Validity of Physical Activity Intensity Predictions by ActiGraph,Actical, and RT3 Accelerometers

Objective: Accelerometers are promising tools for characterizing physical activity (PA) patterns in free‐living persons. To date, validation of energy expenditure (EE) predictions from accelerometers has been restricted to short laboratory or simulated free‐living protocols. This study seeks to determine the capabilities of eight previously published regression equations for three commercially available accelerometers to predict summary measures of daily EE. Methods and Procedures: Study participants were outfitted with ActiGraph, Actical, and RT3 accelerometers, while measurements were simultaneously made during overnight stays in a room calorimeter, which provided minute‐by‐minute EE measurements, in a diverse subject population (n = 85). Regression equations for each device were used to predict the minute‐by‐minute metabolic equivalents (METs) along with the daily PA level (PAL). Results: Two RT3 regressions and one ActiGraph regression were not significantly different from calorimeter measured PAL. When data from the entire visit were divided into four intensity categories—sedentary, light, moderate, and vigorous—significant (P < 0.001) over‐ and underpredictions were detected in numerous regression equations and intensity categories. Discussion: Most EE prediction equations showed differences of <2% in the moderate and vigorous intensity categories. These differences, though small in magnitude, may limit the ability of these regressions to accurately characterize whether specific PA goals have been met in the field setting. New regression equations should be developed if more accurate prediction of the daily PAL or higher precision in determining the time spent in specific PA intensity categories is desired.     

Estimation of Energy Expenditure from Physical Activity Measures: Determinants of Accuracy

Objective: To describe the determinants, specifically age, body mass index, percentage of body fat, and physical activity (PA) level, associated with over‐ and underestimation of energy expenditure (EE) using PA records and the Stanford Seven‐Day Physical Activity Recall (7DR) compared with doubly labeled water (DLW). Research Methods and Procedures: We collected PA measures on 24 males eating a controlled diet designed to maintain body weight, and we determined EE from DLW and estimated EE from PA records and 7DR. Results: Absolute differences in the estimation of EE between DLW and PA assessment methods were greater for the 7DR (30.6 ± 9.9%) than PA records (7.9 ± 3.2%). In PA records, overestimation of EE was greater with older age and higher body fatness; EE was overestimated by 16.7% among men 50 years and older compared with only 5.3% among men <40 years of age. For percentage of body fat, EE was overestimated by 19.7% among men with a percentage of body fat ≥30% compared with only 5.6% among men with a percentage of body fat <25%. A trend for less overestimation of EE with higher levels of PA (measured by DLW/basal metabolic rate [BMR]) also was observed in the PA records. In the 7DR, the estimates of EE varied widely and no trends were observed by age, percentage of body fat, and PA levels. Discussion: Estimation of EE from the 7DR is considerably more variable than from PA records. Factors related to age and percentage of body fat influenced the accuracy of estimated EE in the PA record. Additional studies are needed to understand factors related to accurate reporting of PA behaviors, which are used to estimate EE in free‐living adults.     

Measurement of Human Daily Physical Activity

Objectives: To validate a new device, Intelligent Device for Energy Expenditure and Activity (IDEEA), for the measurement of duration, frequency, and intensity of various types of human physical activity (PA). Research Methods and Procedures: The ability of IDEEA to identify and quantify 32 types of PA, including the most common daily exercise and nonexercise PA, was tested in 76 subjects: Subjects included males (N = 33) and females (N = 43) ranging in age from 13 to 72 years with a mean body mass index (BMI) of 24.7 kg/m² (range: 18.4 to 41.0) [43 females: 13 to 72 years old and BMI 18.4 to ～41.0 kg/m² (mean = 24.7 kg/m² ); 33 males: 15 to ～72 years old and BMI 21.0 to ～38.4 kg/m² (mean = 25.9 kg/m²)]. Postures, limb movements, and jumping were tested using a timed protocol of specific activities. Walking and running were tested using a 60‐meter track, on which subjects walked and ran at 6 self‐selected speeds. Stair climbing and descending were tested by timing subjects who climbed and descended a flight of stairs at two different speeds. Results: Correct identification rates averaged 98.9% for posture and limb movement type and 98.5% for gait type. Pooled correlation between predicted and actual speeds of walking and running was high (r = 0.986, p ≤ 0.0001). Discussion: IDEEA accurately measured duration, frequency, type, and intensity of a variety of daily PAs.     

