Validation of anthropometric equations for predicting body mass and height in older women

Validação de equações antropométricas para a predição da massa corporal e estatura de mulheres idosas

Abstract

To investigate the cross-validity of two equations widely used in national research to predict body mass and height in older Brazilians. Additionally, the importance of possible differences between observed and predicted BMI will be investigated with the help of equations. BM and HEI were measured using mechanical scales and portable stadiometers in a sample of 200 older women (66.6 ± 5.43 years) living in Maceió / AL - Brazil. To verify the validity of equations, the following variables were used: Student's t-test, constant error (CE), total error (TE) and standard error of estimation (SEE). To verify agreement between actual and predicted values, the Bland-Altman test was used. The comparison between BM and HEI values obtained through equations and those verified in measurements showed statistically significant differences (p <0.05). CE between predicted and measured values, TE of tested equations, as well as SEE for the prediction of variables: BM (1.66; 0.11 and 6.33), HEI (-0.02; 0.02 and 0.10) and BMI (1.47; 0.10 and 3.24) allowed determining relative values very close to actual ones (2.6%, 1.31% and 5.3% for BM, HEI and BMI respectively); however, values were not statistically significant. The equations analyzed should not be used in a general way for the population of older Brazilian women with characteristics similar to those analyzed in this study. Therefore, further studies should be carried out with the objective of constructing specific equations for the population of older women and hospitalized patients, especially the most fragile ones.

Key words
Aging; Regression equation; Validation

Resumo

Investigar a validade cruzada de duas equações, largamente utilizadas em pesquisas nacionais, para a predição da massa corporal e estatura em idosos brasileiros. Adicionalmente, será investigado a importância das possíveis diferenças entre o IMC observado e predito com auxílio das equações. As medidas da MC e EST foram mensuradas, com auxílio de balanças mecânicas e estadiômetros portáteis, em amostra de 200 idosas (66.6±5,43 anos) residentes em Maceió/AL - Brasil. Para verificar a validade das equações foram utilizadas as seguintes variáveis: teste t de Student, erro constante (EC), erro total (ET) e o erro padrão de estimativa (EPE). Para verificar a concordância entre os valores reais e preditos utilizou-se o teste Bland-Altman. A comparação entre os valores de MC e EST obtidos através das equações e os verificados na mensuração das medidas, apresentaram diferenças estatisticamente significantes (p<0,05). O EC entre os valores preditos e medidos, os ET das equações testadas, bem como, o EPE para a predição das variáveis: MC (1,66; 0,11 e 6,33), EST (-0,02; 0,02 e 0,10) e IMC (1,47; 0,10 e 3,24) permitiram determinar valores relativos muito próximos dos reais (2,6%, 1,31% e 5,3% para MC, EST e IMC respectivamente), entretanto, não estatisticamente significativos. As equações analisadas não poderiam ser utilizadas de maneira generalizada para a população de idosas brasileiras com características semelhantes às estudadas. Portanto, recomenda-se estudos adicionais desenvolvidos com o objetivo de construir equações específicas, para a população de idosas, hospitalizadas, especialmente as mais frágeis.

Palavras-chave
Envelhecimento; Equação de regressão; Validação

INTRODUCTION

In 2018, the Brazilian population was estimated at 207.8 million people, including 21,872 million, the equivalent of 10.5%, aged 65 years and over, which indicates that the Brazilian elderly population increased by 6%¹.

Given such change in the demographic profile, the concern of society with the health of the elderly population has increased, especially regarding problems related to morphological (body composition) and physiological changes, falls, especially nutritional deficits that may compromise the health and well-being of this age group². Among previously described factors, nutritional status (NS) can be considered a determining variable for successful longevity³; so, it has been the subject of interest to the scientific community.

NS evaluation, in addition to being important for assessing the nutritional conditions of older adults, also helps professionals during nutritional and exercise prescription for people of all age groups, being part of health maintenance or improvement strategies ^4-6, and drug dosage^7-9.

Several anthropometric measurements, such as body mass (BM), height (HEI), perimeters, skinfolds, bone lengths and diameters, among others, have been widely used for NS evaluation in epidemiological studies with the objective of prescribing diets, exercise or medication dosage^10,11. Regarding NS evaluation, Body Mass Index (BMI) obtained through the ratio between body mass and square height (BMI = BM / HEI²) and expressed in kg/m², is the measure most widely used in epidemiological studies³. However, under some conditions, such as lower limb amputations, the presence of disabling diseases, wheelchair use and bedridden patients, such measures are often impracticable or impossible.

