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At least 19 recordsLinked to original sources
PubMed1979

Brain weight-body weight scaling in breeds of dogs and cats.

Autopsy data from 2,100 pet dogs are used to demonstrate that mean brain weight (y) in 26 breeds of dogs is related to mean body weight (x) by the function y = 0.39 x 0.27. Power functions with the exponent 0.27 appear to define intra-species brain-body weight scaling in several other species. These functions may serve as base lines for measuring increases or decreases in encephalization during species evolution. Curiously, averaged data from 1,250 domestic cats of 2 breeds can be plotted on a line with slope of 0.67, which is known to define inter- rather than intra-species brain-body weight scaling among mammals.

Anatomy, Comparative↗
PubMedDate not supplied

[Body weight, body height and menarche. Epidemiological study, in the Province of Pordenone, of the school population from 12 to 15 years old (12,000)].

The relation between body weight, height and the commencement of menstruation was studied in 5324 girls aged 12--15 yr attending secondary schools in the province of Pordenone. The mean age of menarche was 12 2/12 yr and varied little throughout the province. Weight and height appeared closely related to menarche. A threshold of 49.2 kg and 157.3 cm was noted. Attainment of these critical values was apparently the factor that influenced the age at which menstruation commenced.

Adolescent↗
PubMed1979

Body weight and body composition of male rats following hypothalamic lesions.

Carcass analyses were performed on 160 male rats maintaining reduced, normal, or elevated levels of body weight following lateral hypothalamic (LH), sham (control), or ventromedial hypothalamic (VMH) lesions, respectively. Extracted body lipid (ranging from 26 to 738% of the control mean) correlated highly (r = +0.95) with the level of maintained body weight (which ranged from 67 to 191% of control). Neither the nonfat solids (which ranged from 60 to 123% of control) contributed significantly to the variance in body weight (r = +0.01 and +0.06, respectively). Fat thus accounted for approximately 90% of the overall variance in body weight among LH, control, and VMH animals. Consideration of only the LH data, however, revealed a breakdown of this close covariance of body fat and weight. Fat mass correlated significantly with body weight in LH rats maintaining weight 0-12% below normal; but, at maintained body weights below 88%, the correlation between weight and fat in LH rats was only +0.07. Variation in lean body mass then better accounted for differences in body weight. The implications of these observations for existing lipostatic theories of weight regulation are discussed.

Animals↗
PubMed1978

Changes in brain weights during the span of human life: relation of brain weights to body heights and body weights.

More than 20,000 autopsy reports from several general hospitals were surveyed for the purpose of selecting brains without a pathological lesion that had been weighed in the fresh condition. From this number, 2,773 males and 1,963 females were chosen for whom body weight, body height, and cause of death had been recorded. The data were segregated into 23 age groups ranging from birth to 86+ years and subjected to statistical evaluation. Overall, the brain weights in males were greater than in females by 9.8%. The largest increases in brain weights in both sexes occurred during the first 3 years of life, when the value quadruples over that at birth, while during the subsequent 15 years the brain weight barely quintuples over that at birth. Progressive decline in brain weight begins at about 45 to 50 years of age and reaches its lowest values after age 86 years, by which time the mean brain weight has decreased by about 11% relative to the maximum brain weight attained in young adults (about 19 years of age). Computed regression lines for brain weights versus body heights and body weights and for ratios for brain weights to body heights and weights versus age groups show clearly differential rates of change in brain weights which are less affected by sex.

Adolescent↗
PubMed1977

Estimation of body density and lean body weight from body measurements at high altitude.

Body density and other anthropometric data were obtained on 101 Indian soldiers who were continously staying at high altitude (3920 m) for more than 10 months. Use was made of a human body volumeter, and body density was calculated from observed body weight and volume. Measurements were taken on the body using standard techniques. A stepwise linear regression analysis was performed to establish possible relationships of 36 body measurements with density and lean body weight. Thigh anterior, juxta-nipple skin folds and forearm and ankle circumference were selected in the regression equation predicting body density. Multiple correlation coefficient (R) equal to 0.765 was obtained for this equation. For the predicted lean body weight, R equalled 0.930. The regression equations included body weight, thigh, anterior and juxta-nipple skin fold thicknesses, and forearm circumference. Contribution of other body measurements in the regression of these parameters was not significant. The analysis also revealed that a new set of coefficients is required for the measurements included in the published regression equations.

Adipose Tissue↗
PubMed2026

Comparison of Iodinated Contrast Doses Based on Total Body Weight and Lean Body Weight in Pediatric Patients: Impact on Image Quality and Contrast Exposure.