Evaluation of low-intensity physical activity by triaxial accelerometry

Objective: To develop regression‐based equations that estimate physical activity ratios [energy expenditure (EE) per minute/sleeping metabolic rate] for low‐to‐moderate intensity activities using total acceleration obtained by triaxial accelerometry. Research Methods and Procedures: Twenty‐one Japanese adults were fitted with a triaxial accelerometer while also in a whole‐body human calorimeter for 22.5 hours. The protocol time was composed of sleep (8 hours), four structured activity periods totaling 4 hours (sitting, standing, housework, and walking on a treadmill at speeds of 71 and 95 m/min, 2 × 30 minutes for each activity), and residual time (10.5 hours). Acceleration data (milligausse) from the different periods and their relationship to physical activity ratio obtained from the human calorimeter allowed for the development of EE equations for each activity. The EE equations were validated on the residual times, and the percentage difference for the prediction errors was calculated as (predicted value ? measured value)/measured value × 100. Results: Using data from triaxial accelerations and the ratio of horizontal to vertical accelerations, there was relatively high accuracy in identifying the four different periods of activity. The predicted EE (882 ± 150 kcal/10.5 hours) was strongly correlated with the actual EE measured by human calorimetry (846 ± 146 kcal/10.5 hours, r = 0.94 p < 0.01), although the predicted EE was slightly higher than the measured EE. Discussion: Triaxial accelerometry, when total, vertical, and horizontal accelerations are utilized, can effectively evaluate different types of activities and estimate EE for low‐intensity physical activities associated with modern lifestyles.     

Energy Expenditure Determined by Self-Reported Physical Activity Is Related to Body Fatness

BUCHOWSKI, MACIEJ S., KAREN M. TOWNSEND, KONG Y. CHEN, SARI A. ACRA, AND MING SUN. Energy expenditure determined by self-reported physical activity is related to body fatness. Obes. Res. 1999;7:23–33. Objective : Activity self-reports are a commonly used tool in assessing daily physical activity (PA) and associated energy expenditure (EE). This study examined the effect of relative body fatness (%BF) on differences between self-reported and measured duration and associated EE in healthy adults. Research Methods and Procedures: Men and women (n= 115, age 38±9 years), ranging in %BF from 7.9% to 58.9%, spent two separate days (normal and exercise) in a whole-room indirect calorimeter where EE was measured. While in the room calorimeter, subjects reported the type, intensity, and duration of each performed PA. The Compendium of Physical Activity was used to calculate the energy cost of each reported activity. The EE of all self-reported activities (EE_r) was categorized into four intensity levels, synchronized, and compared with EE from the room calorimeter (EE_m). Results : With increasing %BF, subjects significantly overestimated duration of more strenuous activities (≥4.5), while underestimating moderate activities (2.5 to 4.4 metabolic equivalents (METs)). Misreporting of duration and/or intensity caused an overestimation or underestimation of PA-associated EE at these levels. Reported EE sleep was lower than measured EE sleep, although both had similar durations. As a result, total EE_r was similar to EE_m. Discussion : Individual variability of daily total PA and associated EE generated from self-reports in adults is high. Persons with a higher %BF report duration and/or intensity of moderate to high levels of PA with lower accuracy than leaner individuals. We conclude using the Compendium of Physical Activity is not suitable for the accurate estimation of self-reported EE of AA in adults with a higher %BF.     