Given the above, regression equations using different anthropometric measures as predictive variables, such as bone length, wingspan or half-wingspan and foot length have been often used, which are capable of predicting BM and HEI in the elderly population. In this context, since they use easy and accessible measurements (knee height (KH), triceps (TSF) and subscapular (SSF) skinfolds and brachial (PBR) and leg perimeters (PPER), two equations, originally proposed by Chumlea et al.^10,11, have been used in scientific studies to predict BM and HEI.

Interestingly, Monteiro et al.¹² reported that although they were developed using a sample of Americans aged 65-104 years, without considering the influences of possible intervening variables such as ethnicity, genetics, cultural aspects and nutritional habits, among others, such equations have been widely used in Brazil and worldwide.

In addition to being scarce, studies investigating the validity of such equations in samples of Brazilian older women are inconclusive¹³. The above, associated with the approximation of values, due to possible HEI and BM errors, particularly in bedridden subjects, may lead to errors in dietary and exercise prescriptions, as well as in therapeutic planning⁴.

This study was conducted with the objective of evaluating the cross-validation of two equations^10,11 widely used in national and international nutritional studies to predict BM and HEI in older women. Additionally, it was also intended to evaluate the importance of differences caused by the use of equations for BMI calculation.

METHODS

To compose the sample, 200 volunteers with minimum age of 60 years (60-86 years, 66.60 ± 5.43 years) were conveniently selected from a population of 800 women, participants of leisure physical activity programs offered by various institutions in the city of Maceió, who were functionally independent and without diagnosis of bone diseases, amputations or recent fractures, among other diseases that could interfere with performance in tests or that could be aggravated by the participation in the study.

The two equations evaluated proposed by Chumlea et al.^10,11, are shown below:

$$\begin{array}{c}\mathrm{H}\mathrm{E}\mathrm{I}=84.88+(1.83 \mathrm{X} \mathrm{K}\mathrm{H})+(-0.24 \mathrm{X} \text{Age)}\\ \mathrm{B}\mathrm{M}=(0.98 \mathrm{X} \mathrm{P}\mathrm{B}\mathrm{R})+(1.27 \mathrm{X} \mathrm{P}\mathrm{P}\mathrm{E}\mathrm{R})+(0.4 \mathrm{X} \mathrm{S}\mathrm{S}\mathrm{F})+(0.87 \mathrm{XK}\mathrm{H})-62.35\end{array}$$

All anthropometric measurements were performed according to recommendations proposed by Lohman et al.¹⁴.

Normality of distribution and homogeneity of data variances were respectively evaluated with the aid of Kolmogorov-Smirnov and Levene tests. To characterize the sample, central tendency measure (arithmetic mean) and dispersion measure (standard deviation) were used; amplitude was verified by the difference between maximum (MV) and minimum values (mv) for each variable.

To verify the accuracy of Chumlea’s equations based on cross-validation, paired student t, total error (TE), constant error (CE) and standard error of estimation (SEE) statistical tests were used. Additionally, the Bland-Altman test was used to evaluate the agreement between measured values and those estimated by equations proposed by Chumlea et al.^10,11. For all tests, significance level of p≤0.05 was adopted.

All study participants signed the free and informed consent form in accordance with recommendations of Resolution 466/12 of the National Health Council on research involving human subjects and approved by the ethics committee of the Federal University of Alagoas under protocol No. 23065.020769 / 2009 -30.

RESULTS

Values presented by the group of participants for age, BM, HEI and knee height (KH) measures, as well as mean values ​​obtained by prediction equations can be observed in table 1.

Table 1
Descriptive statistics for sample characterization (n = 200)

	M	SD	vm	VM
Age	66.60	5.43	60.00	86.00
Actual weight	64.71	11.68	35.70	102.00
Estimated weight	63.04	12.55	16.51	95.76
Actual height	1.52	.07	1.32	1.75
Estimated height	1.54	.10	1.09	1.72
Actual BMI	27.90	4.79	15.87	45.33
Estimated BMI	26.42	5.04	7.46	43.44
Knee height	46.87	5.78	22.00	56.00

• Note. Vm = minimum value; VM = maximum value; M = mean; SD = standard deviation

To verify the predictive power of Chumlea’s equations, cross-validation was performed using the following procedures, suggested by Lohman¹⁵: 1) comparison test between means (paired t-test) - observed means should not differ statistically; 2) calculation of the standard error of estimation (SEE) - aiming to indicate the expected margin of error in a prediction; 3) constant error (CE), representing differences between estimated and measured values; and 4) total error (TE) - indicating the size of the error associated with the number of subjects evaluated. Results can be seen in table 2.

