Skip to main content

Mineral elements and adiposity-related consequences in adolescents with intellectual disabilities

Abstract

Background

Patients with intellectual disabilities are shown to have a limited capacity for cooperation, communication,and other biological consequences, which significantly require a specialized interest in healthcare professionals worldwide.

Aim

In this respect, the present study was designed to evaluate the levels mineral elements, and their correlation with oxidative stress markers and adiposity markers; leptin (L), adiponectin (A), and L/A ratio in adolescents with intellectual disabilities.

Methods

A total of 350 schoolchildren aged (12–18 years) were randomly invited to participate in this prospective, observational study. Only 300 participants agreed to participate in this study. According to Intelligence quotients scores (IQ) measured by WISC-III, the participants were classified into two groups; the healthy control group (no = 180; IQ = 90–114); and the moderate intellectual disability (MID) group (no = 120; IQ = 35–49). Adiposity markers; body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), physical activity scores, adipokines biomarkers; leptin, adiponectin, L/A ratio, oxidative stress, and plasma mineral elements were evaluated by prevalidated questionnaires, inductively coupled plasma-mass spectrometry (ICP-MS), colorimetric, and immunoassay techniques.

Results

Intellectual disability of moderate type was reported in 40% of the studied populations most of them are men aged 12–18 years (66.6% for men vs. 33.3 for females). Obesity was shown to be associated with the degree of intellectual disability of the students. There was a significant (P = 0.001) increase in the BMI, WHR, and WHtR scores as obesity markers with poor physical activity (P = 0.01) in students with poor disability compared to healthy controls (HC). The levels of leptin (P = 0.001), adiponectin (P = 0.01), and L/A ratio (P = 0.01) as adiposity biomarkers were significantly increased in students with MID compared to healthy controls. Also, oxidative stress measured by malondialdehyde (MDA) (P = 0.01) and total antioxidant capacity (TAC) (P = 0.01) were significantly increased in students with MID compared to healthy control subjects. In addition, mineral elements were shown to be linked with intellectual disability. The data showed that the levels of Fe, Mn, Zn, Hg, Pb, Ca, Cr, Mg, and Ni significantly (P = 0.001) increased, and the levels of Al, Na, K, Cu, and Zn/Cu ratio significantly (P = 0.001) decreased in subjects with MID compared to healthy controls. Correlation analysis concluded that changes in mineral elements significantly correlated with adiposity markers, oxidative stress, and the scores of intellectual disability (WISC III-IQ score).

Conclusion

The intellectual disability of moderate type (MID) was associated with abnormal changes in the levels of essential mineral elements and adipokines and increased levels of cellular oxidative stress. Thus, evaluating plasma mineral elements and adipokines levels could be a potential diagnostic parameter for diagnosing MID.

Peer Review reports

Introduction

Obesity is considered one of the most problematic issues of health worldwide. It affects all populations at different ages and socio-economic levels. Most studies reveal the contribution of obesity to human diseases, including diabetes mellitus [1, 2]. It becomes significantly associated with food containing high calories and poor physical activity. Several research studies linked obesity with economic, social, and lifestyle changes that lead to major public health problems [2,3,4]. In childhood, obesity is shown to be linked with several genetic and environmental factors. Lifestyle, social culture, and genealogy play a potential role in the spreading rates of obesity worldwide [4,5,6,7,8].

On biochemical and cellular levels, obesity is controlled by some proteins expressed from adipocytes, especially leptin. Leptin is a neurohormone (16 kDa) expressed by adipocytic cells and predominantly released into blood circulations. Physiologically, the release of leptin acts as a signal to the brain to control the storage of energy by the human body [9]. Thus, it was reported that leptin significantly controls food intake by inhibiting the release of Neuropeptide Y (NPY) through its hypothalamic receptors, reducing food intake with increased body thermogenesis [9].

Essential menirals and trace elements are cofactors essential for several cellular processes in human bodies. It plays potential roles in normal and diseased cells as regulatory, immunologic, or antioxidant factors, particularly as cofactors or essential components in the structures of cellular enzymes [10]. In obesity, trace elements are shown to be associated with the severity of the disease and its associated complications, such as peroxidation, inflammation, and metabolic disturbances [11, 12].

Previously, the deficiency in the levels of cellular micronutrients was reported to be significantly associated with fat deposition and chronic inflammation [13,14,15]. In addition, low levels of iron, zinc, and a deficiency in the levels of essential vitamins (A, E, and C) were estimated in children and adolescents with obesity compared to non obese controls of the same age [16,17,18,19]. These micronutrients, especially vitamins (A, E, and C), are essential for inhibiting or suppressing leptin expression [13, 20,21,22].

Several research studies reported a significant association between obesity levels and youth with intellectual and developmental disabilities. Obesity was significantly reported in children or adolescents with intellectual disabilities (ID). It was nearly twice the prevalence for those without ID (28.9% vs. 15.5%) [23, 24]. This may be related to poor physical activity and longer time spent sitting in front of screen-based media [25,26,27,28,29,30]. In childhood and adolescence, cognitive, behavioral, and neuropsychological defects; particularly ID, showed to be associated respectively with exposure to heavy metals such as arsenic (As), cadmium (Cd), manganese (Mn), mercury (Hg), and Lead (Pb) [31,32,33]. Reduced IQ and cognitive functions, learning difficulties, and impaired growth were reported in children with Pb blood levels above 10 μg·dL − 1 [34,35,36,37]. The pathophysiology of metal intoxication and producing intellectual or developmental defects may proceed with cellular free radical oxidative stress mechanisms [38, 39]. Higher malondialdehyde (MDA) and lower total antioxidant capacity (TAC) were reported as an indicator of cell membrane injury [38, 39]. In this respect, the present study was designed to evaluate the levels of mineral elements, and their correlation with oxidative stress markers and adiposity markers; leptin (L), adiponectin (A), and L/A ratio in adolescents with intellectual disabilities.

