1. INTRODUCTION:

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition marked by ongoing challenges in social communication, limited interests, and repetitive behaviors^1-4. This issue is gaining recognition as a significant global public health challenge, attributed to its rising prevalence, lasting effects, and the complex nature of its causes. Recent findings indicate that ASD develops from an interplay of genetic factors and environmental influences that occur during crucial periods of neurodevelopment^5-8. Significant progress has been achieved in comprehending the genetic framework of ASD; however, the influence of environmental risk factors, especially the exposure to neurotoxic heavy metals, is still not fully understood and is increasingly drawing interest^9,10.

Recent records indicate that the number of individuals diagnosed with ASD has increased worldwide. This trend was confirmed by multiple reputable institutions and epidemiological reviews¹¹. In the United States, for example, the Centers for Disease Control and Prevention (CDC) reported an increase in ASD prevalence from 1 in 68 children in 2016 to 1 in 54 children in 2020, underscoring an intensified awareness of the condition. Parallel findings are evident in other countries, as systematic reviews cite rates such as 62 per 10,000 children, while Middle Eastern countries like Lebanon, Qatar and Iraq have recorded prevalence levels comparable to global estimates^{12-18, 19{Hasan, 2017 #5}^}

Studies examining the epidemiology and environmental factors associated with ASD in Jordan are limited, even as rates continue to rise, and concerns grow among healthcare providers and public health experts^20-23.

In recent decades, Jordan, especially its capital Amman, has experienced significant industrial growth and urban development, resulting in heightened levels of environmental pollution. In urban environments, industrial emissions, vehicular traffic, and inadequate waste management practices have led to increased concentrations of heavy metals, including lead (Pb), cadmium (Cd), and copper (Cu)^24-26. These metals, although some are required in trace quantities (e.g., copper), can be harmful at elevated doses, particularly to vulnerable populations such as children. Prolonged exposure to these elements has been associated with neurodevelopmental abnormalities via processes including oxidative stress, disturbance of neurotransmitter systems, mitochondrial impairment, and epigenetic alterations^27-31.

Children may encounter heavy metals via several environmental routes, such as contaminated water, soil, food, air, and household dust. Urban habitation, proximity to vehicular traffic, low socioeconomic position, and parental tobacco use are recognized factors contributing to increased metal exposure. Furthermore, prenatal and perinatal exposures are especially alarming, as heavy metals can traverse the placental barrier and accumulate in fetal tissues, potentially hindering early brain development^32-34.

Many research investigations have identified increased concentrations of lead (Pb) and cadmium (Cd) in children residing in contaminated areas relative to their counterparts in unpolluted regions, and concomitant decreases in vital minerals such as magnesium and zinc³⁵. Copper imbalances have been linked to behavioral problems and developmental delays^36-38. Nonetheless, these findings are not universally applicable, and discrepancies among research may be ascribed to variations in technique, demographic variables, and biological sampling matrices.

Hair presents a number of benefits as a matrix for metal analysis. This method demonstrates the benefits of long-term exposure, is easy to collect without causing any disruption, and maintains stability throughout storage and transport. The analysis of hair metal has found extensive application in environmental health research, especially among pediatric populations³⁹.

Despite significant global research interest in the environmental factors associated with autism, there are limited studies that investigated the concentrations of heavy metals in the hair of children with ASD in Jordan⁴⁰. Furthermore, factors related to demographics, including maternal age, exposure to parental tobacco smoke, and the socio-environmental characteristics of neighborhoods, have not been thoroughly investigated in this population^41,42. The existing gap in the literature highlights the importance of conducting research that is relevant to the local context, which can effectively guide public health strategies and clinical interventions specifically designed for the unique environmental and social conditions of Jordan.

The current study was established with two main objectives. The first objective was to measure the quantities of cadmium, lead, and copper in the hair of children diagnosed with ASD and in age-matched neurotypical controls, employing ICP-MS, a precise and sensitive technique for trace element analysis . The second purpose was to examine potential correlations between ASD and various sociodemographic risk factors, including environmental exposures in residential areas and parental tobacco smoking behaviors inside the home. This study seeks to further the understanding of ASD in Jordan and other middle-income nations undergoing swift urbanization and industrial expansion by analyzing environmental toxicants and social determinants of health.