Table 2
Cross validation of Chumlea’s equations^10,11 for older women

	CE	TE	SEE	t	p
BM	1.66	0.11	6.33	2.57	<0.011
HEI	-0.02	0.02	0.10	-3.08	<0.002*
BMI	1.47	0.10	3.34	4.84	0.000*

• Note. t = t student, p = significance level; CE = constant error; TE = total error; SEE = standard error of estimation;
• ^*
  significant difference (p <0.05).

When compared, results showed BM (1.66 kg) and BMI underestimation (1.47 kg / m²) and HEI overestimation (0.02 cm). Regarding predicted HEI and BMI values, significant statistical differences were found, although SEE values were below cutoff point proposed by Lohman¹⁵. In contrast, BM did not present statistically significant differences, although SEE of 6.33 kg does not meet validation criteria of the aforementioned author.

The analysis of the agreement between estimated and measured HEI, BM and BMI values (data not showed), verified using the method proposed by Altman and Bland, showed that the variable that presented the best agreement between measured and estimated values was HEI, which overestimated the actual measurement by only 0.02 cm, while BM and BMI were underestimated by 1.66 kg and 1.47 kg / m² respectively.

Although the values found showed considerable agreement, since mean values ​​were close to zero, especially HEI, graphs showed considerable dispersion between individual values.

DISCUSSION

This study aimed to identify the cross-validity of two prediction equations proposed by Chumlea et al.^10,11 to estimate BM and HEI in Brazilian older adults, since such equations are not only pioneer¹⁶, but also the most accepted and used in Brazil and in most western countries⁹.

The proposed equations use knee height as one of the main alternatives, justified by the fact that it does not change with advancing age. Additionally, it is discussed how possible differences between the two measures could affect BMI results, since this measure is the most used in epidemiological studies investigating NS.

Objectively, the observed results showed significant differences (p <0.001) between actual and predicted measurements for all anthropometric variables, except for BM. These results overestimate measured values by 1.66 kg for BM and 0.02 cm for HEI. As a result of these differences, BMI was also overestimated by 1.47 kg/m².

Standard error values ​​observed were low for HEI (SEE = 0.10 cm) and BMI (SEE = 3.34) although they were high for BM (SEE = 6.33 kg), according to Lohman¹⁶, who established cutoff point for SEE of ≤3.5. It is important to highlight that in relation to SEE, the proposed cutoff point is appropriate for equations developed with the use of skinfolds among independent variables, which reinforces the inadequacy of formulas to predict BM and HEI proposed by Chumlea, as they present SEE above the proposed cutoff point.

The results found differ from other studies, such as Closs et al.¹⁷, which showed that knee height may be a reliable alternative measure in the nutritional assessment of older adults. Using sample composed of 186 individuals (74.3 ± 7.1 years), the author found positive correlation between measured height and height estimated by Chumlea’s equation, although the predicted result overestimated the actual measurement by 3 cm. Likewise, Muncie et al.¹⁸ evaluated the validity of the Chumlea’s equation for predicting HEI in a sample of 19 hospitalized white and black older women (78 ± 6 years) and although it was observed that predicted results underestimated actual results by about 4cm, the results pointed out that the Chumlea’s equation presented good predictive value, showing no statistical differences in relation to actual height. In turn, our study showed underestimation much closer to the actual value (0.02cm), but the results showed significant statistical differences. However, it is necessary to consider that, regarding the height variable, prediction errors found in studies by Closs et al.¹⁷ and Muncie et al.¹⁸ and in our study are within cutoff point proposed by Beghetto et al.¹⁹, which considers 5 cm an acceptable error margin.