Population genetic studies of Alouatta belzebul from the Amazonian and Atlantic Forests

Cytochrome b DNA sequence data (ca. 1,140 bp) of 66 Alouatta belzebul from the Amazonian and the Atlantic Forests of Brazil were used for phylogenetic reconstructions and population studies. Our sample consisted of 60 specimens from the Amazonian Forest (captured in 1984 and 1998 in Pará‐PA state) and six specimens from the Atlantic Forest (Paraíba‐PB state). We found 32 haplotypes, 23 in PA‐1984 (with 12 present in more than one individual), 11 in PA‐1998 (with two present in more than one individual), and a single haplotype in the PB sample. Animals from PA‐1984 and PA‐1998 shared three haplotypes while animals from Pará and Paraíba did not share any haplotype. We found 57 variable sites, consisting of 53 transitions and four transversions, with most replacements occurring at third codon position (77.19%) and less frequently at first and second positions (10.53 and 12.28%, respectively). Genetic distance between all haplotypes varied between 0 and 1.2%. Nucleotide diversity estimates between PA‐1984 haplotypes and PA‐1998 haplotypes were the same (π=0.01), and haplotype diversity estimates were very similar (h=0.96 and 0.93 for PA‐1984 and PA‐1998, respectively). Maximum parsimony, median‐joining, split decomposition, and TCS showed that PA and PB haplotypes had not drastically diverged and that subsequent radiation within these regions was not apparent. No temporal structure was found between PA‐1984 and PA‐1998. The sum of square deviation estimate for PA‐1984 equaled 0.01 (P=0.23), in agreement with a hypothetical model of sudden expansion contrary to PA‐1998 whose sum of square deviation estimate (0.40; P=0.04) was not compatible with this model, although the small sample size of PA‐1998 as well as the smaller area of capture could have also accounted for this result. Fu's F_s and R₂ statistical neutrality tests corroborated these propositions. Lack of drastic differentiation was attributable to the once existing connection between the Atlantic and the Amazonian forests at a non‐distant past. Am. J. Primatol. 70:423–431, 2008. © 2007 Wiley‐Liss, Inc.     

Comparison of Methods for Achieving 24‐Hour Energy Balance in a Whole‐Room Indirect Calorimeter

Objective: To evaluate and compare methods for achieving 24‐hour energy balance in a whole‐room indirect calorimeter. Research Methods and Procedures: Twenty‐four‐hour energy expenditure (EE) for 34 healthy adults (16 women, 18 men) was measured in a calorimeter during a prestudy day and on a subsequent nonconsecutive assessment day (AD). Several methods for estimating EE on the AD using activity factors or regression equations with data available before the AD [anthropometrics, body composition, resting metabolic rate (RMR), sleeping metabolic rate (SMR) on prestudy day, 24‐hour EE on prestudy day] were compared for predictive accuracy. Results: Use of a 24‐hour calorimeter stay gave the smallest mean absolute error (119 ± 16 kcal/d) and smallest single maximum error (361 kcal/d). However, several other methods were only slightly, and not significantly, less accurate (e.g., mean absolute error = 131 ± 17, 140 ± 20, and 141 ± 22 kcal/d and greatest error = 384, 370, and 593 kcal/d for anthropometric, RMR, and SMR regression equations, respectively). Fat‐free mass alone and SMR with a simple activity factor were seen to be less accurate. Discussion: Our results indicate that there may be some improvement in achieving 24‐hour energy balance in a metabolic chamber by using a preceding 24‐hour calorimeter stay; that only slightly less accurate predictions can be obtained using a combination of anthropometric, body composition, and/or RMR measurements; and that there is little or no advantage in using SMR from a previous overnight calorimeter stay.     