2. MATERIALS AND METHODS:

2.1 Participant grouping and ethical consideration:

This research was carried out in Amman Governorate, the capital of Jordan, an area that has undergone considerable urbanization and industrial expansion in recent decades. This study recruited 50 children aged 7 to 18 years. The study group consisted of 25 children diagnosed with ASD, whereas the control group contained 25 age- and sex-matched neurotypical youngsters. Participants were chosen via a randomized procedure to reduce selection bias.

The diagnosis of ASD was previously confirmed by a multidisciplinary team comprising psychiatrists, psychologists, and developmental pediatricians, adhering to globally recognized diagnostic criteria. Informed consent was acquired from the parents or legal guardians of all participants before to their involvement. The study procedure complied with the ethical principles of the Declaration of Helsinki, and ethical permission was secured from the Ethics Committee of the Graduate Studies School at the University of Jordan (Project Code: 4/2018/2017/3/137).

Caregivers in both groups filled out a standardized demographic survey via direct interviews to better grasp possible environmental variables. These surveys recorded information on environmental exposure hazards including household tobacco smoke present, gas stations, and distance to industrial locations. To enhance the environmental background of the research, data were gathered from 100 parents of neurotypical controls and 228 parents of children with ASD.

2.2 Hair Sample Collection:

Hair was used as the biological matrix for examination because it effectively indicates long-term exposure to trace elements³⁹. Hair samples were obtained by meticulously excising strands from the occipital area of the head with sterile stainless-steel scissors. Approximately 0.5 grams of hair were obtained from each participant. The samples were promptly labeled, enclosed in polyethylene bags, and stored at ambient conditions until processing.

2.3 Sample Washing Procedure:

Hair samples were subjected to a standardized washing procedure, modified from earlier published techniques^43,44, to eliminate outside impurities and guarantee precise trace metal detection. A clean 50 mL beaker held each sample, which was progressively rinsed for 5 minutes each with the following solutions: 0.5% Triton X-100, deionized water, acetone, and a final rinse using deionized water. The cleaned samples were then dried in a drying oven at 60 °C overnight.

2.4 Acid Digestion of Hair Samples Heavy Metals Analysis:

Dried hair samples underwent acid digestion to extract trace metals for examination. Approximately 0.5 grams of hair were measured and immersed overnight in 3 mL of pure nitric acid (HNO₃). The following day, an extra 3 mL of HNO₃ was incorporated, and the liquid was cautiously cooked on a hot plate for 90 min until boiling commenced. Throughout the heating process, tiny aliquots of nitric acid (about 15 mL in total) were introduced intermittently to reduce evaporation and guarantee thorough digestion. The digested solution was thereafter cooled, transferred to a 10 mL volumetric flask, and adjusted to volume with ultrapure deionized water^43-45. The levels of concentrations Cd, Pb, and Cu in the digested hair samples were measured using ICP-MS. This method was selected for its exceptional sensitivity and accuracy in identifying tiny amounts of heavy metals in biological matrices.

2.6 Statistical Analysis:

All statistical analyses were conducted utilizing SPSS software, version 17.0 (SPSS Inc., Chicago, IL, USA). Comparisons between children with ASD and controls were performed using the Student’s t-test to assess differences in mean heavy metal concentrations. Results are presented as means ± standard deviations (SD), with a p-value of < 0.05 deemed statistically significant. The Chi-square test was employed to evaluate relationships between category variables obtained from the demographic questionnaire.

RESULTS:

The comparison of heavy metal levels between autistic children and healthy controls revealed significant differences for some elements. As shown in Table 1, the average concentrations of Cd and Pb in hair samples were significantly higher in autistic children compared to controls, with statistically significant differences observed. A higher concentration of Cu was also seen in the autism group, although this difference did not reach statistical significance (p = 0.053).

