.

How Hyperalimentation May Be Necessary to Reverse Severe Malnutrition in Selected Patients Receiving Home Parenteral Nutrition

Standard predictive equations may under- or overestimate caloric requirements in disease states such as obesity or in patients with a low body mass index (BMI). Although this principle is common knowledge among nutrition specialists, it is often not prioritized with other clinicians outside the intensive care unit (ICU). Indirect calorimetry (IC) is often used in the ICU to estimate caloric requirements. This article outlines a very complicated case of a cachectic man with an enterocutaneous fistula who had lost more than 50% of body weight over 2 years. In rehabilitating this patient, we found that the most common formulas of basal needs greatly underestimated the calories required to prepare him for restorative surgery. Key learning points are that in malnourished ambulatory patients, predictive equations may not adequately estimate caloric needs and IC may be required.

Determination of acaricide resistance allele frequencies in field populations of Tetranychus urticae using quantitative sequencing

Resistances to monocrotophos, fenpropathrin and abamectin in Tetranychus urticae are primarily conferred by reduced sensitivities of respective target sites [i.e., acetylcholinesterase (TuAChE), voltage-sensitive sodium channel (TuVSSC) and glutamate-gated chloride channel (TuGluCl)], which are due to point mutations (G228S and F439W in TuAChE; L1022V in TuVSSC; G323D in TuGluCl). As a population-based genotyping technique, a quantitative sequencing (QS) protocol was developed for the determination of the resistance-associated mutation frequencies in T. urticae. Standard prediction equations revealed high correlation coefficients (r2=0.993–0.999), demonstrating that the resistant nucleotide signal ratio is highly proportional to the resistance allele frequencies. The lower and higher detection limits for the four resistance mutations were 3.7–13.1% (7.8±3.3%) and 89.4–97.3% (93.3±3.2%), respectively, suggesting that QS can be employed as a preliminary monitoring tool for the detection of resistance allele frequencies, which ranged approximately 7.8–93.3% at the 95% confidence level. The QS was successfully employed for the determination of resistance allele frequencies in 26 T. urticae populations. The two TuAChE mutations responsible for monocrotophos resistance were almost saturated in most field populations. The TuVSSC L1022V mutation tentatively associated with fenpropathrin resistance was also found in 9 field populations. However, the TuGluCl G323D mutation conferring abamectin resistance was found only in one field population, suggesting that abamectin resistance is not yet widespread. The QS protocol, as an alternative to traditional bioassays, will greatly facilitate resistance monitoring of T. urticae.

P.11.7 Prediction equations based on arm measurements may overestimate standing height in Duchenne Muscular Dystrophy (DMD) patients on glucocorticoid (GC) therapy

Accurate height measurements (HM) are needed for evaluation of growth and nutrition status, calculation of medication doses, glomerular function, pulmonary function tests (PFT) and 6 min walk tests (6MWT). HM is unreliable in patients with inability to stand or joint or spinal deformities. Prediction equations for height based on arm span (AS) and ulnar length measurements have been established in healthy children. To date, there are no similar prediction equations for children with neuromuscular (NM) disorders. (1) To evaluate the bias in predicted height from Gauld’s (2004) equation based on AS (here, bias is defined as observed height minus predicted height); and (2) to correlate AS and segmental arm span (SAS) measurements with standing height (SH) in children with NM disorders. Cross sectional study of 50 males with DMD on GC and 19 males with NM disorders not on GC treatment (Non GC). SH, AS, SAS were measured. Subjects were 69 males with NM disorders with or without GC treatment (GC 0 N = 50, aged 8.8 ± 2.7 y; Non GC – N = 19, aged 8.3 ± 3.0 y). Gauld’s prediction equation based on AS overestimated SH by a mean of 1.68 ± 2.48 cm in GC group ( p p = 0.81). AS and SAS were highly correlated with SH in both groups (GC – AS & SH, r 2 = 0.97; SAS & SH, r 2 = 0.95; non-GC – AS & SH, r 2 = 0.98; SAS & SH, r 2 = 0.97). Our study verified the accuracy of Gauld’s equation based on AS in the non GC group and noted the overestimation of SH in the GC group. GC induced spine compression fractures and linear growth failure may affect SH in children with NM disorders on GC, thereby limiting the use of standard prediction equations for height in this population. Further studies to obtain accurate height prediction equations in NM patients on GC are warranted when accurate PFTs and 6MWTs are integral outcome measures for clinical care and research.