Physical activity patterns during weight maintenance following a low-energy density dietary intervention

Objective: The objective was to determine the role of physical activity (PA) and energy intake on weight maintenance among former University of Alabama at Birmingham EatRight Weight Management Program participants. Research Methods and Procedures: Eighty‐nine former participants completed follow‐up visits ≥1 year after completing EatRight. BMI was calculated using measured height and weight. Diet intake was estimated from 4‐day food records. PA was assessed using a module from the Behavioral Risk Factor Surveillance System Survey. Cut‐off points were chosen based on the distribution of minutes of activity. For moderate and total activity, cut‐off points were 0, 1 to 30, 31 to 60, and >60 minutes. For vigorous activity, the categories were 0, 1 to 20, 21 to 30, and >30 minutes. General linear models determined the association of PA with change in weight at follow‐up controlling for gender and total energy intake (kcal/d). Results: At follow‐up, 80% (n = 71) of participants maintained (regained <5% of program end weight) their body weight and 20% had gained weight. Mean weight change was 1.0 ± 6.5 kg. Maintainers consumed 384 fewer kcal/d on average. Maintainers had a lower energy density dietary pattern (1.58 vs. 2.01 kcal/g, p < 0.01). There was no significant difference in PA min/d reported by maintainers and gainers. Discussion: Our results suggest that, despite being minimally active, weight‐reduced individuals can successfully maintain their newly achieved body weight with appropriate caloric intake. Adopting a lower calorie, low energy density dietary pattern may reduce the amount of PA that is truly necessary for weight maintenance.     

Triaxial accelerometry for assessment of physical activity in young children

Objective: The purpose of the present study was to derive linear and non‐linear regression equations that estimate energy expenditure (EE) from triaxial accelerometer counts that can be used to quantitate activity in young children. We are unaware of any data regarding the validity of triaxial accelerometry for assessment of physical activity intensity in this age group. Research Methods and Procedures: EE for 27 girls and boys (6.0 ± 0.3 years) was assessed for nine activities (lying down, watching a video while sitting and standing, line drawing for coloring‐in, playing blocks, walking, stair climbing, ball toss, and running) using indirect calorimetry and was then estimated using a triaxial accelerometer (ActivTracer, GMS). Results: Significant correlations were observed between synthetic (synthesized tri‐axes as the vector), vertical, and horizontal accelerometer counts and EE for all activities (0.878 to 0.932 for EE). However, linear and non‐linear regression equations underestimated EE by >30% for stair climbing (up and down) and performing a ball toss. Therefore, linear and non‐linear regression equations were calculated for all activities except these two activities, and then evaluated for all activities. Linear and non‐linear regression equations using combined vertical and horizontal acceleration counts, synthetic counts, and horizontal counts demonstrated a better relationship between accelerometer counts and EE than did regression equations using vertical acceleration counts. Adjustment of the predicted value by the regression equations using the vertical/horizontal counts ratio improved the overestimation of EE for performing a ball toss. Discussion: The results suggest that triaxial accelerometry is a good tool for assessing daily EE in young children.     

Categorization of low cardiorespiratory fitness using obesity indices in non-smoking Singaporean women

Objective: To revisit cut‐off values of BMI, waist circumference (WC), and waist‐to‐stature ratio (WSR) based on their association with cardiorespiratory fitness (CRF). The derived cut‐off points were compared with current values (BMI, 25.0 kg/m²; WC, 80 cm) as recommended by the World Health Organization. Research Methods and Procedures: Anthropometric indices were measured in a cross sectional study of 358 Singaporean female employees of a large tertiary hospital (63% Singaporean Chinese, 28% Malays, and 9% Indians). CRF was determined by the 1‐mile walk test. Receiver operating characteristic curves were constructed to determine cut‐off points. Results: The cut‐off points for BMI, WC, and WSR were 23.6 kg/m², 75.3 cm, and 0.48, respectively. The areas under the curve of BMI, WC, and WSR were 0.68, 0.74, and 0.74, respectively. For a given BMI, women with low CRF had higher WSR compared with women with high CRF. Discussion: These findings provide convergent evidence that the cut‐off points for Singaporean women were lower than the World Health Organization's criteria but were in good agreement with those reported for Asians.     