INTRODUCTION: Iodinated contrast dosing in pediatric computed tomography (CT) traditionally relies on total body weight (TBW), which may result in excessive contrast administration, particularly in patients with higher adiposity. Lean body weight (LBW)-based protocols have shown promise in adults but remain underexplored in children. Therefore, the aim of this study was to compare contrast volume requirements and hepatic enhancement quality among three dosing protocols: LBW-based, TBW-based, and the Control Group (CG), based on the institutional standard for pediatric abdominal CT. METHODS: This prospective study enrolled 66 patients (age 0-16 years) undergoing contrast-enhanced abdominal CT between September 2023 and August 2024. Patients were randomly assigned to receive iodinated contrast (iobitridol 350mg I/mL) dosed by: (1) LBW (0.63 g iodine/kg x LBW, calculated using Peters formula; n = 23), (2) TBW (0.46 g iodine/kg x TBW; n = 20), or (3) institutional control protocol (2 mL/kg x TBW, equivalent to 0.7 g iodine/kg; n = 23). Kruskal-Wallis, ANOVA, Two-way ANOVA, ANCOVA, Scheirer-Ray-Hare, and Cohen's Kappa tests with Likert scale were used. RESULTS: The LBW group received lower median contrast volumes (27 mL; IQR, 10-80 mL) compared to the TBW group (34.5 mL; IQR, 18-78 mL) and the CG group (40 mL; IQR, 13-80 mL), although the differences did not reach statistical significance (P > 0.05). Notably, this reduction did not compromise hepatic enhancement, which remained comparable to the CG (552 ± 139 HU; P = 0.107). CONCLUSION: Lean body weight may be a useful parameter for estimating contrast dose in pediatric abdominal CT, potentially reducing administered volumes without compromising diagnostic image quality. IMPLICATIONS FOR PRACTICE: These results provide early evidence that LBW-based dosing may support more individualized contrast administration in pediatric CT, potentially reducing exposure-related risks.

Humans↗
PubMedDate not supplied

Changes in body weight and body protein with intravenous nutrition.

Body weight, protein, fat and water were measured before and after intravenous nutrition in 20 surgical patients. The group included both young and old patients who were suffering from a wide variety of catabolic illnesses and the period of intravenous feeding ranged from 11 to 40 days. Eight of the patients were able to take small amounts of food orally. During the period of intravenous nutrition ten patients gained significant weight although only two of these gained significant protein. Most of the weight gain was due to an increase of water. There was also a gain of water in the patients who lost weight; this water gain occurred in small daily increments over the course of treatment. It is concluded that weight gain can occur without protein gain in patients who are being fed intravenously and that body weight is not a reliable guide to changes in body protein or fat in critically ill patients receiving intravenous nutrition.

Adult↗
PubMed1978

Influence of a liquid diet and meal pattern on body weight and body fat in rats.

Rats weighing 110 to 150 g or 250 g initially were utilized in five experiments to determine the effect of the form of the diet (dry versus liquid) and the pattern of feeding (meal-feeding, force-feeding, nibbling, or ad libitum) on body weight gain and on body fat. A high-carbohydrate, 20% casein or 20% lactalbumin diet was fed for 4 to 8 weeks. Consumption of a diet mixed with an equal weight of water increased weight gain in one of three experiments. Body fat content of the rats was not influenced by addition of water to the diet. Neither force-feeding nor meal-feeding influenced body fat gain provided the respective control rats were pair-fed during the initial adaptation period. Likewise, when rats were pair force-fed to ad libitum fed rats without an initial adaptation meal frequency did not influence body fat gain. When meal-fed rats were switched to ad libitum intake their food intake increased to equal that of rats which had been continuously fed ad libitum; however, the rats which had been switched gained more body fat than did rats continuously fed ad libitum. These results suggest that meal frequency may have a minimal influence on body fat accumulation, but that a shift to a higher level of food intake may cause an increased food efficiency and greater rate of fat deposition than in rats continuously fed the higher level of intake.

Adipose Tissue↗
PubMed1978

Hypothalamic function as related to body weight and body fat in anorexia nervosa.

Percentage body fat is predictive of the onset of menstruation at puberty. In anorexia nervosa a relationship between luteinizing hormone (LH) levels and percentage weight loss has been reported. In the current study the relationship of percentage body fat and of percentage weight loss to LH and LH reactivity was examined in anorexia nervosa. Fifteen women with anorexia nervosa were studied. The resting levels of LH were measured, and in seven of the subjects LH response to luteinizing hormone releasing hormone (LHRH) and clomiphene was tested. The increment in plasma LH was measured in response to a 100 microgram dose of LHRH, and also to a 5-day course of clomiphene 100 mg. The resting LH levels were found to correlate with percentage fat, body weight, and percentage weight loss. Correlations were also found between the response to either LHRH or clomiphene and percentage weight loss, percentage fat, and absolute body weight. Other pituitary hormones measured did not show a relationship to body fat or weight. It is concluded that in addition to being predictive of the onset of menstruation, percentage body fat is significantly related to resting LH and LH reactivity in anorexia nervosa. Although percentage body fat, percentage weight loss, and absolute body weight are all significant correlates of LH reactivity, we cannot at this time conclude that any one in particular is the superior.