Materials and methods

Subjects

A total of 350 Saudi school students aged (12–18 years) attending various schools in Riyadh were randomly invited to participate in this study. Firstly, the school administration was notified about the need and importance of the study. Once necessary permission was obtained, they connected us with the students and their parents. Only 300 participants agreed to participate in this study. None of the selected participants have any physical disabilities, genetic disorders, or acute infections or received medical therapy for ID or obesity that had affected the data. Based on the intelligence quotients (IQ), the participants were classified into two groups; the normal healthy group (no = 180; IQ = 90–114); and the moderate ID group (no = 120; IQ = 35–49). Whole blood samples were collected from all participants and centrifuged ( 1 min at 1400 rpm), and the resulting plasma samples were kept frozen at—20°C until reused. Demographic and clinical data of the participants are in Table 1.

Table 1 Baseline of clinical and laboratory characteristics of the study groups. Healthy control (HC) and adolescents subjects suffering from moderate intellectual disabilities (MID) (n = 300; mean ± SD)

Ethical considerations

The current protocol was prepared according to the ethical guidelines of the 1975 Declaration of Helsinki and finally reviewed and approved by the ethics sub-committee of King Saud University, Kingdom of Saudi Arabia, under file number ID: RRC-2015–089. All participating schoolchildren were informed of the steps and all protocol details. The participants’ parents were assigned to return written informed consent before data collection.

Intelligence assessment

The participants’ intelligence quotients (IQ) were evaluated using a pre-validated Wechsler Intelligence Scale for Children (WISC-III), as previously reported [40, 41]. The results of IQ measured by WISC-III are categorized into seven scores; Mild intellectual disability (IQ 55–69), Moderate intellectual disability (IQ 40–54), below normal (IQ 70–84), normal (IQ 85–114), Above normal (IQ 115–129), Gifted (IQ 130–144), and Highly Gifted (IQ 145–160). In this study, IQ measurements of the participants were in the range of normal (IQ = 85–114; n = 180) and moderate (IQ = 40–54, n = 120), respectively.

Anthropometric measurements

All participants’ height and weight were estimated using standardized procedures such as a tape measure and calibrated Salter Electronic Scales (Digital Pearson Scale; ADAM Equipment Inc., Columbia, MD, USA), respectively. Validated universal cutoff values [42, 43] were used to calculate adiposity parameters, such as BMI and Waist-to-height ratio (WHtR), respectively.

Assessment of adiposity markers

Adiponectin and leptin levels as adiposity biomarkers were estimated in all participants' plasma samples using a specific ELISA kit (R&D Systems®, Minneapolis, USA). All samples were estimated in duplicate according to the manufacturer’s instructions to avoid inter-assay variation, as previously reported [44]. In contrast, the detection limits for adiponectin and leptin were 5 pg/mL, respectively [44].

Assessment of essential mineral elements concentrations

In this experiment, plasma samples of all participants were subjected to estimate mineral elements concentrations by using a Thermo Fisher Scientific (Waltham, MA, USA) iCAP— Q instrument, equipped with standard components and accessories: a MicroMist™ nebulizer (Glass Expansion, Port Melbourne, Australia) as previously reported [45]. This method used multi-element standard solutions (Plasma CAL, SCP Science, Baie D’Urfé, Canada) to prepare calibration standards. In addition, an iso standard solution (Madrid, Spain) was used to prepare the internal standard solution. Ten replicate measurements of the blank solution (2% v/v HNO3) were performed to calculate the limits of detection (LoD) as previously reported [45].

Assessment of oxidative stress

As a quantitative measure of lipid peroxidation, Malondialdehyde was estimated in the plasma samples using high-performance liquid chromatography, as mentioned previously [46,47,48]. In addition, a total antioxidant capacity (TAC), a measure of oxidative stress, was estimated in the plasma samples using a colorimetric assay kit (K274-100; BioVision, Milpitas, CA, USA). The antioxidant activity was measured as a function of Trolox concentration at a wavelength of (λ; 570 nm) as previously reported [47, 48].

Assessment of physical activity

Physical fitness score is measured as maximum oxygen uptake (VO2 max) and total energy expenditure (TEE), as previously reported [29, 47,48,49]. Total energy expenditure (TEE) was evaluated by calculating basal metabolic rates (BMR) from body mass, height, age, sex, and type of physical activity of all participants using a pre-validated equation as previously reported [29, 47, 48].

Statistical analysis

In this study, the statistical software SPSS version 18 was used. The results obtained were expressed as Mean, and standard deviation among groups, Kruskal–Wallis one-way ANOVA and post-hoc (Tukey HSD) test were used to compare the mean values of the studied variables [45]. Additionally, post hoc pairwise multiple comparisons using Bonferroni correction and the one-way analysis of covariance were performed to evaluate significant differences in trace elements hair contents between the study groups. The relationship between various study parameters was performed in steps by Spearman rank correlation analysis. The data obtained were considered significant at P < 0.05 [45].

Results

The clinical and baseline characteristics of 300 adolescents with a mean range of age 14.9 ± 1.5 years who participated in this prospective study are shown in Table 1.

In this study, intellectual disability of moderate type (MID; WISC-IR score:39.2 ± 3.1) was reported in 40% of the study population, most of whom are men (66.6% for men vs. 33.3 for females) (Table 1). Compared to healthy control subjects, adiposity markers; BMI, waist, hips, WHR, and WHtR significantly increased (P = 0.001) in adolescents with MID (Table 1). In addition, physical activity scores measured in terms of VO2 max, BMR, and TEE significantly decreased (P = 0.01) in adolescents with (MID) compared to those of healthy controls (HC), as shown in Table 1 and Fig. 1. Also, IQ-score was lower in adolescents with MID compared to healthy controls, as shown in Table 1 and Fig. 1.

