Classificação do estado nutricional pelo índice de massa gorda: o instrumento de medição importa?

rbcdh Revista Brasileira de Cineantropometria & Desempenho Humano Rev. bras. cineantropom. desempenho hum. 1415-8426 1980-0037 Universidade Federal de Santa Catarina Resumo Avaliar o Estado Nutricional (EN) permite rastrear desnutrição e obesidade, condições associadas a doenças crônicas não transmissíveis. O índice de massa gorda (IMG) destaca-se em relação aos indicadores tradicionais de EN. No entanto, propostas que definem limiares para IMG não são sensíveis para discriminar casos extremos (graus de obesidade ou magreza). Apenas uma proposta (NHANES) estabeleceu oito categorias de classificação EN (IMG), mas foi determinada por densitometria corporal total (DXA). Porém, DXA é caro e nem sempre disponível. O objetivo foi testar a validade do método NHANES usando bioimpedância elétrica (BIA) e dobras cutâneas (DOCs) para classificar o EN. O IMG de 135 (69 mulheres) universitários com idade entre 18 e 30 anos foi obtido por DXA, BIA e DOCs. A concordância foi testada entre os instrumentos (Bland-Altman) e classificações de EN (Qui quadrado e índice Kappa). O teste de concordância com a DXA indicou as DOCs subestimarem o IMG (-1,9 kg/m2) para ambos os sexos e a BIA em mulheres (-2,0 kg/m2). No entanto, as BIA superestimaram o IMG (1,4 kg/m2) nos homens, embora com menos viés. Não houve concordância entre as classificações de EN (NHANES) pelo IMG entre DXA e BIA/DOCs. A exceção ocorreu entre DXA e BIA em homens que apresentaram concordância “razoável” (k = 0,214; p = 0,001). Em conclusão, DOCs e BIA não mostraram concordância suficiente para substituir DXA pela classificação de EN, dentro dos limites NHANES. As ferramentas diferem para medir IMG e classificar categorias de EN (NHANES). INTRODUCTION Nutritional status (NS) assessment is useful for weight (Wt) control and enables mapping malnutrition and obesity. The increase in overweight and obesity rates across the planet is a cause for concern. This scenario impacts public health given a direct association with the development risk of chronic non-communicable diseases1. The body mass index (BMI) is the most popular resource used for epidemiological monitoring of NS. However, BMI is not sensitive for Wt deviation due to excess or deficit in fat mass (FM) or fat-free mass (FFM), under/overestimating NS classification2. Another NS assessment is the fat mass percentage (%FM), which also presents biases if stature (Ht) is not considered. Subjects with similar Wt and %FM values, with different Ht, may present a different NS classification2. Thus, the fat mass index (FMI [kg/m2]) appears as an alternative, since distinguishes FM from FFM and is sensitive to the FM distribution related to Ht2,3. Additionally, it points to greater sensitivity as a health-disease indicator for metabolic syndrome4, hypertension5, and cardiometabolic risk6. FMI calculation requires the measurement of FM, by DXA or more accessible instruments such as anthropometry through skinfolds thickness (ST) or electrical bioimpedance (BIA)7. NS classification proposals by FMI usually consider percentiles, sometimes with normal ranges8,9. However, they do not classify extreme cases of obesity or thinness. Only National Health and Nutrition Examination Survey (NHANES)7 proposal established thresholds analogous to BMI (eight NS classifications). So far, this proposal is valid only for Korea's population (KNHANES IV)10. Furthermore, that proposal has no validity tested for clinical practice instruments (BIA and ST), since the cutoff points originated from DXA7. Therefore, could the proposed NS classification by FMI derived from DXA be applied with BIA and ST? The study hypothesis considered that NS classification no differs between instruments. Although the FMI absolute values of each instrument are not identical, the classification will correspond to the same NS range. Thus, this study aimed to test the concurrent validity