Examining Drug Use Among Different Ethnicities and Analyzing Its Relationship Across Police Station Boundaries in The Federal Territory of Kuala Lumpur and Selangor

  • Norita anak Jubit Borneo Institute for Indigenous Studies (BorIIS), University of Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
  • Tarmiji Masron Centre for Spatially Integrated Digital Humanities (CSIDH), Faculty of Social Science and Humanities, Universiti Malaysia Sarawak, 94300, Kota Samarahan, Kuching, Sarawak, Malaysia.
  • Azizul Ahmad Centre for Spatially Integrated Digital Humanities (CSIDH), Faculty of Social Science and Humanities, Universiti Malaysia Sarawak, 94300, Kota Samarahan, Kuching, Sarawak, Malaysia.
  • Mohd Sofian Redzuan Centre for Spatially Integrated Digital Humanities (CSIDH), Faculty of Social Science and Humanities, Universiti Malaysia Sarawak, 94300, Kota Samarahan, Kuching, Sarawak, Malaysia.
  • Yoshinari Kimura Graduate School of Literature and Human Sciences, Osaka Metropolitan University, 3-3-138 Sugimoto-Cho, Sumiyoshi-Ku, Osaka 5588585, Japan
Keywords: Drug use, ethnicities, police station boundaries, Kuala Lumpur, Selangor

Abstract

In Malaysia, the majority ethnicity involved in drug use is Malay, followed by Chinese and Indian populations. The aimed of this study is to identify the relationship between drug use among different ethnicities. Data was consist of drug use, different ethnicity (Malay, Chinese and Indian) from the years 2015 to 2020 which was obtained from Bukit Aman. In this study, spatial data comprising of police station boundaries of Federal Territory of Kuala Lumpur and Selangor. According to the findings, the study revealed a positive correlation between a higher population of ethnic Malay individual and an increased prevalence of drug use. Furthermore, the study also found a significant positive relationship between a lower population of ethnic Indian and Chinese individuals and higher rates of drug use. There is no redundancy among explanatory variables. GWR shows that police station boundaries of Sentul, Ampang and Cyberjaya classified as strongest relationship between ethnicity and drug users. In addition, the result of GWR did not improve from a global model of OLS can be attributed to the absence of variation in the standard error coefficient for both models. That is probably why the AICc and Adjusted R2 of OLS model and GWR model showing the same result and not improved. This model provides valuable information for policymakers when developing drug policies and strategies. It helps them understand the geographic distribution of drug use across different ethnic groups and provides insights into the local context and challenges. Government can provide support services for all ethnic groups.

Downloads

Download data is not yet available.

References

Abdullah, R. T., Embong, R., Omar, N., Yaakob, R., & Lateh, H. M. (2021). The factors affecting the tendency of drug addiction among Malays in Malaysia. Geintec, 11(4), 2146-2155.

Amanda, K. G., Grisel, G-R., Kennica, F., Nashalys, K. S., Mullican, K., N., Isha, W. M., Ruschelle, M. L., Debra, L. K., Lindsay, M., O., & Kelly, C. D. (2024). The association between alcohol use and sexual assault victimization among college students differs by gender identity and race.

Ambo, H., Mokhtar, S., & Thia, K. (2022). Syabu drug abuse among the muslim community in Sandakan, Sabah: Factors and measures to overcome it. International Journal of Law, Government and Communication, 7(28), 281-295.

Chen, J., Liu, L., Liu, H., Long, D., Xu, C., Zhou, H. (2020). The spatial heterogeneity of factors of drug dealing: A case study from ZG, China. International Journal of Geo-Information, 9(205), 2-13.

Daoud, J. I. (2017). Multicollinearity and regression analysis. IOP Conference Series: Journal of Physics: Conference Series 949(2017), 1-6. https://core.ac.uk/download/pdf/300445858.pdf

ESRI. (2024). Geographically Weighted Regression (GWR) (Spatial Statistics). https ://pro. arcgis.com/en/pro-app/latest/tool-reference/spatial statistics /geographically weighted regression.htm

Foo, Y-C., Tam, C-L., Lee, T-H. (2012). Family and peer influence in drug abuse: A study in Rehabilitation Centre. International Journal of Collaborative Research on Internal Medicine & Public Health, 4(3), 190-201.

Fook, C. Y., & Adnan, N. A. Using geographical information system to identify high risk areas of substance abuse in Malaysia. https://www.adk.gov.my/wp-content/uploads/3-ARTIKEL-JURNAL-DEVELOPING-GIS.pdf

Hakansson, A., Jesionowska, V. (2018). Associations between substance use and type of crime in prisoners with substance use problems – a focus on violence and fatal violence. Substance Abuse and Rehabilitation, 9, 1-9.

Hatta, D.S.W., & Zulkarnain, A. (2010). Religion and drug dependency: A comparative study of Malay male youth in Malaysia. Journal of Religion & Spirituality in Social Work: Social Thought, 29(4), 337-348.