Fig. 1
figure 1

Plasma levels of adiponectin, leptin (L), and L/A ratio (pg/mL) (A), MDA and TAC (B), along with physical activity (C), and IQ-score (D) in HC (n = 180) and MID (n = 120). **p < 0.01 (KruskaleWalis, Dunn’s post hoc test). ***p < 0.001 (KruskaleWalis, Dunn’s post hoc test). HC: healthy controls, MID: moderate intellectual disability; IQ: Intelligence quotients; MDA: malondialdehyde, TAC: total antioxidant capacity

In this study, plasma mineral elements were significantly estimated in all participants (Table 2). Adolescents with MID showed a significant increase in the levels of Fe, Mn, Zn, Hg, Pb, Ca, Cr, Mg, and Ni, and they significantly decreased in Al, Na, K, Cu, and Zn/Cu ratio levels compared to healthy controls (Table 2).

Table 2 Mineral elements levels (µg/g) in plasma samples of the study participants, reported as mean ± SD and (range) according to the intellectual disability status measured by the Wechsler Intelligence Scale test. (HC = healthy control; MID = moderate intellectual disabilities

The physiological changes in the plasma levels of mineral elements correlated positively with the WISC-IQ score, estimating the potential role of these elements in the pathogenesis of intellectual disability among younger ages with MID (Table 3). Moreover, the results showed that the increase in the levels of Fe, Mn, Zn, Hg, Pb, Ca, Cr, Mg, and Ni, and the decrease in the levels Al, Na, K, Cu, and Zn/Cu ratiocorrelated positively with the cellular oxidative stress parameters; MDA, TAC, and negatively with adiposity parameters; BMI, WHR, and WHtR as shown in (Table 4).

Table 3 Correlation between plasma mineral elements with WISC-IQ score as a measure of ID in healthy control (HC) and adolescents with MID
Table 4 Correlation between plasma mineral elements and adiposity parameters, WISC- IQ score,oxidative stress, and gender in adolescents with MID

However, increased or decreased levels of mineral elements showed no statistical significance with gender effect (Table 4). The increment of Fe, Mn, Zn, Hg, Pb, Ca, Cr, Mg, Ni, and decrement in the levels of Al, Na, K, Cu, and Zn/Cu ratio showed no significant effect with gender in subjects with ID (Table 4).

Also, leptin, adiponectin, and L/A ratio as adipokines biomarkers were estimated in all studied populations. Higher plasma levels of leptin and L/A ratio and lower adiponectin concentrations were reported in adolescents with MID (P = 0.001) compared with healthy controls (Fig. 1). In addition, MDA and TAC as parameters of oxidative stress were significantly evaluated in this study. The levels of MDA significantly increased, and TAC significantly decreased in adolescents with MID (P = 0.001) compared to healthy controls (Fig. 1).

In subjects with MID, the correlation between serum levels of adipokines and plasma mineral elements and clinically studied adiposity variables are shown in (Table 4). Leptin, adiponectin, and L/A as adiposity markers correlated negatively with BMI, WHtR, PA scores, and TAC and positively with gender, WISC-IQ score, MDA, and plasma trace elements (Table 5).

Table 5 Correlation between adipokines biomarkers with plasma mineral elements and clinically studied variables of adiposity in adolescents with MID

Regarding gender effect on physical activity, adipokines levels, and oxidative stress, girls with MID had lower physical activity scores than males in the same group (Fig. 2A). Also, higher leptin and L/A ratios with lower plasma adiponectin levels were reported in girls with MID compared to males of the same group (Fig. 2B, C and D). However, in normal control subjects, there were comparable levels of the studied parameters; leptin (p = 0.001), adiponectin (p = 0.001), and L/A ratio (p = 0.001) in boys compared to healthy girls as shown in Fig. 2B, C and D). In addition, a significant increase in the levels of MDA and a decrease in the levels of TAC activity were reported in girls (P = 0.001) compared to men of the same group ( Fig. 3A and B).

Fig. 2
figure 2

Effect of Gender on physical activity (A), plasma levels of adipokines (pg/mL); leptin (B), Adiponectin (C), and L/A ratio (D) in HC (n = 180) and adloscence withMID (n = 120). HC: healthy controls, MID: moderate intellectual diability. **p < 0.01. ***p < 0.001 ManneWhitney test

Fig. 3
figure 3

Effect of Gender on oxidative stress plasma levels MDA (A) and TAC (B) in HC (n = 180) and adloscence withMID (n = 120). *p < 0.01. **p < 0.001 Manne Whitney test. MDA: malondialdehyde, TAC: total antioxidant capcity, HC: healthy controls, MID: moderate intellectual diability

Discussion

Intellectual and developmental disabilities are broadly conceptualized to include a range of physical, mental, and behavioral impairments [26]. Patients with intellectual disabilities have been shown to have a limited capacity for cooperation, communication, and other biological consequences, which significantly requires a specialized interest from healthcare professionals worldwide [50, 51].

In this study, intellectual disability of moderate type (MID) was reported in 40% of the studied populations, most of whom are men aged 12–18 years (66.6% for men vs. 33.3 for females). The incidence of MID among the studied sample was linked with the release of adiposity markers; BMI, WHR, and WHtR, and lower physical activity compared to healthy control subjects. Matched with our results, obesity was significantly reported in children or adolescents with intellectual disabilities (ID); it was nearly twice the prevalence for those without ID (28.9% vs. 15.5%) [23, 24]. This may be related to poor physical activity and longer time spent sitting in front of screen-based media [26,27,28,29,30].

Supported data also recently reported that childhood overweight or obesity is clearly very pervasive or problematic among healthy children and those with ID [23, 52,53,54,55]. This is commonly attributed to poor physical activity and increased sedentary lifestyles, such as excess food intake and screen-based media use for longer periods [23, 52,53,54,55]. In addition, an elevated weight status among youth with ID is the leading risk for mental health problems and increased morbidity and mortality rates among adults with ID [55]. Thus, increasing physical activity and a self-monitoring diet were recommended among younger and older ages to yield clinically meaningful weight losses among adults with ID, reducing the severity of ID-related consequences [26, 56, 57].

