Spatial clustering of autism spectrum disorders in Kelantan, Malaysia: Urban hotspots and rural gaps

Azizul Ahmad, Ruzaini Ijon, Azahah Abu Hassan Shaari, Yohan Kurniawan, Nik Ahmad Farhan Azim @ Nik Azim, Fairuz A’dilah Rusdi, Mohd Hakimi Aiman Ibrahim, Tarmiji Masron, Asykal Syakinah Mohd Ali

Abstract


The geographic distribution of autism spectrum disorders (ASD) remains poorly characterized in many developing settings, including Malaysia, where rural populations face notable healthcare access gaps. We mapped spatial clustering of ASD subtypes (severe, high-functioning and mild) in Kelantan, a predominantly rural Malaysian state, to examine diagnostic disparities. In this cross-sectional spatial epidemiological study, 103 ASD cases (2022–2024) from two major Kelantan centers were analyzed at the district level. Global Moran’s I assessed overall spatial autocorrelation and optimized Hot Spot Analysis (Getis-Ord Gi*) identified local clusters of high or low ASD incidence. Moran’s I revealed significant positive clustering for mild (I≈0.065, p<0.001) and high-functioning ASD (I≈0.039, p=0.0096) cases reflecting urban concentration but no significant autocorrelation for severe ASD. Optimized hotspot analysis localized statistically significant high-incidence clusters in Kota Bharu and surrounding districts, while rural districts emerged as cold spots. This urban-rural pattern mirrors known disparities (ASD diagnoses concentrate where healthcare access is better) and suggests underdiagnosis in underserved areas. Uneven geographic distribution of diagnostic resources likely drives these patterns. These results reveal service-related inequalities in ASD diagnosis in Kelantan and reinforce the need for targeted healthcare interventions and expanded screening in rural communities to ensure equitable care.

 

Keywords: Autism spectrum disorder (ASD), geographic information system (GIS), high-functioning autism, optimized hotspot analysis, spatial autocorrelation

 


Keywords


Autism spectrum disorder (ASD), geographic information system (GIS), high-functioning autism, optimized hotspot analysis, spatial autocorrelation

Full Text:

PDF

References


Ahmad, A., Ardiansyah, A., Ariffin, N. A., Zakaria, Y. S., Said, M. Z., Mohd Ayob, N., Abdullah, M. I., Jamru, L. R., Mohd Ali, A. S., Jubit, N., Soda, R., Kimura, Y., & Masron, T. (2026). Unlocking Langkawi’s tourism potential: Spatial analysis of attractions and facilities. Geografia-Malaysian Journal of Society and Space, 22(1), 182–216.

Ahmad, A., Masron, T., Ringkai, E., Barawi, M. H., Salleh, M. S., Jubit, N., & Redzuan, M. S. (2024). Analisis ruangan hot spot jenayah pecah rumah di Negeri Selangor, Kuala Lumpur dan Putrajaya pada tahun 2015-2020 (Spatial analysis of crimes hot spot of housebreaking in Selangor, Putrajaya, and Kuala Lumpur in 2015-2020). Geografia-Malaysian Journal of Society and Space, 20(1), 49–67.

Antezana, L., Scarpa, A., Valdespino, A., Albright, J., & Richey, J. A. (2017). Rural trends in diagnosis and services for autism spectrum disorder. Frontiers in Psychology, 8, 590.

ArcGIS Pro 3.1. (2022). How Hot Spot Analysis (Getis-Ord Gi*) Works. Redlands, California: Environmental Systems Research Institute, Inc. (ESRI).

ArcGIS Pro 3.3. (2024). How Optimized Hot Spot Analysis Works. Redlands, California: Environmental Systems Research Institute, Inc. (ESRI).

ArcGIS Pro 3.5. (2025). How Spatial Autocorrelation (Global Moran’s I) Works. Environmental Systems Research Institute, Inc. (ESRI).

Ariffin, N. A., Wan Ibrahim, W. M. M., Rainis, R., Samat, N., Mohd Nasir, M. I., Abdul Rashid, S. M. R., Ahmad, A., & Zakaria, Y. S. (2024). Identification of trends, direction of distribution and spatial pattern of tuberculosis disease (2015-2017) in Penang. Geografia-Malaysian Journal of Society and Space, 20(1), 68–84.