Specifically, the concentration of Cd among autistic children ranged from 3.27 to 7.43 µg/g, with a mean of 5.98 ± 1.12 µg/g, whereas the control group showed lower concentrations ranging from 2.1 to 5.43 µg/g, averaging at 4.14 ± 0.92 µg/g. Similarly, Pb concentrations were markedly elevated among autistic children, ranging from 15.6 to 35.45 µg/g, with a mean of 23.99 ± 6.52 µg/g. In contrast, the Pb levels in control children were considerably lower, ranging from 8.66 to 18.65 µg/g, averaging at 14.39 ± 2.73 µg/g. For Cu, autistic children's hair samples ranged from 6.43 to 14.84 µg/g with a mean of 9.83 ± 2.88 µg/g, whereas controls exhibited a narrower range (5.9 to 11.6 µg/g) with an average concentration of 8.50 ± 1.71 µg/g.

Figure 1 further illustrates these differences, highlighting the elevated levels of Cd and Pb in autistic subjects compared to healthy controls. These findings underscore a potential association between elevated heavy metal exposure and autism, warranting further investigation into their roles in the etiology and progression of autism spectrum disorders.

DISCUSSION:

This study investigated the potential correlation between ASD and environmental exposure to heavy metals by analyzing hair samples from autistic children and neurotypical controls in Jordan. The levels of Cd, lead Pb, and Cu were measured using ICP-MS. Furthermore, socio-demographic and environmental variables were assessed to gain a deeper understanding of potential relevant factors.

The choice of hair as a biological matrix for trace metal analysis was based on its capacity to indicate long-term exposure, its non-invasive characteristics, and its stability during storage and transport, rendering it especially appropriate for pediatric populations³⁹.

The results of this study showed substantial increases in hair Cd and Pb concentrations in autistic children relative to neurotypical controls, aligning with many previous works that suggests heavy metal exposure may contribute to the etiology and progression of ASD. Our data indicate a significant elevation in lead and Cd concentrations, with an approximate increase of 166.7%, 144.6 % respectively in autistic individuals compared to controls. In contrast, copper (Cu) levels did not exhibit significant differences between the two groups, indicating that copper exposure, at least within the measured limits, may not substantially influence ASD risk in this population.

The observed increase in lead levels in autistic children agree with earlier studies that indicated comparable results. Lead (Pb), an extensively documented neurotoxic, is recognized for causing harmful neurological effects, especially during critical developmental phases. Increased Pb exposure has been consistently linked to cognitive deficits, behavioral modifications, and interference with neurodevelopmental processes via mechanisms including oxidative stress, mitochondrial dysfunction, neurotransmitter imbalances, and epigenetic alterations^27,28. Our findings contribute to the current evidence by revealing heightened lead levels in a hitherto underexamined Jordanian pediatric population, emphasizing the necessity of environmental monitoring and public health initiatives in the region. Interestingly, a previous study demonstrated elevated aluminum and reduced calcium and manganese in the blood of Jordanian children with ASD. While our study focused on hair as a matrix and investigated Cd, Pb and Cu, their work corroborates the systemic disruptions in trace elements associated with ASD, further supporting the biomarker potential of metal analysis.

The rising Cd levels warrants attention as it is associated with neurotoxicity. The oxidative damage and changes in neurotransmitter systems may be the mechanisms by which Cd causes negative neurodevelopmental impacts, such as cognitive impairments and behavioral abnormalities^46,47.

The Cu levels in the autistic group were elevated, although they did not achieve statistical significance. This finding aligns with previous research demonstrating inconsistent results regarding copper's role in ASD. Copper is crucial in trace quantities for numerous physiological activities, such as brain development; yet imbalances—whether deficiency or excess—are linked to behavioral and developmental disorders. The insignificant outcome in this study may indicate sufficient copper homeostasis among individuals or methodological discrepancies, such variances in sample size, food, or regional environmental factors^33,35-39.

Our study identified no statistically significant correlation between ASD and parental smoking behaviors⁴⁸, residential proximity to petrol stations, industrial zones, or pesticide-treated areas when analyzing socio-demographic and environmental risk variables^49-51. This absence of notable correlations contrasts with prior studies that have connected these environmental exposures to heightened ASD risk. The lack of such relationships in our study may be due to generally uniform exposure levels among the populations examined. These data indicate that the increased heavy metal concentrations may stem from broader environmental influences, such as urbanization and industrial pollution, rather than particular family exposures.