Despite the prevalence of obesity increasing and prevailing among people with disabilities [58, 59], surprisingly, no or little attention has been paid to addressing the profile or potential roles of adipokines as measures of adiposity and metabolic disorders and oxidative stress (OS) among youth with disabilities [60].

In the present study, adiponectin and leptin, the most essential adipokines associated with adiposity and metabolic disorders, were estimated among adolescents e with ID disabilities. Changes in plasma levels of leptin, L/A ratio, and adiponectin are significantly associated with the incidence of ID among adolescents. Higher plasma levels of leptin and L/A ratio and lower adiponectin concentrations were significantly reported in adolescents with MID (P = 0.001) compared with the healthy controls.

In addition, MDA and TAC as parameters of oxidative stress were significantly evaluated in this study. The levels of MDA significantly increased, and TAC significantly decreased in adolescents with MID (P = 0.001) compared to the healthy controls.

In adolescents, obesity was associated with severe health complications such as mental disorders, long-term vascular complications, oxidative stress, and higher rates of severe metabolic syndrome [61, 62] previously. At younger ages, the lower levels of adiponectin and the higher levels of leptin were shown to be associated with the risk for mental health problems, particularly ID [26, 23, 52,53,54,55,56,57,58,59,60,61,62]. Similarly, the levels of OS measured by MDA were significantly higher, along with a reduction in TAC activity in persons with ID compared to the control group [38, 39, 46].

In this current study, leptin, adiponectin, and L/A were measured as markers of adiposity in subjects with ID correlated negatively with BMI, WHtR, PA scores, and TAC and positively with gender, WISC-IQ score, and MDA. A cascade of events characterized by an asymptomatic inflammatory process, including inflammatory cytokines along with oxidative stress significantly associated with the severity of intellectual disabilities (ID) among older and younger ages [46, 62, 63]. Thus, monitoring the levels of oxidative and adipokine molecules could serve as biomarkers of ID which may allow early diagnosis and intervention and improve the quality of care for persons with ID.

In obese people, the metabolic disturbances are decompensated. Although overweight is a preclinical condition, obesity is a clinically manifested metabolic disorder, including mineral imbalances [12], which could play a potential role in the pathogenesis of intellectual disabilities (ID).

In this study, plasma mineral elements were estimated in all participants. A significant increase in the levels of Fe, Mn, Zn, Hg, Pb, Ca, Cr, Mg, and Ni, and a decrease in the levels of Al, Na, K, Cu, and Zn/Cu ratio were reported in cases with MID compared to healthy controls. Changes in the levels of mineral elements correlated positively with plasma levels of adipokines; leptin, adiponectin, L/A ratio, MDA, TAC, and ID score (WISC-IQ score) and negatively with adiposity parameters; BMI, WHR, and WHtR. In addition, the increment of Fe, Mn, Zn, Hg, Pb, Ca, Cr, Mg, Ni, and decrement in the levels of Al, Na, K, Cu, and Zn/Cu ratio showed no significant effect with gender in subjects with ID.

Mineral elements as essential nutrients showed potential regulatory, immunologic, and antioxidant functions in biological systems [10]. Their potential action was significantly related to their incorporation as essential components or cofactors of enzymes throughout cellular metabolism [10]. Thus, it was reported that trace elements and minerals interfere with the pathogenesis of obesity and its complications, such as mental diseases, mainly through their involvement in the processes of peroxidation and inflammation [11]. Reduced IQ and cognitive functions, learning difficulties, and impaired growth were reported in children with Pb blood levels below 10 μg·dL − 1 [34,35,36,37]. Also, the pathophysiology of mental intoxication and producing intellectual or developmental defects may proceed via cellular free radical oxidative stress mechanisms [38, 39]. In recent studies, the levels of iron, copper, and zinc were lower in the plasma / serum of the children with intellectual disabilities compared to typically developing controls [64,65,66,67,68]. However, the relationship between physiological antagonists and intellectual activity is less clear. While some studies have suggested that excess intake of certain minerals can interfere with the absorption or utilization of other essential minerals [69,70,71], it is not clear how this affects cognitive function, and intellectual abilities in children and adolescents.

The usual normal human health needs adequate amounts of essential and trace elements with optimum levels either increasing or decreasing according to the vital cellular processes [72,73,74,75,76]. It was reviewed previously that the administration of selective antioxidants along with essential trace elements and minerals were required efficiently to reduce the extent of oxidative damage and related complications and to avoid serious diseases such as beta-thalassemia major and other brain-related disorders [76]. Elements and minerals should be present in the body in appropriate amounts and must be available for reacting with other elements to form critical molecules as well as to participate in various important chemical reactions [77].

According to the effect of gender, a clinical change in the levels of adipokines; leptin, adiponectin, L/A-ratio, oxidative stress; MDA, TAC, and detrimental changes in the levels of essential trace elements were reported in girls with MID compared to men of the same category.

In addition to that, the levels of adipokines and trace elements were clinically associated with adiposity parameters; BMI, WHR, WHtR, and the severity score (WISC-IQ score) of the severity of intellectual disabilities (ID). It was suggested previously that the inadequate ingress of trace elements into the biological cells may provide deleterious effects on different tissue functions and may lead to disease [78]. For this reason, analyzing changes to oligo-element concentrations in patients with MID could lead to a better understanding of any functional abnormalities associated with MID [78,79,80].

Finally, significant changes in plasma concentrations of plasma mineral elements were reported in obese adolescents with MID, which correlated positively with oxidative stress parameters; MDA, TAC, and adipokines; leptin, adiponectin, L/A ratios, and other related biomarkers of adiposity.