Bakian, A. V, Bilder, D. A., Coon, H., & McMahon, W. M. (2015). Spatial relative risk patterns of autism spectrum disorders in Utah. Journal of Autism and Developmental Disorders, 45(4), 988–1000.

BERNAMA. (2025, August 19). Kelantan Projected to Become Ageing State in Less Than a Decade. New Straits Times. https://www.nst.com.my/news/nation/2025/08/1262495/kelantan-projected-become-ageing-state-less-decade

Bismelah, L. H., Masron, T., Ahmad, A., Mohd Ali, A. S., & Echoh, D. U. (2024). Geospatial assessment of healthcare distribution and population density in Sri Aman, Sarawak, Malaysia. Geografia-Malaysian Journal of Society and Space, 20(3), 51–67.

Chabo, D., Masron, T., Jubit, N., & Ahmad, A. (2026). Spatial analysis of gender-based high risks of school dropout: A comparative study of urban and rural areas in Sarawak, Malaysia. Geografia-Malaysian Journal of Society and Space, 22(1), 111–132.

Chow, H. Y., Salleh, N. S., Cheng, K. W., & Totsika, V. (2026). Families’ experiences of accessing intervention for their children with neurodevelopmental disabilities in Malaysia: A systematic review. International Journal of Developmental Disabilities, 72(1), 148–161.

Cliff, A. D., & Ord, J. K. (1974). Spatial autocorrelation. Biometrics, 30(4), 729.

Cohen, P., & Hesselbart, C. S. (1993). Demographic factors in the use of children’s mental health services. American Journal of Public Health, 83(1), 49–52.

Department of Statistics Malaysia (DOSM). (2020). Kawasanku: Kelantan.

Department of Statistics Malaysia (DOSM). (2024). State Socioeconomic Report, 2023.

Drahota, A., Sadler, R., Hippensteel, C., Ingersoll, B., & Bishop, L. (2020). Service Deserts and service oases: Utilizing Geographic Information Systems to evaluate service availability for individuals with autism spectrum disorder. Autism, 24(8), 2008–2020.

Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189–206.

Ghahari, N., Yousefian, F., Behzadi, S., & Jalilzadeh, A. (2022). Rural-urban differences in age at autism diagnosis: A multiple model analysis. Iranian Journal of Psychiatry, 17(3), 294-303.

Ghani, J. A. (2022, December 5). Dealing with Autism’s ‘Invisible’ Problem. Institute of Strategic & International Studies (ISIS) Malaysia. https://www.isis.org.my/2022/12/05/dealing-with-autisms-invisible-problem/

Gona, J., Newton, C., Rimba, K., Mapenzi, R., Kihara, M., Vijver, F., & Abubakar, A. (2016). Challenges and Coping strategies of parents of children with autism on the Kenyan Coast. Rural and Remote Health, 16, 3517.

Han, Y. L., Wan Sulaiman, W. S., Ahmad Badayai, A. R., & Abdullah @ Mohd. Nor, H. (2023). Validating the Malaysian modified checklist for autism in toddlers, revised with follow-up (M-CHAT-R/F): A cross-cultural adaptation. Frontiers in Child and Adolescent Psychiatry, 2, 1221933.

Hoffman, K., Weisskopf, M. G., Roberts, A. L., Raz, R., Hart, J. E., Lyall, K., Hoffman, E. M., Laden, F., & Vieira, V. M. (2017). Geographic patterns of autism spectrum disorder among children of participants in nurses’ health study ii. American Journal of Epidemiology, 186(7), 834–842.

Ijon, R., Ahmad, A., Kurniawan, Y., Nik Azim, N. A. F., Rusdi, F. A., Abu Hassan Sha’ari, A., Ahmad Tarmizi, S. A., Masron, T., & Mohd Ali, A. S. (2026). Mapping Barriers and Opportunities: Advancing Inclusive Service Delivery for Autistic Children in Kelantan. Proceeding of International University Carnival on E-Learning (IUCEL 2025) “Embracing AI for Innovative Learning and Inclusive Education, 13 November, Universiti Teknikal Malaysia Melaka (UTEM).