Resting energy expenditure in subjects with fibro-calculous pancreatic diabetes (胰腺纤维钙化性糖尿病患者的静息时能量消耗)

Fibro-calculous pancreatic diabetes is an indigenous disorder present in populations largely in tropical regions. Energy expenditure through indirect calorimetry has not been studied in this disorder and may provide important clues as to the pathogenesis of diabetes in these patients. A total of 51 males in three groups comprising fibrocalculous pancreatic diabetes (FCPD) (group 1; n = 24), type 2 diabetes (group 2; n = 15) and healthy controls (group 3; n = 12) were studied. The body composition was measured using Dual Energy X-ray Absorptiometry (DEXA) and the REE was estimated using indirect calorimetry. The predicted energy expenditure (PEE) was calculated using three different equations. Patients in both groups with diabetes had a higher mean waist-hip ratio than the controls (P = 0.002). However patients with type 2 diabetes alone had a significantly higher mean body mass index (P = 0.012), percentage of fat (P = 0.016) and total fat content (P = 0.031). There was no significant difference in REE among the three groups. After adjustment of body mass index (BMI), the REE was significantly higher in patients with FCPD than in those patients with Type 2 diabetes. PEE correlated poorly with indirect calorimetry. Energy expenditure in patients with diabetes varies according to the composition and distribution of body fat and is lower in patients with FCPD. Standard predictive equations were not accurate for the assessment of energy expenditure in patients with FCPD. Further research is required to recommend specific nutritional therapy for this group of patients.

Macronutrient intake in overweight adults with chronic spinal cord injury – analysis before and after dietetic intervention

than the estimated needs (Henry’s approach (4) v. 7-day food diary intake: 8.9MJ/d v. 7.65MJ/d, p <0.01). The present study shows that simple dietetic intervention can improve the quality of the patient’s diet, and there is some evidence that nutrient imbalance in SCI patients relative to the RNI can also be improved. Current guidance on nutritional requirement may be important overestimates for the SCI population. Despite energy intakes at lower than estimated needs the SCI population experiences damaging weight gain. To prevent obesity, we tentatively propose a reduction of 15% of total energy need provision from that proposed by standard predictive equations for individuals with SCI. In order to determine the optimal nutritional requirements in this specific high risk group of patients, further research, measuring energy expenditure and nutrient intake, is warranted.

New Specific Equation to Estimate Resting Energy Expenditure in Severely Obese Patients

Calculating the estimated resting energy expenditure (REE) in severely obese patients is useful, but there is controversy concerning the effectiveness of available prediction equations (PE) using body weight (BW). We evaluated the efficacy of REE equations against indirect calorimetry (IC) in severely obese subjects and aimed to develop a new equation based on body composition compartments. One hundred and twenty severely obese patients had their REE measured (MREE) by IC and compared to the most commonly used PE (Harris-Benedict (HB), Ireton-Jones, Owen, and Mifflin St. Jeor). In a random sample (n = 60), a new REE equation based on fat-free mass (FFM) was developed and validated. All PE studied failed to estimate REE in severe obesity (low concordance correlation coefficient (CCC) and limits of agreement of nearly 50% of the sample ±10% of MREE). The HB equation using actual BW exhibited good results for all samples when compared to IC (2,117 ± 518 kcal/day by HB vs. 2,139 ± 423 kcal/day by MREE, P > 0.01); these results were blunted when patients were separated by gender (2,771 vs. 2,586 kcal/day, P < 0.001 in males and 1,825 vs. 1,939 kcal/day, P < 0.001 in females). A new resting energy expenditure equation prediction was developed using FFM, Horie-Waitzberg, & Gonzalez, expressed as 560.43 + (5.39 × BW) + (14.14 × FFM). The new resting energy expenditure equation prediction, which uses FFM and BW, demonstrates higher accuracy, precision, CCC, and limits of agreement than the standard PE in patients when compared to MREE (2,129 ± 45 kcal/day vs. 2,139 ± 423 kcal/day, respectively, P = 0.1).The new equation developed to estimate REE, which takes into account both FFM and BW, provides better results than currently available equations.