Strengthen and limitations

Our study had several limitations. Although our study generally showed the importance of identifying the levels of mineral elements and their association with obesity and intellectual disability scores among younger aged 12–18 individuals, the lack of association between compromised nutritional status due to factors such as feeding difficulties, limited food choices, and medication side effects should be addressed to evaluate long-lasting changes of mineral elements and their essential roles in the pathogenesis of intellectual disability among younger ages. Our results can be interpreted as preliminary findings. Thus, further studies based on long follow-ups are recommended to understand the potential association of mineral elements with intellectual activities.Therefore, individualized assessments of nutritional status and mineral intake are important for guiding appropriate interventions and monitoring the progress of intellectual abilities among children and adolescents. In addition, our study recommended that it is important for students with moderate intellectual disabilities to receive adequate levels of essential minerals in their diet to support their overall health and well-being. A balanced and varied diet that includes a variety of nutrient-dense foods can help ensure adequate mineral intake.

Conclusions

Moderate intellectual disability (MID) was associated with abnormal changes in essential mineral elements and adipokines levels and increased levels of cellular oxidative stress. Thus, evaluation of the plasma mineral and trace elements, and adipokines levels is used as a potential diagnostic parameter in diagnosing MID.

Availability of data and materials

All data generated or analyzed during this study are presented in the manuscript. Please contact the corresponding author for access to the data presented in this study.

References

  1. Al-Saleh E, Nandakumaran M, Al-Harmi J, Sadan T, Al-Enezi H. Maternal-fetal status of copper, iron, molybdenum, selenium, and zinc in obese pregnant women in late gestation. Biol Trace Elem Res. 2006;113:113–23.

    CAS  PubMed  Google Scholar 

  2. Zatterale F, Longo M, Naderi J, Raciti GA, Desiderio A, Miele C, et al. Chronic adipose tissue inflammation linking obesity to insulin resistance and type 2 diabetes. Front Physiol. 2020;29(10):1607.

    Google Scholar 

  3. Kumar R, Mal K, Razaq MK, Magsi M, Memon MK, Memon S, Afroz MN, Siddiqui HF, Rizwan A. Association of leptin with obesity and insulin resistance. Cureus. 2020;12(12): e12178.

    PubMed  PubMed Central  Google Scholar 

  4. Kojta I, Chacińska M, Błachnio-Zabielska A. Obesity, bioactive lipids, and adipose tissue inflammation in insulin resistance. Nutrients. 2020;12(5):1305.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Robinson E, Boyland E, Chisholm A, Harrold J, Maloney NG, Marty L, et al. Obesity, eating behavior and physical activity during COVID-19 lockdown: a study of UK adults. Appetite. 2021;156: 104853.

    PubMed  Google Scholar 

  6. Lobstein T, Baur L, Uauy R. IASO international obesity TaskForce: obesity in children and young people: a crisis in public health. Obes Rev. 2004;5(1):4–104.

    PubMed  Google Scholar 

  7. Krebs NF, Jacobson MS. American academy of pediatrics committee on nutrition: prevention of pediatric overweight and obesity. Pediatrics. 2003;112(2):424–30.

    PubMed  Google Scholar 

  8. Jurado-Castro JM, Gil-Campos M, Gonzalez-Gonzalez H, Llorente-Cantarero FJ. Evaluation of physical activity and lifestyle interventions focused on school children with obesity using accelerometry: a systematic review and meta-analysis. Int J Environ Res Public Health. 2020;17(17):6031.

    PubMed  PubMed Central  Google Scholar 

  9. Thaler JP, Schwartz MW. Minireview: inflammation and obesity pathogenesis: the hypothalamus heats up. Endocrinology. 2010;151:4109–15.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Pengelly CD, Morris J. Body mass index and weightdistribution. Scott Med J. 2009;54(3):17–21.

    CAS  PubMed  Google Scholar 

  11. Hu K, Staiano AE. Trends in obesity prevalence among children and adolescents aged 2 to 19 years in the US from 2011 to 2020. JAMA Pediatr. 2022;176(10):1037–9.

    PubMed  PubMed Central  Google Scholar 

  12. Ben-Sefer E, Ben-Natan M, Ehrenfeld M. Childhood obesity: current literature, policy and implications for practice. Int Nurs Rev. 2009;56(2):166–73.

    CAS  PubMed  Google Scholar 

  13. García OP, Long KZ, Rosado JL. Impact of micronutrient deficiencies on obesity. Nutr Rev. 2009;67(10):559–72.

    PubMed  Google Scholar 

  14. García OP, Ronquillo D, Caamaño MD, Camacho M, Long KZ, Rosado JL. Zinc, vitamin A, and vitamin C status are associated with leptin concentrations and obesity in Mexican women: results from a cross-sectional study. Nutr Metab. 2012;9:1–9.

    Google Scholar 

  15. Zavala G, Long KZ, García OP, del Carmen CM, Aguilar T, Salgado LM, et al. Specific micronutrient concentrations are associated with inflammatory cytokines in a rural population of Mexican women with a high prevalence of obesity. Br J Nutr. 2013;109(4):686–94.

    CAS  PubMed  Google Scholar 

  16. Aeberli I, Hurrell RF, Zimmermann MB. Overweight children have higher circulating hepcidin concentrations and lower iron status but have dietary iron intakes and bioavailability comparable with normal weight children. Int J Obes (Lond). 2009;33:1111–7.

    CAS  PubMed  Google Scholar 

  17. da Silva LD, da Veiga GV, Ramalho RA. Association of serum concentrations of retinol and carotenoids with overweight in children and adolescents. Nutrition. 2007;23:392–7.

    Google Scholar 

  18. Huang J, Weinstein SJ, Moore SC, Derkach A, Hua X, Liao LM, et al. Serum metabolomic profiling of all-cause mortality: a prospective analysis in the alpha-tocopherol, beta-carotene cancer prevention (ATBC) study cohort. Am J Epidemiol. 2018;187(8):1721–32.

    PubMed  PubMed Central  Google Scholar 

  19. Molnar D, Decsi T, Koletzko B. Reduced antioxidant status in obese children with multimetabolic syndrome. Int J Obes Relat Metab Disord. 2004;28:1197–202.

