Comparative Study of Body Composition, Micronutrient Status and Hormonal Profiles in Undernourished Children With Feeding Difficulties

Comparative Study of Body Composition, Micronutrient Status and Hormonal Profiles in Undernourished Children With Feeding Difficulties | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Comparative Study of Body Composition, Micronutrient Status and Hormonal Profiles in Undernourished Children With Feeding Difficulties Orapa Suteerojntrakool, Patcharapa Thaweekul, Suchaorn Saengnipanthkul, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6641861/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Malnutrition remains a global health concern, with feeding difficulties contributing to its development. This study is a cross-sectional analysis of baseline data from the MARVEL randomized controlled trial, which assessed the prevalence of feeding difficulties and compared nutritional and biological outcomes in children with and without feeding difficulties. 159 children aged 1–6 years with weight-for-height z-score between − 1SD to -3SD without diseases or medications affecting growth or appetite were recruited. Feeding difficulties were identified using the Montreal Children's Hospital Feeding Scale questionnaire. Dietary intake was evaluated via 24-hour dietary recall. Body composition was assessed using bioelectrical impedance analysis (aged ≥ 3 years). CBC, iron status, zinc,25(OH)D, IGF-1, IGFBP-3, and appetite hormones (ghrelin, leptin, peptideYY, insulin) were analysed. Feeding difficulties were present in 68% of the children. No significant differences in dietary intake, anthropometry, micronutrient status, or appetite hormones were found between groups. However, children with feeding difficulties had higher lean and skeletal muscle mass, significantly higher IGFBP-3, and a trend toward lower ghrelin. ID (Iron deficiency, transferrin saturation < 15%), ID anemia, and vitamin D insufficiency (25(OH)D < 20 ng/mL) were found in 18%, 4.7%, and 11% of children, respectively. Findings highlight the need for integrated nutritional and behavioral care in non-organic malnutrition. Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors malnutrition feeding difficulties body composition growth hormones appetite hormones Figures Figure 1 Figure 2 Introduction Malnutrition has remained a major global health issue, especially among children under the age of five. The World Health Organization (WHO) reports that approximately 49 million children in this age group experience stunting, while around 45 million suffer from wasting 1 . Undernutrition is associated with nearly 50% of all deaths in children under five 1 . Beyond its immediate health risks, childhood malnutrition has far-reaching and long-term developmental, medical, social, and economic impacts, not only for the affected children and their families, but also for the broader communities and nations 2 , 3 . Despite widespread global initiatives targeting nutritional improvement, comprehensive insights into feeding behavior patterns and their association with nutritional status remain insufficient. Non-organic feeding difficulties, which occur in the absence of identifiable medical or anatomical causes, are shaped by a complex interplay of biological, psychological, and environmental factors 4 , 5 . Psychosocial influences, including child temperament, parental anxiety, and negative caregiver-child interactions, can lead to maladaptive feeding behaviors such as food refusal and selective eating 5 , 6 . Inconsistent or non-responsive feeding practices may reinforce these patterns, creating a cycle of stress and inadequate intake 5 . Among children who were malnourished or at risk of malnutrition, non-organic feeding difficulties were commonly observed 7 . These difficulties can significantly reduce energy and nutrient intake, contributing to growth faltering, suboptimal body composition and micronutrient deficiencies. These nutritional deficits were often accompanied by alterations in growth and appetite-regulating hormones such as IGF-1, ghrelin and leptin 8 – 10 . Several studies have established that children with feeding difficulties were at a significantly higher risk of malnutrition, with an increased prevalence of both moderate and severe forms 11 – 13 . For instance, Blössner and de Onis reported that feeding problems were more frequently observed in children with moderate to severe malnutrition, commonly manifested as stunting and wasting 11 . Although these studies highlighted a clear association between feeding difficulties and poor nutritional status, there was limited evidence exploring the broader nutritional and physiological implications. Specifically, a few studies have examined differences in body composition, feeding behavior, energy and nutrient intake, micronutrient status, or growth and appetite-related hormones among these undernourished children 14 – 16 . These factors were essential to understand the underlying physiology of malnourished children and can lead to interventions that address both behavioral and nutritional dimensions of care. Therefore, this study aimed to investigate the prevalence of feeding difficulties among children who were malnourished or at risk of malnutrition. In addition, it compared the differences in dietary intake, body composition, feeding behaviors, micronutrient status, as well as growth and appetite-related hormones between those with and without feeding difficulties. Findings from this study are expected to enhance our understanding of the physiological and behavioral profiles of malnourished children and contribute to the formulation of more precise and effective nutritional strategies. Results Table 1 presented the clinical characteristics of the study participants. A total of 159 participants were included in the analysis. The mean age was 3.5 years (95% CI: 3.3–3.8), and 58% of the participants were male. Approximately 80% of the participants came from middle- to high-income families, and 60% had their mothers as the primary caregivers. Based on the MCH-FS criteria, 68.6% of the study population were identified as having feeding difficulties, classified as mild (n = 26), moderate (n = 21), or severe (n = 62), while the remaining participants (n = 50) were classified as having no feeding difficulties. Comparison between children with and without feeding difficulties revealed no significant differences in age, sex, birthweight, early life feeding practices, primary caregiver, socioeconomic status. However, the reported appetite score was significantly lower in children with feeding difficulties. Table 1 Clinical characteristics of the study participants (n = 159) 1 Total (n = 159) With feeding difficulties 2 (n = 109) Without feeding difficulties 2 (n = 50) p-value 3 Age (years) 3.5 (3.3–3.8) 3.6 (3.3–3.9) 3.3 (2.9–3.8) 0.424 Male, n (%) 93 (58.5) 64 (58.7) 29 (58) 0.932 Birthweight (kg) 3.02 (2.97–3.06) 3.04 (2.98–3.10) 2.96 (2.88–3.04) 0.115 Feeding type during the first six months of life, n (%) 0.622 • predominant breastfeeding 121 (76.1) 81 (74.3) 40 (80) • predominant formula feeding 8 (5) 7 (6.4) 1 (2) • mixed breastfeeding and formula feeding 30 (18.9) 21 (19.3) 9 (18) Main caregiver, n (%) 0.325 • mothers 101 (63.5) 65 (59.6) 36 (72) • fathers 11 (6.9) 8 (7.3) 3 (6) • grandfathers/grandmothers 27 (17) 19 (17.4) 8 (16) • others 4 20 (12.6) 17 (15.6) 3 (6) Family income (baht/month), n (%) 0.151 • 15,000–30,000 25 (15.7) 20 (18.4) 5 (10) • > 30,000–50,000 53 (33.3) 36 (33) 17 (34) • > 50,000-100,000 51 (32.1) 35 (32.1) 16 (32) • > 100,000 23 (14.5) 16 (14.7) 7 (14) Appetite score 5 5.14 (4.82–5.46) 4.38 (4.03–4.72) 6.8 (6.33–7.27) < 0.001 1 Values were presented as mean (95%CI) for continuous variables while categorical variables were expressed as n (%). 2 Feeding difficulties were assessed using Montreal Children’s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties 3 Differences in mean and proportion between children with and without feeding difficulties were tested by independent sample t-test and Chi-square test, respectively. 4 Others included children with more than one primary caregiver (e.g., mother and father, grandmother and mother), as well as those cared for by nursery staff or an aunt. 5 Appetite was assessed using a visual analogue scale ranging from 1, indicating very poor appetite, to 10, indicating excellent appetite. Dietary intakes Figure 1 Comparison of daily energy and nutrient intakes between children with and without feeding difficulties, expressed as the mean percentage of intake relative to the Thai Dietary Reference Intakes (DRIs). Grey, orange, and dark green bars represent the mean percentage of intake among all participants (n = 159), children with feeding difficulties (n = 109), and children without feeding difficulties (n = 50), respectively. The red dashed line indicates 100% of the Thai DRIs. There were no statistically significant differences in dietary intakes between children with and without feeding difficulties. Anthropometry and body composition Table 2 summarized the growth parameters of the study population. No significant differences were observed in weight, height, BMI, or their corresponding z-scores between children with and without feeding difficulties. Children with feeding difficulties had higher soft lean mass, fat-free mass, and skeletal muscle mass compared to those without feeding difficulties, while fat mass did not differ between the groups. However, these differences disappeared after adjusting for differences in height using fat-free mass index (fat-free mass divided by height 2 , kg/m 2 ) Table 2 Comparison of anthropometry and body composition between children with and without feeding difficulties 1 Anthropometry Total With feeding difficulties 2 , 3 Without feeding difficulties 2 , 3 p-value Simple anthropometry Weight (kg) 12.34 (11.86–12.83) 12.52 (11.9–13.14) 11.95 (11.18–12.73) 0.288 Height (cm) 94.44 (92.38–96.5) 95.2 (92.61–97.79) 92.78 (89.38–96.18) 0.282 BMI (kg/m 2 ) 13.69 (13.57–13.81) 13.65 (13.5–13.79) 13.79 (13.57–14.01) 0.285 WFA z-score 4 -1.62 (-1.73 to-1.52) -1.62 (-1.76 to -1.48) -1.63 (-1.8 to -1.47) 0.882 HFA z-score 4 -0.92 (-1.07 to -0.77) -0.88 (-1.07 to -0.68) -1.01 (-1.25 to -0.78) 0.411 WFH z-score 4 -1.65 (-1.74 to-1.56) -1.69 (-1.8 to -1.58) -1.57 (-1.72 to -1.42) 0.213 BMI z-score 4 -1.59 (-1.68 to-1.49) -1.62 (-1.74 to -1.51) -1.51 (-1.67 to -1.35) 0.273 Body composition Soft lean mass (kg) 11.98 (11.61–12.35) 12.32 (11.83–12.8) 11.25 (10.82–11.68) 0.007 Skeletal muscle mass (kg) 5.5 (5.27–5.74) 5.71 (5.4–6.02) 5.05 (4.78–5.33) 0.008 Fat free mass (kg) 12.69 (12.28–13.09) 13.04 (12.51–13.57) 11.93 (11.44–12.42) 0.010 Fat-free mass index (kg/m 2 ) 5 11.58 (11.43–11.73) 11.58 (11.42–11.73) 11.58 (11.22–11.94) 0.996 Fat mass (kg) 1.52 (1.32–1.71) 1.51 (1.31–1.71) 1.54 (1.08–1.99) 0.880 Fat mass index (kg/m 2 ) 5 1.34 (1.2–1.48) 1.32 (1.17–1.47) 1.39 (1.07–1.7) 0.645 Percent fat mass 10.31 (9.26–11.36) 10.15 (9.02–11.28) 10.66 (8.25–13.06) 0.658 Visceral fat area (cm 2 ) 19.24 (18.22–20.26) 19.2 (18.1–20.3) 19.35 (16.9–21.79) 0.894 Abbreviation: BMI, body mass index; HFA, height for age; WFA, weight for age; WFH, weight for height. 1 Values were presented as mean (95%CI). Differences in mean were tested by independent sample t-test 2 Feeding difficulties were assessed using Montreal Children’s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties 3 Weight and height were assessed in 109 children with feeding difficulties and 50 children without feeding difficulties. Body composition via bioelectrical impedance analysis was assessed in those aged 3 years old and above, 56 children with and 26 children without feeding difficulties. 4 z-scores for WFA, WFH and HFA were derived using the WHO Anthro Survey Analyzer 5 Fat-free mass index and fat mass index were calculated by dividing fat-free mass and fat mass, respectively, by height squared. Feeding behavior assessed by CEBQ Overall, undernourished children in this study had slightly low scores in food approach subscales, including food responsiveness, emotional overeating, and desire to drink [mean (95%CI): food responsive 2.31 (2.19–2.42); emotional overeating 1.56 (1.48–1.64); desire to drink 2.42 (2.23–2.61)] ( data not shown ). Figure 2 demonstrated differences in feeding behavior subscales assessed by CEBQ between children with and without feeding difficulties. Children with feeding difficulties had significantly higher scores in satiety responsiveness, slowness in eating, and food fussiness subscales, and lower scores in food responsiveness and enjoyment of food compared to those without feeding difficulties. There was no significant difference in desire to drink, emotional overeating, nor emotional undereating subscales between the 2 groups. Micronutrients, growth and appetite hormones Table 3 showed the comparison of micronutrient status between children with and without feeding difficulties. Overall, iron deficiency was observed in approximately 18% of participants, while anemia was present in about 15%. Notably, only 4.7% of the children exhibited anemia attributable to iron deficiency. Vitamin D insufficiency was identified in approximately 11% of the study population, and no cases of zinc deficiency were detected. Further analysis showed no significant difference in the status of iron, vitamin D, or zinc between children with and without feeding difficulties in this undernourished population. Table 3 Comparison of micronutrient status between children with and without feeding difficulties 1 Total (n = 159) With feeding difficulties 2 (n = 109) Without feeding difficulties 2 (n = 50) p-value Laboratory parameters Hemoglobin (g/dL) 12 (11.8–12.2) 12.1 (11.9–12.3) 11.8 (11.5–12.2) 0.224 MCV (fL) 73.6 (72.3–74.9) 73.8 (72.3–75.3) 73 (70.4–75.6) 0.572 RDW (%) 14.7 (14.2–15.1) 14.6 (14-15.1) 14.8 (14.2–15.5) 0.604 Serum iron (mcg/dL) 78.5 (73.5–83.5) 79.1 (73.2–84.9) 77.2 (67.4–87) 0.735 TIBC (mcg/dL) 326.9 (320.3-333.5) 326.9 (319-334.8) 327 (314.7-339.4) 0.987 Transferrin saturation (%) 3 24.4 (22.7–26) 24.6 (22.6–26.5) 23.9 (20.9–26.9) 0.715 Zinc (mcg/dL) 91.3 (89-93.7) 92.1 (89.3–95) 89.5 (85.3–93.7) 0.318 25(OH)D (ng/mL) 29.8 (28.4–31.3) 29.8 (28-31.5) 30.1 (27.4–32.7) 0.853 Micronutrient status, n (%) 4 Iron deficiency 27 (17.8) 17 (16.2) 10 (21.3) 0.448 Anemia 22 (14.7) 13 (12.6) 9 (19.2) 0.295 Iron deficiency anemia 7 (4.7) 4 (3.9) 3 (6.5) 0.490 Vitamin D insufficiency 17 (11.3) 14 (13.3) 3 (6.5) 0.223 Abbreviation: MCV, mean corpuscular volume; RDW, red cell distribution width; TIBC, Total iron binding capacity 1 Values were presented as mean (95%CI) for continuous variables while categorical variables were expressed as n (%). Differences in mean and proportion were tested by independent sample t-test and Chi-square test, respectively. 