International Peer-Reviewed JournalOpen AccessISSN 2456-8880
irejournals@gmail.com+91-7433024337

Home / Current Issue / Paper 1718104

1718104 Vol 9 · Issue 11 Download Paper

Temporal Patterns, Gender Disparities & Future Projections of Suicide Rates (A Statistical Analysis Across Selected WHO Regions and Nigeria (2000–2021))

Egbo M. N. Nwoye O. N. Abiahu O. C. Ogor B. O.

Subject area: Biological & Medical Sciences  ·  Area of research: Suicide Trends & Gender Disparities

DOI: https://doi.org/10.64388/IREV9I11-1718104

Abstract

This study examined the temporal patterns, gender disparities, and future projections of suicide rates across selected WHO regions and Nigeria between 2000 and 2021 using descriptive statistics, trend analysis, moving averages, volatility measures, and ARIMA forecasting techniques. Suicide remains a major global public health challenge, with clear regional and gender-based differences that continue to shape mortality patterns worldwide. The findings revealed substantial regional variation in suicide rates. Europe recorded the highest mean total suicide rate (34.04 per 100,000 population), while the Eastern Mediterranean region recorded the lowest (5.34). Although most regions showed a gradual decline in suicide rates over time, the pace of decline differed considerably. Europe and the Eastern Mediterranean exhibited strong downward trends, whereas Africa showed only slight changes over the study period. The study also confirmed persistent gender inequality in suicide mortality across all regions. Male suicide rates consistently exceeded female rates, with Europe recording the widest gender gap (20.30). Nigeria displayed a distinct pattern characterized by moderate suicide rates but widening gender disparity over time, as the male-to-female suicide ratio increased steadily throughout the study period. This suggests that while overall suicide levels in Nigeria remained relatively stable, male vulnerability to suicide became increasingly pronounced. Forecasting using the ARIMA (0,2,2) model projected that Nigeria’s suicide rates are likely to remain relatively stable up to 2030, with only a slight downward movement if current conditions persist. The study concludes that suicide mortality is influenced by complex social, demographic, and structural factors, and that reducing the burden of suicide will require stronger mental health systems, improved suicide surveillance, gender-sensitive interventions, and proactive long-term public health policies.

Keywords

Suicide Rate, Gender Disparity, Time Series Analysis, Forecasting, Volatility.

References

[1] Ha, K.-M. (2024). Reviewing global suicide rates via X, Y, and Z perspectives. F1000Research, 13, 1112. https://doi.org/10.12688/f1000research.153928.1

[2] Mäkinen, I. H. (2006). Suicide mortality of Eastern European regions before and after the Communist period. Social Science & Medicine, 63(4), 1000–1010. https://doi.org/10.1016/j.socscimed.2006.01.002

[3] Malakouti, S. K., Davoudi, F., Khalid, S., Ahmadzad Asl, M., Khan, M. M., Alirezaei, N., Mirabzadeh, A., & DeLeo, D. (2014). The epidemiology of suicide behaviors among the countries of the Eastern Mediterranean Region of WHO: A systematic review. Iranian Journal of Psychiatry, 9(3), 125–137.

[4] Pirkis, J., Mok, K., Robinson, J., & Nordentoft, M. (2016). Influences on suicidal thoughts and behavior. In R. C. O’Connor & J. Pirkis (Eds.), The international handbook of suicide prevention (2nd ed.). Wiley.

[5] Rotejanaprasert, C., Thanutchapat, P., Phoncharoenwirot, C., Mekchaiporn, O., Chienwichai, P., & Maude, R. J. (2020). Global spatiotemporal analysis of suicide epidemiology and risk factor associations from 2000 to 2019 using Bayesian space-time hierarchical modeling. Scientific Reports, 10, 1–12.

[6] Sha, F., Chang, Q., Zhao, Z., Cai, Z., Li, B., Wu, D., Yu, X., Yip, P. S. F., & Canetto, S. (2024). Absolute and age-relative suicide rates for women and men age 60 years and older at global, regional, and national levels, 1990–2019. Preprint. https://doi.org/10.21203/rs.3.rs-4365103/v1

[7] Turecki, G., & Brent, D. A. (2016). Suicide and suicidal behavior. In R. King & A. Apter (Eds.), Suicide and life-threatening behavior.

[8] Van Der Walt, G., Stein, D. J., & Bantjes, J. (2023). Suicide mortality across Africa, 1990–2023: Temporal, demographic, subregional, and national patterns from the Global Burden of Disease. Preprint. https://ssrn.com/abstract=6210350

[9] World Health Organization. (2014). Preventing suicide: A global imperative. https://www.who.int/mental_health/suicide-prevention/world_report

[10] World Health Organization. (2017). Global Health Observatory (GHO) data. https://www.who.int/gho

[11] Xu, J. Q., Murphy, S. L., Kochanek, K. D., Bastian, B., & Arias, E. (2016). Deaths: Final data for 2016. National Vital Statistics Reports, 67. National Center for Health Statistics.