    CAS  PubMed  Google Scholar 

  20. Garcia-Diaz DF, Campion J, Milagro FI, Boque N, Moreno-Aliaga MJ, Martinez JA. Vitamin C inhibits leptin secretion and some glucose/lipid metabolic pathways in primary rat adipocytes. J Mol Endocrinol. 2010;45:33–43.

    CAS  PubMed  Google Scholar 

  21. Kelishadi R, Hashemipour M, Adeli K, Tavakoli N, Movahedian-Attar A, Shapouri J, et al. Effect of zinc supplementation on markers of insulin resistance, oxidative stress, and inflammation among prepubescent children with metabolic syndrome. Metab Syndr Relat Disord. 2010;8:505–10.

    CAS  PubMed  Google Scholar 

  22. Shen XH, Tang QY, Huang J, Cai W. Vitamin E regulates adipocytokine expression in a rat model of dietary-induced obesity. Exp Biol Med (Maywood). 2010;235:47–51.

    PubMed  Google Scholar 

  23. Grondhuis SN, Aman MG. Overweight and obesity in youth with developmental disabilities: a call to action. J Intellect Disabil Res. 2014;58:787–99.

    CAS  Google Scholar 

  24. Phillips KL, Schieve LA, Visser S, Boulet S, Sharma AJ, Kogan MD, et al. Prevalence and impact of unhealthy weight in a national sample of US adolescents with autism and other learning and behavioral disabilities. Matern Child Health J. 2014;18:1964–75.

    PubMed  PubMed Central  Google Scholar 

  25. Slevin E, Truesdale-Kennedy M, McConkey R, Livingstone B, Fleming P. Obesity and overweight in intellectual and non-intellectually disabled children. J Intellect Disabil Res. 2014;58:211–20.

    CAS  PubMed  Google Scholar 

  26. Bennett EA, Kolko RP, Chia L, Elliott JP, Kalarchian MA. Treatment of obesity among youth with intellectual and developmental disabilities: an emerging role for telenursing. West J Nurs Res. 2017;39(8):1008–27. https://doi.org/10.1177/0193945917697664.

    Article  PubMed Central  Google Scholar 

  27. Segal M, Eliasziw M, Phillips S, Bandini L, Curtin C, Kral T, et al. Intellectual disability is associated with increased risk for obesity in a nationally representative sample of U.S. children. Disabil Health J. 2016;9:392–8.

    PubMed  Google Scholar 

  28. Stanish HI, Curtin C, Must A, Phillips S, Maslin M, Bandini LG. Physical activity enjoyment, perceived barriers, and beliefs among adolescents with and without intellectual disabilities. J Phys Act Health. 2016;13:102–10.

    PubMed  Google Scholar 

  29. Alghadir AH, Iqbal ZA, Gabr SA. Differences among Saudi and expatriate students: body composition indices, sitting time associated with media use and physical activity pattern. Int J Environ Res Public Health. 2020;17(3):E832. https://doi.org/10.3390/ijerph17030832.

    Article  Google Scholar 

  30. Curtin C, Bandini LG, Must A, Gleason J, Lividini K, Phillips S, et al. Parent support improves weight loss in adolescents and young adults with down syndrome. J Pediatr. 2013;163:1402–8.

    PubMed  Google Scholar 

  31. Rodríguez-Barranco M, Lacasaña M, Aguilar-Garduño C, Alguacil J, Gil F, González-Alzaga B, et al. Association of arsenic, cadmium and manganeseexposure with neurodevelopment and behavioural disorders in children: a systematic review andmeta-analysis. Sci Total Environ. 2013;454:562–77.

    PubMed  Google Scholar 

  32. Grandjean P, Weihe P, Debes F, Choi AL, Budtz-Jørgensen E. Neurotoxicity from prenatal and postnatal exposure to methylmercury. Neurotoxicol Teratol. 2014;43:39–44.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Khan K, Wasserman GA, Liu X, Ahmed E, Parvez F, Slavkovich V, et al. Manganese exposure from drinking water and children’s academic achievement. Neurotoxicology. 2012;33:91–7.

    CAS  PubMed  Google Scholar 

  34. Selevan SG, Rice DC, Hogan KA, Euling SY, Pfahles-Hutchens A, Bethel J. Blood lead concentration and delayed puberty in girls. N Engl J Med. 2003;348:1527–36.

    CAS  PubMed  Google Scholar 

  35. Kim Y, Cho S-C, Kim B-N, Hong Y-C, Shin M-S, Yoo H-J, et al. Association between blood lead levels(<5μg/dL)and inattention-hyperactivity and neurocognitive profiles in school-aged Korean children. Sci Total Environ. 2010;408:5737–43.

    CAS  PubMed  Google Scholar 

  36. Bellinger DC. Prenatal exposures to environmental chemicals and children’s neurodevelopment: An update. Saf Health Work. 2013;4:1–11.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Vigeh M, Yokoyama K, Matsukawa T, Shinohara A, Ohtani K. Low level prenatal blood lead adversely affects early childhood mental development. J Child Neurol. 2014;29(10):1305–11. https://doi.org/10.1177/0883073813516999.

    Article  PubMed  Google Scholar 

  38. Koivula MJ, Kanerva M, Salminen J-P, Nikinmaa M, Eeva T. Metal pollution indirectly increases oxidative stress in great tit (Parus major) nestlings. Environ Res. 2011;111:362–70.

    CAS  PubMed  Google Scholar 

  39. Grotto D, Santa Maria L, Boeira S, Valentini J, Charão M, Moro A, et al. Rapid quantification of malondialdehyde in plasma by high performance liquid chromatography-visible detection. J Pharm Biomed Anal. 2007;43:619–24.

    CAS  PubMed  Google Scholar 

  40. Canivez G, Watkins M. Exploratory and higher-order factor analyses of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) adolescent subsample. Sch Psychol Q. 2010;25(4):223–35.