These findings highlight the need for improved public health initiatives and additional research into environmental risk factors for ASD in swiftly urbanizing areas. It underscores the necessity for regional studies to clarify the interaction between environmental exposures and neurodevelopmental disorders across diverse socio-cultural and geographic contexts. Future research must utilize longitudinal designs, larger sample sizes, and thorough environmental exposure assessments to elucidate the etiological connections between heavy metal exposure and ASD, thereby guiding prevention strategies and policy interventions to mitigate pediatric exposure to neurotoxicants.

CONCLUSION:

This study reveals notable increases in hair cadmium and lead concentrations in autistic children relative to neurotypical controls in Jordan, underscoring the possible influence of environmental heavy metals on the development of ASD. Although copper levels were not markedly different among the groups, increased concentrations of lead and cadmium indicate a correlation between environmental exposure and neurodevelopmental hazards. The lack of notable correlations with household-level characteristics suggests that widespread environmental contamination is a probable culprit. These findings highlight the necessity of continuous environmental surveillance and focused public health initiatives to reduce heavy metal exposure, especially in swiftly urbanizing areas. Subsequent research should further examine these correlations to guide effective preventive and therapeutic strategies.

ETHICAL CONSIDERATION:

Ethical approval was secured by the ethics committee of the deanship of scientific research at the University of Jordan, Amman, Jordan, in accordance with the criteria established in the Declaration of Helsinki (2013 revision). Furthermore, permission was secured from the Autism Academy of Jordan (No.: 19/192, Date: 25/03/2019). Informed written consent was obtained from the parents or guardians of all children participating in the study before its initiation.

DECLARATION OF COMPETING INTEREST AND AI ASSISTANCE:

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. During the preparation of this work the authors used QuillBot and ChatGPT in to improve language and readability. After using this service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

ACKNOWLEDGMENT:

Authors would like to acknowledge Al-Ahliyya Amman University, University of Sharjah, The University of Jordan for their support.

REFERENCES:

1. Lim HK, Yoon JH, Song M. Autism Spectrum Disorder Genes: Disease-Related Networks and Compensatory Strategies. Frontiers in Molecular Neuroscience. 2022; 15. doi: 10.3389/fnmol.2022.922840.

2. Ayasrah M, AL khateeb A, Beirat M, et al. Behavioral Consequences Among Children with Autism Spectrum Disorders at the Special Care Centers Clinical Schizophrenia and Related Psychoses. 2022; 16(2): 2-5. doi: 10.3371/CSRP.MMWY.100123

3. Ayasrah MAk, A., Beirat M, Alkhawaldeh M. Parental Adjustments to the Behaviour of Children with ASD. Clinical Schizophrenia and Related Psychoses,. 2022; 16(2). doi: 10.3371/CSRP.MMWY.100124.

4. Sarika Y. Autism Spectrum Disorder- A Review. Int J Nur Edu and Research. 2016; 4(2): 223-226. doi.

5. Cortese S, Bellato A, Gabellone A, et al. Latest clinical frontiers related to autism diagnostic strategies. Cell Rep Med. 2025; 6(2). doi: 10.1016/j.xcrm.2024.101916.

6. Mirza R, Sharma P, Kulkarni GT, et al. Flutamide Alters Markers of Inflammation and Oxidative stress in Experimental Model of Autism. Res J Pharm Technol. 2023; 16(11): 5142-5148. doi: 10.52711/0974-360X.2023.00833.

7. Yugander P, Jagannath M. Structural neuroimaging findings in autism spectrum disorder: A systematic review. Res J Pharm Technol. 2021; 14(4): 2341-2347. doi: 10.52711/0974-360X.2021.00413.

8. Vinay Kumar G, Sathish DK. A Study to Evaluate the Effectiveness of Structured Teaching Programme on Knowledge Regarding Autism among Parents of Autistic Children in Selected Autistic Schools at Mysore. Asian Journal of Nursing Education and Research. 2018; 8(3): 362-364. doi: 10.5958/2349-2996.2018.00073.3.

