Assessing Factors Associated with Non-Fatal Injuries from Road Traffic Accidents among Malaysian Adults: A Cross-Sectional Analysis of the PURE Malaysia Study
Abstract
:1. Introduction
2. Methodology
2.1. Study Population
2.2. Measures
2.3. Statistical Analysis
2.4. Ethical Approval
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- May, L.W.; Hassin, R.A.R.M.F.; Diah, J.M.; Mashros, N.; Abdullah, M.E.; Masirin, M.I.B.M. An Overview of the Practice of Traffic Impact Assessment in Malaysia. Int. J. Eng. Adv. Technol. 2019, 8, 914–920. [Google Scholar] [CrossRef]
- Yusoff, I.; Ng, B.K.; Azizan, S.A. Towards Sustainable Transport Policy Framework: A Rail-Based Transit System in Klang Valley, Malaysia. PLoS ONE 2021, 16, e0248519. [Google Scholar] [CrossRef] [PubMed]
- Zulkifli, M.; Razali, A.M.; Masseran, N.; Ismail, N. Statistical Analysis of Vehicle Theft Crime in Peninsular Malaysia Using Negative Binomial Regression Model. Sains Malays. 2015, 44, 1363–1370. [Google Scholar] [CrossRef]
- Kulanthayan, S.; Phang, W.K.; Hayati, K.S. Traffic Light Violation among Motorists in Malaysia. IATSS Res. 2007, 31, 67–73. [Google Scholar] [CrossRef] [Green Version]
- Chiu Chuen, O.; Karim, M.R.; Yusoff, S. Mode Choice between Private and Public Transport in Klang Valley, Malaysia. Sci. World J. 2014, 2014, 394587. [Google Scholar] [CrossRef] [Green Version]
- Rahman, R.; Nemmang, M.S.; Nazimuddin, N.A.; Abdul Hamid, H. Comparison of Traffic Speed Before, During and After “Banci Lalu Lintas” at Federal Road FT005. MATEC Web Conf. 2017, 103, 08004. [Google Scholar] [CrossRef] [Green Version]
- Hamdan, N.; Daud, N. Estimating Cost Ratio Distribution between Fatal and Non-Fatal Road Accidents in Malaysia. In AIP Conference Proceedings; American Institute of Physics: College Park, MD, USA, 2014; Volume 1605, pp. 1051–1055. [Google Scholar]
- MOT Ministry of Transport Malaysia Official Portal Malaysia Road Fatalities Index. Available online: https://www.mot.gov.my/en/land/safety/malaysia-road-fatalities-index (accessed on 18 November 2021).
- Darma, Y.; Karim, M.R.; Abdullah, S. An Analysis of Malaysia Road Traffic Death Distribution by Road Environment. Sādhanā 2017, 42, 1605–1615. [Google Scholar] [CrossRef] [Green Version]
- Che-Him, N.; Roslan, R.; Rusiman, M.S.; Khalid, K.; Kamardan, M.G.; Arobi, F.A.; Mohamad, N. Factors Affecting Road Traffic Accident in Batu Pahat, Johor, Malaysia. J. Phys. Conf. Ser. 2018, 995, 12033. [Google Scholar] [CrossRef]
- Musa, M.F.; Hassan, S.A.; Mashros, N. The Impact of Roadway Conditions towards Accident Severity on Federal Roads in Malaysia. PLoS ONE 2020, 15, e0235564. [Google Scholar] [CrossRef]
- Chow, C.K.; Teo, K.K.; Rangarajan, S.; Islam, S.; Gupta, R.; Avezum, A.; Bahonar, A.; Chifamba, J.; Dagenais, G.; Diaz, R. Prevalence, Awareness, Treatment, and Control of Hypertension in Rural and Urban Communities in High-, Middle-, and Low-Income Countries. JAMA 2013, 310, 959–968. [Google Scholar] [CrossRef] [Green Version]
- Teo, K.; Chow, C.K.; Vaz, M.; Rangarajan, S.; Yusuf, S. The Prospective Urban Rural Epidemiology (PURE) Study: Examining the Impact of Societal Influences on Chronic Noncommunicable Diseases in Low-, Middle-, and High-Income Countries. Am. Heart J. 2009, 158, 1–7. [Google Scholar] [CrossRef]
- DOSM Population and Housing Census. Available online: https://www.dosm.gov.my/v1/index.php?r=column/cone&menu_id=bDA2VkxRSU40STcxdkZ4OGJ0c1ZVdz09 (accessed on 20 June 2022).
