We report on the normal gender-independent relationship of LVM determined by 2D-echocardiography and cardiac MRI to body size and on the ability of indexed LVM to detect obesity-associated LVH and predict CVE and death among middle-aged/older adults. We determined allometric exponents for LVM with and without adjustment for gender and found that the larger body size among men is an important confounder of the body size-LVM relationship, because gender is an independent determinant of LVM. The exponent that described the body height-LVM relationship was 1.7 (rather than 2.7, as previously described based on analyses that did not account for gender).6
demonstrated important residual relationships with body height (which were even stronger
than those seen with ratiometric normalization) and systematically misclassified individuals with long or short body heights, demonstrating that this is not an adequate indexation method. We present normative data for 2D-echocardiography and cardiac-MRI-derived LVM. We demonstrate significant ethnic differences in indexed LVM. We show that LVM/height1.7
was most consistently associated with different outcomes, including all-cause-death.
Given the impact of gender on LVM and body size, normalization must exclude this confounding effect. This concept, although not obvious for allometric models, is essentially no different than the concept applied for other inference procedures in which gender affects the variables at hand. Not only is the presence of a common exponent applicable to both genders an important assumption that must be ascertained, but allometric normalization itself must not be influenced by the body size-independent gender effect. Only under these circumstances can an exponent be identified that is not affected by gender itself, ensuring that estimates of associations between LVH and CVE are not affected by male gender, which is associated with higher cardiovascular risk. We show that when the gender effect is ignored, an important residual relationship between indexed LVM and body height occurs, which biases the relationship between indexed LVM and cardiovascular risk, because body height itself is associated with CVE13
. Therefore, LVM/height2.7
artificially captures prognostic information associated with body height. Despite this artificial advantage, LVM/height2.7
was not a superior predictor of CVE as a continuous variable and LVH defined by LVM/height2.7
was less consistently associated with CVE and, in contrast to LVH defined by LVM/height1.7
, failed to predict all-cause death. Furthermore, the prognostic disadvantage of LVM/height2.7
is likely to be even greater than apparent from our relatively short-term follow-up, during which CVE related to LVH are expected to occur predominantly among subjects with the most pronounced increases in LVM, likely to be classified as LVH regardless of the indexation method.
Previous data in which the gender effect was not considered suggested that the LVM-body weight relationship in adults is approximately linear, that the BSA-LVM relationship is described by a power of ~1.5, whereas the body height-LVM relationship is approximately cubic.6
This was explained on the basis of assumed relationships between LVM (3-dimensional measure), body weight (related to body mass, a 3-dimensional measure), BSA (2-dimensional measure) and body height (1-dimensional measure). Such relationships were said to be expected based on the ratio of the measured dimensions. Therefore, LVM would be expected to relate linearly to the first power of weight (dimension ratio=3/3), the 1.5th
power of BSA (dimension ratio=3/2) and the 3rd
power of height (dimension ratio=3/1). However, such expectations are only valid if: (1) the relationship between body height and other body dimensions is isometric; (2) The relative amount of body tissues with different densities is constant across the entire body height range. Clearly, such assumptions are untenable as demonstrated by the body weight-height relationship, which is not cubic as expected by their dimension ratio (3/1), but approximately quadratic. The wide use of BMI(weight/height2
) to normalize body weight for height, assumes such relationship. The non-cubic weight-height relationship is therefore inconsistent with previously reported allometric powers for LVM (particularly height2.7
), which were confounded by the body-size independent gender effect on LVM. The widely assumed approximately cubic relationship between body height and LVM is also highly inconsistent with the reports by Lauer14
and Brumbach15 et al
, who found this relationship to be approximately quadratic, in agreement with our results. Our results are also highly consistent with theoretical physiologic considerations related to mechanical myocardial load and circulatory dynamics, as discussed in the online supplemental section (http://hyper.ahajournals.org
The landmark contributions by De Simone et al
represented important steps forward in understanding the importance of non-linear LVM-body size relationships and the need for allometric LVM normalization.6, 16, 17
However, there is a need to improve normalization methods to avoid the bias introduced by gender, which results in an overestimation of allometric exponents (), residual relationships with body size () and important systematic misclassification of individuals ().