between BIA, ST, and DXA for the NS classification by FMI (NHANES) in young adults. METHODS Study design and sample This is a cross-sectional design study. The University's Ethics and Research Committee authorized the research (CAAE 03471118.9.0000.5659) according to the World Medical Association and the Helsinki Declaration. The sample is non-probabilistic, for convenience, composed of 135 university students aged 18 to 30 years old of both sexes (69 women). Individuals without diagnoses of diseases; who did not use drugs that alter metabolism or body composition; who did not have amputated body parts; non-athletes or with physical exercise less than 10 hours/week were included. Cases with some personal or clinical impairment (diseases, personal accidents); withdrawal or did not complete all stages of the study were excluded. The data collections were performed (10/2016 to 06/2017) at the university hospital, always in the morning to avoid circadian variations. All individuals received the instructions for exams11. Initially, they answered a questionnaire on general health status and self-declaration of ethnicity; then they performed the anthropometric measurements and the other exams. Body measurements The Ht (m) and Wt (kg) measurements were performed according to recommendations12, with a fixed wall stadiometer and a digital scale (Filizola® Model ID 1500), respectively. Then, the BMI (kg/m2) was calculated. FM and FFM (kg) were determined using three instruments: DXA (GE Medical Systems Lunar scanner, Prodigy Advance, encore software version 13.60 in a linear fan-beam scanner); BIA (tetrapolar type, Biodynamics®, model BIA 450) according to the manufacturers' guidelines; and ST (PrimeMed® calliper, Prime Vision DGi model). DXA supplied directly the FMDXA and FFMDXA using a two-component approach (2-C). We calculate FFMBIA using the equations13 and body density by ST using generalized equations for men14 and women15. The %FMST was determined as well as FMST, FFMST and FMBIA, by their respective relationships (2-C) with the BM16. Test-retest of 11 individuals verifies the reliability of the DXA measurements. The coefficient of variation for lean soft tissue, FM, and bone mineral content was 0.8%, 1.6%, and 1.6%, respectively. The ST technical error of measurements (TEM) was within the acceptable limits for experienced evaluators (<5%)17. FMI and FFMI have obtained from the Vanitallie et al.2 equations with FM and FFM measured by the three instruments. We establish the NS classification in categories for BMI, %FMDXA18, and FMI7. The NHANES7 reference values were adopted for the NS classifications by FMI for the three instruments. Statistical analysis We reviewed the data by double typing and exploratory analysis for error detection. We use parametric statistics when comparing continuous variables, considering the central limit theorem19. Differences between sexes were checked by t-test. We compared visually NS indicators (BMI, %FMDXA, and FMIDXA) with an adaptation of Hattori’s chart20. The adaptation involved the addition of the NS categories classification for each indicator (BMI, %FMDXA and FMIDXA), expressed in the NCSS 2020 statistical analysis software (version 20.0.3). We verified the agreement of the FMI absolute values between BIA and ST and the reference (DXA) by the Bland Altman test and the combinations of NS from FMIBIA, FMIST, and FMIDXA by cross-tabulation and chi-square. The reproducibility of the classifications by the Kappa coefficient followed the classification by Landis and Koch21. SPSS 20.0 and MedCalc 15.2 packages were used, with significance previously established (α=5%). RESULTS Most individuals (78.5%) were Caucasians, followed by Spanish (10.4%), Asian (3%), and African (2.2%). Nobody declared themselves indigenous while 5.9% did not declare an ethnic class. Regarding lifestyle, only 20.7% declared themselves sedentary (17 women and 11 men) and 6.7% of the total were smokers (four women and five