The paradoxical contrast of metabolic obesity biomarker(s) in over half the surveyed children with conventional anthropometric diagnoses of undernutrition is intriguing, but probably an accurate reflection of the current reality in India. The data emanate from a nationally representative survey with meticulous attention to quality control procedures, especially for anthropometry and biomarkers [18]. In the earlier phase of nutrition transition, almost 15 years ago, similar findings were documented in a lower proportion (9%) of thin children and adolescents in Delhi schools [17]. The MONW phenotype, defined as ≥1 metabolic obesity biomarker and BMI-for-age between -2Z and +1Z of WHO reference, occurred in 56% of normal-weight participants. This prevalence resonates with similar reports from national surveys in Iran (41% and 55% dyslipidemia in 2010 and 2015, respectively) and China (63% in 2002 among 12-18 years adolescents), urban schools in Chennai, India (65% in 2006 among 12-19 years adolescents), and 10 cities from 9 European countries (70% in 2006-2007 among adolescents), but is substantially higher than a national survey in Germany (3-13% individual lipid abnormalities in 2003-2006 among 0-18 years old) and a regional population-survey in Denmark (4.3% elevated fasting glucose in 2010-2015) [14-16,26-29]. However, these studies did not specifically report on the paradoxical co-existence of anthropometric undernutrition (thinness or stunting) and metabolic obesity. Progressively more metabolic abnormalities (0, 1, 2, or 3) are associated with dose-dependent increases in the risk of cardiovascular disease in normal-weight adults [13]. Clustering of two and all three core biochemical abnormalities (2-MetS and 3-MetS), commonly used for defining metabolic syndrome [25], occurred in 13% and 2% of thin and normal-weight participants, respectively. We could not locate any specific data for comparison; however, these figures are compatible with similar clustering observed in 10%-19% and 1%-2% of normal-weight adolescents from Asia, albeit with the use of additional criteria of hypertension and abdominal obesity [15,16,26].
The greater prevalence of metabolic obesity biomarkers at higher BMI categories and ages, and their relative preponderance patterning conforms with the current understanding and guidelines [14-16,20,21,26-29]. Our diagnosis of abnormal biomarkers was aligned with the internationally recommended cut-offs for identification of 5-19-year-old children with prediabetes or diabetes, and at risk of developing future cardiovascular disease [20,21]. Although the utility of these cut-offs for accurately predicting the risk of adult disease could be debated, the diagnosis of specific type(s) of existing metabolic obesity (metabolically unhealthy or metabolic dysfunction/overnutrition or cardiometabolic risk factors) cannot be disputed, particularly when the recommended [20,21] core interventions, such as dietary restrictions and active lifestyle, are directed towards inducing a negative energy balance [30]. The evaluated biomarkers are probably not reflective of short-term changes (few days) in individual metabolic profiles, especially HbA1c, which informs the glycosylation status over 3-4 months. Further, the observed prevalence of abnormal biomarkers cannot be solely attributed to rare inherited metabolic disorders like familial hypercholesterolemia and hypertriglyceridemia.
The primary cut-offs used by us underestimate the proportion of children warranting active lifestyle interventions to induce an appropriate energy balance and body composition. Considering the recommended ‘borderline abnormal’ lipid cut-offs for initiating action [20], nearly half (42%-52%) of anthropometrically undernourished (mild/moderate or greater) participants had HDL or triglyceride perturbations, while ~30% had clustering of two core metabolic syndrome components. Conversely, a mere 1%-4% of such children had either hypoalbuminemia or hypoglycemia, the traditionally used biomarkers for clinically relevant, severe and chronic undernutrition. Thus, an overwhelming majority of these children exhibited biomarkers associated with obesity instead of clinically relevant macronutrient inadequacy. These data question the usual narrative of equating undersize in children with undernutrition or hunger, instead of being defined as a broader surrogate of developmental deprivation that may also include energy and nutrient inadequacy [31].
Similarly, apart from the relatively rare, genetic and primary endocrinal conditions, inappropriate dietary intakes and low physical activity levels may now be more important determinants of these metabolic abnormalities. Reviews on the effects of overfeeding [32] and calorie restriction [33] in humans confirm the etiological role of excess energy intake. A moderate calorie restriction (12%) over two years in healthy normal-weight, young and middle-aged adults, improved multiple cardiometabolic risk factors well below the conventional risk thresholds [34]. Substantial evidence confirms the crucial role of physical activity and cardiorespiratory fitness in improving lipid and glucose homeostasis, both in adults and children; consequently, these life style interventions form the core of primary preventive recommendations from various professional organizations [20,35-38]. There are scant data specifically investigating the role of lifestyle interventions in MONW subjects. A recent study in Asian adults, after a diet-induced modest (~5%) weight loss, documented improvements in body composition, lipid profile and insulin sensitivity [39]. A 2-month life style modification trial in 12-16-year olds, comprising aerobic activity classes, diet education and behaviour modification, reduced body fat mass and improved lipid profile and inflammation [40]. Postulated mechanisms from observational evidence in adults and children also include greater relative fat accumulation, especially in the visceral adipose tissue, liver and upper body, inferior aerobic fitness, lower skeletal muscle mass and strength, increased screen time and diet quality - lower fruits and vegetables - and higher fructose and glucose intakes [13,41,42]. Mechanisms underlying a similar phenomenon in thin (underweight) subjects have not been investigated.