2 Feeding difficulties were assessed using Montreal Children’s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties. 3 Transferrin saturation (%) was calculated as serum iron divided by TIBC. 4 Iron deficiency: transferrin saturation < 15%; Anemia: hemoglobin < 11 g/dL for children < 5 years, or < 11.5 g/dL for ≥ 5 years; Iron deficiency anemia: presence of both anemia and iron deficiency; Vitamin D insufficiency: 25(OH)D < 20 ng/mL In terms of hormonal profiles, the levels of IGF-1 and IGF BP3 were within the normal range of age and sex. However, children with feeding difficulties exhibited significantly higher levels of IGF BP-3, and a non-significant trend toward lower ghrelin levels compared to their peers. Levels of other hormones, including IGF-1, leptin, PYY, and insulin, did not differ significantly between the two groups (Table 4 ). There were no significant correlations between any feeding difficulties scores according to MCH-FS and any micronutrients and hormonal levels ( data not shown ) Table 4 Comparison of growth and appetite hormones between children with and without feeding difficulties 1 Total (n = 159) With feeding difficulties 2 (n = 109) Without feeding difficulties 2 (n = 50) p-value Growth hormone derivatives IGF-1 (ng/mL) 63.33 (57.98–68.69) 65.61 (58.84–72.38) 58.25 (49.65–66.85) 0.210 IGF BP-3 (mg/L) 2.92 (2.77–3.06) 3.04 (2.85–3.23) 2.64 (2.46–2.81) 0.010 Appetite hormones Ghrelin (pg/mL) 292.4 (267.32-317.48) 277.24 (248.07-306.42) 326.18 (277.67-374.68) 0.075 Leptin (pg/mL) 239.67 (182.92-296.42) 220.98 (155.14-286.82) 284.34 (170.29-398.39) 0.316 Peptide YY (pg/mL) 179.16 (164.85-193.48) 178.45 (163.31-193.59) 180.74 (148.29-213.19) 0.884 Insulin (pg/mL) 502.45 (422.17-582.73) 510.26 (412.83–607.7) 483.87 (337.26-630.47) 0.768 Abbreviation: IGF BP-3, Insulin-like growth factor-binding protein 3; IGF-1, insulin-like growth factor-1; 1 Values were presented as mean (95%CI) for continuous variables while categorical variables were expressed as n (%). Differences in mean and proportion were tested by independent sample t-test and Chi-square test, respectively. 2 Feeding difficulties were assessed using Montreal Children’s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties. Discussion Malnutrition-at-risk and malnourished children continue to represent a significant global health concern. In the absence of identifiable organic causes, malnutrition in this population is often associated with behavioral factors, particularly feeding difficulties, which can adversely impact nutritional intake and physiological regulation. This study found that the prevalence of feeding difficulties was very high at 68.6% of children classified as malnutrition-at-risk or malnourished who did not have underlying medical conditions known to affect growth. The findings also suggested that in children without significant underlying medical conditions, disordered eating behaviors may contribute to alterations in growth and appetite-regulating hormones. This high prevalence of feeding difficulties in this population underscored the substantial role of feeding behavior in the etiology of malnutrition in children without significant organic pathology. Feeding difficulties, including food refusal, selective eating, and poor appetite, can contribute to inadequate nutrient intake, ultimately impairing growth and nutritional status. Previous studies have similarly demonstrated an association between feeding difficulties and an increased risk of undernutrition. For instance, a study in Malaysia reported that children under 5 years old with feeding difficulties had significantly higher odds of being wasted (AOR: 1.48) and of experiencing at least one form of undernutrition (AOR: 1.45) compared to those without feeding problems 13 . Similarly, Dubios L et al revealed that children identified as picky eaters were twice as likely to be underweight at 4.5 years of age compared to those who were never reported as picky eaters 12 . These results highlighted the need for early detection and tailored interventions for feeding difficulties as a critical component in the prevention and management of childhood malnutrition. In our study, we found that malnourished children consumed relatively high protein intakes when compared to the Thai DRIs. This observation aligns with findings from previous research examining dietary patterns among Thai children. The Southeast Asian Nutrition Survey II (SEANUTS II) found that the protein intake of most Thai children was often adequate or exceeded recommendations 17 . Similarly, the Thai National Health Examination Survey IV reported that protein intake among preschool children, particularly those aged 1–3 years, was approximately 1.4 to 2.1 times higher than the Thai DRIs 18 . These findings imply a consistent pattern in which Thai children, including those at risk of malnutrition, tend to consume diets low in total energy yet relatively high in protein. This imbalance may result from feeding practices that emphasize protein-rich foods, such as milk and animal products, while neglecting energy-dense sources like fats and carbohydrates. The issue appeared to be more pronounced among children with feeding difficulties, who may experience reduced appetite, oral-motor dysfunction, or behavioral challenges that further limit dietary variety and intake volume 19 , 20 . Such a dietary pattern can impair catch-up growth, as protein would be diverted to meet energy demands rather than being used for tissue synthesis when energy intake was insufficient 21 . Although there were no significant differences in basic anthropometric measurements between children with and without feeding difficulties among malnutrition-at-risk and malnourished children, those with feeding difficulties were found to have higher lean body mass compared to those without. This finding contrasted with previous studies. For example, Dahl and Sundelin reported that children with feeding refusal exhibited significantly lower weight and height gain compared to those without such difficulties 22 . In addition, a recent large cross-sectional study from Saudi Arabia demonstrated that underweight status was significantly more prevalent among picky eaters compared to non-picky eaters. Moreover, the picky eaters had significantly lower skeletal muscle mass than their non-picky counterparts 23 . These discrepancies may be attributed to differences in study populations, as our study specifically focused on children who were malnourished or at risk of malnutrition, whereas previous studies emphasized feeding behavior problems in general pediatric population. Furthermore, the definitions and assessment methods for feeding difficulties varied across studies. In our study, a validated questionnaire was used to classify children with and without feeding difficulties, providing a more robust and standardized approach compared to the earlier studies, which relied on brief screening questions. The higher skeletal muscle mass observed among children with feeding difficulties in our study may be explained by the possibility that these children received more targeted nutritional support or feeding interventions, such as oral nutritional supplements or caregiver-directed high-protein diets, which could contribute to improved lean mass despite ongoing feeding challenges. However, after adjusting by height using fat-free mass index, this difference disappeared, suggesting that this finding may partly resulted from the height difference in the subgroup who had their body composition assessed. In addition, this finding should be interpreted with caution, as only half of the study population underwent body composition assessment by BIA, potentially limiting the statistical power of the analysis. Further studies should be conducted in a larger population using more precise and validated methods, such as dual-energy X-ray absorptiometry (DEXA), to better assess body composition and bone health in these children. Regarding feeding behavior, children with feeding difficulties showed higher scores on food avoidance subscales, such as satiety responsiveness, slowness in eating, and food fussiness, and lower scores on food approach subscales, including food responsiveness and enjoyment of food, compared to those without feeding difficulties. These results were consistent with earlier studies suggesting that children with feeding difficulties frequently exhibited diminished appetite and increased sensitivity to internal satiety cues, which may lead to decreased food intake. For example, Wardle et al. reported that picky eaters tended to have higher scores in satiety responsiveness and food fussiness 24 . Similarly, Charoensriwattanakul et al. found that children who scored lower on enjoyment of food and higher on slowness in eating and food fussiness subscales had significantly higher t-scores on the MCH-FS, indicating more likelihood of having feeding difficulties 25 . However, there were no significant differences in the "desire to drink," "emotional undereating," and "emotional overeating" subscales between children with and without feeding difficulties. These findings hinted that interventions targeting feeding difficulties in undernourished children may need to focus more on behavioral traits such as food fussiness, satiety responsiveness, and sensory sensitivity rather than emotional or beverage-related eating patterns. Nutritional strategies, such as the use of ONS in a liquid form, may therefore be particularly beneficial for improving intake in this group, as they provide a concentrated source of energy and nutrients without relying on changes in emotionally driven eating behaviors. Our study also revealed that iron deficiency and vitamin D insufficiency were more prevalent among toddlers and preschool-aged children with malnutrition. Specifically, the prevalence of iron deficiency, iron deficiency anemia, and vitamin D insufficiency in our cohort was 17.8%, 4.7%, and 11.3%, respectively. The rates of iron deficiency and iron deficiency anemia observed in our study are consistent with findings from the Southeast Asian Nutrition Surveys II (SEANUTS II) 17 . However, the prevalence of vitamin D insufficiency in our sample was notably higher, more than double, compared to the SEANUTS II report (11.3% vs. 5.5%) 17 . This disparity may indicate that children with malnutrition are at greater risk of vitamin D insufficiency. However, our findings may have been influenced by the demographic characteristics of our study population, which consisted of malnourished children living in urban settings. Limited outdoor activity and reduced sun exposure in urban environments could contribute to lower endogenous vitamin D synthesis, thereby increasing the risk of insufficiency in this group. Additionally, our study assessed growth and appetite hormone profiles in malnourished children, comparing those with and without feeding difficulties. Although no statistically significant differences were found in appetite-regulating hormones between the groups, ghrelin levels tended to be lower in children with feeding difficulties. Previous studies have shown that ghrelin, an orexigenic hormone, is elevated during states of malnutrition or fasting 26 . The observed lower ghrelin levels in children with feeding difficulties may reflect a blunted hunger signaling response, potentially contributing to their poor oral intake. This physiological finding aligned with the subjective appetite assessment, as children with feeding difficulties also reported lower appetite scores on a visual analogue scale. These results suggested that in some undernourished children, feeding difficulties may be associated with alterations in the hormonal regulation of appetite. Recognizing this potential hormonal dysregulation was important, as it may affect the responsiveness