Prenatal Exposure to Arsenic and Body Mass Index Trajectories in Child: The POSGRAD Birth Cohort Study

Introduction

Childhood overweight/ obesity is one of the most important public health problems worldwide and its prevalence continues to increase alarmingly [1]. Mexico is one of the countries most affected by this epidemic, with prevalence’s of obesity in schoolage children and adolescents of 33% and 36%, respectively [2]. One of the most important implications of childhood overweight/obesity is that increased the risk of a wide variety of chronic degenerative diseases in adulthood, including diabetes, hypertension, ischemic heart disease, and lipid metabolism disorders, among others [3]. Excessive calorie intake, genetic factors and sedentary lifestyle are the main known risk factors for the development of obesity; however, not all cases are explained by these conditions [3-5]. In this sense, it has been reported that certain environmental determinants [6] are capable of modifying the susceptibility to develop metabolic disorders, signalling, that exposure to environmental pollutants (even at low concentrations) called endocrine disruptors [7] may cause alterations in the control of the energy balance towards lipid production and accumulation for his ability to interfere with the normal functioning of natural hormones. The most studied compounds in recent years include phthalic acid esters, bisphenol A and heavy metals [7].

Of particular interest in this paper is to evaluate the prenatal exposure to inorganic Arsenic (iAs), a naturally occurring and abundant element in the environment that is found in groundwater and certain foods (e.g., rice, grains) [8]. It is estimated that 140 million people worldwide are exposed to arsenic-contaminated drinking water at levels above the World Health Organization’s recommended guideline value [9]. In the United States, approximately 13 million Americans are exposed to arsenic from drinking water that exceeds the Environmental Protection Agency’s current standard of 10 µg/L [10]. Mexico is one of the most affected countries, estimating that approximately six million inhabitants have an exposure to As especially naturally. Similarly, the state of Morelos is considered an area with significant concentrations of As, primarily due to mining activities [11]. Epidemiological studies identify As a risk factor for human health [10,12,13], until now and even with the vast number of studies performed [14], It is not well known the molecular mechanisms of the toxic and carcinogenic effects of As. In addition, the number of metabolic pathways altered by As is too extensive to fully understand, and there is not a suitable animal model for the study of the long-term toxicity effects of As exposure. The toxicity of arsenic is influenced by its metabolism, after absorption, iAs is metabolized into mono- and di-methylated compounds (MMA and DMA) and the three arsenic forms are excreted in the urine [12]. iAs is a carcinogen and long-term exposure is known to cause skin lesions and carry an elevated risk of cancer, among other health effects, including cardiometabolic risk outcomes [13]. The association between arsenic exposure and obesity has been poorly studied. Previous studies have suggested an association between arsenic exposure and triglycerides, high-density lipoprotein cholesterol and the risk of hypertension [14], However, most of the epidemiologic studies carried out previously have been cross-sectional and conducted in adults [15]. In this sense, in cross-sectional studies, urinary arsenic levels were positively associated with prevalent diabetes in populations from Canada (urine arsenic geometric mean 12.9 ug/L) [16]. However, in Bangladesh, the concentrations of well water arsenic were no associated with the prevalence of diabetes mellitus [17]. Despite a growing body of evidence on the role of low or moderate arsenic exposure and obesity [18-21], the association has remained unclear and some of studies that have previously examined these associations have thrown contradictory results. For this reason, we realized the present study with the aim to evaluate the prospective association of prenatal exposure to arsenic and Body Mass Index (BMI) trajectories in a cohort of Mexican children’s participants of a Prenatal Omega-3 Fatty Acid Supplementation and Child Growth Development (POSGRAD) birth cohort study.