9. Kazantzidou P, Antonopoulou K, Costarelli V, et al. Environmental factors associated with autism spectrum disorder in Southern Europe: a systematic review. Int J. 2025; 71(1): 30-40. doi: 10.1080/20473869.2023.2215012.

10. Dhariyal RS, Kimothi V, Singh S. A Review on Autism. Research Journal of Pharmacology and Pharmacodynamics. 2019. doi: 10.5958/2321-5836.2019.00013.2.

11. Santomauro DF, Erskine HE, Mantilla Herrera AM, et al. The global epidemiology and health burden of the autism spectrum: findings from the Global Burden of Disease Study 2021. The Lancet Psychiatry. 2025; 12(2): 111-121. doi: 10.1016/S2215-0366(24)00363-8.

12. Elsabbagh M, Johnson MH. Autism and the Social Brain: The First-Year Puzzle. Biol Psychiatry. 2016; 80(2): 94-99. doi: 10.1016/j.biopsych.2016.02.019.

13. Elsabbagh M. Linking risk factors and outcomes in autism spectrum disorder: Is there evidence for resilience? BMJ. 2020; 368. doi: 10.1136/bmj.l6880.

14. Sulaimani MF, Daghustani WH. Autism in Saudi Arabia: Media and the Medical Model of Disability. Educ Res Int. 2022; 2022. doi: 10.1155/2022/4824606.

15. Zeidan J, Fombonne E, Scorah J, et al. Global prevalence of autism: A systematic review update. Autism Res. 2022; 15(5): 778-790. doi: 10.1002/aur.2696.

16. Alshaban FA, Aldosari M, Ghazal I, et al. Consanguinity as a Risk Factor for Autism. J Autism Dev Disord. 2023; doi: 10.1007/s10803-023-06137-w.

17. Alshaban F, Aldosari M, Al-Shammari H, et al. Prevalence and correlates of autism spectrum disorder in Qatar: a national study. J Child Psychol Psychiatry Allied Discip. 2019; 60(12): 1254-1268. doi: 10.1111/jcpp.13066.

18. Al-Mamari W, Idris AB, Al Aamri H, et al. Could a National Screening Program Reduce the Age of Diagnosis of Autism Spectrum Disorder? J Autism Dev Disord. 2025. doi: 10.1007/s10803-025-06770-7.

19. Obaidi A. A systematic review of the correlation between exposure to environmental pollution and autism in children under 9 years in Middle Eastern countries. Middle East Curr Psychiatry. 2024; 31(1). doi: 10.1186/s43045-024-00489-4.

20. Alkhatib A, Nuseir K, Abdo N, et al. Behavioral interventions with and without pharmacological treatment: A comparative study at an autistic center in Jordan. Jordan J Pharm. 2024; 17(2): 395-406. doi: 10.35516/jjps.v17i2.1974.

21. B. Rashaid AH, Shanayneh T, Alqhazo M, et al. Elemental examination in blood and urine samples of Jordanian children with autism spectrum disorder. Biomark Neuropsychiatry. 2024; 11. doi: 10.1016/j.bionps.2024.100110.

22. Al-Omari LM, Beirat MA, Faris ME, et al. Impact of Sublingual Glutathione on Oxidative Biomarkers and Behavior in Children with Autism: A Pilot Investigation with Pharmacist Involvement. Pharm Pract.2026;24(1) doi: 10.18549/PharmPract.2026.1.3366.

23. Al-Omari LM, Hunaiti AA, Beirat MA, et al. Study of MTHFR C677T Polymorphism and Associated Oxidative Stress Biomarkers among Autism Spectrum Disorder Patients in Jordan. Jordan Journal of Biological Sciences. 2020; 13(2): 247-252.

24. Holdridge G, Simpson I, Lichtenberger A, et al. Urban gardens in Antiquity: The case of Gerasa/Jerash in Jordan. JArchaeol Sci Rep. 2022; 46. doi: 10.1016/j.jasrep.2022.103633.

