Allometric scaling of left ventricular mass by body dimensions in males and females

Batterham, Alan M.; George, Keith; Mullineaux, David R.

doi:10.1097/00005768-199702000-00003

Cited by 76 publications

(79 citation statements)

References 19 publications

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“…These scaled LV mass indices were independent of FFM and body mass, whereas LV mass scaled ratiometrically to body mass was not. 37 A pooled cohort of 611 normotensive subjects spanning an age range from infancy to late maturity, however, demonstrated dimensionally consistent relationships between LV mass and all anthropomorphic parameters considered, including body mass. 36 These apparent disparities may result from different age ranges in the studied subjects and from differences in methodology used to determine the relationship between anthropometry and cardiac dimensions.…”

Section: Evidence For Allometric Scaling Of Cardiovascular Structurementioning

confidence: 88%

“…Gender differences were completely abolished in some studies when cardiac dimensions were scaled allometrically 26,40 but persisted, albeit at reduced magnitude, in other studies. 37,41 Vascular scaling research has primarily been constrained to interspecies studies, in which vessel diameter and total cross-sectional area scale allometrically in theoretically and empirically derived relationships to mammal mass. 35,42 In these studies, aortic diameter scales with body mass with an allometric exponent of Ϸ0.4, [42][43][44] whereas capillary density appears to be relatively invariant with regard to body size.…”

Section: Evidence For Allometric Scaling Of Cardiovascular Structurementioning

confidence: 99%

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Does Size Matter?

et al. 2008

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Abstract-Extensive evidence is available that cardiovascular structure and function, along with other biological properties that span the range of organism size and speciation, scale with body size. Although appreciation of such factors is commonplace in pediatrics, cardiovascular measurements in the adult population, with similarly wide variation in body size, are rarely corrected for body size. The patient is a very tall 23-yearold competitive rower with a height of 203 cm and weight of 100 kg referred to the clinic for preparticipation athletic screening. He has never experienced syncope, palpitations, or chest pain during exertion and has no significant past medical history, but he occasionally feels "light-headed" at the end of an exhaustive competitive workout. He has no family history of sudden cardiac death or of premature cardiovascular disease. He is actively training 5 to 6 hours per day, 6 days per week in preparation for the upcoming Olympic Games. The examination is remarkable only for a soft systolic ejection murmur, cardiomegaly, and a third heart sound. An ECG is ordered, which is remarkable for sinus bradycardia, a 15-mV R wave in lead aVL, and R-wave voltage in lead V 5 plus S-wave voltage in lead V 1 totaling 46 mV. On a follow-up echocardiogram, septal and posterior wall thicknesses of 14.5 mm are observed with a left ventricular (LV) internal dimension in diastole of 53 mm. No significant obstructive LV outflow pattern is present, and wall thickness appears symmetrical. On the basis of current echocardiographic criteria, this patient is in the "gray zone" between physiological and pathological hypertrophy. His nonspecific symptoms and lack of other contributing history add to the ambiguity in diagnosis. Clinical Vignette No. 2:The patient is a 66-year-old woman who has a height of 155 cm and a body mass of 49 kg.She has a history of hyperlipidemia and abdominal aortic aneurysm. She comes to the clinic for her yearly ultrasound follow-up, which shows a maximum aneurysm diameter of 50 mm. She is in a "gray zone" in which neither surgical correction nor watchful waiting is definitively indicated.Considerable evidence is available that biological processes from metabolic enzyme activity 1 to plant and animal metabolic rates 2-4 to cancer metastasis 5 scale with body size over the entire range of organism size and speciation. Cardiovascular structural and functional variables also scale with body size. Compare, for instance, the blue whale, which has a heart mass of 600 kg and a resting heart rate of 6 bpm, with the smallest mammal, the shrew, which has a heart mass of 12 mg and a resting heart rate of up to 1200 bpm. 6 Despite the clear relationship between body size and cardiovascular dimensions and functional parameters, the practice of scaling cardiovascular measurements is poorly applied in adult clinical cardiology. This contrasts with pediatric medicine, in which measurements are universally indexed to body size. The intuitive idea that body growth implies a greater need for scaling in pe...