to conventional nutritional counselling. Moreover, we found that IGF-1 levels were slightly lower in malnourished children but there was no difference between children with and without feeding difficulties. However, IGF BP-3 was significantly higher in children with feeding difficulties, suggesting altered growth hormone axis regulation in this subgroup. These findings partially aligned with previous studies which reported reduced IGF-1 and IGF BP-3 levels in malnourished children due to impaired growth hormone action in the context of protein-energy malnutrition 14 , 27 . However, the elevated IGF BP-3 observed in children with feeding difficulties in our study may reflect a compensatory mechanism or a stress-related physiological response, which has been less commonly reported and merits further investigation. A key strength of this study was its comprehensive assessment of undernourished children, including detailed evaluations of dietary intake, anthropometry, body composition, feeding behavior, micronutrient status, and growth and appetite hormones. Furthermore, the study compared children with and without feeding difficulties, using validated caregiver-reported questionnaires. This allowed for a more nuanced understanding of the physiological and behavioral characteristics of children with non-organic malnutrition, providing valuable insights into how feeding challenges may influence nutritional and hormonal profiles. Nevertheless, several limitations should be noted. Firstly, the study population was recruited mainly from middle-to-high income families in Thailand, which may limit the generalizability of the findings to other socio-demographic contexts. Secondly, the BIA tool used to assess body composition was validated only for children aged 3 years and older, potentially affecting the study’s power and representation of younger children. Lastly, this study did not include a healthy control group. Therefore, the interpretation of hormonal findings was limited to within-group comparisons, and direct comparisons to well-nourished children could not be performed. Future studies should include healthy control groups and larger, more diverse populations to improve generalizability and enable direct comparisons of hormonal profiles. Longitudinal and interventional study is also needed to evaluate the effects of nutritional interventions on growth, body composition, micronutrient status and hormonal dynamics over time. In conclusion, malnutrition-at-risk and malnourished children are more likely to have feeding difficulties and poor eating behaviors. Despite meeting overall dietary requirements, these suboptimal feeding patterns may affect body composition and contribute to hormonal alterations associated with growth and appetite regulation. Our findings highlight the complex interplay between nutrition, behavior, and physiological adaptation in non-organic malnutrition. Early identification and targeted interventions addressing both nutritional intake and feeding behavior are essential to improve health outcomes in this vulnerable population. Methods Study design and study population This cross-sectional study was conducted as part of the MARVEL study (Malnutrition At Risk Intervention for Visible and Effective Long-term Growth), a multicenter randomized controlled trial registered in the Thai Clinical Trials Registry (TCTR20220908004). Data were collected over a 14-month period, from September 2022 to November 2023. Ethical approval was obtained prior to study initiation from three independent ethics committees: the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University (COA 0717/2022), the Human Research Ethics Committee of Thammasat University (COA 228/2022), and the Khon Kaen University Ethics Committee for Human Research (HE651330). Written informed consent was obtained from all parents or caregivers before participant enrollment. The study was conducted in accordance with the principles of the International Conference on Harmonisation - Good Clinical Practice (ICH-GCP), the Declaration of Helsinki (64th WMA General Assembly, Fortaleza, Brazil, October 2013), and all applicable Thai laws and regulations. Children aged 1–6 years were enrolled from the outpatient department of King Chulalongkorn Memorial Hospital (Bangkok), Thammasat University Hospital (Pathum Thani), and Srinagarind Hospital ( Khon Kaen), Thailand. Recruitment was carried out through direct contact by researchers and outreach via social media platforms. Eligible participants who met the following inclusion criteria: age between 1 and 6 years, weight-for-length or weight-for-height z-score ranging from − 1 to -3 standard deviations according to the WHO Child Growth Standards, and full-term born with birth weight between 2.5 and 4.5 kilograms were recruited. Children were excluded if they had any medical conditions known to affect growth, were taking medications that influence appetite, nutrient absorption, or growth, or had a diagnosis of cow's milk protein allergy. Written informed consent was obtained from the legal guardians of all participants following a comprehensive explanation of the study by the research team. Data collection Demographic data, including age, sex, birth weight, primary caregiver, and household income, were gathered through structured interviews conducted by trained research assistants. Appetite was evaluated using a visual analogue scale, with scores ranging from 1 (very poor appetite) to 10 (excellent appetite). Caregivers completed two self-administered questionnaires to assess eating behaviors and feeding difficulties. The Children’s Eating Behavior Questionnaire (CEBQ), a validated parent-report instrument for children over one year of age, was used to evaluate various aspects of eating behavior 28 . This tool assessed eight dimensions: food responsiveness, emotional overeating, enjoyment of food, desire to drink, satiety responsiveness, slowness in eating, emotional undereating, and food fussiness. Feeding difficulties were assessed using the Montreal Children’s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties 29 . All questionnaire responses were reviewed for completeness and accuracy by research staff during interviews. Dietary intake was evaluated using 24-hour dietary recall conducted by trained research dietitians. Energy, macronutrient, and micronutrient analyses were performed using INMUCAL-Nutrients V.4.0 software developed by the Institute of Nutrition, Mahidol University, Thailand. Energy and nutrient intakes were then compared to the Thai Dietary Reference Intakes (Thai DRIs) 30 . Anthropometric data including weight, length/height, and body composition were measured by trained research assistants. Weight was recorded to the nearest 100 grams using a calibrated digital scale (Detecto 6129, Detecto, Missouri, USA), and length/height was measured to the nearest 0.1 cm using a length board (Seca 417, Seca, Hamburg, Germany) or a stadiometer (Detecto 6129, Detecto, Missouri, USA) depending on age. Each measurement was taken twice, and the average was used for analysis. Body composition was assessed using bioelectrical impedance analysis (King Chulalongkorn Memorial hospital site: InBody 770, Cerritos, CA, USA; Thammasat University and Srinagarind hospital sites: InBody 720, Cerritos, CA, USA) in participants aged 3 years and older. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m²), and z-scores for weight-for-age (WFA), weight-for-height (WFH), and height-for-age (HFA) were derived using the WHO Anthro Survey Analyzer 31 . Laboratory Assessment Fasting venous blood samples (8 mL) were collected for complete blood count (CBC), iron, total iron binding capacity (TIBC), 25-hydroxyvitamin D [25 (OH)D], zinc and hormonal analysis including ghrelin, peptide YY (PYY), leptin, insulin, insulin-like growth factor 1 (IGF-1) and insulin-like growth factor binding protein 3 (IGFBP-3) One milliliters of blood were collected in an EDTA tube for CBC, and an additional 4 milliliters were collected in a clot-activator tube for micronutrient analysis, including serum iron, TIBC, 25(OH)D, and zinc. CBC was analyzed using Sysmex XN-10 hematology analyser (XN-10, Sysmex, Kobe, Japan) while serum iron and TIBC were measured using the Ferene colorimetric method on an automated analyzer (Alinity, Abbott Laboratories, Illinois, USA) at each study site. For 25(OH)D and zinc analysis, blood samples were centrifuged at 1000 g for 10 minutes; plasma was then separated and stored at − 20°C before being transported to Chulalongkorn University for analysis. Serum 25(OH)D concentrations were determined using the chemiluminescent immunoassay (CLIA) method on the LIAISON® XL system (DiaSorin, Saluggia, Italy), and zinc levels were measured using flame atomic absorption spectrophotometry (PerkinElmer AAnalyst 400, PerkinElmer, Massachusetts, USA). The inter-assay coefficients of variation for all measurements were below 10%. Transferrin saturation (%) was calculated as the ratio of serum iron to TIBC. Iron deficiency was defined as a transferrin saturation of less than 15% 32 . Anemia was defined as a hemoglobin concentration of < 11 g/dL in children under 5 years of age and < 11.5 g/dL in children aged 5 years and older, according to World Health Organization criteria 33 . Iron deficiency anemia was defined as the presence of both anemia and iron deficiency. Vitamin D insufficiency was defined as a serum 25-hydroxyvitamin D [25(OH)D] concentration below 20 ng/mL 34 . For appetite hormones analysis, 1 mL of blood collected in clot-activator tubes containing a protease inhibitor cocktail (AEBSF, hydrochloride; Merck KGaA, Darmstadt, Germany) were used. Samples were centrifuged at 1,000 g for 10 minutes, and the supernatant was then aliquoted into 500 µL microtubes and stored at − 20°C until analysis. Appetite hormones were quantified using the Milliplex Human Metabolic Hormones Panel V3 (Merck KGaA, Darmstadt, Germany) via Luminex multiplex assays. This technology allowed simultaneous quantification of multiple hormones using color-coded microspheres coated with specific antibodies. The assay detection ranges for ghrelin, leptin, PYY, and insulin were 14–10,000 pg/mL, 137–100,000 pg/mL, 21–15,000 pg/mL, and 206–150,000 pg/mL, respectively. Detection sensitivities were 9.2 pg/mL for ghrelin, 27 pg/mL for leptin, 20.2 pg/mL for PYY, and 46.9 pg/mL for insulin. Intra- and inter-assay precision values were below 10% and 20%, respectively. For analysis of IGF-1 and IGFBP-3, 2 mL of blood was collected in a separate clotting tube and processed using the same centrifugation protocol. These hormones were measured using electrochemiluminescence immunoassay (ECLIA) on a Cobas® Pro analyzer (Roche Diagnostics, Tokyo, Japan), with inter-assay coefficients of variation ranging from 2.9–3.1% for IGF-1 and 1.5–2.0% for IGFBP-3. Statistical analysis Statistical analyses were conducted using Stata version 18.5 (StataCorp., College Station, TX, USA). Prior to analysis, the distribution of continuous variables was assessed for normality using histograms and the Kolmogorov-Smirnov test. Categorical variables such as sex, household income and primary caregiver were summarized using frequencies and percentages. Continuous variables, including age, birth weight and length, dietary intake, appetite scores, anthropometric measurements, levels of growth and appetite-related hormones as well as micronutrients were reported as mean with 95% confidence intervals. Comparisons between children with feeding difficulties and those without were conducted using Chi-square test and independent sample t-tests accordingly. All statistical tests were two-sided, with a p-value of less than 0.05 considered statistically significant. Declarations Acknowledgements The authors sincerely thank Professor Chitsanu Pancharoen and the Chula Kids Club team for their invaluable support in participant recruitment. The authors also gratefully acknowledge Ms. Jiratchaya Sophonphan from the HIV Netherlands Australia Thailand Research Collaboration (HIV-NAT) at the Thai Red Cross AIDS Research Centre for her support with statistical analysis. Most importantly, the authors express their deep gratitude to all the children and families who generously participated in this study. *The MARVEL study team Nathawan Khunsri 1 , Siriporn Khabuan 1 , Siriluck Poonkatkij 1 , Apichaya Khowijitpaisal 1 , Umroh laman1, Jutamat Tonglim 3 , Saranrat Boonsawat 3 , Warisara Deetienin 3 , Sakuntala Supasai 4 , Sasupang Musikaboonleart 4 Author contributions The study's conception and design were carried out by OS and SC. Data collection involved OS, PT, SS, EM, KW, and the MARVEL study team. Data analysis and interpretation was conducted by OS and SC. OS wrote the first draft of the manuscript. SC edited and revised the manuscript. All authors jointly approved the final draft. Funding This study was funded by the Ratchadapiseksompotch Fund, Faculty of Medicine, Chulalongkorn University, grant number RA67/009, and Danone Specialized Nutrition. Data Availability Data described in the manuscript, codebook, and analytic code will be made available upon request in a de-identified form. Conflict of interest This study was partially funded by Danone Specialized Nutrition. Approval from the three Ethics Committees was obtained before start of the study, and was documented in a letter to the investigators specifying the date on which the committee met and granted the approval. Written informed consent was obtained from all parents/caregivers before inclusion in the study. The study was registered in Thai Clinical Trials Registry (no. TCTR 20220908004 ). The study was conducted according to ICH-GCP principles, and in compliance with the principles of the ‘Declaration of Helsinki’ ( 75 th WMA General Assembly, Helsinki, Finland, October 2024 ) and with the Thai laws and regulations. References WHO. Malnutrition , (2024). https://www.who.int/news-room/fact-sheets/detail/malnutrition De Sanctis, V. et al. Early and Long-term Consequences of Nutritional Stunting: From Childhood to Adulthood. Acta Biomed. 