- Rahman, N.H.N.; Baharuddin, K.A.; Mohamad, S.M.S. Burden of Motorcycle-Related Injury in Malaysia. Int. J. Emerg. Med. 2015, 8, 17. [Google Scholar] [CrossRef] [Green Version]
- Kamarudin, M.K.A.; Abd Wahab, N.; Umar, R.; Saudi, A.S.M.; Saad, M.H.M.; Rosdi, N.R.N.; Razak, S.A.A.; Merzuki, M.M.; Abdullah, A.S.; Amirah, S. Road Traffic Accident in Malaysia: Trends Selected Underlying Determinants and Status Intervention. Int. J. Eng. Technol. 2018, 7, 112–117. [Google Scholar] [CrossRef] [Green Version]
- Sarani, R.; Allyana, S.; Shaw Voon, W. Malaysian Road Fatalities Prediction for Year 2020. J. Australas. Coll. Road Saf. 2016, 27, 18–22. [Google Scholar]
- Solhi, F. Malaysia Records over 4.94 Million Accidents in Last Decade. New Straits Times, 24 June 2021; 1. [Google Scholar]
- Manan, M.M.A.; Várhelyi, A. Motorcycle Fatalities in Malaysia. IATSS Res. 2012, 36, 30–39. [Google Scholar] [CrossRef] [Green Version]
- Jiménez-Mejías, E.; Prieto, C.A.; Martínez-Ruiz, V.; Del Castillo, J.D.D.L.; Lardelli-Claret, P.; Jiménez-Moleón, J.J. Gender-Related Differences in Distances Travelled, Driving Behaviour and Traffic Accidents among University Students. Transp. Res. Part F Traffic Psychol. Behav. 2014, 27, 81–89. [Google Scholar] [CrossRef]
- Karacasu, M.; Er, A. An Analysis on Distribution of Traffic Faults in Accidents, Based on Driver’s Age and Gender: Eskisehir Case. Procedia-Soc. Behav. Sci. 2011, 20, 776–785. [Google Scholar] [CrossRef] [Green Version]
- Liew, S.; Hamidun, R.; Mohd Soid, N.F. Differences of Driving Experience and Gender on Traffic Offences Among Malaysian Motorists. MATEC Web Conf. 2017, 103, 08016. [Google Scholar] [CrossRef] [Green Version]
- Kulanthayan, S.; Umar, R.S.R.; Hariza, H.A.; Nasir, M.T.M. Modeling of Compliance Behavior of Motorcyclists to Proper Usage of Safety Helmets in Malaysia. Traffic Inj. Prev. 2001, 2, 239–246. [Google Scholar] [CrossRef]
- Abegaz, T.; Gebremedhin, S. Magnitude of Road Traffic Accident Related Injuries and Fatalities in Ethiopia. PLoS ONE 2019, 14, e0202240. [Google Scholar] [CrossRef] [Green Version]
- Mohamed, M.; Bromfield, N.F. Attitudes, Driving Behavior, and Accident Involvement among Young Male Drivers in Saudi Arabia. Transp. Res. Part F Traffic Psychol. Behav. 2017, 47, 59–71. [Google Scholar] [CrossRef]
- Zuwairy, M.S.; Harith, A.A.; Nobuyaki, H.; Naim, N.M.; Yon, R. Road Traffic Accidents: A Descriptive Study of Commuting Injury Among Healthcare Workers in Malaysia 2014–2016. Int. J. Public Health Clin. Sci. 2020, 7, 58–71. [Google Scholar]
- Shaadan, N.; Azhar Suhaimi, M.I.K.; Hazmir, M.I.; Hamzah, E.N. Road Accidents Analytics with Data Visualization: A Case Study in Shah Alam Malaysia. J. Phys. Conf. Ser. 2021, 1988, 012043. [Google Scholar] [CrossRef]
- Rahman, N.H.; Rainis, R.; Noor, S.H.; Mohamad, S.M.S. Geospatial and Clinical Analyses on Pediatric Related Road Traffic Injury in Malaysia. World J. Emerg. Med. 2016, 7, 213. [Google Scholar] [CrossRef] [Green Version]
