مطالعات جمعیتی

مطالعات جمعیتی

برآورد جداول عمر چند‌کاهشی ایران در سال‌های 1390 تا 1400 و پیش‌بینی برای سال 1405

نوع مقاله : پژوهشی

نویسندگان
1 استادیار جمعیت‌شناسی، گروه جمعیت و سلامت، مؤسسه تحقیقات جمعیت کشور، تهران، ایران (نویسنده مسئول).
2 استادیار آمار، گروه بیمه اشخاص، پژوهشکده بیمه، تهران، ایران.
3 دانش‌آموخته دوره دکتری جمعیت‌شناسی، گروه جمعیت شناسی، دانشکده علوم اجتماعی، دانشگاه یزد، یزد، ایران.
4 دانش‌آموخته دوره دکتری جمعیت‌شناسی، گروه جمعیت شناسی، دانشکده علوم اجتماعی، دانشگاه تهران، تهران، ایران.
چکیده
این مطالعه با هدف سنجش تأثیر حذف علل اصلی مرگ‌ومیر بر شاخص امید زندگی در بدو تولد در ایران طی سال‌های 1390 تا 1405 انجام شده است. داده‌های مورد نیاز از مطالعه بار جهانی بیماری‌ها (2021) گرفته شده است. این داده‌ها شامل تعداد مرگ براساس سن، جنس و علت مرگ در سال‌های 1400-1390 است. پس از ساخت جداول عمر پایه برای زنان و مردان ایرانی برای هر سال، تأثیر علل اصلی مرگ بر امید زندگی، از طریق تکنیک جدول عمر چندکاهشی، محاسبه شد. همچنین با استفاده از روش لی - کارتر، میزان مرگ براساس سن برای سال 1405 پیش‌بینی و جداول عمر چندکاهشی برای علل اصلی مرگ‌ومیر محاسبه شد. یافته‌ها نشان می‌دهد بیشترین افزایش امید زندگی در بدو تولد مردان و زنان ایرانی با حذف بیماری‌های قلبی ـ عروقی صورت گرفته است. ظرفیت افزایش امید زندگی در بدو تولد مردان و زنان طی دوره مورد مطالعه با حذف بیماری‌های قلبی - عروقی و حوادث ترافیکی، کاهش و با حذف سرطان‌ها و دیابت افزایش یافته است. نتایج این پژوهش، کاربردهای مهمی در برنامه‌ریزی و سیاست‌گذاری جمعیتی و اقتصادی دارد و می‌تواند مبنایی برای بهبود محاسبات و ساختار پرداخت‌های بیمه در کشور باشد. 
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Estimating Multiple-Decrement Life Tables in Iran, 2011-2021 and Forecast for 2026

نویسندگان English

Mohamad Sasanipour 1
Mitra Ghanbarzadeh 2
Saeedeh Shahbazin 3
Mahyar Moheby Meymandy 4
1 Assistant Professor of Demography, Department of Population and Health, National Institute for Population Research, Tehran, Iran.
2 Assistant Professor of Statistics, Department of Personal Insurance, Insurance Research Center, Tehran, Iran.
3 PhD in Demography, Department of Demography, Faculty of Social Sciences, Yazd University, Yazd, Iran.
4 PhD in Demography, Department of Demography, Faculty of Social Sciences, University of Tehran, Tehran, Iran.
چکیده English

This study aimed to measure the impact of eliminating the main causes of death on life expectancy at birth in Iran during 2021-2025. The required data were obtained from the Global Burden of Disease Study (2021). These data include the number of deaths by age, sex, and cause of death for 2011-2021. After constructing life tables for Iranian women and men for each year, the impact of the main causes of death on life expectancy was calculated using the multiple-decrement life table technique. Also, using the Lee-Carter method, the age-specific mortality rate was predicted for 2026, and multiple-decrement life tables were calculated for the main causes of death. The findings show that the greatest increase in life expectancy at birth for Iranian men and women occurred by eliminating cardiovascular diseases. By eliminating cardiovascular diseases and traffic accidents, the potential for increasing life expectancy at birth for men and women decreased during the study period, but the potential for increasing life expectancy increased by eliminating cancers and diabetes. The results of this study have important applications in demographic and economic planning and policy-making, and can be a basis for improving the calculations and structure of insurance payments in Iran.

کلیدواژه‌ها English

Mortality
Multiple-decrement life table
Causes of mortality
Mortality prediction
Lee-Carter method

