The Relationship Between HDI Values and Road Traffic Fatality Rates
Cilt 9 Sayı 19 kapak
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Keywords

Human Development Index
road safety
road traffic fatalities
traffic fatality rates

How to Cite

Düzyol, S. G., Daibaşoğlu, K., & Üzümcüoğlu, Y. (2021). The Relationship Between HDI Values and Road Traffic Fatality Rates. Nesne Journal of Psychology, 9(19), 42-51. https://doi.org/10.7816/nesne-09-19-04

Article History

Received: 10 September 2020
Revised: 18 December 2020
Accepted: 24 January 2021
Published: 15 April 2021

Abstract

Road traffic accidents are a serious but an avoidable problem that cause both life and economic loss worldwide. There are some common factors such as income, education and health that affect both socioeconomic development and road traffic fatality rates of countries. Examination of these factors separately during the analyze of road traffic fatality rates might cause misleading results due to the relationships between stated variables. Thus, using an inclusive parameter like Human Development Index (HDI), may provide more realistic results. In the current study, the relationship between HDI, its dimensions (GNI per capita, expected years of schooling, mean years of schooling and life expectancy at birth) and road traffic fatality rates are examined. Hierarchical regression analysis was conducted in order to obtain results about the effects of each dimension of HDI. Results showed that all dimensions of HDI negatively predicted road traffic fatalities. Results have been discussed according to related literature and suggestions have been made for further research and applications.

Öz

Trafik kazaları dünya çapında yaşam kayıplarına ve ekonomik kayıplara neden olan ciddi ancak önlenebilir sorunlardır. Sağlık, eğitim ve gelir gibi faktörler de ülkelerin sosyoekonomik gelişmişlik düzeylerini ve trafik kazaları ölüm oranlarını etkileyen faktörlerdendir. Karayolu trafik ölüm oranlarının analizi sırasında bu faktörlerin ayrı ayrı incelenmesi, belirtilen değişkenler arasındaki ilişkilerden dolayı yanıltıcı sonuçlara neden olabilir. İnceleme yaparken İnsan Gelişmişlik Endeksi (İGE) gibi kapsayıcı bir parametre kullanmak daha realistik sonuçlar elde etmemize olanak sağlar. Bu çalışmada İGE endeksi, İGE endeksinin her bir boyutu (kişi başı gayrisafi milli hasıla, beklenen eğitim görme yılı, ortalama eğitim alınan yıl ve doğumdaki yaşam beklentisi) ve ölümlü trafik kazaları ile arasındaki ilişki incelenmiştir. İGE endeksinin her bir boyutunun etkilerini inceleyebilmek amacıyla hiyerarşik regresyon analizi kullanılmıştır. Sonuçlara göre İGE’nin tüm boyutları, karayolu trafik ölüm oranlarını negatif bir ilişki içerisinde tahmin etmektedir. Sonuçlar ilgili literatür ışığında tartışılmış ve uygulamalar ve gelecek çalışmalar için önerilerde bulunulmuştur.

Anahtar Kelimeler: İnsan Gelişmişlik Endeksi, yol güvenliği, karayolu trafik ölümleri, trafik ölüm oranları

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References

Anbarci, N., Escaleras, M., & Register, C. A. (2009). Traffic fatalities: does income inequality create an externality. Canadian Journal of Economics/Revue Canadienne D'économique, 42(1), 244-266.

Beck, L. F., Downs, J., Stevens, M. R., & Sauber-Schatz, E. K. (2017). Rural and urban differences in passenger-vehicle–occupant deaths and seat belt use among adults—United States, 2014. MMWR Surveillance Summaries, 66(17), 1-13.

Bester, C. J. (2001). Explaining national road fatalities. Accident Analysis & Prevention, 33(5), 663-672.

Bishai, D., Quresh, A., James, P., & Ghaffar, A. (2006). National road casualties and economic development. Health Economics, 15(1), 65-81.

