Nearly 18% of U.S. children aged 2–18 years have obesity.1 Childhood obesity is associated with cardiometabolic comorbidities in childhood and later in life.2–6 Thus the identification of antecedents and correlates of adiposity and cardiometabolic risk is critical to inform early opportunities for targeted obesity prevention. Both prenatal (maternal) and childhood (mainly sedentary lifestyle and unhealthy dietary habits) risk factors contribute to obesity and its complications in children.3,7 Emerging data indicate that metals may play critical roles in driving obesity and cardiometabolic risks in children and adults.8–13
Exposure to toxic metals is widespread.
Metals are present in living tissues in small amounts. Some of them are nutritious/essential metals (e.g., selenium [Se], magnesium [Mg], iron [Fe], and zinc [Zn]) while others are toxic/non-essential metals (e.g., arsenic [As], lead [Pb], mercury [Hg], and cadmium [Cd]) that have deleterious effects on health via accumulation in vital organs and displacement of vital nutritious metals. The National Health and Nutrition Examination Survey (NHANES) data showed that 75% of US individuals ≥6 years of age were exposed to two or three toxic metals (As, Pb, Hg, and Cd).14 Exposure to toxic metals typically occurs via drinking water and contaminated foods like seafood and rice.15,16 Half-life of these toxic metals in blood is about 1–4 months.17–19
Exposure to toxic metals may contribute to childhood obesity.
Some human studies have assessed the cross-sectional associations of individual toxic metal in blood, i.e. As,20 Pb,21–23 Hg,21,24 and Cd,25 with childhood obesity risk; however, results are inconsistent (Table 1). , owing to limitations of study design – namely, cross-sectional data, small sample size, inadequate control for major confounders (maternal pre-pregnancy body mass index [BMI], and children’s birth weight, dietary intake, and physical activity), and reliance on anthropometric measures rather than direct measures of adiposity.
Table. 1.
Previous studies on the association between blood metals and the risk of childhood obesity
| Metals | Specimen | Study design | No. of samples | Age of child, years | BMI/waist measures | DXA/MRI measures | Temporal changes | Adjusting for major factors* | Replication study | Association |
|---|---|---|---|---|---|---|---|---|---|---|
| Arsenic20 | Urinary | Cross-sectional | 835 | 12–19 | BMI | No | No | No | No | None |
| Lead 21 | Blood | Cross-sectional | 5404 | 6–19 | BMI | No | No | No | No | Inverse |
| Lead 23 | Blood | Cross-sectional | 1271 | 2–15 | BMI | No | No | Yes | No | Positive |
| Mercury 21 | Blood | Cross-sectional | 5404 | 6–19 | BMI | No | No | No | No | None |
| Mercury 24 | Blood | Cross-sectional | 1567 | 10–19 | BMI/waist | No | No | No | No | Positive |
| Cadmium 25 | Blood | Case-control | 320 | 10–18 | BMI | No | No | No | No | None |
| Selenium 21 | Blood | Cross-sectional | 5404 | 6–19 | BMI | No | No | No | No | None |
| Selenium 34 | Blood | Cross-sectional | 117 | 7–13 | BMI | No | No | Birth weight | No | Inverse |
| Selenium 35 | Blood | Case-control | 80 | 6–17 | BMI | No | No | No | No | Inverse |
| Magnesium 43 | Blood | Cross-sectional | 203 | 11–12 | BMI | No | No | No | No | Inverse |
| Magnesium 44 | Blood | Case-control | 140 | 2–14 | BMI | No | No | No | No | Inverse |
| Iron (7 studies)45 | Blood | Cross-sectional | Meta-analysis | <18 | BMI | No | No | No | No | Inverse |
| Zinc 21 | Blood | Cross-sectional | 5404 | 6–19 | BMI | No | No | No | No | Inverse |
| Zinc 47 | Blood | Case-control | 1178 | 5–18 | BMI | No | No | No | No | Inverse |
Major risk factors include maternal pre-pregnancy BMI and smoking, and children’s birth weight, dietary intake, and physical activity.
As:
As is a ubiquitous mineral present in various compounds, and is widely distributed in the soil and water.15,16 Both in vitro and in vivo studies have found that As can significantly decrease the size of adipocytes or white adipose tissue.26 Limited evidence from cross-sectional study has been inconsistent in linking As exposure to BMI or the risk of childhood obesity.20
Pb:
Pb exposure remains widespread due to continued use in batteries and prior use in house paint and plumbing.14 Early-life Pb exposure was associated with increased body weight in mice.27,28 However, human studies among children are very few and cross-sectional (Table 1). An analysis of the U.S. NHANES21 and one small U.S. study22 indicated an inverse association between blood Pb levels and childhood overweight risk; however, these two studies did not consider significant confounders such as maternal pre-pregnancy BMI and children’s birth weight, dietary intake, and physical activity. Recently, another study in Boston found a non-significantly positive association between blood Pb levels and childhood obesity risk.23
Hg:
Hg is a widespread environmental toxicant and pollutant. The primary sources of chronic low-level mercury exposure in humans are fish or seafood consumption (methylmercury, MeHg) and dental amalgams (mercury vapor, Hg0). Laboratory studies indicate that exposure to methylmercury may induce oxidative stress and cause pancreatic islet β-cell dysfunction, suggesting that mercury exposure may be a risk factor for obesity.29 The Korea NHANES found a positive cross-sectional association between blood mercury levels and obesity risk among children;24 however, an analysis of U.S. NHANES data did not support adverse effects of methylmercury on childhood obesity risk (Table 1).21
Cd:
Cd is a ubiquitous heavy metal present in the environment. Smoking cigarettes accounts for a significant portion of human exposure to Cd, while diet (shellfish, organ meats, green leafy and root vegetables, and whole grains) is the primary source of Cd exposure among non-smokers.17 Experimental studies have observed the influence of Cd on adipose tissue pathophysiology via reducing adipocyte size30,31 and decreasing numbers of insulin receptors and insulin receptor density in adipocytes.32 Only one human case-control study indicated no relation of blood Cd with childhood obesity risk (Table 1);25 however, this study did not control significant confounders in the analysis.