- Rahman, N.H.N.; Naing, N.N. Geoclinical Analyses for Areas at High Risk for Motorcycle-Related Road Traffic Injury in a District in Malaysia. Hong Kong J. Emerg. Med. 2019, 27, 146–154. [Google Scholar] [CrossRef] [Green Version]
- Borrell, C.; Plasència, A.; Huisman, M.; Costa, G.; Kunst, A.; Andersen, O.; Bopp, M.; Borgan, J.K.; Deboosere, P.; Glickman, M.; et al. Education Level Inequalities and Transportation Injury Mortality in the Middle Aged and Elderly in European Settings. Inj. Prev. 2005, 11, 138–142. [Google Scholar] [CrossRef]
- Moafian, G.; Aghabeigi, M.R.; Heydari, S.T.; Hoseinzadeh, A.; Lankarani, K.B.; Sarikhani, Y. An Epidemiologic Survey of Road Traffic Accidents in Iran: Analysis of Driver-Related Factors. Chin. J. Traumatol. 2013, 16, 140–144. [Google Scholar] [CrossRef]
- Shahbazi, F.; Nazari, S.S.H.; Soori, H.; Khodakarim, S. Socioeconomic Inequality in Mortality from Road Traffic Accident in Iran. J. Res. Health Sci. 2019, 19, e00437. [Google Scholar] [CrossRef]
- Shiferaw, B.A.; Downey, L.A.; Westlake, J.; Stevens, B.; Rajaratnam, S.M.W.; Berlowitz, D.J.; Swann, P.; Howard, M.E. Stationary Gaze Entropy Predicts Lane Departure Events in Sleep-Deprived Drivers. Sci. Rep. 2018, 8, 2220. [Google Scholar] [CrossRef] [Green Version]
- Mahajan, K.; Velaga, N.R. Sleep-Deprived Car-Following: Indicators of Rear-End Crash Potential. Accid. Anal. Prev. 2021, 156, 106123. [Google Scholar] [CrossRef]
- Lazar, M.; Davenport, L. Barriers to Health Care Access for Low Income Families: A Review of Literature. J. Community Health Nurs. 2018, 35, 28–37. [Google Scholar] [CrossRef] [PubMed]
- Chen, S.; Kuhn, M.; Prettner, K.; Bloom, D.E. The Global Macroeconomic Burden of Road Injuries: Estimates and Projections for 166 Countries. Lancet Planet. Health 2019, 3, e390–e398. [Google Scholar] [CrossRef]
- Sari, B.; Idris, H. Determinant of Independent National Health Insurance Ownership in Indonesia. Malays. J. Public Health Med. 2019, 19, 109–115. [Google Scholar] [CrossRef]
- Kay, G.G.; McLaughlin, D. Relationship Between Obesity and Driving. Curr. Obes. Rep. 2014, 3, 336–340. [Google Scholar] [CrossRef]
- Razzaghi, A.; Soori, H.; Kavousi, A.; Abadi, A.; Khosravi, A.; Alipour, A. Risk Factors of Deaths Related to Road Traffic Crashes in World Health Organization Regions: A Systematic Review. Arch. Trauma Res. 2019, 8, 57–86. [Google Scholar]
- Zhu, S.; Kim, J.E.; Ma, X.; Shih, A.; Laud, P.W.; Pintar, F.; Shen, W.; Heymsfield, S.B.; Allison, D.B. BMI and Risk of Serious Upper Body Injury Following Motor Vehicle Crashes: Concordance of Real-World and Computer-Simulated Observations. PLoS Med. 2010, 7, e1000250. [Google Scholar] [CrossRef] [Green Version]
- Lavallière, M.; Tremblay, M.; Lefebvre, F.; Billot, M.; Handrigan, G.A. Aging, Obesity, and Motor Vehicle Collisions. Front. Sustain. Cities 2020, 2, 33. [Google Scholar] [CrossRef]
- Becker, M.J.; Calkins, L.N.; Simmons, W.; Welki, A.M.; Zlatoper, T.J. Obesity and Motor Vehicle Deaths: A Panel-Data Analysis. J. Econ. Stud. 2020, 47, 1233–1246. [Google Scholar] [CrossRef]