Jubit, N., Masron, T., Puyok, A., & Ahmad, A. (2023). Geographic distribution of voter turnout, ethnic turnout and vote choices in Johor state election. Geografia-Malaysian Journal of Society and Space, 19(4), 64–76.

Kumar, A., & Bhattacharya, S. (2024). Unveiling autism spectrum disorder in South East Asia through a public health lens. Frontiers in Child and Adolescent Psychiatry, 3, 1489269.

Lin, Y., Chen, G., Lu, H., Qin, R., Jiang, J., Tan, W., Luo, C., Chen, M., Huang, Q., Huang, L., Dong, A., & Qin, J. (2025). Inequality and heterogeneity in medical resources for children with autism spectrum disorders: A study in the ethnic minority region of Southern China. BMC Public Health, 25(1), 1677–1694.

Maenner, M. J., Warren, Z., Williams, A. R., Amoakohene, E., Bakian, A. V, Bilder, D. A., Durkin, M. S., Fitzgerald, R. T., Furnier, S. M., Hughes, M. M., Ladd-Acosta, C. M., McArthur, D., Pas, E. T., Salinas, A., Vehorn, A., Williams, S., Esler, A., Grzybowski, A., Hall-Lande, J., … Shaw, K. A. (2023). Prevalence and characteristics of autism spectrum disorder among children aged 8 years - Autism and developmental disabilities monitoring network, 11 sites, United States, 2020. Morbidity and Mortality Weekly Report (MMWR) Surveillance Summaries, 72(2), 1–14.

Magen-Molho, H., Harari-Kremer, R., Pinto, O., Kloog, I., Dorman, M., Levine, H., Weisskopf, M. G., & Raz, R. (2020). Spatiotemporal distribution of autism spectrum disorder prevalence among birth cohorts during 2000–2011 in Israel. Annals of Epidemiology, 48, 1–8.

Mahamud, M. H., Rahmat, N. E., & Wan Mohd Razali, W. A. A. (2025). The high cost of autism care in Malaysia: A review of financial burdens and policy gaps. International Journal of Research and Innovation in Social Science, IX(VII), 4638–4643.

Marzuki, A., Zakaria, Y. S., Masron, T., Ariffin, N. A., Bagheri, M., & Ahmad, A. (2026). Forecasting coastal morphodynamics and urban expansion at Sungai Karang, Malaysia: A machine learning approach within Google Earth Engine toward 2030. Land Degradation & Development, 37(12).

Masron, T., Ahmad, A., Jubit, N., Sulaiman, M. H., Rainis, R., Redzuan, M. S., Junaini, S. N., Jamian, M. A. H., Mohd Ali, A. S., Salleh, M. S., Zaini, F., Soda, R., & Kimura, Y. (2024). Crime Map Book. Centre for Spatially Integrated Digital Humanities (CSIDH), Faculty of Social Sciences and Humanities, Universiti Malaysia Sarawak.

Mazumdar, S., Winter, A., Liu, K.-Y., & Bearman, P. (2013). Spatial clusters of autism births and diagnoses point to contextual drivers of increased prevalence. Social Science & Medicine, 95, 87–96.

McGrath, K., Bonuck, K., & Mann, M. (2020). Exploratory Spatial analysis of autism rates in New York School Districts: Role of sociodemographic and language differences. Journal of Neurodevelopmental Disorders, 12(1), 35.

Mohd Ali, A. S., Junaini, S. N., Masron, T., Kimura, Y., & Ahmad, A. (2025). Urbanization and aging in ASEAN: A comparative demographic analysis from 1970 to 2023. Geografia-Malaysian Journal of Society and Space, 21(2), 34–53.

Mohd Rofiee, N. A. S., Majid, N., Nordin, R., Munjidah, A., & Hashim, N. (2025). Awareness and stigma towards autism spectrum disorder among sub-urban community: A cross-sectional study. Malaysian Journal of Medicine and Health Sciences, 21(5), 328–335.

Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1–2), 17–23.