Adipose Tissue↗
PubMed1979

Organ weights and organ:body weight ratios of the African white-tailed rat (Mystromys albicaudatus).

Fifty-three adult female and 51 adult male white-tailed rats (Mystromys albicaudatus) were killed with ether and weighed; the spleen, kidneys, liver, heart, lung, pancreas, brain and gonads were dissected free of adhering tissue and weighted. The mean absolute organ weight and organ:body weight ratios by sex and organ were calculated and compared. The male rats were significantly (p less than or equal to 0.05) heavier. The mean weight of the males was 110.0 +/- 23.8 g versus 82.9 +/- 16.1 g for the females. The absolute weights of the heart, liver and kidneys were significantly (p less than or equal to 0.05) greater for the males. The organ:body weight ratios, except for heart and brain (excluding ovary and testicle), were unaffected by sex. The heart to body weight ratio and the brain to body weight ratio were significantly (p less than or equal to 0.05) larger in female rats.

Animals↗
PubMed2026

Genome-wide association study of body weight and body size traits in Langya hens.

Langya chicken is a Chinese indigenous chicken breed with high genetic diversity. To systematically analyse the genetic basis of body size traits, eight traits (including BW, comb shape, and body size) of 2 952 Langya hens were measured at 130 days of age and at first egg of age. A total of 9 708 856 high-quality single-nucleotide polymorphisms (SNPs) were obtained through whole-genome resequencing and used for subsequent genetic parameter estimation and genome-wide association study (GWAS). The results of genetic parameter analysis revealed significant differences in the SNP heritability of different body size traits, with an overall range of 0.13-0.64. In particular, BW, comb length, comb height, and tibia length exhibited moderate-to-high heritability (0.34-0.64) during both developmental stages. GWAS revealed significantly associated SNP loci distributed across multiple chromosomal regions, indicating that body size traits have a complex multilocus genetic regulatory structure and that some chromosomal regions recur for different body size traits and during different developmental stages, showing potential pleiotropic effects or shared genomic regions. Notably, multiple stable body size trait-associated regions were identified on Gallus gallus autosome (GGA) 1, 4, and 27, including genomic regions on GGA1 (167.56-178.18 Mb), GGA4 (68.24-81.17 Mb), and GGA27 (5.22-6.73 Mb), in which significantly associated signals were repeatedly detected for multiple body size traits, such as BW and tibia length. The significant SNPs in the above regions were characterised by strong linkage disequilibrium and were associated with multiple body size traits, indicating that these SNPs may serve as important genetic hotspots for the regulation of chicken body shape and structure. Candidate genes annotated in these core regions include NCAPG, KPNA3, LDB2, PPARGC1A, FNDC3A, SOST, RB1, STON2, and TARP; the functions of these genes are involved mainly in the regulation of cell proliferation, energy metabolism, bone development, and tissue growth. NCAPG was consistently associated with multiple traits at both developmental stages. Functional enrichment analysis further revealed that these candidate genes were significantly enriched in the phosphatidylinositol, GnRH, energy metabolism, skeletal development and protein biosynthesis signalling pathways. The genetic characteristics of Langya chicken body size traits during the growth stage at the genome-wide level and the underlying molecular mechanisms were systematically revealed in this study. The findings provide important candidate gene resources and a theoretical basis for the screening of molecular markers for body size traits and the genomic breeding of regional chicken breeds.

Candidate genes↗
PubMed1977

Prediction accuracy of body density, lean body weight, and total body volume equations.

The purpose of this study was to determine the accuracy of percent fat estimates derived from regression equations with functions of predicting body density (BD), lean body weight (LBW), and total body volume (TBV) from anthropometric variables. BD, LBW, and TBV equations were derived from the data of 95 young, adult men (percent fat X = 13.4%). The multiple correlations for these equations were: BD, 0.86-0.83; LBW, 0.96-0.95; and TBV, 0.99. The zero order correlations between laboratory determined percent fat and percent fat derived by the BD, LBW, and TBV equations ranged from 0.80 to 0.86 with standard errors from 3.1% to 3.7%. This shows that BD, LBW, and TBV equations have similar accuracy when transformed to percent fat. The derived equations were cross validated with three additional, but diverse, samples (percent fat X = 5.1%; 16.7%; 27.1%). The cross validations results revealed that all equations exhibited similar accuracy. With samples differing in percent fat, systematic prediction errors occurred. The results further confirm population specificity of prediction equations.

Adipose Tissue↗