The main findings of this study are: 1) WC, WHtR and RFMp can be used to estimate truncal fat because the used models explain that their change is associated to the analyzed variables (Table 2), with this association reasonably higher in the whole sample adding valuable information to the BMI lesser estimative capacity of body fat content. 2) The estimators exhibit differences between boys and girls in all nutritional groups whereas BMI did not, being understood that the non-statistically significance, in this case is not a primary outcome for equality (20). Estimators mean values and uncertainty range in each nutritional group were obtained.
Derived risk of excessive trunk fat was described in mid 1900s in the adult (21) stressing the body shape of the individuals. These risks were proven later by means of the association with T2D (22, 23), hyperuricemia (24), elevation of free T₃ and MRI assessed abdominal fat distribution (25), with heart failure mid- range ejection fraction (26), or even with the vintage metabolic syndrome, this relationship was established by means of different waist circumference derived indexes (27). It is worth referring to the conclusions of Baton Rouge (28) after analyzing these varied equations, although in favor of the Waist circumference index, considered the indexes capacity for evaluating an individual person’s health risks. For gaining feasibility other waist-height indexes may be useful (29) and have already been tested in different geographic areas in children as cardio-metabolic risk factor (30). More specifically and due to the simplicity and reliability of measures, WHtR was chosen for assessing central adiposity successfully in children in a remote South Pacific archipelago (31). With the present-day conception of pediatric obesity risks it is worth considering that these elevated trunk markers are associated with the main biochemical markers for insulin resistance, inflammatory and metabolic abnormalities (32). The clinical approach of trunk fat has led to the description of a situation out of 17000 participants with BMI < 25 kg/m², but with excessive body fat (33). In children and youngsters, the estimation of trunk fat by by-proxy methods has been slow due to the varied charts for WC despite the publications of McCarthy (34, 35) facilitating Zs calculation. More recent publications (12, 36) included the international centile cut-offs, but nevertheless truncal assessment has not reached the accepted level of BMI in clinical grounds. WC is still considered as a reliable measure for assessing abdominal obesity (37) especially in countries with uneven care distribution, and in others, with better conditions its evaluation is the first or preliminary step for subsequent more precise tests (38)
Waist-to-height ratio. WHtR was proposed almost simultaneously in adults in 1995 in Japan by SD Hsieh and in the UK by M Ashwell (14) demonstrating that ratios > 0.5 were strongly associated with myocardial ischemia and metabolic risk factors (T2D). This association has also been described in children and adolescents elsewhere (39, 40). Other variants of this ratio (41) are not widely used. In the AVON longitudinal study (8) with nearly 3000 children followed over 8 years, ratios > 0.5 were associated in adolescents with raised fasting blood lipids, glucose, insulin and blood pressure for boys (OR 6.8; 95% CI 4.4–10.6) and for girls (OR 3.8; 95% CI 2.3–6.3) and also the stubbornness of this ratio once established, being highly specific versus BMI. Similar results had been shown after a systematic review and meta-analysis (42). WHtR, could be considered as a simple and reliable first step.
Relative fat mass pediatrics (RFMp). As mentioned, Woolcott and Bergman (15) derived an equation from adult height/ waist for estimation of whole-body fat percentage and later on for children and adolescents (16) always matched with DXA values. The novelty of this estimator is the sex consideration that decreases the rate of misclassification of relative fat mass with a more precise diagnosis of obesity/ adiposity in females. This equation has been tested in other parts of the world (43, 44) in adult populations but also in adolescents (45). In our study the initial correlation to BMI as the major standard criterion for overweight and obesity classification, was significant, clearly in the whole sample and Normal weight groups, but in Overweight and Obese ones the degree of correlation slightly decreased, in agreement with the next multiple regression comment. This fact is interesting because for BMI calculation waist circumference doesn’t intervene which would be more related to body or trunk fat than BMI. The normal distribution and density of RFMp in this study could give an adequate probability to upcoming data (Figure)
Multiple linear regression. The high aR² values are indicative of the appropriateness of the used estimators but as below 90% (predictive capacity), they should be considered as indicative of association mainly for female gender and for waist circumference and in a lesser extent to BMI Zs. Specific analyses of our nutritional statuses pointed out in All group, the ones with greater fat deposit (obese) to the lowest (underweight) an association between gender and RFMp, the regression B coefficients would imply that these girls have an increment of 3.36 units in their RFMp in respect to the boys, or in the case of WC Zs each unit of increment implies an increase of 2.97 in the RFMp. This associative trend has been very similar and regular in the Normal weight, Overweight and Obese groups. All of this would indicate a greater precision than BMI Zs, basically due to the fact that BMI does not consider waist circumference, which is also manifest through its lower coefficients (Table 2). In WHtR these associations remain at a lower level but keeping their p-values, therefore the simplicity of its calculation (just a cm ratio Waist/Height) and its well proved threshold of 0.5 make it an efficacious screening tool.