On the other hand, Myers et al.²⁰ investigated the suitability of the same HEI prediction equation used in our study in 16 men (72 ± 7.4 years) and 16 women (72 ± 8.7 years) of Japanese descent and found that the equation overestimated HEI for women by 1.5 (± 0.64cm), which results were not statistically significant. Although values ​​are very close to those found in this study, ethnic and age differences between samples, as well as the quite different physical conditions between samples seem to explain the significant differences found.

Similarly, Berger et al.⁸ using 250 subjects aged 16-89 years (61.4 ± 15.2 years), tested the validity of the Chumlea’s equation¹¹ for HEI and found significant differences when compared to direct measurements, overestimating actual values ​​by five and seven centimeters. It is noteworthy that the age groups used in samples were very different and in addition to not reporting the ethnicity of subjects, individuals were physically very fragile, which may explain differences found, since the long time required for measurements, as well as the need for great effort and help in obtaining them can lead to significant measurement errors²¹.

A study by Rabito et al.⁷ conducted on hospitalized Brazilians of both sexes (49 ± 17 years) tested some equations proposed by Chumlea for HEI and BM and among them those used in our study, which showed statistically significant differences (p> 0.05). For both HEI and BM, the distinct ethnic characteristics between samples, according to the author, may have been responsible for differences found, although in our study, also with Brazilians (not hospitalized), measured and estimated values were closer, contrary to the justification of that study. It is important to highlight that the ethnicity factor, according to Freire²², should not be considered in Brazil, as its intense miscegenation makes it difficult to establish any racial pattern with minimal security.

Oliveira and Filho⁴ validated Chumlea et al.^10,11 equations for the prediction of BM and HEI in a sample of 30 physically active women (66.6 ± 6.68 years) from the state of Paraíba, northeastern Brazil. Unlike our results, the authors found no significant difference between measured and estimated BM and HEI, although HEI and BM were both underestimated (2.38 cm and 1.92 kg respectively). However, according to Filho²³, the small sample (n = 30) and the large data dispersion (evidenced by the high standard deviation) may contribute to estimation errors such as those found in the above study. Despite the clear validation, the authors only verified differences between averages of actual and predicted values ​​using the t-test, which for many authors, is insufficient to validate any prediction method. Similarly, Galisa and Pustiglione²⁴ validated the Chumlea’s equation for HEI in 50 hospitalized Brazilian women, demonstrating strong correlation between actual and estimated measurements. In that study, the sample size may have significantly contributed to results found.

According to Chumlea et al.²⁵, the fact that HEI was significantly overestimated seems to be somewhat predicted, and therefore height estimates should be used primarily over direct measurements, since directly measured HEI does not reflect the exact HEI of older adults undergoing physical changes as a result of advancing age. Sampaio et al.²⁶ reinforces this statement arguing that estimated HEI seems to be more compatible with the height of the individual in adulthood. However, one of the reasons that led us to question the validity of this equation was that some studies, contrary to statements above, found HEI underestimation²⁷.

With regard to body mass, Bernal-Orozco et al.⁹ were unable to validate the Chumlea et al.¹⁰ equation in a sample of 95 Mexican older women. In that study, values ​​obtained compared to directly measured BM showed differences of - 3.7 and - 6.6 Kg, underestimating values, ​​similarly to our results. It is important to note that the sample of this study was composed of hospitalized and / or institutionalized older women, which may have influenced BM underestimation, since Chumlea’s equations were obtained from physically active older adults. In a study with 209 adult and older adult patients of both sexes from the city of Fortaleza, Sampaio et al.²⁶ demonstrated that the equations proposed by Chumlea showed good correlation with direct measurements, both in adults and older adults, although with differences in averages obtained, underestimating BM by 1.34 kg, which result are very close to those of this study.

Similarly, a study conducted with a population of hospitalized older adults (> 65 years) of both sexes in Barcelona-Spain²⁷, whose ethnicity was not reported, tested the validity of Chumlea’s equations for BM, and although finding statistically significant correlations between actual and estimated weight, demonstrated that Chumlea’s equations underestimated the actual values ​​of all variables analyzed (p <0.001). The study reinforced the need for the development of specific equations for the estimation of variables analyzed.

In hospitalized or institutionalized older patients, BM tends to be underestimated, especially in women, since in this age group, there is a decline in lean body mass, as well as an inversion in body fat distribution from limbs to the abdominal region, influencing estimated weight validity, since these formulas use arm and calf circumference and subscapular skinfold, and in obese individuals, these errors seem to be greater²⁸.