- Lim, S.M.; Chia, S.E. The Prevalence of Fatigue and Associated Health and Safety Risk Factors among Taxi Drivers in Singapore. Singap. Med. J. 2015, 56, 92. [Google Scholar] [CrossRef] [Green Version]
- Joseph, B.; Hadeed, S.; Haider, A.A.; Ditillo, M.; Joseph, A.; Pandit, V.; Kulvatunyou, N.; Tang, A.; Latifi, R.; Rhee, P. Obesity and Trauma Mortality: Sizing up the Risks in Motor Vehicle Crashes. Obes. Res. Clin. Pract. 2017, 11, 72–78. [Google Scholar] [CrossRef]
- Enayatollah, H.R.; Khodadady-Hasankiadeh, N.; Kouchakinejad-Eramsadati, L.; Javadi, F.; Haghdoost, Z.; Hosseinpour, M.; Tavakoli, M.; Davoudi-Kiakalayeh, A.; Mohtasham-Amiri, Z.; Yousefzadeh-Chabok, S. The Relationship between Weight Indices and Injuries and Mortalities Caused by the Motor Vehicle Accidents: A Systematic Review and Meta-Analysis. J. Inj. Violence Res. 2020, 12, 85. [Google Scholar] [CrossRef]
- Yeap, S.S.; Goh, E.M.L.; Das Gupta, E. Knowledge about Osteoporosis in a Malaysian Population. Asia-Pac. J. Public Health 2010, 22, 233–241. [Google Scholar] [CrossRef]
- Han Byun, J.; Jeong, B.Y.; Park, M.H. Characteristics of Motorcycle Crashes of Food Delivery Workers. J. Ergon. Soc. Korea 2017, 36, 157–168. [Google Scholar] [CrossRef]
- Rusli, R.; Oviedo-Trespalacios, O.; Abd Salam, S.A. Risky Riding Behaviours among Motorcyclists in Malaysia: A Roadside Survey. Transp. Res. Part F Traffic Psychol. Behav. 2020, 74, 446–457. [Google Scholar] [CrossRef]
- Abdul Manan, M.M.; Várhelyi, A. Motorcyclists’ Road Safety Related Behavior at Access Points on Primary Roads in Malaysia—A Case Study. Saf. Sci. 2015, 77, 80–94. [Google Scholar] [CrossRef]
- Faraut, B.; Andrillon, T.; Vecchierini, M.F.; Leger, D. Napping: A Public Health Issue. From Epidemiological to Laboratory Studies. Sleep Med. Rev. 2017, 35, 85–100. [Google Scholar] [CrossRef]
- Zhou, Y.; Jiang, X.; Fu, C.; Liu, H. Operational Factor Analysis of the Aggressive Taxi Speeders Using Random Parameters Bayesian LASSO Modeling Approach. Accid. Anal. Prev. 2021, 157, 106183. [Google Scholar] [CrossRef]
- Wilhelm, I.; Born, J.; Kudielka, B.M.; Schlotz, W.; Wüst, S. Is the Cortisol Awakening Rise a Response to Awakening? Psychoneuroendocrinology 2007, 32, 358–366. [Google Scholar] [CrossRef]
- Qian, L.; Ru, T.; Chen, Q.; Li, Y.; Zhou, Y.; Zhou, G. Effects of Bright Light and an Afternoon Nap on Task Performance Depend on the Cognitive Domain. J. Sleep Res. 2021, 30, e13242. [Google Scholar] [CrossRef]
- Lovato, N.; Lack, L. The Effects of Napping on Cognitive Functioning. Prog. Brain Res. 2010, 185, 155–166. [Google Scholar] [CrossRef]
- Tumiran, M.A.; Rahman, N.N.A.; Saat, R.M.; Kabir, N.; Zulkifli, M.Y.; Adli, D.S.H. The Concept of Qailulah (Midday Napping) from Neuroscientific and Islamic Perspectives. J. Relig. Health 2015, 57, 1363–1375. [Google Scholar] [CrossRef]
- Lockley, S.W.; Barger, L.K.; Ayas, N.T.; Rothschild, J.M.; Czeisler, C.A.; Landrigan, C.P. Effects of Health Care Provider Work Hours and Sleep Deprivation on Safety and Performance. Jt. Comm. J. Qual. Patient Saf. 2007, 33, 7–18. [Google Scholar] [CrossRef]