25. Al-Massaedh AA, Al-Momani IF. Assessment of Heavy Metal Contamination in Roadside Soils along Irbid-Amman Highway, Jordan by ICP-OES. Jordan J Chem. 2020; 15(1): 1-12. doi: 10.47014/15.1.1.

26. Al-Hanini M, Makhamreh Z, Al Bakain R. Chemometric Evaluation of Residual Soil Contents: Application to Heavy Metals at Public Parks in Amman – Jordan. Jordan J Earth Environ Sci. 2024; 15(2): 115-122.

27. Chouari R, Leftat L, Arabi FE, et al. Environmental Impact of the Heavy Metal Intoxication on Metabolic, Physiological and Nutritional Profiles in Children with Autism Spectrum Disorder in Morocco. Ecol Eng Environ Tech. 2024; 25(7): 150-161. doi: 10.12912/27197050/188057.

28. Ding M, Shi S, Qie S, et al. Association between heavy metals exposure (cadmium, lead, arsenic, mercury) and child autistic disorder: a systematic review and meta-analysis. Front Pediatr. 2023; 11. doi: 10.3389/fped.2023.1169733.

29. Alhyasat RAE, Khleifat K, Khlaifat AM, et al. Oxidative Stress and its connection to Jordanians' Red Blood Cell Storage. Research Journal of Pharmacy and Technology. 2024; 17(9): 4304-4310. doi: 10.52711/0974-360X.2024.00665.

30. Santhosh Kumar R, Asha Devi S. Lead toxicity on male reproductive system and its mechanism: A review. Res J Pharm Technol. 2018; 11(3): 1228-1232. doi: 10.5958/0974-360X.2018.00228.7.

31. Mohammed MB, Alrubaye YSJ. The Oxidative status in Children with Autism receiving Melatonin. Res J Pharm Technol. 2022; 15(1): 338-342. doi: 10.52711/0974-360X.2022.00055.

32. Fujiwara T, Morisaki N, Honda Y, et al. Chemicals, nutrition, and autism spectrum disorder: A mini-review. Front Neurosci. 2016; 10(APR). doi: 10.3389/fnins.2016.00174.

33. Raparthi N, Yadav S, Khare A, et al. Chemical and oxidative properties of fine particulate matter from near-road traffic sources. Environ Pollut. 2023; 337. doi: 10.1016/j.envpol.2023.122514.

34. Schoentgen B, Chatin E, Sallé H, et al. Socioeconomic impact of neurodevelopmental disorders in France. Encephale. 2025. doi: 10.1016/j.encep.2024.11.015.

35. Zhang Y, Maimaiti R, Lou S, et al. Risk prediction of autism spectrum disorder behaviors among children based on blood elements by nomogram: A cross-sectional study in Xinjiang from 2018 to 2019. J Affective Disord. 2022; 318: 1-6. doi: 10.1016/j.jad.2022.08.130.

36. Liu H, Huang M, Yu X. Blood and hair copper levels in childhood autism spectrum disorder: A meta-analysis based on case-control studies. Rev Environ Health. 2024; 39(3): 511-517. doi: 10.1515/reveh-2022-0256.

37. Faber S, Zinn GM, Kern Ii JC, et al. The plasma zinc/serum copper ratio as a biomarker in children with autism spectrum disorders. Biomarkers. 2009; 14(3): 171-180. doi: 10.1080/13547500902783747.

38. El-Baz F, Mowafy ME, Lotfy A. Study of serum copper and ceruloplasmin levels in Egyptian autistic children. Egypt J Med Hum Genet. 2018; 19(2): 113-116. doi: 10.1016/j.ejmhg.2017.08.002.

39. Zhou X, Xia X, Li L, et al. Evaluation of Heavy Metals and Essential Minerals in the Hair of Children with Autism Spectrum Disorder and Their Association with Symptom Severity. Biol Trace Elem Res. 2025. doi: 10.1007/s12011-025-04588-z.

40. Al-Bazzaz A, A-Dahir K, Almashhadani A, et al. Estimation of fasting serum levels of glucose, zinc, copper, zinc /copper ratio and their relation to the measured lipid profile in autistic patients and non-autistic controls in Jordan. Biomed Pharmacol J. 2020; 13(1): 481-488. doi: 10.13005/bpj/1909.