Cubbin, C., LeClere, F. B., & Smith, G. S. (2000). Socioeconomic status and injury mortality: ndividual and neighbourhood determinants. Journal of Epidemiology & Community Health, 54(7), 517-524.

Eun, S. J. (2020). Trends in mortality from road traffic injuries in South Korea, 1983–2017: Joinpoint regression and age-period-cohort analyses. Accident Analysis & Prevention, 134, 105325.

Garg, N., & Hyder, A. A. (2006). Exploring the relationship between development and road traffic injuries: a case study from India. The European Journal of Public Health, 16(5), 487-491.

Gaygısız, E. (2010). Cultural values and governance quality as correlates of road traffic fatalities: a nation level analysis. Accident Analysis & Prevention, 42, 1894–1901.

Gustafson, P. (1997). Large Hierarchical Bayesian Analysis of Multivariate Survival Data. Biometrics, 53(1), 230-242.

Høye, A. (2016). How would increasing seat belt use affect the number of killed or seriously injured light vehicle occupants?. Accident Analysis & Prevention, 88, 175-186.

Kim, H., Jung, K. Y., Kim, S. P., Kim, S. H., Noh, H., Jang, H. Y., ... & Ju, J. M. (2012). Changes in preventable death rates and traumatic care systems in Korea. Journal of the Korean Society of Emergency Medicine, 23(2), 189-197.

Kopits, E., & Cropper, M. L. (2005). Why Have Traffic Fatalities Declined in Industrialized Countries: Implications for Pedestrians and Vehicle Occupants. . World Bank Publications, 3678

Law, T. H., Noland, R. B., & Evans, A. W. (2011). The sources of the Kuznets relationship between road fatalities and economic growth. Journal of Transport Geography, 19(2), 355-365.

Noland, R. B. (2003). Medical treatment and traffic fatality reductions in industrialized countries. Accident Analysis & Prevention, 35(6), 877-883.

Özkan, T., & Lajunen, T. (2007). The role of personality, culture, and economy in unintentional fatalities: An aggregated level analysis. Personality and Individual Differences, 43(3), 519–530.

Pan, W. T. (2017). A newer equal part linear regression model: a case study of the influence of educational input on gross national income. Eurasia Journal of Mathematics, Science and Technology Education, 13(8), 5765-5773

Spoerri, A., Egger, M., & von Elm, E. (2011). Mortality from road traffic accidents in Switzerland: longitudinal and spatial analyses. Accident Analysis & Prevention, 43(1), 40-48

Taylor, N. L., & Daily, M. (2019). Self-reported factors that influence rear seat belt use among adults. Journal of Safety Research, 70, 25–31

Todaro, M. P., & Smith, S. C. (2015). Economic Development. United Kingdom: Pearson Education.

United Nations Development Programme. (2020a). Human Development Index (HDI). http://hdr.undp.org/en/content/human-development-index-hdi

United Nations Development Programme. (2020b). Human Development Data (1990-2018). http://hdr.undp.org/en/data

Üzümcüoğlu, Y., Solmazer, G., Özkan, T. (2020). The relationship between culture and traffic fatality rates at national level: the moderating role of the economy. Trafik ve Ulaşım Araştırmaları Dergisi , 3(1) , 28-38.

van Beeck, E. F., Borsboom, G. J., & Mackenbach, J. P. (2000). Economic development and traffic accident mortality in the industrialized world, 1962–1990. International Journal of Epidemiology, 29(3), 503- 509.

Wangdi, C., Gurung, M. S., Duba, T., Wilkinson, E., Tun, Z. M., & Tripathy, J. P. (2018). Burden, pattern and causes of road traffic accidents in Bhutan, 2013–2014: a police record review. International Journal of Injury Control and Safety Promotion, 25(1), 65-69.

World Health Organization. (2018a). Global Status Report on Road Safety 2018. https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/

World Health Organization. (2018b, July 5). Disability-adjusted Life Years (DALYs). https://www.who.int/gho/mortality_burden_disease/daly_rates/text/en/

World Health Organization (2020, February 7). Road traffic injuries. https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries

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