- Van Dongen, H.P.A.; Dinges, D.F. Circadian Rhythms in Fatigue, Alertness, and Performance. Princ. Pract. Sleep Med. 2000, 20, 391–399. [Google Scholar]
- Ishak, S.Z.; Syed Md Rahim, S.A. Where Is Malaysia at the End of the Decade of Action 2011–2020? Int. J. Road Saf. 2020, 1, 1–3. [Google Scholar]
- Eusofe, Z.; Evdorides, H. Assessment of Road Safety Management at Institutional Level in Malaysia: A Case Study. IATSS Res. 2017, 41, 172–181. [Google Scholar] [CrossRef]
- Sultan, Z.; Ngadiman, N.I.; Kadir, F.D.A.; Roslan, N.F.; Moeinaddini, M. Factor Analysis of Motorcycle Crashes in Malaysia. Plan. Malays. 2016, 4, 135–146. [Google Scholar]
- Shahid, S.; Minhans, A.; Che Puan, O.; Hasan, S.A.; Ismail, T. Spatial and temporal pattern of road accidents and casualties in peninsular malaysia. J. Teknol. 2015, 76, 57–65. [Google Scholar] [CrossRef] [Green Version]
- Choy, L.K.; Noor, N.N.H.M. Kajian Perubahan Guna Tanah Menerusi Aplikasi Penderiaan Jauh (Land Use Change Detection Using Remote Sensing Approach). Malays. J. Soc. Sp. 2018, 14, 108–124. [Google Scholar]
- Othman, A.G.; Ali, K.H.; Yin, I.; Tan, M.L.; Jizan, N.H.M. Urbanization and Land Use Changes in Rural Town: Guar Cempedak, Kedah. J. Malays. Inst. Plan. 2021, 19, 1–13. [Google Scholar] [CrossRef]
- Barau, A.S.; Said, I. From Goodwill to Good Deals: FELDA Land Resettlement Scheme and the Ascendancy of the Landless Poor in Malaysia. Land Use Policy 2016, 54, 423–431. [Google Scholar] [CrossRef]
Risk Factors | Road Traffic Accident | p-Value | ||
---|---|---|---|---|
Yes n (%) | No n (%) | |||
303 (35.1) | 560 (64.9) | |||
Age (years old) | 35–40 | 40 (32.0) | 85 (68.0) | 0.644 |
41–50 | 90 (33.7) | 177 (66.3) | ||
51–60 | 102 (35.7) | 184 (64.3) | ||
61–70 | 71 (38.4) | 114 (61.6) | ||
Gender | Female | 104 (24.8) | 315 (75.2) | <0.001 ** |
Male | 199 (44.8) | 245 (55.2) | ||
Education level | Primary | 141 (35.8) | 253 (64.2) | 0.002 * |
Secondary | 137 (39.0) | 214 (61.0) | ||
Tertiary | 25 (21.2) | 93 (78.8) | ||
Socioeconomic status | Low | 133 (35.8) | 238 (64.2) | 0.330 |
Middle | 153 (35.7) | 275 (64.3) | ||
High | 17 (26.6) | 47 (73.4) | ||
Marital status | Currently unmarried | 25 (28.1) | 64 (71.9) | 0.138 |
Currently married | 278 (36.0) | 494 (64.0) | ||
Employment status | Yes | 238 (41.3) | 338 (58.7) | <0.001 ** |
No | 65 (22.6) | 222 (77.4) | ||
Location | Urban | 104 (31.4) | 227 (68.6) | 0.079 |
Rural | 199 (37.4) | 333 (62.6) | ||
BMI | Normal | 95 (32.1) | 201 (67.9) | 0.202 |
Overweight (obese) | 208 (36.7) | 359 (63.3) | ||
Smoking status | Yes | 179 (31.7) | 386 (68.3) | 0.002 * |
No | 124 (41.6) | 174 (58.4) | ||
Alcohol consumer | Yes | 283 (35.2) | 520 (64.8) | 0.889 |
No | 20 (33.3) | 40 (66.7) | ||
Perceived stress | Yes | 119 (40.1) | 178 (59.9) | 0.030 * |
No | 183 (32.6) | 379 (67.4) | ||
Financial stress | Yes | 56 (37.1) | 95 (62.9) | 0.575 |
No | 247 (34.7) | 465 (65.3) | ||
Depression | Yes | 280 (35.9) | 499 (64.1) | 0.128 |
No | 20 (26.7) | 55 (73.3) | ||
On medication | Yes | 184 (38.0) | 300 (62.0) | 0.044 * |
No | 117 (31.3) | 257 (68.7) | ||
Siestas | Yes | 190 (37.0) | 324 (63.0) | 0.168 |