Comparison of body composition methods in obese African-American women

Objective : To compare the accuracy of percentage body fat (%BF) estimates between bioelectrical impedance analysis (BIA) and DXA in obese African‐American women. Research Methods and Procedures : Fifty‐five obese African‐American women (mean age, 45 years; mean BMI, 38; mean %BF, 48%) were studied. BF was assessed by both BIA (RJL Systems BIA 101Q; RJL Systems, Clinton Township, MI) and DXA (Hologic QDR‐2000 Bone Densitometer; Hologic Inc., Bedford, MA). Generalized and ethnicity‐ and obese‐specific equations were used to calculate %BF from the BIA. Bland‐Altman analyses were used to compare the agreement between the BIA and the DXA, with the DXA serving as the criterion measure. Results : Two of the generalized equations provided consistent estimates across the weight range in comparison with the DXA estimates, whereas most of the other equations increasingly underestimated %BF as BF increased. One of the generalized and one of the ethnicity‐specific equations had mean differences that were not significantly different from the DXA value. Discussion : The findings show that the Lukaski equation provided the most precise and accurate estimates of %BF in comparison with the QDR 2000 and provide preliminary support for the use of this equation for obese African‐American women.     

Conducting animal censuses amongst abrupt topography; a GIS‐based alternative to Distance

Management often bases decisions on estimates of animal density and population size. Aerial sampling is expensive whilst current ground methods, noticeably Distance sampling, assume a single detection function for each habitat and that visibility in a given habitat type declines in a smooth, increasing manner with distance from the observer. If the visibility within a habitat varies widely or is suddenly cut off, as amongst abrupt topography, these assumptions are invalidated. We present an affordable, accessible and accurate method for conducting repeated annual censuses on large herbivores in such terrain. We used a GIS habitat‐based approach. Monthly, over a two year period, we conducted repeated road transects in Ithala Game Reserve, South Africa, using GPS to record the geographic position of each sighting. These records (n = 8742) were then imported into a GIS and overlaid onto an existing habitat‐type GIS layer. With the sampled area thus defined as an irregular polygon in the GIS encompassing all records, we calculated densities of each herbivore species by habitat type and extrapolated total population size estimates. Estimates of maximum population size for wildebeest and zebra correlated (±15%) with management's estimates based on aerial surveys, walked transects and experience. White rhino are individually counted in the reserve and our estimates (year 1: 52; year 2: 57) matched these known numbers (year 1: 50; year 2: 53). Our method also yielded realistic numbers for impala, but unrealistic numbers for kudu and warthog. Our GIS‐based census technique produced realistic maximum population estimates for abundant grazing and mixed‐feeder mesoherbivores and for scarce, but highly visible, megaherbivores, but not for cryptic species. With the increasing availability of GIS data, the technique is recommended to those working in abrupt terrain frustrated by the inability of current ground census techniques, principally Distance sampling, to produce realistic population estimates.     

Gold Immunochromatography Assay for the Rapid Detection of Spiramycin in Milk and Beef Samples Based on a Monoclonal Antibody

Spiramycin (SP) residues in food do harm to human health. It is necessary to establish rapid detection method for SP. In this work, a monoclonal antibody (mAb)‐based gold immunochromatography assay (GICA) is developed for the rapid detection of SP. Under optimum conditions, the half‐maximal inhibitory concentration of SP‐mAb is 0.43 ng mL^–1. The subtype of SP‐mAb is IgG2b. This antibody has no cross‐reactivity with other analogues and has high affinity (4.52 × 10¹⁰ L mol^–1). Qualitative results can be visualized with the naked eye, with a visual detection limit of 1.0 ng mL^–1 and cut‐off value of 10 ng mL^–1. A hand‐held strip scanner is used for the quantitative analysis, with LOD 0.43 ng mL^–1 in assay buffer. The recoveries of SP ranged from 72.3% to 112% in milk and 98.5% to 115% in beef, with variable coefficient ranging from 9.4% to 11.7% in milk and 8.14% to 15.4% in beef. Besides, the proposed GICA method for SP is confirmed by LC–MS/MS in SP‐spiked milk and beef samples. Overall, the developed GICA can be a useful tool for SP residues on‐site screening in milk and beef samples.     