92 , e2021168. https://doi.org:10.23750/abm.v92i1.11346 (2021). Büttner, N. et al. Economic Growth and Childhood Malnutrition in Low- and Middle-Income Countries. JAMA Netw. Open. 6 , e2342654. https://doi.org:10.1001/jamanetworkopen.2023.42654 (2023). Black, R. E. et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet 382 , 427–451. https://doi.org:10.1016/s0140-6736(13)60937-x (2013). Kerzner, B. et al. I. A practical approach to classifying and managing feeding difficulties. Pediatrics 135 , 344–353. https://doi.org:10.1542/peds.2014-1630 (2015). Scaglioni, S. et al. Factors Influencing Children's Eating Behaviours. Nutrients 10 (2018). https://doi.org:10.3390/nu10060706 Edwards, S. T. et al. Demographics of children with feeding difficulties from a large electronic health record database. JPEN J. Parenter. Enteral. Nutr. 46 , 1022–1030. https://doi.org:10.1002/jpen.2379 (2022). Kjaer, T. W. et al. Correlates of serum IGF-1 in young children with moderate acute malnutrition: a cross-sectional study in Burkina Faso. Am. J. Clin. Nutr. 114 , 965–972. https://doi.org:10.1093/ajcn/nqab120 (2021). Kucuk, N., Orbak, Z., Karakelloglu, C. & Akcay, F. The effect of therapy on plasma ghrelin and leptin levels, and appetite in children with iron deficiency anemia. J. Pediatr. Endocrinol. Metab. 32 , 275–280. https://doi.org:10.1515/jpem-2018-0352 (2019). Soliman, A. T., ElZalabany, M. M., Salama, M. & Ansari, B. M. Serum leptin concentrations during severe protein-energy malnutrition: correlation with growth parameters and endocrine function. Metab. Clin. Exp. 49 , 819–825. https://doi.org:10.1053/meta.2000.6745 (2000). Blössner, M., de Onis, M. & WHO. Malnutrition: Quantifying the health impact at national and local levels . (, (2005). Dubois, L., Farmer, A., Girard, M., Peterson, K. & Tatone-Tokuda, F. Problem eating behaviors related to social factors and body weight in preschool children: A longitudinal study. Int. J. Behav. Nutr. Phys. Act. 4 , 9. https://doi.org:10.1186/1479-5868-4-9 (2007). Lee, W. S. et al. Prevalence of undernutrition and associated factors in young children in Malaysia: A nationwide survey. Front. Pediatr. 10 , 913850. https://doi.org:10.3389/fped.2022.913850 (2022). Rahmawati, D. A. et al. Malnutrition in children associated with low insulin-like growth factor binding protein-3 (IGFBP-3) levels. Gac Sanit. 35 (Suppl 2), S275–s277. https://doi.org:10.1016/j.gaceta.2021.07.019 (2021). Sinha, R. K. et al. Association between anthropometric criteria and body composition among children aged 6–59 months with severe acute malnutrition: a cross-sectional assessment from India. BMC Nutr. 8 , 56. https://doi.org:10.1186/s40795-022-00551-6 (2022). Teshome, M. S. et al. Body composition and associated factors among 5-7-year-old children with moderate acute malnutrition in Jimma town in southwest Ethiopia: A comparative cross-sectional study. Matern Child. Nutr. 20 , e13655. https://doi.org:10.1111/mcn.13655 (2024). Pongcharoen, T. et al. South East Asian Nutrition Surveys II (SEANUTS II) Thailand: triple burden of malnutrition among Thai children aged 6 months to 12 years. Public. Health Nutr. 27 , e152. https://doi.org:10.1017/s1368980024000053 (2024). Institute, H. S. R. Thai National Health Examination Survey IV (Health Systems Research Institute, 2011). Northstone, K. & Emmett, P. The associations between feeding difficulties and behaviours and dietary patterns at 2 years of age: the ALSPAC cohort. Matern Child. Nutr. 9 , 533–542. https://doi.org:10.1111/j.1740-8709.2012.00399.x (2013). Walton, K. et al. Eating Behaviors, Caregiver Feeding Interactions, and Dietary Patterns of Children Born Preterm: A Systematic Review and Meta-Analysis. Adv. Nutr. 13 , 875–912. https://doi.org:10.1093/advances/nmac017 (2022). Golden, M. H. Proposed Recommended Nutrient Densities for Moderately Malnourished Children. FoodNutr. Bull. 30 , S267–S342. https://doi.org:10.1177/15648265090303S302 (2009). Dahl, M. & Sundelin, C. Feeding problems in an affluent society. Follow-up at four years of age in children with early refusal to eat. Acta Paediatr. 81 , 575–579. https://doi.org:10.1111/j.1651-2227.1992.tb12303.x (1992). Sleiman, R., Abdelkader, W. & AlTannir, D. Assessing the Body Composition of Picky Eaters Using Body Impedance Analysis: An Experience From a Tertiary Care Center. Cureus 16 , e60538. https://doi.org:10.7759/cureus.60538 (2024). Wardle, J., Guthrie, C. A., Sanderson, S. & Rapoport, L. Development of the Children's Eating Behaviour Questionnaire. J. Child Psychol. Psychiatry Allied Discip. 42 , 963–970. https://doi.org:10.1111/1469-7610.00792 (2001). Charoensriwattanakul, K. et al. Feeding Difficulties and Feeding Behaviors of Thai Children with Cow's Milk Protein Allergy. Int J Pediatr 6630167 (2023). (2023). https://doi.org:10.1155/2023/6630167 Altinkaynak, S., Selimoglu, M. A., Ertekin, V. & Kilicarslan, B. Serum ghrelin levels in children with primary protein-energy malnutrition. Pediatr. Int. 50 , 429–431. https://doi.org:10.1111/j.1442-200X.2008.02606.x (2008). Bier, D. M. Growth hormone and insulin-like growth factor I: nutritional pathophysiology and therapeutic potential. Acta Paediatr. Scand. Suppl. 374 , 119–128. https://doi.org:10.1111/j.1651-2227.1991.tb12014.x (1991). Sirirassamee, T., Hunchangsith, P., CHILDREN’S EATING & BEHAVIOR QUESTIONNAIRE: FACTORIAL VALIDATION AND DIFFERENCES IN SEX AND EDUCATIONAL LEVEL IN THAI SCHOOL-AGE CHILDREN. Southeast Asian J. Trop. Med. Public Health 47 , 1325–1334 (2016). Benjasuwantep, B., Rattanamongkolgul, S. & Ramsay, M. The Thai version of the Montreal Children's Hospital Feeding Scale (MCH-FS): psychometric properties. J. Med. Association Thail. = Chotmaihet thangphaet . 98 , 163–169 (2015). Bureau of Nutrition, D. o. H. Dietary reference intake for Thais 2020. A.V. Progressive LTD, (2020). WHO. WHO Anthro Survey Analyser and other tools , (2018). https://www.who.int/tools/child-growth-standards/software WHO. Assessing the iron status of populations: Report of a joint WHO/CDC technical consultation on the assessment of iron status at the population level 2nd edn (WHO, 2007). WHO. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Vitamin and Mineral Nutrition Information System. WHO, (2011). Munns, C. F. et al. Global Consensus Recommendations on Prevention and Management of Nutritional Rickets. J. Clin. Endocrinol. Metab. 101 , 394–415. https://doi.org:10.1210/jc.2015-2175 (2016). Additional Declarations Competing interest reported. This study was partially funded by Danone Specialized Nutrition. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6641861","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":473421495,"identity":"5cc0c017-ab00-439e-8836-55e92a88aebe","order_by":0,"name":"Orapa Suteerojntrakool","email":"","orcid":"","institution":"Chulalongkorn University","correspondingAuthor":false,"prefix":"","firstName":"Orapa","middleName":"","lastName":"Suteerojntrakool","suffix":""},{"id":473421496,"identity":"0e485bbb-939a-4640-804c-395b53695676","order_by":1,"name":"Patcharapa Thaweekul","email":"","orcid":"","institution":"Thammasat University","correspondingAuthor":false,"prefix":"","firstName":"Patcharapa","middleName":"","lastName":"Thaweekul","suffix":""},{"id":473421497,"identity":"a50d3ca6-a48b-4aa2-af15-c7ab75313337","order_by":2,"name":"Suchaorn Saengnipanthkul","email":"","orcid":"","institution":"Khon Kaen University","correspondingAuthor":false,"prefix":"","firstName":"Suchaorn","middleName":"","lastName":"Saengnipanthkul","suffix":""},{"id":473421498,"identity":"829885a0-fb19-425e-bdb4-9cbe2cc82179","order_by":3,"name":"Kamolmart Wannaphahoon","email":"","orcid":"","institution":"Thammasat University","correspondingAuthor":false,"prefix":"","firstName":"Kamolmart","middleName":"","lastName":"Wannaphahoon","suffix":""},{"id":473421499,"identity":"59339daa-ff98-4607-9903-fc6a9bfae25f","order_by":4,"name":"Eakkarin Mekangkul","email":"","orcid":"","institution":"Chulalongkorn University","correspondingAuthor":false,"prefix":"","firstName":"Eakkarin","middleName":"","lastName":"Mekangkul","suffix":""},{"id":473421500,"identity":"c926e41e-0a96-42e5-9c4d-ce86ab93d4a6","order_by":5,"name":"Sirinuch Chomtho","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIie2PvQrCMBRGrwTSJcU14OArRFwctL6KpeCkggiCW0G4jp19DkEcUwJO6jPYxcml9AW8xd/F2NEhZ8khcMgXAIfjH2EAmo4BmSbv3G9rcaWED8jl/Ta1JQ8oEapa0lz5mZliMAHvkBdTlE3wzJnlu++JMp4ya4xmIMabxhplKxZDBenBkjAOxkcdxtLfMh8lfXxEw9AybPlKxKVM+nH9ak/AvBNeJiQ/XlFlIk5RiGLYboiTjFBelD7ahiV7Voh5ECaeyUi6vaQeZeeFbdgT/im6QuBwOBwOCzcQ1Eh6Gseg5AAAAABJRU5ErkJggg==","orcid":"","institution":"Chulalongkorn University","correspondingAuthor":true,"prefix":"","firstName":"Sirinuch","middleName":"","lastName":"Chomtho","suffix":""},{"id":473421501,"identity":"8128bbbb-6b92-4de4-9874-c39b2dfa7e29","order_by":6,"name":"Marvel study team","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Marvel","middleName":"study","lastName":"team","suffix":""}],"badges":[],"createdAt":"2025-05-12 00:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6641861/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6641861/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85385658,"identity":"4e94a75e-bdb0-4ae7-975d-6a22dcb57ae8","added_by":"auto","created_at":"2025-06-25 09:49:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":72134,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of daily energy and nutrient intakes between children with and without feeding difficulties, expressed as the mean percentage of intake relative to the Thai Dietary Reference Intakes (DRIs). Grey, orange, and dark green bars represent the mean percentage of intake among all participants (n=159), children with feeding difficulties (n=109), and children without feeding difficulties (n=50), respectively. The red dashed line indicates 100% of the Thai DRIs. There were no statistically significant differences in dietary intakes between children with and without feeding difficulties.\u003c/p\u003e","description":"","filename":"Figure1DRI.png","url":"https://assets-eu.researchsquare.com/files/rs-6641861/v1/10921a7d138c621c2c33f3e8.png"},{"id":85387253,"identity":"c093abdd-0fd8-4e75-993f-a157da8d93f7","added_by":"auto","created_at":"2025-06-25 09:57:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81831,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of feeding behavior subscales assessed by Children’s Eating Behavior Questionnaire (CEBQ) between children with and without feeding difficulties. The orange, and dark green lines represent the scores of children with and without feeding difficulties, respectively. \u003csup\u003e\u0026nbsp;\u003c/sup\u003eDifferences of the subscale scores between the two groups were assessed by independent sample t-test. The asterisk (*) indicated p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure2CEBQ.png","url":"https://assets-eu.researchsquare.com/files/rs-6641861/v1/16785f4321521dc688ca5bfe.png"},{"id":109612321,"identity":"fa4e451e-6f7c-4aa7-b6e5-710146b2b7b3","added_by":"auto","created_at":"2026-05-20 07:56:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":528767,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6641861/v1/9e2331de-617d-4d6d-bcc7-2ec83db3456b.pdf"}],"financialInterests":"Competing interest reported. This study was partially funded by Danone Specialized Nutrition.","formattedTitle":"\u003cp\u003eComparative Study of Body Composition, Micronutrient Status and Hormonal Profiles in Undernourished Children With Feeding Difficulties\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMalnutrition has remained a major global health issue, especially among children under the age of five. The World Health Organization (WHO) reports that approximately 49\u0026nbsp;million children in this age group experience stunting, while around 45\u0026nbsp;million suffer from wasting\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Undernutrition is associated with nearly 50% of all deaths in children under five\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Beyond its immediate health risks, childhood malnutrition has far-reaching and long-term developmental, medical, social, and economic impacts, not only for the affected children and their families, but also for the broader communities and nations\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Despite widespread global initiatives targeting nutritional improvement, comprehensive insights into feeding behavior patterns and their association with nutritional status remain insufficient.