men). Table 1 presents the descriptive statistics and differences between sexes. Table 1 Comparison of anthropometric variables and indicators of body composition between genders. Female (n=69) Male (n=66) Diferences test CI 95% CI 95% t p Unit Mean SD Lower to Upper Mean SD Lower to Upper Age Years 23.9 3.4 23.1 to 24.8 24.5 3.6 23.6 to 25.4 -0.947 0.346 Stature m 1.7 0.1 1.7 to 1.7 1.8 0.1 1.8 to 1.8 -10.169 <0.001 Wt Kg 59.7 8.6 57.6 to 61.7 75.4 12.1 72.4 to 78.4 -8.671 <0.001 BMI kg/m2 21.7 2.8 21.0 to 22.3 23.8 3.2 23.0 to 24.6 -4.173 <0.001 DXA FMDXA Kg 20.2 6.8 18.6 to 21.9 15.3 8.5 13.2 to 17.4 3.725 <0.001 FFMDXA Kg 39.4 4.0 38.5 to 40.4 60.1 6.9 58.4 to 61.8 -21.292 <0.001 %FMDXA % 33.2 7.1 31.5 to 34.9 19.4 8.1 17.4 to 21.4 10.561 <0.001 FMIDXA kg/m2 7.3 2.3 6.8 to 7.9 4.8 2.6 4.2 to 5.4 5.945 <0.001 FFMIDXA kg/m2 14.3 1.3 14.0 a 14.6 19.0 1.7 18.6 to 19.4 -18.046 <0.001 BIA FMBIA Kg 14.6 1.5 14.3 to 15.0 19.6 2.9 18.9 to 20.4 -12.557 <0.001 FFMBIA Kg 45.0 8.0 43.1 to 47.0 55.8 9.6 53.4 to 58.1 -7.029 <0.001 %FMBIA % 24.9 3.4 24.1 to 25.7 26.2 2.0 25.7 to 26.6 -2.766 0.007 FMIBIA kg/m2 5.3 0.5 5.2 to 5.4 6.2 0.7 6.0 to 6.4 -8.374 <0.001 FFMIBIA kg/m2 16.3 2.7 15.7 to 17.0 17.6 2.6 17.0 to 18.3 -2.799 0.006 ST FMST Kg 15.0 5.1 13.8 to 16.20 9.4 6.0 7.9 to 10.9 5.799 <0.001 FFMST Kg 44.7 4.9 43.5 to 45.9 66.0 8.0 64.1 to 68.0 -18.662 <0.001 %FMST % 24.6 5.6 23.3 to 26.0 11.8 5.8 10.4 to 13.2 13.061 <0.001 FMIST kg/m2 5.4 1.8 5.0 to 5.9 3.0 1.8 2.5 to 3.4 7.967 <0.001 FFMIST kg/m2 16.2 1.5 15.9 to 16.6 20.9 2.0 20.4 to 21.4 -15.746 <0.001 Note. BIA: electrical bioimpedance; Wt: weight; BMI: body mass index; CI: confidence interval; DXA: dual-energy X-ray absorptiometry; FM: fat mass; FMI: fat mass index; FFM: fat-free mass; FFMI: fat-free mass index; Kg: kilograms; Kg/m2: kilogram per square meter; m: meters; SD: standard deviation; ST: skinfolds thickness; %FM: percentage of fat mass. Genders were significantly different for all comparisons, except for age. Men had higher muscle indicators Wt (FFM and FFMI), BMI, and FM per BIA (FMBIA, FMIBIA, and %FMBIA) than women for the three instruments. On the other hand, women showed higher fat indicators (%FMDXA, %FMST, FMDXA, FMST,FMIDXA, and FMIST). Figure 1 shows the comparison for each sex between NS classification according to BMI, %FMDXA18, and FMIDXA7. Figure 1 illustrates the differences between FFMIDXA and FMIDXA between the sexes (p<0.001; Table 1) with a greater concentration of dispersion in the upper left quadrant for females and in the lower right quadrant for males. Men presented higher FFMIDXA while women had higher FMIDXA. In the women's NS classification, “normal” was more frequent, whose variation was 76.8% (BMI), 53.6% (%FMDXA), and 63.8% (FMIDXA). “Thinness” cases by BMI (11.6%), %FMDXA (17.4%) and FMIDXA (11.8%) were smaller than “overweight” by BMI (11.6%), %FMDXA (18.8%) or FMIDXA (23.2%). BMI observed any case of “obesity”, but %FMDXA (10.2%) and FMIDXA (1.4%) indicated the lowest occurrences. Among men, “normal” was 66.7% (BMI), 34.8% (%FMDXA) and 34.8% (FMIDXA). “Thinness” frequency cases were very low for BMI (1.5%), but were more than a third of the sample with %FMDXA (37.9%) and FMIDXA (34.8%). “Overweight” was 27.3% (BMI), 15.2% (%FMDXA), 21.2% (FMIDXA), while “obesity”, was the lowest observed frequency with 4.5% (BMI), 12.1% (%FMDXA) and 9.1% (FMIDXA). Figure 1 Relationship between BMI, %FMDXA, FMIDXA and FFMIDXA and the description of the nutritional status classification according to BMI, %FMDXA, FMIDXA for female (a) and male (b) young adults. BIA: electrical bioimpedance; BMI: body mass index2; DXA: dual energy X-ray absorptiometry; FMI: fat mass index8; FFMI: fat-free mass index; ST: skinfolds thickness; %FM: percentage of fat mass20 Figure 2 shows for each sex the agreement between the FMI measurement instruments (BIA, ST, and DXA). For females, FMIBIA (-2.0 kg/m2) and FMIST (-1.9 kg/m2) did not show good agreement with FMIDXA, indicating