Variable dietary management of methylmalonic acidemia: metabolic and energetic correlations

Isolated methylmalonic acidemia (MMA) is managed by dietary protein restriction and medical food supplementation. Resting energy expenditure (REE) can be depressed in affected individuals for undefined reasons. The objective was to document the spectrum of nutritional approaches used to treat patients with MMA, measure REE, and analyze the dependence of REE on body composition, biochemical, and nutritional variables. Twenty-nine patients with isolated MMA (22 mut, 5 cblA, 2 cblB; 15 males, 14 females; age range: 2-35 y) underwent evaluation. REE was measured with open-circuit calorimetry and compared with predicted values by using age-appropriate equations. Nutritional regimens were as follows: protein restriction with medical food (n = 17 of 29), protein restriction with medical food and supplemental isoleucine or valine (n = 5 of 29), or the use of natural protein alone for dietary needs (n = 7 of 29). Most mut patients had short stature and higher percentage fat mass compared with reference controls. Measured REE decreased to 74 ± 13.6% of predicted (P < 0.001) in the ≤ 18-y group (n = 22) and to 83 ± 11.1% (P = 0.004) in patients aged >18 y (n = 7). Linear regression modeling suggested that age (P = 0.001), creatinine clearance (P = 0.01), and height z score (P = 0.04) accounted for part of the variance of measured REE per kilogram of fat-free mass (model R² = 0.66, P < 0.0001). There is wide variation in the dietary treatment of MMA. Standard predictive equations overestimate REE in this population primarily due to their altered body composition and decreased renal function. Defining actual energy needs will help optimize nutrition and protect individuals from overfeeding. This trial is registered at clinicaltrials.gov as NCT00078078.

Ability of commonly used prediction equations to predict resting energy expenditure in children with inflammatory bowel disease

Paediatric onset inflammatory bowel disease (IBD) may cause alterations in energy requirements and invalidate the use of standard prediction equations. Our aim was to evaluate four commonly used prediction equations for resting energy expenditure (REE) in children with IBD. Sixty-three children had repeated measurements of REE as part of a longitudinal research study yielding a total of 243 measurements. These were compared with predicted REE from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict equations using the Bland-Altman method. Mean (±SD) age of the patients was 14.2 (2.4) years. Mean measured REE was 1566 (336) kcal per day compared with 1491 (236), 1441 (255), 1481 (232), and 1435 (212) kcal per day calculated from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict, respectively. While the Schofield equation demonstrated the least difference between measured and predicted REE, it, along with the other equations tested, did not perform uniformly across all subjects, indicating greater errors at either end of the spectrum of energy expenditure. Smaller differences were found for all prediction equations for Crohn's disease compared with ulcerative colitis. Of the commonly used equations, the equation of Schofield should be used in pediatric patients with IBD when measured values are not able to be obtained.