BMI and waist circumference as indicators of health among Samoan women

Objective: High rates of obesity and chronic disease make establishment of effective indicators of risk for chronic disease important. The objective was to examine adequacy of anthropometric cut‐off points as indicators of risk for chronic disease among Samoan women in Hawaii. Research Methods and Procedures: A cross‐sectional survey of 55 Samoan women 18 to 28 years of age that included blood lipids, cholesterol, and glucose (including after a 2‐hour oral glucose test); anthropometry (weight, height, waist circumference); and DXA of body composition. Results: Using the Centers for Disease Control and Prevention (CDC)/World Health Organization (WHO) cut‐off points for BMI, 22% of women were overweight and 58% were obese. Cholesterol, lipid, and glucose values were all linearly related to DXA body fat, BMI, and waist circumference. BMI and waist circumference at WHO/NIH cut‐off points predicted levels of blood lipids and glucose that indicate elevated risk for disease. Discussion: WHO/NIH cut‐off points for BMI and waist circumference reflect risk indicators of chronic disease among young Samoan women in Hawaii.     

BMI and waist circumference in predicting cardiovascular risk factor clustering in Chinese adolescents

Objective: To derive the optimal BMI and waist circumference (WC) cut‐off values to predict clustering of cardiovascular risk factors in Hong Kong Chinese adolescents. Research Methods and Procedures: A total of 2102 Hong Kong Chinese 12 to 19 years of age were recruited. Participants were considered to have clustering of risk factors if at least three of the following risk factors were present: 1) high‐density lipoprotein cholesterol (HDL‐C) ≤1.03 mM, 2) low‐density lipoprotein cholesterol (LDL‐C) ≥2.6 mM, 3) triglyceride (TG) ≥1.24 mM, 4) fasting plasma glucose (FPG) ≥6.1 mM, and 5) age‐, sex‐, and height‐adjusted systolic or diastolic blood pressure (BP) ≥ 90th percentile. Receiver operating characteristics (ROC) curves were generated to identify the optimal age‐adjusted BMI and WC cut‐off values to predict clustering of risk factors in boys and girls separately. These age‐adjusted BMI and WC cut‐offs were transformed to percentile values. Cole's lambda‐mu‐sigma (LMS) method was used to obtain smoothed age‐specific BMI and WC at these percentile values. Results: The areas under ROC curves for BMI in girls and boys were 0.85 [95% confidence interval (CI), 0.77 to 0.92] and 0.76 (95% CI, 0.66 to 0.85), respectively. The respective areas under ROC curves for WC in girls and boys were 0.82 (95% CI, 0.74 to 0.91) and 0.78 (95% CI, 0.68 to 0.87). The optimal BMI thresholds were at the 78th percentile for girls and the 72nd percentile for boys. The respective values for WC were at the 77th percentile for girls and the 76th percentile for boys. The sensitivities and specificities of these cut‐off values ranged from 72% to 80%. Discussion: Age‐ and sex‐specific BMI and WC cut‐off values can be used to identify adolescents with clustering of cardiovascular risk factors.     

Manganese‐oxidizing bacteria mediate the degradation of 17α‐ethinylestradiol

Manganese (II) and manganese‐oxidizing bacteria were used as an efficient biological system for the degradation of the xenoestrogen 17α‐ethinylestradiol (EE2) at trace concentrations. Mn²⁺‐derived higher oxidation states of Mn (Mn³⁺, Mn⁴⁺) by Mn²⁺‐oxidizing bacteria mediate the oxidative cleavage of the polycyclic target compound EE2. The presence of manganese (II) was found to be essential for the degradation of EE2 by Leptothrix discophora, Pseudomonas putida MB1, P. putida MB6 and P. putida MB29. Mn²⁺‐dependent degradation of EE2 was found to be a slow process, which requires multi‐fold excess of Mn²⁺ and occurs in the late stationary phase of growth, implying a chemical process taking place. EE2‐derived degradation products were shown to no longer exhibit undesirable estrogenic activity.     