\u003c/p\u003e \u003cp\u003eNon-organic feeding difficulties, which occur in the absence of identifiable medical or anatomical causes, are shaped by a complex interplay of biological, psychological, and environmental factors\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Psychosocial influences, including child temperament, parental anxiety, and negative caregiver-child interactions, can lead to maladaptive feeding behaviors such as food refusal and selective eating\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Inconsistent or non-responsive feeding practices may reinforce these patterns, creating a cycle of stress and inadequate intake\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Among children who were malnourished or at risk of malnutrition, non-organic feeding difficulties were commonly observed\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. These difficulties can significantly reduce energy and nutrient intake, contributing to growth faltering, suboptimal body composition and micronutrient deficiencies. These nutritional deficits were often accompanied by alterations in growth and appetite-regulating hormones such as IGF-1, ghrelin and leptin\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSeveral studies have established that children with feeding difficulties were at a significantly higher risk of malnutrition, with an increased prevalence of both moderate and severe forms\u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. For instance, Bl\u0026ouml;ssner and de Onis reported that feeding problems were more frequently observed in children with moderate to severe malnutrition, commonly manifested as stunting and wasting\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Although these studies highlighted a clear association between feeding difficulties and poor nutritional status, there was limited evidence exploring the broader nutritional and physiological implications. Specifically, a few studies have examined differences in body composition, feeding behavior, energy and nutrient intake, micronutrient status, or growth and appetite-related hormones among these undernourished children\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. These factors were essential to understand the underlying physiology of malnourished children and can lead to interventions that address both behavioral and nutritional dimensions of care.\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to investigate the prevalence of feeding difficulties among children who were malnourished or at risk of malnutrition. In addition, it compared the differences in dietary intake, body composition, feeding behaviors, micronutrient status, as well as growth and appetite-related hormones between those with and without feeding difficulties. Findings from this study are expected to enhance our understanding of the physiological and behavioral profiles of malnourished children and contribute to the formulation of more precise and effective nutritional strategies.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presented the clinical characteristics of the study participants. A total of 159 participants were included in the analysis. The mean age was 3.5 years (95% CI: 3.3\u0026ndash;3.8), and 58% of the participants were male. Approximately 80% of the participants came from middle- to high-income families, and 60% had their mothers as the primary caregivers. Based on the MCH-FS criteria, 68.6% of the study population were identified as having feeding difficulties, classified as mild (n\u0026thinsp;=\u0026thinsp;26), moderate (n\u0026thinsp;=\u0026thinsp;21), or severe (n\u0026thinsp;=\u0026thinsp;62), while the remaining participants (n\u0026thinsp;=\u0026thinsp;50) were classified as having no feeding difficulties. Comparison between children with and without feeding difficulties revealed no significant differences in age, sex, birthweight, early life feeding practices, primary caregiver, socioeconomic status. However, the reported appetite score was significantly lower in children with feeding difficulties.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical characteristics of the study participants (n\u0026thinsp;=\u0026thinsp;159)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;159)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWith feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWithout feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5 (3.3\u0026ndash;3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6 (3.3\u0026ndash;3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3 (2.9\u0026ndash;3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.424\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93 (58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (58.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirthweight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.02 (2.97\u0026ndash;3.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.04 (2.98\u0026ndash;3.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.96 (2.88\u0026ndash;3.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeeding type during the first six months of life, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; predominant breastfeeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121 (76.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81 (74.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; predominant formula feeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; mixed breastfeeding and formula feeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMain caregiver, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; mothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101 (63.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (59.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; fathers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; grandfathers/grandmothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; others\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily income (baht/month), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; \u0026lt;\u0026thinsp;15,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; \u0026gt;\u0026thinsp;15,000\u0026ndash;30,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; \u0026gt;\u0026thinsp;30,000\u0026ndash;50,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; \u0026gt;\u0026thinsp;50,000-100,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; \u0026gt;\u0026thinsp;100,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAppetite score\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.14 (4.82\u0026ndash;5.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.38 (4.03\u0026ndash;4.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.8 (6.33\u0026ndash;7.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eValues were presented as mean (95%CI) for continuous variables while categorical variables were expressed as n (%).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003eFeeding difficulties were assessed using Montreal Children\u0026rsquo;s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003eDifferences in mean and proportion between children with and without feeding difficulties were tested by independent sample t-test and Chi-square test, respectively.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003eOthers included children with more than one primary caregiver (e.g., mother and father, grandmother and mother), as well as those cared for by nursery staff or an aunt.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003eAppetite was assessed using a visual analogue scale ranging from 1, indicating very poor appetite, to 10, indicating excellent appetite.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDietary intakes\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e Comparison of daily energy and nutrient intakes between children with and without feeding difficulties, expressed as the mean percentage of intake relative to the Thai Dietary Reference Intakes (DRIs). Grey, orange, and dark green bars represent the mean percentage of intake among all participants (n\u0026thinsp;=\u0026thinsp;159), children with feeding difficulties (n\u0026thinsp;=\u0026thinsp;109), and children without feeding difficulties (n\u0026thinsp;=\u0026thinsp;50), respectively. The red dashed line indicates 100% of the Thai DRIs. There were no statistically significant differences in dietary intakes between children with and without feeding difficulties.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnthropometry and body composition\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarized the growth parameters of the study population. No significant differences were observed in weight, height, BMI, or their corresponding z-scores between children with and without feeding difficulties. Children with feeding difficulties had higher soft lean mass, fat-free mass, and skeletal muscle mass compared to those without feeding difficulties, while fat mass did not differ between the groups. However, these differences disappeared after adjusting for differences in height using fat-free mass index (fat-free mass divided by height\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of anthropometry and body composition between children with and without feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnthropometry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWith feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWithout feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eSimple anthropometry\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.34 (11.86\u0026ndash;12.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.52 (11.9\u0026ndash;13.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.95 (11.18\u0026ndash;12.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94.44 (92.38\u0026ndash;96.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.2 (92.61\u0026ndash;97.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.78 (89.38\u0026ndash;96.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.282\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.69 (13.57\u0026ndash;13.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.65 (13.5\u0026ndash;13.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.79 (13.57\u0026ndash;14.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWFA z-score\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.62 (-1.73 to-1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.62 (-1.76 to -1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.63 (-1.8 to -1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHFA z-score\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.92 (-1.07 to -0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.88 (-1.07 to -0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.01 (-1.25 to -0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWFH z-score\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.65 (-1.74 to-1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.69 (-1.8 to -1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.57 (-1.72 to -1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI z-score\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.59 (-1.68 to-1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.62 (-1.74 to -1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.51 (-1.67 to -1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody composition\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoft lean mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.98 (11.61\u0026ndash;12.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.32 (11.83\u0026ndash;12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.25 (10.82\u0026ndash;11.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkeletal muscle mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.5 (5.27\u0026ndash;5.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.71 (5.4\u0026ndash;6.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.05 (4.78\u0026ndash;5.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat free mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.69 (12.28\u0026ndash;13.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.04 (12.51\u0026ndash;13.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.93 (11.44\u0026ndash;12.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat-free mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.58 (11.43\u0026ndash;11.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.58 (11.42\u0026ndash;11.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.58 (11.22\u0026ndash;11.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.52 (1.32\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.51 (1.31\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.54 (1.08\u0026ndash;1.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.880\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.34 (1.2\u0026ndash;1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32 (1.17\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.39 (1.07\u0026ndash;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercent fat mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.31 (9.26\u0026ndash;11.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.15 (9.02\u0026ndash;11.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.66 (8.25\u0026ndash;13.