bias. The limits of agreement (±1.96 SD) between FMIDXA and FMIBIA were higher (2.0 and - 6.2 kg/m2) than FMIST (-0.0 and -3.8 kg/m2). BIA (r=0.94; p<0.001) and ST (r=0.449; p<0.001) present heteroscedasticity with the reference. Figure 2 Analysis of agreement (Bland-Altman) between FMIBIA, and FMIST concerning FMIDXA for the female and male sexes. BIA: electrical bioimpedance; DXA: dual-energy X-ray absorptiometry; FMI: fat mass index; ST: skinfolds thickness. For males, FMIBIA overestimated FMIDXA with a bias of 1.4 kg/m2, while FMIST was underestimated by -1.9 kg/m2. The limits of agreement (±1.96 SD) between FMIDXA and FMIBIA (5.3 and -2.5 kg/m2) were higher than FMIST (-0.1 and -3.8 kg/m2). There is heteroscedasticity for BIA (r=0.971; p<0.001) and ST (r=0.739; p<0.001), confirming the lack of agreement with the reference (DXA). Tables 2 (female) and 3 (male) shows the NS classification comparison with the cutoff points of the FMIDXA (NHANES)8 and BIA/ST. Table 2 Cross-tabulation of the nutritional status classifications according to FMIDXA and FMIBIA; FMIDXA and FMIST for females. Severe fat deficit n (%) Moderate fat deficit n (%) Mild fat deficit n (%) Normal n (%) Excess fat n (%) Total n (%) FMIDXA FMIBIA Severe fat deficit - - 3 (100%) - - 3 (100%) Mild fat deficit - - 3 (60%) 2 (40%) - 5 (100%) Normal - - 12 (27.3%) 32 (72.7%) - 44 (100%) Excess fat - - - 16 (100%) Obese Class I - - - 1 (100%) FMIDXA FMIST Severe fat deficit 3 (100%) - - - - 3 (100%) Mild fat deficit 5 (100%) - - - - 5 (100%) Normal - 7 (15.9%) 17 (38.6%) 20 (45.5%) - 44 (100%) Excess fat - - - 14 (87.5%) 2 (12.5%) 16 (100%) Obese Class I - - - - 1 (100%) 1 (100%) Note. BIA: electrical bioimpedance; DXA: dual energy X-ray absorptiometry; FMI: fat mass index; FFMI: fat-free mass index; n: absolute frequency; ST: skinfolds thickness; %: relative frequency.Kappa Index (k)=0.033; p=0.607 for BIA; k=0.023; p=0.696 for ST. Table 3 Cross-tabulation of the nutritional status classifications according to FMIDXA and FMIBIA; FMIDXA and FMIST for males. Severe fat deficit n (%) Moderate fat deficit n (%) Mild fat deficit n (%) Normal n (%) Excess fat n (%) Total n (%) FMIDXA FMIBIA Severe fat deficit - - - 4 (100%) - 4 (100%) Moderate fat deficit - - - 3 (100%) - 3 (100%) Mild fat déficit - - - 14 (87.5%) 2 (12.5%) 16 (100%) Normal - - - 15 (62.2%) 8 (34.8%) 23 (100%) Excess fat - - - - 14 (100%) 14 (100%) Obese Class I - - - - 6 (100%) 6 (100%) FMIDXA FMIST Severe fat deficit 4 (100%) - - - - 4 (100%) Moderate fat deficit 3 (100%) - - - - 3 (100%) Mild fat deficit 15 (93.8%) 1 (6.3%) - - - 16 (100%) Normal 6 (26.1%) 5 (21.7%) 5 (21.7%) 7(30.4%) - 23 (100%) Excess fat - - - 13 (92.9%) 1 (7.1%) 14 (100%) Obese Class I - - - 2 (33.3%) 4 (66.7%) 6 (100%) Note. BIA: electrical bioimpedance; DXA: dual energy X-ray absorptiometry; FMI: fat mass index; FFMI: fat-free mass index; n: absolute frequency; ST: skinfolds thickness; %: relative frequency. Kappa index (k)= 0.214; p = 0.001 for BIA; k = 0.002; p = 0.973 for ST. For females, the coefficients of agreement between the NS classifications by FMIBIA and FMIDXA were “slight” (k=0.033; p=0.607), coinciding in 50.7% of the classifications. FMIBIA did not classify cases of “severe deficit”, “moderate deficit”, “excess” of fat, or “obesity”. The 17 women classified by FMIDXA with “excess fat” (n=16) and “obesity” (n=1), were all considered “normal” by FMIBIA. About 40% of those who had a “mild deficit” of fat (FMIDXA) were also “normal” by FMIBIA. The agreement between the classifications by FMIST and FMIDXA was “slight” (k=0.023; p=0.696), coinciding with 36.2% of the classifications. FMIST did not discriminate against cases of “obesity” and agreed with FMIDXA in only 12.5% of “excess fat” cases. There were also 87.5% of women with “excess fat” (FMIDXA) classified as “normal” by FMIST. FMIST also classified more than half (55.5%) of women in “normal” NS (FMIDXA) as “moderate fat deficit” (n=7) or “mild fat