The aforementioned evidence thus justifies the term “metabolic obesity” for describing unambiguous biochemical aberrations; this will unequivocally alert the policy stakeholders and public about the conflicting nutritional signals originating from the thin, short and normal-weight phenotypes. We suggest restricting the terms “metabolic dysfunction” and “metabolically unhealthy” [13] for borderline biochemical abnormalities. Further, we propose the nomenclature “metabolically obese undersized” (MOU) for those who are thin or short.
India is currently undergoing a rapid nutrition transition with attendant escalation of overnutrition related NCDs [43]. Within this backdrop, we hypothesize that at the individual level, thin or stunted or normal-weight children with co-existent metabolic obesity are in positive energy balance. Whether this is a consequence of overfeeding and/or reduced physical activity, among other factors, needs investigation. Lower skeletal muscle mass and strength is likely to be an important mediator or moderator of this phenomenon. Infants, children and adolescents living in India have been characterised by a muscle-thin but adipose body composition compared with those in other countries [44,45]. The National Sample Survey Office [46] report of dietary consumption patterns in 100,547 households across India, shows that while the carbohydrate intake is high in general, the poor consume an even greater proportion of their energy intake as carbohydrates including free sugars (73% vs 60% in the lowest and highest socioeconomic status quintiles, respectively). However, the proportion of fat intake is greater in wealthier households (15% vs 27%, respectively). Rural-urban comparisons show a slightly higher carbohydrate consumption by about 2-3% in rural settings across all quintiles. High carbohydrate intakes are associated with high de novo lipogenesis [47], and these dietary consumption patterns are consonant with higher HbA1c, fasting glucose and triglyceride abnormalities in the rural setting and the poor, and the converse association for serum cholesterol [32,48].
The following limitations merit consideration. Information on all evaluated biomarkers was not available for every recruited participant; however, this did not bias the prevalence estimates (data not presented). Other important indicators of metabolic obesity (insulin sensitivity, inflammation, blood pressure) and potential explanatory factors (physical activity, body composition and muscle-strength) were either not evaluated in the survey or could not be analysed, pending the release of relevant data.
Urgent research is required on (i) Biological and mechanistic characterization of the MONW and MOU phenotypes, including an evaluation of hepatic and visceral fat distribution. (ii) Optimal public health interventions to address this intraindividual double burden of malnutrition, including focus on dietary quality and exercise plus resistance training that improves body composition without substantial weight loss. (iii) The burden of this phenotype in other geographical regions and its adult health and human capital consequences. (iv) Determining if similar phenotypes exist in the under-five age group and women planning pregnancies. In this eventuality, it is crucial to evaluate and mitigate the potential risks from consuming energy-dense therapeutic foods in wasted children [49] and dietary supplementation for pregnancies in what are believed to be undernourished populations [50].
The unexpected huge burden of metabolic obesity in Indian children, whether normal or undersized, argues strongly for commensurate investments to address overnutrition along with undernutrition. When this occurs in undersized children, considerable reflection is required on how such children should be fed, since targeting a simple negative energy balance should not be the sine qua non of the remedy. Focusing solely on anthropometry to identify at-risk (overweight/obese) individuals to prevent adult NCDs will miss 90% of those harbouring invisible metabolic threats. Lead national and global stakeholders should therefore urgently determine the optimal strategy to include these phenotypes in programmatic interventions and decide whether, in the current era, nutritional status should be defined through additional, logistically feasible and reliable biomarker(s) instead of anthropometry alone. This is also desirable from an equity and ethical perspective since poor, illiterate and vulnerable populations generally have undersized or normal-weight children. The continued reliance on undersize metrics sans biomarker(s), to quantify ‘hunger’ and occasionally ‘near starvation’ [51,52], contributes to misdirected stigma and the response thereof, primarily an enthusiastic but often blunt approach of food or nutrient(s) supplementation, with a sole focus on the ‘left-hand’ side of the distribution.
In conclusion, there is a paradoxical contrast of metabolic obesity biomarker(s) in over half of anthropometrically undernourished and normal-weight children and adolescents in India. Almost one-third had clustering of two metabolic dysfunctions warranting immediate, active and appropriate life-style interventions, particularly in the undersized. There is a crucial need for commensurate investments to address overnutrition along with undernutrition, biological characterization of these phenotypes, and consideration for defining nutritional status through additional reliable biomarker(s) instead of anthropometry alone.