The Underweight group, (7.4% of all) deserve few words for its presence here, all these children were discreetly affected (BMI Zs -1.35 SD; 95% CI -1.46 to -1.24) and with a minor reduction of target height (-0.05 SD; 95% CI -0.23 to 0.25) in 20 instances where both progenitors were measured, suggesting a light undernutrition of familiar component, furthermore their social level could be hardly considered as of lower class. The inclusion in the study was motivated in order to assess the estimators’ behavior on the opposite spectrum side of overweight.
As regards sex, in all nutritional groups BMI did not show differences between genders conversely the estimators clearly did, as weight apart from fat comprises non-fat body components that veil adiposity. Furthermore, DXA studies revealed a greater proportion of fat in girls particularly when they come up to puberty (46, 47). This association with DXA was already studied by us (48) in 142 overweight and obese with an age (mean, 95%CI) of 11.5 (10.3–11.8) years, with no differences between boys and girls in age neither in BMI Zs; furthermore, in this study we found a relation and differences between %trunk fat and sex, 42.2 % (40.3–44.1) in boys versus 45.8 % (43.7–47.8) in girls, p = 0.001 and also for WC Zs of 1.9 (1.7–2.2) boys versus 2.4 (2.1–2.8) girls. p = 0.001; the regression analysis between WC and %trunk fat gave for WC a regression coefficient of β = 2.9 (P = 0.001). Thus, the need to separate sexes in pediatric obesity studies.
The prepuberal age of our girls w BMI%: relative body mass index; MLR: multiple linear regression; NG: nutritional groups; OB: obese; OW: overweight; RFMp; relative fat mass index pediatric; WC: waist circumference; WHtR: waist to height ratio.
ould justify the growing values of RFMp on the Normal, Overweight and Obese groups, again this occurs with BMI Z scores no different from boys. The median of RFMp is significantly higher in girls than in boys, sharing the same classificatory BMI range in all groups (whatever the BMI degrees were), this is probably in agreement to higher fat content in girls at this age (16) consequently giving an idea of the abdominal fat.
Blood pressure. Only a weak relation of diastolic blood pressure to RFMp (r = 0 .206, p < 0.001) appeared in the All group. Despite well-established policies for BP measurement in the clinical area of this Unit, results are not as consistent as other clinical parameters, and probably the doubts about BP screening (49, 50) not only apply to these data but lead to reconsidering these policies.
Present techniques allow the measurement of abdominal fat separately from subcutaneous fat in children (51, 52), but these could not be the available method for better evaluation of the growing heavier section of double burden malnutrition in Low- and Middle-Income Countries (LMIC), so it is natural to look for by-proxy estimators. Further, they are useful even where DXA is available but cannot be justified in every follow-up visit. Therefore, and after firm association of estimators based on waist circumferences with trunk fat, we recommend the studied estimators to be used because of their safety, simplicity (53) and longtime known low variability of (54) and good correlation with CT and MRI (55) when facing this silent and metabolically unhealthy fat accumulation (3, 57) and furthermore for gaining precision as considering gender (56) and as in the adult, if more than one is used (58)
Limitations. Having a series of accurate standardized anthropometric data, we tried to check eventual advantages of WHtR and RFMp, therefore without a specific design for child obesity studies (59). As females were predominant (286/472, 60.6%) the subsequent higher proportion in the study groups could be a confounding consequence, nor was it possible to consider the validation concept (60). In this way another weak point is the lack of precise comparative pattern as could have been DXA as just mentioned, but in this case the aim was implementing diagnosis purposes through anthropometry for nutritional deviations, some of them not requiring more complex technics with side effects.
Conclusions. WHtR is a very simple and reliable method that does not need reference growth centile charts, consequently it should be the first step screening, while RFMp gives an idea of the body (and trunk) fat content in both genders. Both could warn us of cardio metabolic consequences already present or in the near future specially if they increase in the follow-up. At present BMI Z score is considered the widest marker for overweight and obesity (while BMI percentage is better understood by the family), hence and in order to increase clinical accuracy both estimators should be added in routine anthropometric measurements in primary health care and in specific surveys.