We used data from 2 independent studies using different methods to measure LVM. Because different imaging methods provide different absolute LVM estimates, we did not attempt to combine data from these studies. Instead, we performed independent analyses in both datasets to test the consistency of our findings and provide normative data for LVM assessed by both methods. Interestingly, equations describing the relationship between echocardiography-derived LVM and body height in the Asklepios study were essentially identical to those obtained from white MESA participants, resulting in similar cut-off values to define LVH. However, LVM estimates are sensitive to the imaging method. In this regard, it is interesting to note that a slightly non-linear exponent was obtained from Asklepios study participants for BSA, whereas a linear relationship was observed in MESA. This was likely due to geometric LV variations with increasing body size. Specifically, the ASE formula assumes a constant LV shape, whereas cardiac-MRI-derived LVM does not depend on geometric assumptions. Therefore, geometric changes associated with increasing body size (such as those in LV sphericity) that would have been undetected by 2D-echocardiography in the Asklepios study likely resulted in a mild exaggeration of the BSA-LVM relationship (slightly higher exponent).
In addition to the methods presented and validated herein, Bluemke et al
proposed an approach in which MRI-derived LVM was expressed as a ratio of expected/observed LVM4
, where expected LVM was computed from an individual's body height and weight using gender-specific non-linear equations. This height-weight method has been shown to be superior to non-indexed LVM to predict a composite endpoint of nonfatal and fatal CHD and stroke.15
Although these equations optimally fit the body size-LVM relationship among normal individuals, we found that the model fit between BSA and LVM was very similar to the fit of a model containing separate terms for height and weight in both studies (data not shown). The use of body height and BSA represent simple methods of normalization, particularly for clinical use and are complementary to the combined weight-height method proposed by Bluemke et al
. Of note, Bluemke et al
reported that normalization for body height to the power of 1.9 did not fully eliminate the LVM-body height relationship, which is not inconsistent with our findings since as shown by our results, Chinese individuals have lower values of LVM indexed for height. Since Chinese individuals also tend to demonstrate shorter body heights compared to other ethnic groups, the LVM-height relationship in the overall sample is expected to be influenced by the effect of Chinese ethnicity. Our findings unequivocally demonstrate that normalization for body height1.7
fully eliminates the ethnic-independent, gender-independent relationship between LVM and body height in our reference samples ().
Our cutoffs to establish abnormal values to define LVH were derived from data distribution in reference samples of normotensive, normal-weight individuals without conventional risk factors and demonstrate the prognostic validity of this approach. However, factors other than blood pressure, obesity and conventional risk factors may impact LVM. Furthermore, dichotomization was performed for operative definitions using an arbitrary percentile in reference samples. This approach may not establish optimal cut-points to define LVH. In addition, the relationship between LVH and cardiovascular risk may be continuous rather than discrete. Clearly, further studies are required to assess optimal cutoffs to define LVH based on the magnitude of risk increase with increasing degrees of LVH. However, this will require larger sample sizes and/or number of events.
Our study has limitations. Given our strict exclusion criteria, we did not study an adequate number of healthy African-Americans and Hispanics. Consequently, normalization using powers derived from white and Chinese populations may not be optimal for these ethnic groups. Therefore, data from these populations should be considered preliminary. Inclusion of these ethnic groups in analyses evaluating the association between LVH and CVE may have influenced our results. Longer time to follow-up resulting in a greater number of CVE will provide adequate power to assess ethnic-specific associations between LVH and CVE. Because age influences LVM, data presented herein should be strictly applied according to the age distribution of the described populations. The Asklepios study population was restricted to middle-aged adults (35-55 years). We did not determine methods for LVM normalization to the mass of tissues with different metabolic rates (lean body mass and fat mass). Previous studies demonstrated that LVM is more strongly related to fat-free than adipose mass18
and that indexation for fat-free mass eliminates gender-related differences in LVM.19
Although future research is needed to identify the prognostic implications of indexation to fat-free mass, we provide information for appropriate indexation to the most practical and commonly used body size indices in clinical and epidemiologic settings.