    Google Scholar 

  41. Wechsler D. Wechsler adult intelligence scale–Fourth Edition (WAIS–IV). Vol. 22(498). San Antonio: NCS Pearson; 2008. p. 1.

  42. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. Br Med J. 2000;320:1–6.

    Google Scholar 

  43. Fan Y, Wang R, Ding L, Meng Z, Zhang Q, Shen Y, et al. Waist circumference and its changes are more strongly associated with the risk of type 2 diabetes than body mass index and changes in body weight in Chinese adults. J Nutr. 2020;150(5):1259–65.

    PubMed  Google Scholar 

  44. Al-Rawaf HA. Circulating microRNAs and adipokines as markers of metabolic syndrome in adolescents with obesity. Clin Nutr. 2019;38(5):2231–8. https://doi.org/10.1016/j.clnu.2018.09.024.

    Article  CAS  PubMed  Google Scholar 

  45. Cabral Pinto MM, Marinho-Reis P, Almeida A, Pinto E, Neves O, Inácio M, et al. Links between cognitive status and trace element levels in hair for an environmentally exposed population: A case study in the surroundings of the estarreja industrial area. Int J Environ Res Public Health. 2019;16(22):4560. https://doi.org/10.3390/ijerph16224560.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Carmeli E, Imam B, Bachar A, Merrick J. Inflammation and oxidative stress as biomarkers of premature aging in persons with intellectual disability. Res Dev Disabil. 2012;33(2):369–75.

    PubMed  Google Scholar 

  47. Alghadir AH, Gabr SA, Al-Eisa ES. Effects of moderate aerobic exercise on cognitive abilities and redox state biomarkers in older adults. Oxid Med Cell Longev. 2016;2016:2545168. https://doi.org/10.1155/2016/2545168.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Alghadir AH, Gabr SA, Anwer S, Al-Eisa E. Fatigue and oxidative stress response to physical activity in type 2 diabetic patients. Int J Diabetes Dev Ctries. 2016;36:59–64.

    CAS  Google Scholar 

  49. Rusdiana A. Analysis differences of Vo2max between direct and indirect measurement in badminton, cycling and rowing. Int J Appl Exerc Physiol. 2020;9(3):162–70.

    Google Scholar 

  50. Zhou N, Wong HM, Wen YF, Mcgrath C. Oral health status of children and adolescents with intellectual disabilities: a systematic review and meta-analysis. Dev Med Child Neurol. 2017;59:019–1026.

    Google Scholar 

  51. Oliveira JS, Prado Júnior RR, de Sousa Lima KR, de Oliveira AH, Moita Neto JM, Mendes RF. Intellectual disability and impact on oral health: a paired study. Spec Care Dentist. 2013;33(6):262–8.

    PubMed  Google Scholar 

  52. Collins K, Staples K. The role of physical activity in improving physical fitness in children with intellectual and developmental disabilities. Res Dev Disabil. 2017;69:49–60.

    PubMed  Google Scholar 

  53. Martínez-Leal R, Salvador-Carulla L, Gutiérrez-Colosía MR, Nadal M, Novell-Alsina R, Martorell A, et al. Health among persons with intellectual disability in Spain: the European POMONA-II study. Rev Neurol. 2011;53(7):406–14.

    PubMed  Google Scholar 

  54. Smyth P, McDowell C, Leslie JC, Leader G, Donnelly M, Simpson E, et al. Managing weight: what do people with an intellectual disability want from mobile technology? Stud Health Technol Inform. 2017;242:273–8.

    PubMed  Google Scholar 

  55. Basil JS, Santoro SL, Martin LJ, Healy KW, Chini BA, Saal HM. Retrospective study of obesity in children with Down Syndrome. J Pediatr. 2016;173:143–8.

    PubMed  Google Scholar 

  56. Martínez-Zaragoza F, Campillo-Martínez J, Ato-García M. Effects on physical health of a multicomponent programme for overweight and obesity for adults with intellectual disabilities. J Appl Res Intellect Disabil. 2016;29(3):250–65.

    PubMed  Google Scholar 

  57. Lobenius-Palmér K, Sjöqvist B, Hurtig-Wennlöf A, Lundqvist LO. Accelerometer-assessed physical activity and sedentary time in youth with disabilities. Adapt Phys Activ Q. 2017;26:1–19.

    Google Scholar 

  58. Mikulovic J, Marcellini A, Compte R, Duchateau G, Vanhelst J, Fardy PS, et al. Prevalence of overweight in adolescents with intellectual deficiency: Differences in socio-educative context, physical activity and dietary habits. Appetite. 2011;56:403–7.

    PubMed  Google Scholar 

  59. Weil E, Wachterman M, McCarthy EP, Davis RB, O’Day B, Iezzoni LI, et al. Obesity among adults with disabling conditions. JAMA. 2002;288(10):1265–8.

    PubMed  Google Scholar 

  60. Fasshauer M, Bluher M. Adipokines in health and disease. Trends Pharmacol Sci. 2015;36(7):461e70.

    Google Scholar 

  61. Philips EM, Santos S, Trasande L, Aurrekoetxea JJ, Barros H, von Berg A, et al. Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: An individual participant data meta-analysis of 229,000 singleton births. PLoS Med. 2020;17(8): e1003182.

    PubMed  PubMed Central  Google Scholar 

  62. Weiss R, Dziura J, Burgert TS, Tamborlane WV, Taksali SE, Yeckel CW, et al. Obesity and the metabolic syndrome in children and adolescents. N Engl J Med. 2004;350(23):2362e74.

    Google Scholar 

  63. Pérez-Pérez A, Vilariño-García T, Fernández-Riejos P, Martín-González J, Segura-Egea JJ, Sánchez-Margalet V. Role of leptin as a link between metabolism and the immune system. Cytokine Growth Factor Rev. 2017;35:71–84. https://doi.org/10.1016/j.cytogfr.2017.03.001.