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Section: Evidence For Allometric Scaling Of Cardiovascular Structurementioning

confidence: 88%

Section: Evidence For Allometric Scaling Of Cardiovascular Structurementioning

confidence: 99%

Does Size Matter?

et al. 2008

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“…However, in order to estimate valid and unbiased body mass exponents when investigating the power-law association between a physiological output variable (e.g., Kleiber (1950) Metabolic rate Allometry Stroke volume Kory et al (1961) Pulmonary function, FEV 1 Linear regression Jolicoeur and Heusner (1971) Oxygen consumption Allometry Cole (1975) FEV Albrecht et al (1993) Facial height Ratios, regression, and allometry Nevill (1994) Physiological variables Allometry Nevill and Holder (1994) VO 2max Log-linear model Rogers et al (1995) VO 2 sm Allometry Jungers et al (1995) Crania of male monkeys Ratios and allometry Nevill and Holder (1995a) Percentage body fat, Body Mass Index, Lean Body Mass Index Allometry and linear regression Vanderburgh et al (1995) Grip strength Allometry VO 2max Allometry Performance time Allometry Welsman et al (1996) Peak VO 2 Allometry Batterham and Tolfrey (1996) VO 2 Allometry Heil (1997) VO 2peak Allometry Simple ratio Nevill et al (1997b) Systolic and diastolic blood pressure Allometry and log-linear regression Batterham et al (1997b) VO 2peak \Full" allometry Intercept Batterham and George (1997) Maximal muscular function Allometry Batterham et al (1997a) Left ventricular mass Allometry West et al (1997) Metabolism Allometry George et al (1998) Left . In humans, there is strong evidence to suggest that the muscle mass of both the arms and legs increases at a greater proportion to body mass than that expected by geometric similarity (Nevill et al, 2003a(Nevill et al, , 2004c.…”

Section: Controlling For Differences In Body Size Historical Backgroundmentioning

confidence: 99%

Modeling Physiological and Anthropometric Variables Known to Vary with Body Size and Other Confounding Variables

Nevill

Bate

Holder

2005

Am. J. Phys. Anthropol.

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This review explores the most appropriate methods of identifying population differences in physiological and anthropometric variables known to differ with body size and other confounding variables. We shall provide an overview of such problems from a historical point of view. We shall then give some guidelines as to the choice of body-size covariates as well as other confounding variables, and show how these might be incorporated into the model, depending on the physiological dependent variable and the nature of the population being studied. We shall also recommend appropriate goodness-of-fit statistics that will enable researchers to confirm the most appropriate choice of model, including, for example, how to compare proportional allometric models with the equivalent linear or additive polynomial models. We shall also discuss alternative body-size scaling variables (height, fat-free mass, body surface area, and projected area of skeletal bone), and whether empirical vs. theoretical scaling methodologies should be reported. We shall offer some cautionary advice (limitations) when interpreting the parameters obtained when fitting proportional power function or allometric models, due to the fact that human physiques are not geometrically similar to each other. In conclusion, a variety of different models will be identified to describe physiological and anthropometric variables known to vary with body size and other confounding variables. These include simple ratio standards (e.g., per body mass ratios), linear and additive polynomial models, and proportional allometric or power function models. Proportional allometric models are shown to be superior to either simple ratio standards or linear and additive polynomial models for a variety of different reasons. These include: 1) providing biologically interpretable models that yield sensible estimates within and beyond the range of data; and 2) providing a superior fit based on the Akaike information criterion (AIC), Bayes information criterion (BIC), or maximum log-likelihood criteria (resulting in a smaller error variance). As such, these models will also: 3) naturally lead to a more powerful analysis-of-covariance test of significance, which will 4) subsequently lead to more correct conclusions when investigating population (epidemiological) or experimental differences in physiological and anthropometric variables known to vary with body size. Yrbk Phys Anthropol 48: 141-153, 2005.

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“…21 According to dimensional analysis and empirical studies, V O 2 should be expressed in relation to body mass raised to the power of 0.75, 22 whereas ventricular mass should be expressed with the scaling exponent 0.78, which empirically is the best approximation when lean body mass is unavailable. 23 …”

Section: Allometric Scalingmentioning

confidence: 99%