Genetic Ancestry in Lung-Function Predictions

Self-identified race or ethnic group is used to determine normal reference standards in the prediction of pulmonary function. We conducted a study to determine whether the genetically determined percentage of African ancestry is associated with lung function and whether its use could improve predictions of lung function among persons who identified themselves as African American. We assessed the ancestry of 777 participants self-identified as African American in the Coronary Artery Risk Development in Young Adults (CARDIA) study and evaluated the relation between pulmonary function and ancestry by means of linear regression. We performed similar analyses of data for two independent cohorts of subjects identifying themselves as African American: 813 participants in the Health, Aging, and Body Composition (HABC) study and 579 participants in the Cardiovascular Health Study (CHS). We compared the fit of two types of models to lung-function measurements: models based on the covariates used in standard prediction equations and models incorporating ancestry. We also evaluated the effect of the ancestry-based models on the classification of disease severity in two asthma-study populations. African ancestry was inversely related to forced expiratory volume in 1 second (FEV(1)) and forced vital capacity in the CARDIA cohort. These relations were also seen in the HABC and CHS cohorts. In predicting lung function, the ancestry-based model fit the data better than standard models. Ancestry-based models resulted in the reclassification of asthma severity (based on the percentage of the predicted FEV(1)) in 4 to 5% of participants. Current predictive equations, which rely on self-identified race alone, may misestimate lung function among subjects who identify themselves as African American. Incorporating ancestry into normative equations may improve lung-function estimates and more accurately categorize disease severity. (Funded by the National Institutes of Health and others.)

Poor prediction of resting energy expenditure in obese women by established equations

The objective of the study was to evaluate the accuracy of established prediction equations that calculate resting energy expenditure (REE) in obese women. This was a cross-sectional study. In 273 mildly to severely obese women (age, 41.7 ± 13.2 years; body mass index, 42.8 ± 7.0 kg/m 2), REE was measured by indirect calorimetry (mREE), along with fat mass (FM) and fat-free mass (FFM) by bioelectrical impedance analysis. Eleven established equations were used to predict REE (pREE), with 9 equations basing on the anthropometric parameters body weight and height and 2 equations including body composition parameters (FM, FFM). All equations provided pREE values that significantly correlated with mREE ( r > 0.66, P < .001), although 8 equations systematically underestimated mREE ( P < .05). Of note, even the best equation was not able to accurately predict mREE with a deviation of less than ±10% in more than 70% of the tested women. Furthermore, equations using body composition data were not superior in predicting REE as compared with equations exclusively including anthropometric variables. Multiple linear regression analyses revealed 2 new equations—one including body weight and age and another including FM, FFM, and age—that explained 56.9% and 57.2%, respectively, of variance in mREE. However, when these 2 new equations were applied to an independent sample of 33 obese women, they also provided an accurate prediction (±10%) of mREE in only 56.7% and 60.6%, respectively, of the women. Data show that an accurate prediction of REE is not feasible using established equations in obese women. Equations that include body composition parameters as assessed by bioelectrical impedance analysis do not increase the accuracy of prediction. Based on our results, we conclude that calculating REE by standard prediction equations does not represent a reliable alternative to indirect calorimetry for the assessment of REE in obese women.

Rapid Measurement of Total Body Water to Facilitate Clinical Decision Making in Hospitalized Elderly Patients

Bioelectrical impedance analysis (BIA) is a noninvasive rapid and simple bedside technique that can be used to predict total body water (TBW), extracellular water (ECW), and intracellular water (ICW) and identify altered fluid distribution following critical illness. An equivalence study of BIA in 32 hospitalized elderly patients was compared with reference standard dilutional measurements of deuterated water (TBW) and sodium bromide (ECW). The results were compared with anthropometric equations commonly used to predict TBW. There was variability in TBW content among the participating hospitalized elderly patients. This variability was within (+/-5 L) and the percent difference between the standard and BIA was as follows: mean (range) -4.1% (-18.5 to 11.2). BIA reliably predicted TBW and ECW in individual participants, whereas standard prediction equations uniformly over- or underestimated TBW in individuals and whole group population. TBW in hospitalized elderly patients can be estimated noninvasively by bedside BIA. Standardized anthropometric equations have to be used with caution in this population.