Determinants of new onset cardiometabolic risk among normal weight children

Abstract

Objective To identify determinants for the development of "normal weight metabolically unhealthy" (NWMU) profiles among previously metabolically healthy normal weight children. Methods The QUALITY cohort comprises youth 8-10 years of age with a parental history of obesity (n = 630). Of these, normal weight children with no metabolic risk factors were identified and followed up 2 years later (n = 193). Children were classified as NWMU if they remained normal weight but developed at least one cardiometabolic risk factor. They were classified as normal weight metabolically healthy otherwise. Multivariable logistic regression models were used to identify whether adiposity (anthropometrics and DXA), lifestyle habits (physical activity, screen time, vegetables, and fruit-and sugar-sweetened beverages intake), fitness, and family history of cardiometabolic disease were associated with new onset NWMU. Results Of the 193 normal weight and metabolically healthy children at baseline, 45 (23%) became NWMU 2 years later (i.e., 48% had elevated HDL cholesterol, 13% had elevated triglycerides, and 4% had impaired fasting glucose). Changes in adiposity between baseline and follow-up were associated with an increased risk of NWMU for all adiposity measures examined (e.g., for ΔzBMI OR = 3.95; 95% CI: 1.76, 8.83). Similarly, a 2-year change in screen time was associated with incident NWMU status (OR = 1.24; 95% CI 1.04, 1.49). Conclusions Children who increase their adiposity levels as they enter puberty, despite remaining normal weight, are at risk of developing cardiometabolic risk factors. Studies examining long-term consequences of NWMU profiles in pediatrics are needed to determine whether changes in screening practice are warranted.

Dietary fibre intake in childhood or adolescence and subsequent health outcomes: A systematic review of prospective observational studies

“…One study of 8899 participants followed for 4 months linked higher fibre intake to a decreased frequency of hard stools 44 . Higher vegetable and fruit intake as a composite marker was associated with a decrease in school grades in 334 children, 45 but not becoming ‘normal‐weight metabolically unhealthy’ 46 . Two 47,48 of three studies with 2554 participants identified decreased incidence of metabolic syndrome with higher vegetable intake, with the third study providing a non‐significant odds ratio of 0.95 (95% CI 0.85 to 1.04) 49 .…”

“…Body weight [23][24][25][26][27][28][29]32,[69][70][71] Blood lipids 26,32 Glycaemia 32 Blood pressure 25,32,38 Metabolic syndrome 48,49 Bone health 41 Cognition 50,51 Vegetables and fruit 13 5286 Body weight 22,34,35,46,65,72 Blood lipids 33 Glycaemia 34 Blood pressure 36,73,74 Bone health 39,40 Cognition 45 Refined or whole grains 6 10 037 Body weight 26,27 Blood lipids 26,33 Glycaemia 67 Metabolic syndrome 49 Cognition 51 with a higher intake of fruit 50,51 ; however, these benefits were not observed with higher vegetable or wholegrain intakes. 51…”

Intraindividual coexistence of anthropometric undernutrition and “metabolic obesity” in Indian Children: A paradox that needs action

“…A 2-month life style modi cation trial in 12-16-year olds, comprising aerobic activity classes, diet education and behaviour modi cation, reduced body fat mass and improved lipid pro le and in ammation [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 tness, 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.…”

Cardiometabolic risk and its association with dietary diversity, activity patterns and the nutritional status of workers in tertiary educational institutions in Southwestern Nigeria

“…The relationships between WHtR, BMI, WC and WHR have been previously reported by various studies. [6,[8][9][10][11]20] Neck circumference as an indicator of cardiometabolic risk has also been reported, [21][22][23] but it is relatively recent and an emerging topic which should be better explored.…”