Material and Methods

Study design and study population

In this study, we included a subsample of 450 pairs (motherchild), all participants of the POSGRAD birth cohort study aimed to evaluate the effect of DHA supplementation during pregnancy on the offspring´s growth and cognitive development. A detailed description of the design and methods has been published previously [22]. Briefly, eligible women were 18 to 35 years of age with 18 to 22 weeks of gestation, and the intention to give birth in the General Hospital of Mexican Institute of Social Security (IMSS) in Cuernavaca (Morelos, Mexico). The subsample considered for the present report included 450 mother-child pairs with information about arsenic exposure measurements, as well as anthropometric variables. Information on sociodemographic characteristics and other maternal characteristics (obstetric history and lifestyle habits) were collected through interviewbased questionnaires. Anthropometric measures were taken, and the Body Mass Index (BMI) was calculated from birth until 10 years or life with the height and weight data. All women signed an informed consent and the Emory University Institutional Review Board, the Committees of Biosafety, Investigation and Ethics from the National Institute of Public Health (INSP) and the IMSS General Hospital’s Human Subjects Board approved this study.

Anthropometric measures of the child

Birth weight (to the nearest 10 g) and length (to the nearest 1 mm) were measured with the use of a pediatric scale and a portable length measurement board following standard procedures. Children´s weight, height and Waist Circumference (WC) were measured by standardized procedures at 1, 3, 6, 9, 12, 18, 24, 36, 48, 60, 72, 84, 96, 108 and 120 months of life, with the same equipment and procedures23,24. Waist Circumference (WC) was measured using a Gulick fiber glasstape (Creative Health Products, Inc.) accurate to within 0.1 cm. Trained study personnel at the Mexican Social Security Institute’s Hospital General I in Cuernavaca, Mexico, performed data collection. BMI was calculated with the height and weight data by the reference standards of the World Health Organization [23,24].

Exposure assessment to arsenic during pregnancy

First morning urine samples were collected from the mother between 18-22 weeks of pregnancy, containers were provided previously, and they were instructed on sample collection procedures. The urine samples were refrigerated at 4°C and were then aliquoted and frozen at −70°C until the time of analysis. Arsenic concentrations were measured using inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) (Thermo Scientific) after a sample digestion step in the laboratory of the Technological Institute of Sonora. Briefly, 3 ml of the urine samples were placed in a linear microwave digestion vessel, 3 ml of concentrated nitric acid (HNO₃) and 1.5 ml of hydrogen peroxide (H₂O₂) were added, and the samples were digested (CEM Corp., Matthews, NC) for 35 min at 200°C. After microwave digestion, samples were adjusted to a final volume of 25 ml with water HPLC grade. For quality control purposes, blank and duplicate samples were analyzed during the procedure. SRM 3669 Standard Reference Material, Arsenic Species in Frozen Human Urine (NIST, Gaithersburg, MD) and CWW-TB Certified Wastewater Standard (High Purity, Charleston, SC) were analyzed to ensure assay quality. For arsenic, the recovery was between 82-106%, the coefficient of correlation was of 0.99 and the coefficient of variation was less than 8%. The detection limit of arsenic had an average value of 0.010 mg/L11.

Other maternal characteristics

At baseline, the participating women responded to a general health questionnaire that included information on weight and height before delivery, sociodemographic characteristics, health, and gynecological antecedents. During the 18 and 22 weeks of pregnancy, we administered an environmental questionnaire inquiring on water consumption, source of food and water, tobacco exposure, humidity, mildew, mold or saline formation on walls or floor, pet presence at home, presence of industry near home, and pesticide use, as well as 24–recall and FFQ dietary questionnaire. Data on age, sex, educational level of the mothers, and smoking status were collected via an interview. Height, weight, and waist circumference were collected by physical examination using a standardized protocol, and BMI was calculated by dividing the weight into kilograms by the square of height in meters.

Other information about the children

Information on age, sex, diet, health status during follows up, physical activity was obtained by questionnaire. As well as information about birth, breastfeeding and other environmental exposure. Details of the methods are included in the previous reports [11].