    Article  CAS  PubMed  Google Scholar 

  64. Behl S, Mehta S, Pandey MK. Abnormal levels of metal micronutrients and autism spectrum disorder: a perspective review. Front Mol Neurosci. 2020;13:586209. https://doi.org/10.3389/fnmol.2020.586209.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Skalny AV, Mazaletskaya AL, Ajsuvakova OP, Bjørklund G, Skalnaya MG, Chernova LN, et al. Magnesium status in children with attention-deficit/hyperactivity disorder and/or autism spectrum disorder. Soa Chongsonyon Chongsin Uihak. 2020;31(1):41–5. https://doi.org/10.5765/jkacap.190036.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Barišić A, Ravančić ME, Majstorivić D, Vraneković J. Micronutrient status in children and adolescents with Down syndrome: systematic review and meta-analysis. J Intellect Disabil Res. 2023;67(8):701–19. https://doi.org/10.1111/jir.13042.

    Article  PubMed  Google Scholar 

  67. Grabeklis AR, Skalny AV, Skalnaya AA, Zhegalova IV, Notova SV, Mazaletskaya AL, et al. Hair mineral and trace element content in children with down’s syndrome. Biol Trace Elem Res. 2019;188:230–8.

    CAS  PubMed  Google Scholar 

  68. Fiore M, Barone R, Copat C, Grasso A, Cristaldi A, Rizzo R, et al. Metal and essential element levels in hair and association with autism severity. J Trace Elem Med Biol. 2020;57: 126409.

    CAS  PubMed  Google Scholar 

  69. Beard JL. Iron biology in immune function, muscle metabolism and neuronal functioning. J Nutr. 2001;131(2S-2):568S-579S. https://doi.org/10.1093/jn/131.2.568S. discussion 580S.

    Article  CAS  PubMed  Google Scholar 

  70. Murray-Kolb LE, Beard JL. Iron treatment normalizes cognitive functioning in young women. Am J Clin Nutr. 2007;85(3):778–87. https://doi.org/10.1093/ajcn/85.3.778.

    Article  CAS  PubMed  Google Scholar 

  71. Hambidge KM, Krebs NF. Zinc deficiency: a special challenge. J Nutr. 2007;137(4):1101–5. https://doi.org/10.1093/jn/137.4.1101.

    Article  CAS  PubMed  Google Scholar 

  72. Osredkar J, Sustar N. Copper and zinc, biological role and significance of copper/zinc imbalance. J Clinic Toxicol S. 2011;3(2161):0495.

    Google Scholar 

  73. Rao TS, Asha MR, Ramesh BN, Rao KJ. Understanding nutrition, depression and mental illnesses. Indian J Psychiatry. 2008;50(2):77.

    PubMed  PubMed Central  Google Scholar 

  74. Li Z, Liu Y, Wei R, Yong VW, Xue M. The important role of zinc in neurological diseases. Biomolecules. 2022;13(1):28.

    PubMed  PubMed Central  Google Scholar 

  75. Indika NL, Frye RE, Rossignol DA, Owens SC, Senarathne UD, Grabrucker AM, et al. The rationale for vitamin, mineral, and cofactor treatment in the precision medical care of autism spectrum disorder. J Personal Med. 2023;13(2):252.

    Google Scholar 

  76. Shazia Q, Mohammad ZH, Rahman T, Shekhar HU. Correlation of oxidative stress with serum trace element levels and antioxidant enzyme status in Beta thalassemia major patients: a review of the literature. Anemia. 2012;2012: 270923.

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Zoroddu MA, Aaseth J, Crisponi G, Medici S, Peana M, Nurchi VM. The essential metals for humans: a brief overview. J Inorg Biochem. 2019;195:120–9.

    CAS  PubMed  Google Scholar 

  78. Bhattacharya PT, Misra SR, Hussain M. Nutritional aspects of essential trace elements in oral health and disease: an extensive review. Scientifica (Cairo). 2016;2016:1–12. https://doi.org/10.1155/2016/5464373.

  79. Alghadir AH, Gabr SA, Al-Eisa E. Effects of physical activity on trace elements and depression related biomarkers in children and adolescents. Biol Trace Elem Res. 2016;172(2):299–306. https://doi.org/10.1007/s12011-015-0601-3.

  80. Watanabe K, Tanaka T, Shigemi T, Hayashida Y, Maki K. Mn and Cu concentrations in mixed saliva of elementary school children in relation to sex, age, and dental caries. J Trace Elem Med Biol. 2009;23:93–9.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the Researchers Supporting Project number (RSP2023R382), King Saud University, Riyadh, Saudi Arabia for funding this research.

Funding

The study was funded by the Researchers Supporting Project number (RSP2023R382), King Saud University, Riyadh, Saudi Arabia.

Author information

Authors and Affiliations

Authors

Contributions

G.S.A. A.H.A. and A.I. proposed the study conception and design. G.S.A. completed the practical work. G.S.A. collected data. G.S.A. and A.I. contributed to the data analysis. A.H.A. G.S.A. and A.I. contributed to data interpretation. A.H.A. G.S.A. and A.I. prepared the manuscript’s initial draft. A.H.A. critically reviewed and edited the intellectual content of the manuscript. All authors read, understood, reviewed, and approved the manuscript’s final version to be submitted/published and took responsibility for the intellectual content of the same manuscript.

Corresponding author

Correspondence to Amir Iqbal.

Ethics declarations

Ethics approval and consent to participate

The study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki. It was reviewed and approved by the Ethics Sub-Committee of King Saud University, Saudi Arabia, under file number ID: RRC-2015–089. The study’s aims and risks were explained to all participants, and their written informed consent was obtained before starting the study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests, either financial or non-financial.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Alghadir, A.H., Gabr, S.A. & Iqbal, A. Mineral elements and adiposity-related consequences in adolescents with intellectual disabilities. BMC Mol and Cell Biol 24, 29 (2023). https://doi.org/10.1186/s12860-023-00490-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12860-023-00490-5

Keywords