Morrison, C. N., Rundle, A. G., Branas, C. C., Chihuri, S., Mehranbod, C., & Li, G. (2020). The unknown denominator problem in population studies of disease frequency. Spatial and Spatio-Temporal Epidemiology, 35, 100361.

Omar, A. F., Mokhtar, I. W., & Ahmad, M. S. (2023). Challenges in healthcare management of individuals with special needs in Malaysia: Perceptions of caregivers. Journal of International Society of Preventive and Community Dentistry, 13(2), 148–156.

Pamukçu, E., Bayir, T., & Uysal, S. (2026). Global spatial clustering of MPOX outbreaks: A geospatial analysis from 2022 to 2024. International Journal of Environmental Health Research, 36(5), 1133–1142.

Piras, G., Muzi, F., & Zylka, C. (2024). Integration of BIM and GIS for the digitization of the built environment. Applied Sciences, 14(23), 11171.

Roman-Urrestarazu, A., van Kessel, R., Allison, C., Matthews, F. E., Brayne, C., & Baron-Cohen, S. (2021). Association of race/ethnicity and social disadvantage with autism prevalence in 7 million school children in England. JAMA Pediatrics, 175(6), e210054.

Roman-Urrestarazu, A., Yang, J. C., van Kessel, R., Warrier, V., Dumas, G., Jongsma, H., Gatica-Bahamonde, G., Allison, C., Matthews, F. E., Baron-

Cohen, S., & Brayne, C. (2022). Autism incidence and spatial analysis in

more than 7 million pupils in english schools: A retrospective, longitudinal, school registry study. The Lancet Child & Adolescent Health, 6(12), 857–868.

Samsudin, N. A., Shamsuddin, S., & Abdullah, R. (2025). Brief report: Pseudo-autism in Malaysia- The unseen struggles and impact on parents’ mental health. International Journal of Special Education (IJSE), 40(1), 49–61.

Selvam, K. (2024, March 2). Lack of Medical Facilities, Care for Autism Spectrum Disorder Plagues Rural Areas. Sinar Daily. https://www.sinardaily.my/article/216829/culture/health/lack-of-medical-facilities-care-for-autism-spectrum-disorder-plagues-rural-areas

Shair, S. N., Zaki, N. R., Mohd, M. A., Mohd Amin, M. N., Zainan Abidin, A. W., Ahmad, S., & Jamil, N. (2024). Prevalence of Autism spectrum disorder among school-age children in Malaysia: Analysis by age and states. Malaysian Journal of Public Health Medicine, 24(3), 71–80.

Shrestha, M., Basukala, S., Thapa, N., Shrestha, O., Basnet, M., Shrestha, K., Regmi, S., Chhetri, S. T., & Kunwor, B. (2024). Prevalence of autism spectrum disorder among children in Southeast Asia from 2002 to 2022: An updated systematic review and meta-analysis. Health Science Reports, 7(4), e2005.

Surya Pratama, F., Erasiah, E., Dalela, R., Syauqi Ardy, M., & Kumala Dewi, S. (2023). Kelantan the little mecca: Its influence on the archipelago’s 15th-19th century islamic civilisation to the present day. Jurnal Lektur Keagamaan, 21(1), 125–156.

Talantseva, O. I., Romanova, R. S., Shurdova, E. M., Dolgorukova, T. A., Sologub, P. S., Titova, O. S., Kleeva, D. F., & Grigorenko, E. L. (2023). The global prevalence of autism spectrum disorder: A three-level meta-analysis. Frontiers in Psychiatry, 14, 1071181.

Wan Zainodin, N. N. A., & Zainal, M. S. (2025). Adolescents with high-functioning autism in Asia: Reviewing learning barriers, social development, and future directions. International Journal of Education Psychology and Counseling, 10(61), 207–221.

WHO. (2023, November 15). Autism: Key Facts. World Health Organization (WHO).

Zakaria, Y. S., Akhir, M. F., Muslim, A. M., Ariffin, N. A., & Ahmad, A. (2025). Estimating forest aboveground biomass density using Remote Sensing and Machine Learning: A RSME approach. Land Degradation & Development, 36(18), 6514–6527.


Refbacks

  • There are currently no refbacks.