Statistical Analysis

First, baseline characteristics of the study population were performed using frequency measures and dispersion measures according to a variable type. For the exposure, the characteristics of the urinary concentrations of arsenic were described. Next, we calculated the BMI for each subject using the measurements taken from birth to 10 years and the growth trajectories of the BMI for each child were evaluated. For the construction of the BMI growth curves, the age was used in months, from 0 (birth) to 120 months (10 years). A quadratic term for age was included to allow a nonlinear BMI growth trajectory. Subsequently, a bivariate analysis was carried out, identifying the effect of exposure on growth trajectories at the different BMI measurement points; for this, a GEEs model was used. These effects were assessed considering the exposure variable in quartiles. For the model fit, an a priori approach was used to identify the main independent predictors of BMI (maternal age at the time of pregnancy, BMI before pregnancy, parity, type of delivery, passive smoking in home during pregnancy, schooling of the mother, socio-economic status). In addition, in the final model we included the interaction term between age in months and exposure in quartiles, the interaction term of the quadratic term of age in months and exposure. Finally, to evaluate the effect of the prenatal exposure to arsenic measured in quartiles on the BMI trajectories we use a General Equation Models (GEEs) for longitudinal data [25] adjusted by age in months, quadratic term for age in months, gender, weight before pregnancy, passive smoking in home during pregnancy and interaction term between exposure in quartiles and gender, age in months and quadratic term for age in months. For the exposure, the 1st. quantile was the reference category, and for sex, male was the reference category. Statistical significance was defined by an alpha level of 0.05. Analyses were performed with STATA software, version 14.0 (Stata Corp, College Station, TX).

Results

We included 450 mother-child pairs with complete information, all participants of the POSGRAD birth cohort study. Children included in the present analysis did not differ in terms of the main variables of the participants from the POSGRAD cohort sample and non-included in the analysis (data not shown). The mothers included in this study had a mean age of (+ SD) 26.1 (+4.8) at the second trimester. Socioeconomic status was categorized as low in 33.6%, medium in 36.4% and high in 30%. Considering BMI before pregnancy, about half of them had a normal BMI (54%), while 27.4 percent were overweight and 12.2% obese. 32.7% of these women were primipara. Only 2.1% of women reported smoking during pregnancy, however, 36.5% reported that someone in their home smoked during pregnancy. 48.6% of deliveries were normal and the rest caesarean, 53.6% of new-borns were male (Table 1). We did not observe significant differences between the participants included vs those not included for the main variables studied (p> 0.05) (Data not shown).

Table 1: Main characteristics of the study population.

The mean and standard deviation of the concentration of arsenic during pregnancy is in Table 2. The mean concentration was 0.06 mg/L, SD (0.04 mg/L).

Table 2: Prenatal arsenic concentrations (mg/L) in urine samples.

Regarding the metabolism indicators, 11.7% of the boys were above the 90th percentile for abdominal circumference (57.2 cm) and in girls; this figure was 5.3% (58.9 cm). 12.7% of the boys were overweight (BMI z-score> 1DE) (Data not shown).

We found a significant association between prenatal exposure to arsenic and the BMI trajectories from 0 to 10 years of age (b_quartile2 vs. quartile1 = 2.18. (bquartile3 vs quartile1= 2.54, p-trend<0.05) (Table 3, Figure 1). Finally, we observed an interaction effect between exposure and age in months, which indicates that the rate of change in BMI increases when the child’s age increases, however, when the child is exposed to arsenic during pregnancy, the increase of the BMI is significant more accelerate in these population (p<0.05) (Figure 2).

Table 3: Association between prenatal exposure to arsenic concentrations and BMI trajectories from 0 to 10 years of age in children’s participants of the POSGRAD birth cohort study.

Figure 1: Association between BMI trajectories in children and prenatal exposure to arsenic.

Figure 2: Predictive BMI trajectories in quartiles of arsenic concentrations with 95% CIs.

Discussion

The results of the present study strengthen the evidence that prenatal exposure to arsenic is associated with a faster rate of BMI gain through 10 years of age, which can be translated into higher risk of obesity especially if the BMI z-scores are already >0 at birth. This is a very important finding to public health, since this compound have the ability to interfere with the normal functioning of natural hormones [26] and may increase the risk of other important health problems (diabetes, hypertension and metabolic diseases) in early age of life. We found a positive association between prenatal exposure to arsenic and BMI trajectories. Our results are consistent with those reported in the literature, however, most of them are derived from experimental studies conducted in animals [27]. To our