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisceral fat area (cm\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.24 (18.22\u0026ndash;20.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.2 (18.1\u0026ndash;20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.35 (16.9\u0026ndash;21.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviation: BMI, body mass index; HFA, height for age; WFA, weight for age; WFH, weight for height.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eValues were presented as mean (95%CI). Differences in mean were tested by independent sample t-test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003eFeeding difficulties were assessed using Montreal Children\u0026rsquo;s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Weight and height were assessed in 109 children with feeding difficulties and 50 children without feeding difficulties. Body composition via bioelectrical impedance analysis was assessed in those aged 3 years old and above, 56 children with and 26 children without feeding difficulties.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e z-scores for WFA, WFH and HFA were derived using the WHO Anthro Survey Analyzer\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Fat-free mass index and fat mass index were calculated by dividing fat-free mass and fat mass, respectively, by height squared.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eFeeding behavior assessed by CEBQ\u003c/h3\u003e\n\u003cp\u003eOverall, undernourished children in this study had slightly low scores in food approach subscales, including food responsiveness, emotional overeating, and desire to drink [mean (95%CI): food responsive 2.31 (2.19\u0026ndash;2.42); emotional overeating 1.56 (1.48\u0026ndash;1.64); desire to drink 2.42 (2.23\u0026ndash;2.61)] (\u003cb\u003edata not shown\u003c/b\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e demonstrated differences in feeding behavior subscales assessed by CEBQ between children with and without feeding difficulties. Children with feeding difficulties had significantly higher scores in satiety responsiveness, slowness in eating, and food fussiness subscales, and lower scores in food responsiveness and enjoyment of food compared to those without feeding difficulties. There was no significant difference in desire to drink, emotional overeating, nor emotional undereating subscales between the 2 groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eMicronutrients, growth and appetite hormones\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e showed the comparison of micronutrient status between children with and without feeding difficulties. Overall, iron deficiency was observed in approximately 18% of participants, while anemia was present in about 15%. Notably, only 4.7% of the children exhibited anemia attributable to iron deficiency. Vitamin D insufficiency was identified in approximately 11% of the study population, and no cases of zinc deficiency were detected. Further analysis showed no significant difference in the status of iron, vitamin D, or zinc between children with and without feeding difficulties in this undernourished population.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of micronutrient status between children with and without feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;159)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWith feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWithout feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eLaboratory parameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (11.8\u0026ndash;12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.1 (11.9\u0026ndash;12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.8 (11.5\u0026ndash;12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCV (fL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.6 (72.3\u0026ndash;74.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.8 (72.3\u0026ndash;75.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73 (70.4\u0026ndash;75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.572\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRDW (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.7 (14.2\u0026ndash;15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.6 (14-15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.8 (14.2\u0026ndash;15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.604\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum iron (mcg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.5 (73.5\u0026ndash;83.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.1 (73.2\u0026ndash;84.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.2 (67.4\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIBC (mcg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e326.9 (320.3-333.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e326.9 (319-334.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e327 (314.7-339.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransferrin saturation (%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.4 (22.7\u0026ndash;26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.6 (22.6\u0026ndash;26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.9 (20.9\u0026ndash;26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZinc (mcg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.3 (89-93.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.1 (89.3\u0026ndash;95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.5 (85.3\u0026ndash;93.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25(OH)D (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.8 (28.4\u0026ndash;31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.8 (28-31.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.1 (27.4\u0026ndash;32.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMicronutrient status, n (%)\u003c/b\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIron deficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIron deficiency anemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin D insufficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviation: MCV, mean corpuscular volume; RDW, red cell distribution width; TIBC, Total iron binding capacity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eValues were presented as mean (95%CI) for continuous variables while categorical variables were expressed as n (%). Differences in mean and proportion were tested by independent sample t-test and Chi-square test, respectively.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003eFeeding difficulties were assessed using Montreal Children\u0026rsquo;s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Transferrin saturation (%) was calculated as serum iron divided by TIBC.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003eIron deficiency: transferrin saturation\u0026thinsp;\u0026lt;\u0026thinsp;15%; Anemia: hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;11 g/dL for children\u0026thinsp;\u0026lt;\u0026thinsp;5 years, or \u0026lt;\u0026thinsp;11.5 g/dL for \u0026ge;\u0026thinsp;5 years; Iron deficiency anemia: presence of both anemia and iron deficiency; Vitamin D insufficiency: 25(OH)D\u0026thinsp;\u0026lt;\u0026thinsp;20 ng/mL\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn terms of hormonal profiles, the levels of IGF-1 and IGF BP3 were within the normal range of age and sex. However, children with feeding difficulties exhibited significantly higher levels of IGF BP-3, and a non-significant trend toward lower ghrelin levels compared to their peers. Levels of other hormones, including IGF-1, leptin, PYY, and insulin, did not differ significantly between the two groups (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). There were no significant correlations between any feeding difficulties scores according to MCH-FS and any micronutrients and hormonal levels (\u003cb\u003edata not shown\u003c/b\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of growth and appetite hormones between children with and without feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;159)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWith feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWithout feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eGrowth hormone derivatives\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGF-1 (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.33 (57.98\u0026ndash;68.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.61 (58.84\u0026ndash;72.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.25 (49.65\u0026ndash;66.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGF BP-3 (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.92 (2.77\u0026ndash;3.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.04 (2.85\u0026ndash;3.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.64 (2.46\u0026ndash;2.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAppetite hormones\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGhrelin (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e292.4 (267.32-317.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e277.24 (248.07-306.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e326.18 (277.67-374.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeptin (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e239.67 (182.92-296.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220.98 (155.14-286.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e284.34 (170.29-398.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.316\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeptide YY (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e179.16 (164.85-193.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e178.45 (163.31-193.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e180.74 (148.29-213.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e502.45 (422.17-582.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e510.26 (412.83\u0026ndash;607.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e483.87 (337.26-630.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.768\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviation: IGF BP-3, Insulin-like growth factor-binding protein 3; IGF-1, insulin-like growth factor-1;\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eValues were presented as mean (95%CI) for continuous variables while categorical variables were expressed as n (%). Differences in mean and proportion were tested by independent sample t-test and Chi-square test, respectively.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003eFeeding difficulties were assessed using Montreal Children\u0026rsquo;s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMalnutrition-at-risk and malnourished children continue to represent a significant global health concern. In the absence of identifiable organic causes, malnutrition in this population is often associated with behavioral factors, particularly feeding difficulties, which can adversely impact nutritional intake and physiological regulation. This study found that the prevalence of feeding difficulties was very high at 68.6% of children classified as malnutrition-at-risk or malnourished who did not have underlying medical conditions known to affect growth. The findings also suggested that in children without significant underlying medical conditions, disordered eating behaviors may contribute to alterations in growth and appetite-regulating hormones.\u003c/p\u003e \u003cp\u003eThis high prevalence of feeding difficulties in this population underscored the substantial role of feeding behavior in the etiology of malnutrition in children without significant organic pathology. Feeding difficulties, including food refusal, selective eating, and poor appetite, can contribute to inadequate nutrient intake, ultimately impairing growth and nutritional status. Previous studies have similarly demonstrated an association between feeding difficulties and an increased risk of undernutrition. For instance, a study in Malaysia reported that children under 5 years old with feeding difficulties had significantly higher odds of being wasted (AOR: 1.48) and of experiencing at least one form of undernutrition (AOR: 1.45) compared to those without feeding problems\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Similarly, Dubios L et al revealed that children identified as picky eaters were twice as likely to be underweight at 4.5 years of age compared to those who were never reported as picky eaters\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. These results highlighted the need for early detection and tailored interventions for feeding difficulties as a critical component in the prevention and management of childhood malnutrition.