Ismail, R., Abdul Manaf, M. R., Hassan, M. R., Mohammed Nawi, A., Ibrahim, N., Lydon, N. (2022). Prevalence of Drug and Substance Use among malaysian youth: A nationwide survey. International Journal of Environmental Research and Public Health, 19(4684), 2-15.

Ji, H., Shin, S. H., Rogers, A., Neese, J., & Lee, H. Y. (2022). Racial/ethnic disparities in drug use during the COVID 19 pandemic: Moderating effects of non-profit substance use disorder service expenditures. PLoS ONE, 17(6): e0270238. https: //doi.org /10.1371/journal.pone.0270238

Kianfar, N., Mesgari, M. S. (2022). GIS-based spatio-temporal analysis and modelling of COVID-19 incidence rates in Europe. Spatio and Spatio-temporal Epidemiology, 41, 2-16.

Marinelli, S., Basile, G., Manfredini, R., & Zaami, S. (2023). Sex-and gender-specific drug abuse dynamics: The need for tailored therapeutic approaches. Journal of Personalized Medicine, 13(6), 2-14.

NADA. Laporan Tahunan Agensi Anti Dadah Kebangsaan. 2019. Available from: https://www.adk.gov.my/wpcontent/uploads/BUKU-LAPORANTAHUNAN-2019.pdf

Nagelhout, G. E., Hummel, K., Goeij, M. C. M. de., Vries, H. de., Kaner, E., Lemmens, P. (2017). How economic recessions and unemployment affect illegal drug use: A systematic realist literature review. International Journal of Drug Policy, 44, 69-83.

National Anti-Drug Agency, Ministry of Home Affairs. (2020). Drug Information. https://www.adk.gov.my/wp-content/uploads/Buku-Maklumat-Dadah-2020.pdf

National Anti-Drug Agency, Ministry of Home Affairs. Drug Information 2022. https://www.adk.gov.my/wp-content/uploads/BMD2020_BM-eBook_compressed.pdf

Nkeki, F. N., & Osirike, A. B. (2013). GIS-based local spatial statistical model of cholera occurrence: Using Geographically Weighted Regression. Journal of Geographic Information System, 5(6), 531-542.

Nordin, M. N., Masron, T., Jubit, N., Yunos, N. (2022). The spatial relationship between drug abuse and home burglaries: Northeast District of Penang. International Journal of Current Science Research and Review. An open access peer reviewed Journal, 5(7), 2312-2325.

Nordin, M. N., Masron, T., Yaakub, N. F., Salleh, M. S., Yunos, N. E., Junaini, S. N. (2020). GIS of drug abuse cases among youth in the Nortehast district of Penang. Malaysia Journal of Tropical Geography, 46(1&2): 85-99.

Norita, Jubit, Tarmiji Masron & Mohd Azizul Hafiz, Jamian (2022) Permodelan Jenayah harta Benda dan Kebimbangan Tentang Jenayah di Bandar Raya Kuching, Sarawak. UNIMAS Publisher, Kota Samarahan, Sarawak, Malaysia. ISBN 978-967-0054-01-8

Ogowewo, B., Noh, S., Hamilton, H., Brands, B., Gastaldo, D., Gloria, M. D., Wright, M., Cumsille, F., & Khenti, A. (2015). Gender differences for peer influence on drug use among students from one university in Guyana: Curriculum Implications, 24, 170-176. http://dx.doi.org/10.1590/0104-07072015001200014

Rodzlan Hasani, W, Shakira., Miaw Yn, J. L., Saminathan, T. Arasu., Robert Lourdes, T. G., Ramly, R., Abd Hamid, H. A., Ismail, Hasimah., Abd Majid, N. L., Mat Rifin, H., S Maria Awaluddin., Mohd Yusoff, M. F. (2019). Risk factors for illicit drug use among Malaysian male adolescenst. Asia Pacific Journal of Public Health, 31(8), 48-56. https://doi.org/10.1177/1010539519865053

Shafiee, A. A. H., Othman, K., Baharudin, D. F., Mohamad Yasin, N., Amat, S., Mohd Jaladin, R. A., Anuar Rahimi, M. K., Mokhtar, A. N., Wahab, S., Khairul Anuwar, H. H. (2023). An analysis on youth drug abuse: Protective and risk factors in high-risk area. Pertanika Journal of Social Science and Humanities, 31(2), 585-605.

Toriman, M. E., Abdullah, S. N. F., Azizan, I. A., Kamarudin, M, K, A., Umar, R., Mohamad, N. (2015). Malaysian Journal of Analytical Sciences, 19(6), 1361-1373.

UNODC “Turning the Tide for Women and Girls Who Use Drugs in Afghanistan.” 2014.

Wang, J., Hu, J., Shen, S., Zhuang, J., & Ni, S. (2020). Crime risk analysis through big data algorithm with urban metrics, 545, 123627.

World Drug Report. (2023). Inequalities xacerbating health problems associated with drug use. United Nations, New York.

Published
2026-08-31
Section
Articles