41. Shalan N, Jarrar Y, Nofal H, et al. Factors Associated with Tobacco Smoking Initiation in Jordan: A Cross-Sectional Study. Asian Pac J Cancer Preven. 2024; 25(11): 4089-4096. doi: 10.31557/APJCP.2024.25.11.4089.

42. Hasan AA. A Descriptive Study among Children suffering from Autism in Baghdad, Iraq. Res J Pharm Technol. 2017. doi: 10.5958/0974-360X.2017.00336.5.

43. Rashaid AB, Alqhazo M, Newbury DF, et al. Evaluation of elements in hair samples of children with developmental language disorder (DLD). Nutr Neurosci. 2023; 26(2): 138-147. doi: 10.1080/1028415X.2021.2022068.

44. Varrica D, Tamburo E, Alaimo MG. Levels of trace elements in human hair samples of adolescents living near petrochemical plants. Environ Geochem Health. 2022; 44(11): 3779-3797. doi: 10.1007/s10653-021-01124-5.

45. Suresh P, Kumar KR. Determination of elemental impurities of Arsenic, Cadmium, Mercury, Lead and Palladium content in Testosterone propionate by using ICP-MS. Asian Journal of Research in Chemistry. 2021. doi: 10.52711/0974-4150.2021.00035.

46. Moyano P, de Frias M, Lobo M, et al. Cadmium induced ROS alters M1 and M3 receptors, leading to SN56 cholinergic neuronal loss, through AChE variants disruption. Toxicology. 2018; 394: 54-62. doi: 10.1016/j.tox.2017.12.006.

47. Li CH, Luo JJ, Peng JC, et al. Research progress in central neurotoxicity and mechanism of lead and cadmium in individual or combined exposure. Chin J Pharmacol Toxicol. 2023; 37(6): 446-455. doi: 10.3867/j.issn.1000-3002.2023.06.006.

48. Hertz-Picciotto I, Korrick SA, Ladd-Acosta C, et al. Maternal tobacco smoking and offspring autism spectrum disorder or traits in ECHO cohorts. Autism Res. 2022; 15(3): 551-569. doi: 10.1002/aur.2665.

49. Duque-Cartagena T, Dalla MDB, Mundstock E, et al. Environmental pollutants as risk factors for autism spectrum disorders: a systematic review and meta-analysis of cohort studies. BMC Public Health. 2024; 24(1). doi: 10.1186/s12889-024-19742-w.

50. Yenkoyan K, Mkhitaryan M, Bjørklund G. Environmental Risk Factors in Autism Spectrum Disorder: A Narrative Review. Curr Med Chem. 2024; 31(17): 2345-2360. doi: 10.2174/0109298673252471231121045529.

51. Gul A, Bhat N, Ganie ZA. The Effect of Parenting Behavior on Behavior Problems of Children with Autism Spectrum Disorders. Research Journal of Humanities and Social Sciences. 2019; 10(4): 1059. doi: 10.5958/2321-5828.2019.00173.6.

Received on 05.05.2025 Revised on 17.09.2025

Accepted on 22.12.2025 Published on 20.05.2026

Available online from May 25, 2026

Research J. Pharmacy and Technology. 2026;19(5):2260-2266.

DOI: 10.52711/0974-360X.2026.00325

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.

Element	Autism Range	Mean ± SD	Control Range	Mean ± SD	P value¹
Cd	3.27-7.43	5.983±1.123	2.1-5.43	4.138±0.918	<0.05
Pb	15.6-35.45	23.994±6.522	8.66-18.65	14.39±2.725	<0.05
Cu	6.43-14.84	9.832±2.88	5.9-11.6	8.50±1.71	0.053

Risk factor	Autistic	Normal	P value*
Smoking father	36.8%	35%	0.768
Smoking mother	2.2%	2%	0.999
Family living near petrol station (within 3km)	61.%	5.5%	0.756
Industrial regions	5.7%	5%	0.756
Pesticides area	3.1%	3%	0.999


(a)	(b)

(c)