\u003c/p\u003e \u003cp\u003eIn our study, we found that malnourished children consumed relatively high protein intakes when compared to the Thai DRIs. This observation aligns with findings from previous research examining dietary patterns among Thai children. The Southeast Asian Nutrition Survey II (SEANUTS II) found that the protein intake of most Thai children was often adequate or exceeded recommendations\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Similarly, the Thai National Health Examination Survey IV reported that protein intake among preschool children, particularly those aged 1\u0026ndash;3 years, was approximately 1.4 to 2.1 times higher than the Thai DRIs\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. These findings imply a consistent pattern in which Thai children, including those at risk of malnutrition, tend to consume diets low in total energy yet relatively high in protein. This imbalance may result from feeding practices that emphasize protein-rich foods, such as milk and animal products, while neglecting energy-dense sources like fats and carbohydrates. The issue appeared to be more pronounced among children with feeding difficulties, who may experience reduced appetite, oral-motor dysfunction, or behavioral challenges that further limit dietary variety and intake volume\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Such a dietary pattern can impair catch-up growth, as protein would be diverted to meet energy demands rather than being used for tissue synthesis when energy intake was insufficient\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough there were no significant differences in basic anthropometric measurements between children with and without feeding difficulties among malnutrition-at-risk and malnourished children, those with feeding difficulties were found to have higher lean body mass compared to those without. This finding contrasted with previous studies. For example, Dahl and Sundelin reported that children with feeding refusal exhibited significantly lower weight and height gain compared to those without such difficulties\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In addition, a recent large cross-sectional study from Saudi Arabia demonstrated that underweight status was significantly more prevalent among picky eaters compared to non-picky eaters. Moreover, the picky eaters had significantly lower skeletal muscle mass than their non-picky counterparts\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. These discrepancies may be attributed to differences in study populations, as our study specifically focused on children who were malnourished or at risk of malnutrition, whereas previous studies emphasized feeding behavior problems in general pediatric population. Furthermore, the definitions and assessment methods for feeding difficulties varied across studies. In our study, a validated questionnaire was used to classify children with and without feeding difficulties, providing a more robust and standardized approach compared to the earlier studies, which relied on brief screening questions. The higher skeletal muscle mass observed among children with feeding difficulties in our study may be explained by the possibility that these children received more targeted nutritional support or feeding interventions, such as oral nutritional supplements or caregiver-directed high-protein diets, which could contribute to improved lean mass despite ongoing feeding challenges. However, after adjusting by height using fat-free mass index, this difference disappeared, suggesting that this finding may partly resulted from the height difference in the subgroup who had their body composition assessed. In addition, this finding should be interpreted with caution, as only half of the study population underwent body composition assessment by BIA, potentially limiting the statistical power of the analysis. Further studies should be conducted in a larger population using more precise and validated methods, such as dual-energy X-ray absorptiometry (DEXA), to better assess body composition and bone health in these children.\u003c/p\u003e \u003cp\u003eRegarding feeding behavior, children with feeding difficulties showed higher scores on food avoidance subscales, such as satiety responsiveness, slowness in eating, and food fussiness, and lower scores on food approach subscales, including food responsiveness and enjoyment of food, compared to those without feeding difficulties. These results were consistent with earlier studies suggesting that children with feeding difficulties frequently exhibited diminished appetite and increased sensitivity to internal satiety cues, which may lead to decreased food intake. For example, Wardle et al. reported that picky eaters tended to have higher scores in satiety responsiveness and food fussiness\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Similarly, Charoensriwattanakul et al. found that children who scored lower on enjoyment of food and higher on slowness in eating and food fussiness subscales had significantly higher t-scores on the MCH-FS, indicating more likelihood of having feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. However, there were no significant differences in the \"desire to drink,\" \"emotional undereating,\" and \"emotional overeating\" subscales between children with and without feeding difficulties. These findings hinted that interventions targeting feeding difficulties in undernourished children may need to focus more on behavioral traits such as food fussiness, satiety responsiveness, and sensory sensitivity rather than emotional or beverage-related eating patterns. Nutritional strategies, such as the use of ONS in a liquid form, may therefore be particularly beneficial for improving intake in this group, as they provide a concentrated source of energy and nutrients without relying on changes in emotionally driven eating behaviors.\u003c/p\u003e \u003cp\u003eOur study also revealed that iron deficiency and vitamin D insufficiency were more prevalent among toddlers and preschool-aged children with malnutrition. Specifically, the prevalence of iron deficiency, iron deficiency anemia, and vitamin D insufficiency in our cohort was 17.8%, 4.7%, and 11.3%, respectively. The rates of iron deficiency and iron deficiency anemia observed in our study are consistent with findings from the Southeast Asian Nutrition Surveys II (SEANUTS II)\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, the prevalence of vitamin D insufficiency in our sample was notably higher, more than double, compared to the SEANUTS II report (11.3% vs. 5.5%)\u003csup\u003e17\u003c/sup\u003e. This disparity may indicate that children with malnutrition are at greater risk of vitamin D insufficiency. However, our findings may have been influenced by the demographic characteristics of our study population, which consisted of malnourished children living in urban settings. Limited outdoor activity and reduced sun exposure in urban environments could contribute to lower endogenous vitamin D synthesis, thereby increasing the risk of insufficiency in this group.\u003c/p\u003e \u003cp\u003eAdditionally, our study assessed growth and appetite hormone profiles in malnourished children, comparing those with and without feeding difficulties. Although no statistically significant differences were found in appetite-regulating hormones between the groups, ghrelin levels tended to be lower in children with feeding difficulties. Previous studies have shown that ghrelin, an orexigenic hormone, is elevated during states of malnutrition or fasting\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The observed lower ghrelin levels in children with feeding difficulties may reflect a blunted hunger signaling response, potentially contributing to their poor oral intake. This physiological finding aligned with the subjective appetite assessment, as children with feeding difficulties also reported lower appetite scores on a visual analogue scale. These results suggested that in some undernourished children, feeding difficulties may be associated with alterations in the hormonal regulation of appetite. Recognizing this potential hormonal dysregulation was important, as it may affect the responsiveness to conventional nutritional counselling.\u003c/p\u003e \u003cp\u003eMoreover, we found that IGF-1 levels were slightly lower in malnourished children but there was no difference between children with and without feeding difficulties. However, IGF BP-3 was significantly higher in children with feeding difficulties, suggesting altered growth hormone axis regulation in this subgroup. These findings partially aligned with previous studies which reported reduced IGF-1 and IGF BP-3 levels in malnourished children due to impaired growth hormone action in the context of protein-energy malnutrition\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. However, the elevated IGF BP-3 observed in children with feeding difficulties in our study may reflect a compensatory mechanism or a stress-related physiological response, which has been less commonly reported and merits further investigation.\u003c/p\u003e \u003cp\u003eA key strength of this study was its comprehensive assessment of undernourished children, including detailed evaluations of dietary intake, anthropometry, body composition, feeding behavior, micronutrient status, and growth and appetite hormones. Furthermore, the study compared children with and without feeding difficulties, using validated caregiver-reported questionnaires. This allowed for a more nuanced understanding of the physiological and behavioral characteristics of children with non-organic malnutrition, providing valuable insights into how feeding challenges may influence nutritional and hormonal profiles. Nevertheless, several limitations should be noted. Firstly, the study population was recruited mainly from middle-to-high income families in Thailand, which may limit the generalizability of the findings to other socio-demographic contexts. Secondly, the BIA tool used to assess body composition was validated only for children aged 3 years and older, potentially affecting the study\u0026rsquo;s power and representation of younger children. Lastly, this study did not include a healthy control group. Therefore, the interpretation of hormonal findings was limited to within-group comparisons, and direct comparisons to well-nourished children could not be performed. Future studies should include healthy control groups and larger, more diverse populations to improve generalizability and enable direct comparisons of hormonal profiles. Longitudinal and interventional study is also needed to evaluate the effects of nutritional interventions on growth, body composition, micronutrient status and hormonal dynamics over time.\u003c/p\u003e \u003cp\u003eIn conclusion, malnutrition-at-risk and malnourished children are more likely to have feeding difficulties and poor eating behaviors. Despite meeting overall dietary requirements, these suboptimal feeding patterns may affect body composition and contribute to hormonal alterations associated with growth and appetite regulation. Our findings highlight the complex interplay between nutrition, behavior, and physiological adaptation in non-organic malnutrition. Early identification and targeted interventions addressing both nutritional intake and feeding behavior are essential to improve health outcomes in this vulnerable population.\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eStudy design and study population\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted as part of the MARVEL study (Malnutrition At Risk Intervention for Visible and Effective Long-term Growth), a multicenter randomized controlled trial registered in the Thai Clinical Trials Registry (TCTR20220908004). Data were collected over a 14-month period, from September 2022 to November 2023. Ethical approval was obtained prior to study initiation from three independent ethics committees: the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University (COA 0717/2022), the Human Research Ethics Committee of Thammasat University (COA 228/2022), and the Khon Kaen University Ethics Committee for Human Research (HE651330). Written informed consent was obtained from all parents or caregivers before participant enrollment. The study was conducted in accordance with the principles of the International Conference on Harmonisation - Good Clinical Practice (ICH-GCP), the Declaration of Helsinki (64th WMA General Assembly, Fortaleza, Brazil, October 2013), and all applicable Thai laws and regulations.\u003c/p\u003e \u003cp\u003eChildren aged 1\u0026ndash;6 years were enrolled from the outpatient department of King Chulalongkorn Memorial Hospital (Bangkok), Thammasat University Hospital (Pathum Thani), and Srinagarind Hospital ( Khon Kaen), Thailand. Recruitment was carried out through direct contact by researchers and outreach via social media platforms. Eligible participants who met the following inclusion criteria: age between 1 and 6 years, weight-for-length or weight-for-height z-score ranging from \u0026minus;\u0026thinsp;1 to -3 standard deviations according to the WHO Child Growth Standards, and full-term born with birth weight between 2.5 and 4.5 kilograms were recruited. Children were excluded if they had any medical conditions known to affect growth, were taking medications that influence appetite, nutrient absorption, or growth, or had a diagnosis of cow's milk protein allergy. Written informed consent was obtained from the legal guardians of all participants following a comprehensive explanation of the study by the research team.