deficit” (n=17). For males, there was a “fair” coefficient of agreement between the FMIBIA and FMIDXA NS classifications (k=0.214; p=0.001), coinciding in 43.9% of classifications. FMIBIA classified men in only two categories of the NS: “normal” and “excess fat”. About 91% of the cases classified by FMIDXA with some fat deficits (n=21) were classified as “normal” by the FMIBIA. About 12% of the “mild fat deficit” cases with FMIDXA were classified as “excess fat” by FMIBIA. “Obesity” cases (n=6) by FMIDXA were classified as “excess fat” with FMIBIA. There was a “poor” agreement between the FMIDXA and FMIST NS classifications (k=0.002; p=0.973), coinciding in 18.8% of classifications. FMIST classifies 69.5% of the normal cases (FMIDXA), with some fat deficit; FMIST still classified 93% of the “excess fat” by FMIDXA as “normal” cases. In addition, of the total cases of “obesity class I” by FMIDXA, 33.3% were “normal” and 66.7% were “excess fat” by FMIST. DISCUSSION The main finding of this study was not confirming our hypothesis, BIA/ST could not be used to determine the NS according to the referential (NHANES)7 established by DXA. Since ST/BIA are clinically available instruments we expected that the FMI differences with DXA would not invalidate their interchange use, as it deals with classification within a given interval. There was also no agreement (Bland Altman) between the instruments in determining the FMI absolute values. For FMI absolute values, BIA agreed less with the reference (DXA) than ST, while for NS classification ST became to agree less with the reference (DXA) than BIA. This was because BIA did not classify cases of extreme fat deficits, while ST and DXA did. Precisely in the fat deficit cases, the cut-off points range smaller7, being more susceptible to exhibit classification divergences between ST and DXA. In other populations was also observed the lack of agreement between FMIBIA and FMIST22,23. Despite the index used relativizing FM by Ht2 the differences remain significant suggesting that instrument choice matters. In addition to using different methodologies, an explanation is that instruments indirectly estimate FM based upon different conceptual assumptions and positions in the five-level model of body composition established by Wang et al.24 When DXA, BIA, and ST measure FMI, the values are not the same because they have different baseline assumptions. DXA was used to determine NHANES’s NS threshold, corresponding to level II (molecular) in the five-level model. DXA also indirectly estimates FM with acceptable precision by the mass attenuation coefficient (R) of the double X-ray beams of the atomic elements that compose the FM. Each atomic element has a characteristic mass R-value. The elements with low atomic numbers (hydrogen and carbon) have a lower R, while the elements with a high atomic number (calcium and phosphorus) have a higher R. FM, which contains more carbon, has less R-value than the FFM11. BIA, in turn, is based on electrical conductivity, not corresponding in a particular position in the five-level model24, without consensus about classification, being found in levels II25, III (cellular)26 or V (whole-body)27. BIA estimates FM by the inverse relationship between impedance (Z) and the volume of TBW through which the alternating electric current flows. In addition, BIA estimates FFM through TBW, which hydration influences much more than DXA/ST11. Men have a higher rate of sweating and are more prone to dehydration28, which possibly explains the positive biases concerning FMIBIA (and the negative of its complement, FFMIBIA)23. The ST corresponds to level V24 based on the body density derived from BM and total body volume, considering constant values for each component (FM: 0.900 g/cm3; FFM: 1.100 g/cm3). Therefore, in a 2-C approach based on the relationship between subcutaneous fat and total FM11, the ST regression equations to determine body density allow %FM calculation. Indeed, beyond the