Se:
Se is an essential element and is increasingly used in enriched foods, supplements, and fertilizers in the U.S. In addition to its role in enzyme function, selenium is involved in the complex system of defense against oxidative stress through selenium-dependent glutathione peroxidases and other selenoproteins.33 Although Se may be protective against obesity development in theory, epidemiological data on Se and childhood obesity risk are limited (Table 1).21,34,35 Two cross-sectional studies conducted in China34 and Poland35 found that blood Se levels were inversely related to childhood obesity risk. However, there was no association between serum Se and childhood obesity risk in the U.S. NHANES without adjustment for significant confounders.21
Mg:
Mg is an essential metabolic cofactor for over 300 enzymatic reactions involved in human metabolism.36 Theoretically, Mg could have an anti-obesity effect because Mg can form soaps with fatty acids in the intestine and thus reduce the digestible energy content of the diet.37,38 Epidemiological studies have indicated that Mg may attenuate the development of insulin resistance39,40 and type 2 diabetes among adults.40–42 However, only two small cross-sectional/case-control studies found lower Mg concentrations among children with obesity compared to children without obesity (Table 1).43,44
Fe:
Fe is an essential component of hemoglobin, an erythrocyte (red blood cell) protein that transfers oxygen from the lungs to the tissues. A meta-analysis of 26 cross-sectional and case-control studies found that overweight/obese participants had lower serum iron concentrations compared with non-overweight participants (Table 1).45
Zn:
Zn is another essential mineral with antioxidant activity and functions related to energy metabolism.46 Moreover, zinc has been shown to serve a regulatory role in several signaling pathways, including potentiation of leptin and insulin signaling.46 One recent meta-analysis of 15 case-control studies indicated that blood Zn levels were lower in children with obesity as compared to the non-obese controls (Table 1),47 and the cross-sectional analysis from the U.S. NHANES supported this finding.21
Gender specific associations:
Few studies have assessed there are gender differences in the effects and association of metals with childhood obesity and metabolic disorder risk. The cross-sectional analysis from the U.S. NHANES found almost same associations of Pb and Zn with childhood obesity between boys and girls.21
The importance of considering metal mixtures.
As a counterpart to toxic metals, nutritious metals are derived from dietary consumption of plants and animals or from drinking water and ingesting specific foods rich or dietary supplements. They function primarily as catalysts for enzyme function, including activating cofactors and coenzymes that control metabolism, genetic transcription, and oxidative stress. Nutritious metals also play a role in lipid and carbohydrate metabolism.13 Mg is one of the indispensable metal elements in the human body, and Se, Fe, and Zn are essential metals. Considering the co-exposure of toxic and nutritious metals is crucial as biological interactions occur via synergistic or antagonistic mechanisms.48–50 When toxic and nutritious metals co-occur, the effects of toxic metals are stronger than the protective effects of nutritious metals in the early stages of life, bearing long-lasting consequences on health that manifest in childhood and track into adulthood. Very few studies have explored the toxic metal mixtures in relation to obesity in adults,51 and only one study from the member of our group has examined the associations of prenatal toxic and nutritional metal mixtures with obesity risk in childhood.52 Moreover, we are not aware of any studies that assessed change in metal exposure in relation to cardiometabolic outcomes – an important inquiry that will shed light on the extent to which interventions to reduce metal exposure can mitigate disease risk.
Blood as the bio-specimen for assessing chronic metal exposure.
Although the primary source of most metals is via intakes of foods and beverages, use of dietary assessment methods like the food frequency questionnaire and 24-hour recall may not accurately reflect intake of metals because of relatively low content and wide variation in metal content of the same foods grown in different areas.13 Thus, use of biochemical markers of metal intake is ideal for establishing chronic exposure. Whole blood measures are widely used to estimate whole As,53 Pb,21–23 Hg,21,24 Cd,25 Se,21,34,35 Mg,43,44 Fe,45,54 and Zn21,47 exposures in epidemiological studies because the biological half-life of most metals in the blood is 1–4 months. Nail measurements provide relatively long-term exposure and urinary measurements provide relatively very short-term exposure of most metals.
In conclusion, the association of some metals with childhood obesity risk have not been well established because prior studies are largely limited by: 1) the cross-sectional or case-control design, small sample size, inadequate control for major confounders, lack of replication, or reliance on anthropometric measures rather than direct measures of adiposity; and 2) no studies that analyzed if temporal changes in minerals are related to the changes in adiposity risk although minerals are modified by changes in dietary habits. Thus, well-designed studies and careful consideration of confounding variables and interactions are needed.
Highlights.
The association of some metals with childhood obesity risk have not been well established because prior studies are largely limited by: 1) the cross-sectional or case-control design, small sample size, inadequate control for major confounders, lack of replication, or reliance on anthropometric measures rather than direct measures of adiposity; and 2) no studies that analyzed if temporal changes in minerals are related to the changes in adiposity risk although minerals are modified by changes in dietary habits. Thus, well-designed studies and careful consideration of confounding variables and interactions are needed.
Funding/support
Dr. Hu is partially supported by the grant from the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK132011 and R01DK141453) and the National Institute of General Medical Sciences (U54GM104940) of the National Institutes of Health.
Footnotes
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Conflict of interest
The authors have no conflict of interest to disclose.
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