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eDemographic data, including age, sex, birth weight, primary caregiver, and household income, were gathered through structured interviews conducted by trained research assistants. Appetite was evaluated using a visual analogue scale, with scores ranging from 1 (very poor appetite) to 10 (excellent appetite).\u003c/p\u003e \u003cp\u003eCaregivers completed two self-administered questionnaires to assess eating behaviors and feeding difficulties. The Children\u0026rsquo;s Eating Behavior Questionnaire (CEBQ), a validated parent-report instrument for children over one year of age, was used to evaluate various aspects of eating behavior\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. This tool assessed eight dimensions: food responsiveness, emotional overeating, enjoyment of food, desire to drink, satiety responsiveness, slowness in eating, emotional undereating, and food fussiness. Feeding difficulties were assessed using the Montreal Children\u0026rsquo;s Hospital Feeding Scale (MCH-FS), with a t-score above 61 indicating the presence of feeding difficulties\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. All questionnaire responses were reviewed for completeness and accuracy by research staff during interviews.\u003c/p\u003e \u003cp\u003eDietary intake was evaluated using 24-hour dietary recall conducted by trained research dietitians. Energy, macronutrient, and micronutrient analyses were performed using INMUCAL-Nutrients V.4.0 software developed by the Institute of Nutrition, Mahidol University, Thailand. Energy and nutrient intakes were then compared to the Thai Dietary Reference Intakes (Thai DRIs)\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAnthropometric data including weight, length/height, and body composition were measured by trained research assistants. Weight was recorded to the nearest 100 grams using a calibrated digital scale (Detecto 6129, Detecto, Missouri, USA), and length/height was measured to the nearest 0.1 cm using a length board (Seca 417, Seca, Hamburg, Germany) or a stadiometer (Detecto 6129, Detecto, Missouri, USA) depending on age. Each measurement was taken twice, and the average was used for analysis. Body composition was assessed using bioelectrical impedance analysis (King Chulalongkorn Memorial hospital site: InBody 770, Cerritos, CA, USA; Thammasat University and Srinagarind hospital sites: InBody 720, Cerritos, CA, USA) in participants aged 3 years and older. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m\u0026sup2;), and z-scores for weight-for-age (WFA), weight-for-height (WFH), and height-for-age (HFA) were derived using the WHO Anthro Survey Analyzer\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory Assessment\u003c/h2\u003e \u003cp\u003eFasting venous blood samples (8 mL) were collected for complete blood count (CBC), iron, total iron binding capacity (TIBC), 25-hydroxyvitamin D [25 (OH)D], zinc and hormonal analysis including ghrelin, peptide YY (PYY), leptin, insulin, insulin-like growth factor 1 (IGF-1) and insulin-like growth factor binding protein 3 (IGFBP-3)\u003c/p\u003e \u003cp\u003eOne milliliters of blood were collected in an EDTA tube for CBC, and an additional 4 milliliters were collected in a clot-activator tube for micronutrient analysis, including serum iron, TIBC, 25(OH)D, and zinc. CBC was analyzed using Sysmex XN-10 hematology analyser (XN-10, Sysmex, Kobe, Japan) while serum iron and TIBC were measured using the Ferene colorimetric method on an automated analyzer (Alinity, Abbott Laboratories, Illinois, USA) at each study site. For 25(OH)D and zinc analysis, blood samples were centrifuged at 1000 g for 10 minutes; plasma was then separated and stored at \u0026minus;\u0026thinsp;20\u0026deg;C before being transported to Chulalongkorn University for analysis. Serum 25(OH)D concentrations were determined using the chemiluminescent immunoassay (CLIA) method on the LIAISON\u0026reg; XL system (DiaSorin, Saluggia, Italy), and zinc levels were measured using flame atomic absorption spectrophotometry (PerkinElmer AAnalyst 400, PerkinElmer, Massachusetts, USA). The inter-assay coefficients of variation for all measurements were below 10%. Transferrin saturation (%) was calculated as the ratio of serum iron to TIBC. Iron deficiency was defined as a transferrin saturation of less than 15%\u003csup\u003e32\u003c/sup\u003e. Anemia was defined as a hemoglobin concentration of \u0026lt;\u0026thinsp;11 g/dL in children under 5 years of age and \u0026lt;\u0026thinsp;11.5 g/dL in children aged 5 years and older, according to World Health Organization criteria\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Iron deficiency anemia was defined as the presence of both anemia and iron deficiency. Vitamin D insufficiency was defined as a serum 25-hydroxyvitamin D [25(OH)D] concentration below 20 ng/mL\u003csup\u003e34\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor appetite hormones analysis, 1 mL of blood collected in clot-activator tubes containing a protease inhibitor cocktail (AEBSF, hydrochloride; Merck KGaA, Darmstadt, Germany) were used. Samples were centrifuged at 1,000 g for 10 minutes, and the supernatant was then aliquoted into 500 \u0026micro;L microtubes and stored at \u0026minus;\u0026thinsp;20\u0026deg;C until analysis. Appetite hormones were quantified using the Milliplex Human Metabolic Hormones Panel V3 (Merck KGaA, Darmstadt, Germany) via Luminex multiplex assays. This technology allowed simultaneous quantification of multiple hormones using color-coded microspheres coated with specific antibodies. The assay detection ranges for ghrelin, leptin, PYY, and insulin were 14\u0026ndash;10,000 pg/mL, 137\u0026ndash;100,000 pg/mL, 21\u0026ndash;15,000 pg/mL, and 206\u0026ndash;150,000 pg/mL, respectively. Detection sensitivities were 9.2 pg/mL for ghrelin, 27 pg/mL for leptin, 20.2 pg/mL for PYY, and 46.9 pg/mL for insulin. Intra- and inter-assay precision values were below 10% and 20%, respectively.\u003c/p\u003e \u003cp\u003eFor analysis of IGF-1 and IGFBP-3, 2 mL of blood was collected in a separate clotting tube and processed using the same centrifugation protocol. These hormones were measured using electrochemiluminescence immunoassay (ECLIA) on a Cobas\u0026reg; Pro analyzer (Roche Diagnostics, Tokyo, Japan), with inter-assay coefficients of variation ranging from 2.9\u0026ndash;3.1% for IGF-1 and 1.5\u0026ndash;2.0% for IGFBP-3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using Stata version 18.5 (StataCorp., College Station, TX, USA). Prior to analysis, the distribution of continuous variables was assessed for normality using histograms and the Kolmogorov-Smirnov test. Categorical variables such as sex, household income and primary caregiver were summarized using frequencies and percentages. Continuous variables, including age, birth weight and length, dietary intake, appetite scores, anthropometric measurements, levels of growth and appetite-related hormones as well as micronutrients were reported as mean with 95% confidence intervals. Comparisons between children with feeding difficulties and those without were conducted using Chi-square test and independent sample t-tests accordingly. All statistical tests were two-sided, with a p-value of less than 0.05 considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors sincerely thank Professor Chitsanu Pancharoen and the Chula Kids Club team for their invaluable support in participant recruitment. The authors also gratefully acknowledge Ms. Jiratchaya Sophonphan from the HIV Netherlands Australia Thailand Research Collaboration (HIV-NAT) at the Thai Red Cross AIDS Research Centre for her support with statistical analysis. Most importantly, the authors express their deep gratitude to all the children and families who generously participated in this study.\u003c/p\u003e\n\u003cp\u003e*The MARVEL study team\u003c/p\u003e\n\u003cp\u003eNathawan Khunsri\u003csup\u003e1\u003c/sup\u003e, Siriporn Khabuan\u003csup\u003e1\u003c/sup\u003e, Siriluck Poonkatkij\u003csup\u003e1\u003c/sup\u003e, Apichaya Khowijitpaisal\u003csup\u003e1\u003c/sup\u003e, Umroh laman1, Jutamat Tonglim\u003csup\u003e3\u003c/sup\u003e, Saranrat Boonsawat\u003csup\u003e3\u003c/sup\u003e, Warisara Deetienin\u003csup\u003e3\u003c/sup\u003e, Sakuntala Supasai\u003csup\u003e4\u003c/sup\u003e, Sasupang \u0026nbsp; Musikaboonleart\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study\u0026apos;s conception and design were carried out by OS and SC. Data collection involved OS, PT, SS, EM, KW, and the MARVEL study team. Data analysis and interpretation was conducted by OS and SC. OS wrote the first draft of the manuscript. SC edited and revised the manuscript. All authors jointly approved the final draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Ratchadapiseksompotch Fund, Faculty of Medicine, Chulalongkorn University, grant number RA67/009, and Danone Specialized Nutrition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData described in the manuscript, codebook, and analytic code will be made available upon request in a de-identified form.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was partially funded by Danone Specialized Nutrition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eApproval from the three Ethics Committees was obtained before start of the study, and was documented in a letter to the investigators specifying the date on which the committee met and granted the approval.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWritten informed consent was obtained from all parents/caregivers before inclusion in the study. The study was registered in Thai Clinical Trials Registry (no.\u0026nbsp;\u003c/strong\u003eTCTR 20220908004\u003cstrong\u003e). The study was conducted according to ICH-GCP principles, and in compliance with the principles of the \u0026lsquo;Declaration of Helsinki\u0026rsquo; (\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e75\u003csup\u003eth\u003c/sup\u003e WMA General Assembly, Helsinki, Finland, October 2024\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e) and with the Thai laws and regulations.\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWHO. \u003cem\u003eMalnutrition\u003c/em\u003e, (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/malnutrition\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/malnutrition\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Sanctis, V. et al. 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Metab.\u003c/em\u003e \u003cb\u003e101\u003c/b\u003e, 394\u0026ndash;415. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1210/jc.2015-2175\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1210/jc.2015-2175\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"malnutrition, feeding difficulties, body composition, growth hormones, appetite hormones","lastPublishedDoi":"10.21203/rs.3.rs-6641861/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6641861/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMalnutrition remains a global health concern, with feeding difficulties contributing to its development. This study is a cross-sectional analysis of baseline data from the MARVEL randomized controlled trial, which assessed the prevalence of feeding difficulties and compared nutritional and biological outcomes in children with and without feeding difficulties. 159 children aged 1–6 years with weight-for-height z-score between − 1SD to -3SD without diseases or medications affecting growth or appetite were recruited. Feeding difficulties were identified using the Montreal Children's Hospital Feeding Scale questionnaire. Dietary intake was evaluated via 24-hour dietary recall. Body composition was assessed using bioelectrical impedance analysis (aged ≥ 3 years). CBC, iron status, zinc,25(OH)D, IGF-1, IGFBP-3, and appetite hormones (ghrelin, leptin, peptideYY, insulin) were analysed. Feeding difficulties were present in 68% of the children. No significant differences in dietary intake, anthropometry, micronutrient status, or appetite hormones were found between groups. However, children with feeding difficulties had higher lean and skeletal muscle mass, significantly higher IGFBP-3, and a trend toward lower ghrelin. ID (Iron deficiency, transferrin saturation \u0026lt; 15%), ID anemia, and vitamin D insufficiency (25(OH)D \u0026lt; 20 ng/mL) were found in 18%, 4.7%, and 11% of children, respectively. Findings highlight the need for integrated nutritional and behavioral care in non-organic malnutrition.\u003c/p\u003e","manuscriptTitle":"Comparative Study of Body Composition, Micronutrient Status and Hormonal Profiles in Undernourished Children With Feeding Difficulties","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-25 09:49:47","doi":"10.21203/rs.3.rs-6641861/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"70de3db4-9db7-4955-bb17-37616430fe6a","owner":[],"postedDate":"June 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50355772,"name":"Health sciences/Health care"},{"id":50355773,"name":"Health sciences/Medical research"},{"id":50355774,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-05-20T07:53:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-25 09:49:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6641861","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6641861","identity":"rs-6641861","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}