epidemiological context, the BMI is widely used to categorize NS and brings a conceptual confusion. BMI does not assess the FM nor its distribution across the body. For instance, “normal” NS classified with BMI is with FMI “obese” in 4% of cases3. In the “overweight” BMI category, FMI classified 65.5% of men and 71.3% of women as “obese”3. Therefore, BMI and FMI cannot be used interchangeably. One of them involves the original population to determine BIA and ST equations since these equations are originally from other countries. Our convenience sample limits the generalization of our findings, mainly due to the lack of ethnic representativeness. Even considering the high Brazilian miscegenation, it is worth mentioning that in the NHANES study there were no ethnic differences in the NS classification between Africans, Caucasians, and Hispanics7. Thus, the ethnic difference does not seem to influence the results since the indexes deal with intrapersonal relationships of body measures. Even though, our intention was exclusively inferential in the comparison between instruments, without an additional purpose for populating the findings. We used DXA as a comparative reference instrument, just like NHANES. Another strong point involves the use of the adapted Hattori Chart20. We allow the NS categories visualization of each indicator at the same time, identifying the divergences between them. In addition, the demarcation lines of the NS of each indicator allow comparing the NS classifications on a case-by-case basis. In the field of application of physical and aesthetic performance, the simultaneous use of BMI with FMI can detect skeletal muscle mass loss with the preservation of FM. This can result in serious impacts on the various performances, alerting to the need for planned interventions to adjust the Wt29. In the clinical field, there are cut-off points for FMI to diagnose metabolic syndrome: 6.97 kg/m2 for men and 11.86 km/m2 for women4. The sensitivity of FMI, to detect changes in body composition was evaluated during Wt control program for obese children30, The FMI compared to %FM and BMI showed greater sensitivity for revealing adiposity reduction in a shorter period. BMI detects rates of reduction of only 5% in adiposity in 33.3% of children, but the figures reached 63.3% using the %FM and up to 70.0% when the losses were based on the FMI. When comparing the meantime (days) to detect differences in adiposity, the result was similar between FMI (71) and BMI (70), but both were significantly shorter than the required for %FM (88)30. CONCLUSION Different forms of NS classification according to the FMI between the instruments (DXA, BIA, and ST) do not guarantee reliable agreement to use those interchangeably. We recommend in clinical practice or research use the NHANES NS classification proposal exclusively by DXA if body indexes are determined. The NS thresholds must be specifically determined for each sex and instrument, respecting population characteristics. Thus, the challenge remains for future NS classification proposals using clinically viable instruments (ST and BIA) with more detailed categories, capable of differentiating degrees of “obesity” or “thinness”. The lack of agreement between the instruments confirms that the principles are not the same for determining the absolute values of FMI, indicating that the instrument used in each situation does matter, even though there is some interdependence between the instruments capable of distinguishing FM from FFM. How to cite this article Borges FG, Abdalla PP, Alves TC, Venturini ACR, Santos AP, Tasinafo Júnior MF, Aznar S, Mota J, Machado DRL. Classification of nutritional status by fat mass index: does the measurement tool matter? Rev Bras Cineantropom Desempenho Hum 2022, 24:e84048. DOI: https://doi.org/10.1590/1980-0037.2022v24e84048 Funding This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - 33002029053P1. 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