[12] Egbo, M. N., Nwafor, G. O., Owolabi, T. W., Onukwube, O. G., Okechukwu, B. N., & Ofodile, O. R. (2025). Statistical analysis of suicide rates across WHO regions. Scholars Journal of Physics, Mathematics and Statistics, 12(6), 240–245. https://doi.org/10.36347/sjpms.2025.v12i06.005

[13] World Health Organization. (2025). Suicide mortality rate (SDG 3.4.2). World Health Organization

[14] European Institute for Gender Equality. (2023). Gender disparity. European Institute for Gender Equality

[15] MathWorks. (2024). What is time series analysis? MathWorks

[16] Tableau. (2024). Time series forecasting: Definition, applications, and examples. Tableau

[17] Hayes, A. (2024). Volatility definition. Investopedia

[18] Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley.

[19] Wooldridge, J. M. (2016). Introductory Econometrics: A Modern Approach (6th ed.). Cengage Learning.

[20] Pearson, K. (1895). Notes on regression and inheritance in the case of two parents. Proceedings of the Royal Society of London, 58, 240–242. https://doi.org/10.1098/rspl.1895.0041

[21] Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time series analysis: Forecasting and control (5th ed.). Wiley.

[22] Khan, F.Z. Indian Research on Suicide Ind. Journal of psy 2010 52 (Supp11) S291-56

[23] Hawton, K and Heeringen, K.V. (2009). Lancet Medical Journal Volume 373, Issue 9672, P 1372 – 1381 Doi:10.1016/S0140-6736(09)60372-x

[24] De Leo, D. (2015). Can we rely on Suicide Mortality Data? Journal of Crisis, 36 (1): 1-3. Doi:10.1027/0227-5910/9000315

[25] Egbo, I. And Egbo, M.N. (2010). Probability and Statistical Inference for Engineering and the Sciences (1st ed) ISBN 978-38334-9-9. Milestone Publishers Ltd 44 Erekwerenwa Street Owerri.

How to cite this paper

Egbo M. N., Nwoye O. N., Abiahu O. C., Ogor B. O. "Temporal Patterns, Gender Disparities & Future Projections of Suicide Rates (A Statistical Analysis Across Selected WHO Regions and Nigeria (2000–2021))" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 4232-4245 https://doi.org/10.64388/IREV9I11-1718104
Egbo M. N., Nwoye O. N., Abiahu O. C., Ogor B. O. "Temporal Patterns, Gender Disparities & Future Projections of Suicide Rates (A Statistical Analysis Across Selected WHO Regions and Nigeria (2000–2021))" Iconic Research And Engineering Journals, vol. 9, no. 11, May. 2026, doi: https://doi.org/10.64388/IREV9I11-1718104
Egbo M. N., Nwoye O. N., Abiahu O. C., Ogor B. O. (2026). Temporal Patterns, Gender Disparities & Future Projections of Suicide Rates (A Statistical Analysis Across Selected WHO Regions and Nigeria (2000–2021)). Iconic Research And Engineering Journals, 9(11). doi: https://doi.org/10.64388/IREV9I11-1718104
Egbo M. N., Nwoye O. N., Abiahu O. C., Ogor B. O. "Temporal Patterns, Gender Disparities & Future Projections of Suicide Rates (A Statistical Analysis Across Selected WHO Regions and Nigeria (2000–2021))" Iconic Research And Engineering Journals, vol. 9, no. 11, May. 2026. Crossref, https://doi.org/10.64388/IREV9I11-1718104
@article{1718104,
      author = {Egbo M. N., Nwoye O. N., Abiahu O. C., Ogor B. O.},
      title = {Temporal Patterns, Gender Disparities & Future Projections of Suicide Rates (A Statistical Analysis Across Selected WHO Regions and Nigeria (2000–2021))},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {11},
      pages = {4232-4245},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1718104.pdf},
      abstract = {This study examined the temporal patterns, gender disparities, and future projections of suicide rates across selected WHO regions and Nigeria between 2000 and 2021 using descriptive statistics, trend analysis, moving averages, volatility measures, and ARIMA forecasting techniques. Suicide remains a major global public health challenge, with clear regional and gender-based differences that continue to shape mortality patterns worldwide. The findings revealed substantial regional variation in suicide rates. Europe recorded the highest mean total suicide rate (34.04 per 100,000 population), while the Eastern Mediterranean region recorded the lowest (5.34). Although most regions showed a gradual decline in suicide rates over time, the pace of decline differed considerably. Europe and the Eastern Mediterranean exhibited strong downward trends, whereas Africa showed only slight changes over the study period. The study also confirmed persistent gender inequality in suicide mortality across all regions. Male suicide rates consistently exceeded female rates, with Europe recording the widest gender gap (20.30). Nigeria displayed a distinct pattern characterized by moderate suicide rates but widening gender disparity over time, as the male-to-female suicide ratio increased steadily throughout the study period. This suggests that while overall suicide levels in Nigeria remained relatively stable, male vulnerability to suicide became increasingly pronounced. Forecasting using the ARIMA (0,2,2) model projected that Nigeria’s suicide rates are likely to remain relatively stable up to 2030, with only a slight downward movement if current conditions persist. The study concludes that suicide mortality is influenced by complex social, demographic, and structural factors, and that reducing the burden of suicide will require stronger mental health systems, improved suicide surveillance, gender-sensitive interventions, and proactive long-term public health policies.},
      keywords = {Suicide Rate, Gender Disparity, Time Series Analysis, Forecasting, Volatility.},
      month = {May},
      doi = {https://doi.org/10.64388/IREV9I11-1718104}
  }