No | 113 (32.4) | 236 (67.6) |
Variables | B | S.E | AOR (95% CI) | p-Value | |
---|---|---|---|---|---|
Age (years old) | 35–40 | 1 | |||
41–50 | −0.061 | 0.249 | 0.941 (0.577–1.533) | 0.806 | |
51–60 | 0.078 | 0.264 | 1.081 (0.645–1.814) | 0.767 | |
61–70 | 0.175 | 0.295 | 1.191 (0.668–2.122) | 0.554 | |
Gender | Female | 1 | |||
Male | 0.732 | 0.23 | 2.079 (1.325–3.263) | <0.001 ** | |
Location | Rural | 0.346 | 0.229 | 1.413 (0.902–2.214) | 0.132 |
Urban | 1 | ||||
Education level | Primary | 0.925 | 0.301 | 2.522 (1.398–4.549) | 0.002 * |
Secondary | 0.97 | 0.271 | 2.637 (1.551–4.486) | <0.001 ** | |
Tertiary | 1 | ||||
Socioeconomic status | Low | −0.209 | 0.398 | 0.811 (0.372–1.768) | 0.598 |
Middle | 0.073 | 0.337 | 1.076 (0.556–2.08) | 0.828 | |
High | 1 | ||||
Marital status | Currently unmarried | 0.032 | 0.271 | 1.033 (0.608–1.755) | 0.906 |
Currently married | 1 | ||||
BMI | Normal | 1 | |||
Overweight (obese) | 0.333 | 0.167 | 1.396 (1.006–1.937) | 0.046 * | |
Smoking status | Yes | −0.234 | 0.196 | 0.791 (0.539–1.162) | 0.233 |
No | |||||
Alcohol consumption | Yes | −0.129 | 0.316 | 0.879 (0.473–1.633) | 0.683 |
No | |||||
Employment status | Yes | 0.707 | 0.223 | 2.028 (1.310–3.140) | 0.002 * |
No | |||||
Perceived stress | Yes | −0.26 | 0.17 | 0.771 (0.552–1.076) | 0.126 |
No | 1 | ||||
Financial stress | Yes | −0.03 | 0.211 | 0.971 (0.641–1.469) | 0.888 |
No | 1 | ||||
Clinical depression | Yes | −0.127 | 0.291 | 0.88 (0.498–1.556) | 0.661 |
No | 1 | ||||
On medication | Yes | −0.289 | 0.162 | 0.749 (0.545–1.029) | 0.075 |
No | 1 | ||||
Siesta (noon nap) | Yes | 1 | |||
No | 0.321 | 0.16 | 1.378 (1.007–1.887) | 0.045 * | |
Constant | −2.535 | 0.516 | <0.001 * |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Md Isa, Z.; Ismail, N.H.; Ismail, R.; Mohd Tamil, A.; Ja’afar, M.H.; Mat Nasir, N.; Miskan, M.; Zainol Abidin, N.; Ab Razak, N.H.; Yusof, K.H. Assessing Factors Associated with Non-Fatal Injuries from Road Traffic Accidents among Malaysian Adults: A Cross-Sectional Analysis of the PURE Malaysia Study. Int. J. Environ. Res. Public Health 2022, 19, 8246. https://doi.org/10.3390/ijerph19148246
Md Isa Z, Ismail NH, Ismail R, Mohd Tamil A, Ja’afar MH, Mat Nasir N, Miskan M, Zainol Abidin N, Ab Razak NH, Yusof KH. Assessing Factors Associated with Non-Fatal Injuries from Road Traffic Accidents among Malaysian Adults: A Cross-Sectional Analysis of the PURE Malaysia Study. International Journal of Environmental Research and Public Health. 2022; 19(14):8246. https://doi.org/10.3390/ijerph19148246
Chicago/Turabian StyleMd Isa, Zaleha, Noor Hassim Ismail, Rosnah Ismail, Azmi Mohd Tamil, Mohd Hasni Ja’afar, Nafiza Mat Nasir, Maizatullifah Miskan, Najihah Zainol Abidin, Nurul Hafiza Ab Razak, and Khairul Hazdi Yusof. 2022. "Assessing Factors Associated with Non-Fatal Injuries from Road Traffic Accidents among Malaysian Adults: A Cross-Sectional Analysis of the PURE Malaysia Study" International Journal of Environmental Research and Public Health 19, no. 14: 8246. https://doi.org/10.3390/ijerph19148246