In fact, variations in BM values ​​may reflect relevant nutritional imbalances and may characterize fragility or adverse health effects such as disease aggravation, hospitalization and death⁶. Inadequate BM estimates may lead to the use of drug and diet therapies that do not meet actual individual or collective needs. In physical exercise programs for the elderly population, reliable BM and HEI data are required for adequate and individualized prescription⁴. Therefore, BM is an important tool for the early identification of older individuals at nutritional risk, thus improving the quality of care⁹. In this sense, other studies conducted to verify the applicability of Chumlea’s equations in a population of hospitalized / institutionalized older adults in Brazil^6,15,28 could not confirm the validity of these equations.

Consequently, prediction errors in HEI and BM measurements generate inaccuracy in BMI, leading to possible calculation errors for nutritional supply with consequent impairment in the recovery of hospitalized older patients²⁷. Therefore, its use is controversial, especially in the elderly, due to the decrease in height, adipose tissue accumulation, reduction in muscle mass and in the amount of body water³.

Our results demonstrate BMI underestimation (1.47kg / m²) when predicted and overestimated HEI and predicted and underestimated BM were used. Similarly, Fogal et al.¹⁶ found BMI underestimation in older women (0.9 kg / m²) when overestimated EST was used. The same underestimation was found by Salgado et al.²⁷ using underestimated HEI and BM to calculate BMI. Similar BMI underestimation results were found in other studies^17,26. It is important to note that the equations proposed by Chumlea considered in this study were developed from physically active older adults, which can maximize HEI overestimation in less healthy individuals and consequent underestimate BMI; however, considering more homogeneous and specific samples of each population avoids major nutritional assessment errors while promoting health gains.

The divergent results found between above studies and our study allow us observing that the aging process acts individually in people of different ethnicities⁵, also considering possible anatomical differences. Considering that both HEI and BM are important variables for assessing nutritional status and, especially drug dosing, specific prediction equations for these measures should be developed for older adults, especially Brazilians, taking into account gender, age and ethnic miscegenation. It is equally important that predictive models should present partial significance of variables, lower standard error of estimate (SEE), higher multiple correlation coefficient (r²), model practicality and fewer independent variables¹⁶.

From the statistical point of view, the fact that studies did not analyze the standard error of estimation established by Lohman¹⁵ as one of the main validation techniques of new equations may explain the different results found in the main studies. Moreover, differences in ethnicities, age groups, cultural aspects and physical conditions verified in the different studies may contribute to the discrepancy found between actual and estimated measurements.

Studies using anthropometric measurements should be interpreted with caution. According to Sullivan et al.²⁸, to avoid erroneous conclusions, the reliability of the measurement technique should be considered, even when using experienced evaluators, since reproducibility varies considerably, being able to transfer to prediction equations measurement errors that can theoretically be sources of prediction errors. Careful attention should be paid to measurement procedures; otherwise, the results obtained could be totally useless for analysis purposes. This becomes relevant, since many validation studies do not declare the reproducibility of anthropometric measurements used^29,30.

CONCLUSION

The analyzed equations could not be used in a general way for the Brazilian elderly population, at least with regard subjects with characteristics similar to those of this study. In this sense, further studies should be carried out with the objective of constructing specific equations capable of predicting valid BM, HEI and BMI results for the hospitalized elderly Brazilian population, especially the most fragile ones.

COMPLIANCE WITH ETHICAL STANDARDS

• Funding

  This research did not receive any specific grant from funding agencies in the public, commercial, or non-profit sectors. This study was funded by the authors

• Ethical approval

  Ethical approval was obtained from the local Human Research Ethics Committee – Research Ethics Committee of the Federal University of Alagoas: Protocol No. 23065.020769 / 2009 -30, and it was written in accordance with standards set by the Declaration of Helsinki.

How to cite this article

• Santos Júnior GM, Geraldes AAR, Oliveira DWL, Pereira PMG, Albuquerque RB. Validation of anthropometric equations for predicting body mass and height in older women. Rev Bras Cineantropom Desempenho Hum 2021, 23:e77985. DOI: http://doi.org/10.1590/1980-0037.2021v23e77985

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Publication Dates

• Publication in this collection
  05 Apr 2021
• Date of issue
  2021

History

• Received
  02 Oct 2020
• Accepted
  08 Dec 2020