An Objective Method for Measurement of Sedentary Behavior in 3‐ to 4‐Year Olds

Objective: To test the ability of accelerometry to quantify sedentary behavior in 3‐ to 4‐year‐old children. Research Methods and Procedures: We developed a cut‐off for accelerometry output (validation study) in 30 healthy 3 to 4 year olds, which provided highest sensitivity and specificity for the detection of sedentary behavior relative to a criterion method of measurement, direct observation using the children's physical activity form. We then cross‐validated the cut‐off in an independent sample of healthy 3 to 4 year olds (n = 52). Results: In the validation study, optimal sensitivity and specificity for the detection of sedentary behavior were obtained at an accelerometry output cut‐off of <1100 counts/min. In the cross‐validation, sensitivity was 83%: 438/528 inactive minutes were correctly classified. Specificity was 82%: 1251/1526 noninactive minutes were correctly classified using this cut‐off. Discussion: Sedentary behavior can be quantified objectively in young children using accelerometry. This new technique could be considered for a wide variety of applications in the etiology, prevention, and treatment of childhood obesity.     

Utility of Childhood BMI in the Prediction of Adulthood Disease: Comparison of National and International References

Objective: To determine whether the U.S. Centers for Disease Control and Prevention (CDC; CDC Reference) or International Obesity Task Force (IOTF; IOTF Reference) BMI cut‐off points for classifying adiposity status in children are more effective at predicting future health risk. Research Methods and Procedures: The sample (N = 1709) included 4‐ to 15‐year‐old (at baseline) boys and girls from the Bogalusa Heart Study. Overweight and obesity status were determined using both the CDC Reference and IOTF Reference BMI cut‐off points at baseline. The ability of childhood overweight and obesity, determined from the two BMI classification systems, to predict obesity and metabolic disorders in young adulthood (after a 13‐ to 24‐year follow‐up) was then compared. Results: Independently of the classification system employed to determine adiposity based on childhood BMI, the odds of being obese and having all of the metabolic disorders in young adulthood were significantly (p < 0.05) higher in the overweight and obese groups by comparison with the nonoverweight groups. Childhood overweight and obesity, determined by both the CDC Reference and IOTF Reference, had a low sensitivity and a high specificity for predicting obesity and metabolic disorders in young adulthood. Overweight and obesity as determined by the CDC Reference were slightly more sensitive and slightly less specific than the corresponding values based on the IOTF Reference. Discussion: Overweight and obesity during childhood, as determined by both the CDC and IOTF BMI cut‐off points, are strong predictors of obesity and coronary heart disease risk factors in young adulthood. The differences in the predictive capacity of the CDC Reference and IOTF Reference are, however, minimal.     

Temporal change in the morphometry–body mass relationship of polar bears

Accurate information on animal body mass is often an essential component of wildlife research and management. However, for many large-bodied species, obtaining direct scale weights from individuals may be difficult. In these cases, morphometric equations (e.g., based on girth or length) may provide accurate and precise estimates of body mass. We developed predictive equations to estimate the body mass of free-ranging polar bears (Ursus maritimus) in western Hudson Bay, Canada. Using multiple linear and non-linear regression, we identified a strong relationship between polar bear body weight and linear measures of straight line length and axillary girth. The mass–morphometry relationship appeared to change over time and we developed separate equations for polar bears measured during 2 time periods, 1980–1996 and 2007–2009. Non-linear models were more accurate and provided body mass estimates within 5.8% (R² = 0.98) and 6.1% (R² = 0.98) of scale weight in the earlier and later time periods, respectively. Earlier equations developed for polar bears in this subpopulation performed poorly when applied to recently sampled individuals. In contrast, some contemporary equations from other regions performed reasonably well, suggesting that temporal changes within a subpopulation may be more pronounced than regional differences and can render earlier predictive equations obsolete. Our results have important implications for current and future studies of polar bear body condition and the effects of ongoing climate warming. © 2011 The Wildlife Society.