Extended abstract
Introduction
Life expectancy at birth is a key indicator of human development and health system efficiency, reflecting the overall social and economic conditions of a population. Over the past decades, Iran, similar to many countries, has experienced a remarkable improvement in life expectancy - from about 25 years in the early 20th century to more than 76 years in recent years- mainly due to better health services, lower infant mortality, and control of infectious diseases. However, the epidemiological transition has led to a shift in mortality patterns toward non-communicable diseases such as cardiovascular diseases, cancers, and diabetes.
Given the significant effects of the COVID-19 pandemic on mortality patterns, analyzing how the elimination of major causes of death affects life expectancy has become increasingly important. Therefore, this study aims to estimate the multiple-decrement life tables for Iran from 2011 to 2021 and to forecast them for 2026, providing a comprehensive view of how major causes of death contribute to changes in life expectancy.
Method and Data
This descriptive-analytical study relies on secondary data analysis using information from the Global Burden of Disease (2021). The dataset includes the number of deaths by age, sex, and cause of death for the years 2011–2021. The quality and completeness of death registration were assessed using the Bennett–Horiuchi method.
After data correction, standard life tables were constructed separately for men and women. Age-specific mortality rates for 2026 were projected using the Lee - Carter model - a stochastic two-factor model widely used in actuarial and demographic forecasting - implemented in R software. Then, using the MORTPAK package, both standard and multiple-decrement life tables were computed.
Six major causes of death were included: cardiovascular diseases, cancers, diabetes and kidney diseases, respiratory infections and tuberculosis, chronic respiratory diseases, and traffic accidents. For each, separate life tables were generated to evaluate the potential increase in life expectancy under a hypothetical elimination of that specific cause.
Findings
The results showed that in 2011 and 2019, cardiovascular diseases were the most important cause of death for Iranian men and women, accounting for between 40 and 50 percent of all deaths among men and women. After that, cancers and traffic accidents accounted for the largest share among men, and cancers and diabetes accounted for the largest share among women. In 2021, under the influence of the Covid-19 pandemic, respiratory infections and tuberculosis took the first place among the causes of death, and the share of cardiovascular diseases decreased to 26 percent in men and 35 percent in women. The forecast for 2026 shows that with the control of the pandemic, cardiovascular diseases, cancers, and diabetes will again be the three leading causes of death in both sexes.
Based on life table calculations, life expectancy at birth for men has increased from 73.45 years in 2011 to 75.93 in 2019 and 77.17 in 2026. For women, it has also increased from 76.84 to 78.45 and then 79.70 years, respectively. The temporary decrease in life expectancy in 2021 (due to Covid-19) has been calculated to be 71.13 years for men and 75.94 years for women.
In the multi-decrement life tables, the largest increase in life expectancy was observed due to the elimination of cardiovascular diseases: in 2021, the elimination of this cause increased life expectancy by 3.4 years for men and 4.4 years for women. The share of cancers and diabetes in the increase in life expectancy has also been growing, especially in recent years, while the share of traffic accidents has continuously decreased. Also, in 2021, the simultaneous elimination of the three major causes of death (cardiovascular diseases, cancers and traffic accidents) could have increased life expectancy at birth by 9.8 years for men and 9.9 years for women.
The age pattern of causes of death showed that deaths from heart disease and diabetes were mainly concentrated in those over 55 years of age, while deaths from traffic accidents accounted for the largest share in the 20-40 age group. The sex ratio of deaths from cancer was also higher than 100 in all years, indicating that more men died than women.
Discussion and Conclusion
Iran has clearly transitioned to the stage of predominance of non-communicable diseases within the epidemiological transition framework. Although eliminating cardiovascular diseases yields the highest potential improvement in life expectancy, its declining contribution during the past decade suggests that Iran has entered the fourth phase—characterized by delayed deaths from chronic conditions. Conversely, the growing role of cancers and diabetes underscores the need for more effective prevention and management of chronic diseases.
Forecasting results indicate that life expectancy in Iran will continue to increase

 

ساسانی‌پور، محمد و محبی میمندی، مصیب (1398). بررسی امکان بهبود امید زندگی ایران با حذف علل عمده مرگ طی دوره 1394-1385. مطالعات جمعیتی، 5(1): 7-29. https://jips.nipr.ac.ir/article_108265.html
ساسانی‌پور، محمد (1402). نابرابری امید زندگی در بدو تولد: مطالعه مقایسه‌ای ایران و کشورهای منطقه خاورمیانه و شمال آفریقا. نامه انجمن جمعیت‌شناسی ایران، 18 (36)، 405-443. https://doi.org/10.22034/jpai.2024.2019269.1320
سرایی، حسن (1376). مرحله اول گذار جمعیتی ایران. نامه علوم اجتماعی،10(9): 51-67. https://jnoe.ut.ac.ir/article_17100.html
فتحی، الهام، شریفی، منصور، ابراهیم پور، محسن و زنجانی، حبیب اله (1397). علل عمده مرگ‌ومیر در ایران در سال 1395 با استفاده از جدول عمر چندکاهشی. نامه انجمن جمعیت‌شناسی ایران، 26: 155-185. https://dor.isc.ac/dor/20.1001.1.1735000.1397.13.26.6.8
کمیجانی اکبر، کوششی، مجید و نیاکان، لیلی (1392). برآورد و پیش‌بینی میزان مرگ‌ومیر در ایران با استفاده از مدل لی ـ کارتر. نشریه علمی پژوهشنامه بیمه، 2(4)، 295-310. https://doi.org/10.22056/ijir.2013.04.01
کوششی، مجید و ریحان، رضا (1397). تحلیل مقطعی- سنی اثر الگوی مرگ زودرس بر درآمد از دست‌‌رفته صندوق تأمین اجتماعی. مطالعات جمعیتی، 4(1): 167-198. https://jips.nipr.ac.ir/article_96179.html
کوششی، مجید، اردشیر، خسروی، ساسانی‌پور، محمد و اسعدی، سجاد (1392). تأثیر علل اصلی مرگ‌ومیر بر امید زندگی استان فارس با استفاده از روش جدول عمر چند کاهشی. مجله تخصصی اپیدمیولوژی ایران، 9(4)، 1-7. https://irje.tums.ac.ir/article-1-5161-fa.html
Bennett, N., & Horiuchi, S. (1981). Estimating the completeness of death registration in a closed population. Population Index, 47(2), 207–221. https://www.jstor.org/stable/2736447
Caldwell, J.C. (2003). Population health in transition. Bulletin of the World Health Organization, 79(2)و 159-160. https://pmc.ncbi.nlm.nih.gov/articles/PMC2566355/
Cao, G., Liu, J., Liu, M., & Liang, W. (2023). Effects of the COVID-19 pandemic on life expectancy at birth at the global, regional, and national levels: A joinpoint time-series analysis. Journal of Global Health, 20 (13), 06042. https://doi.org/10.7189/jogh.13.06042
Cappucio, F.P. (2004). Epidemiological transition, migration, and cardiovascular disease. International Journal of Epidemiology, 33(2), 387-388. https://doi.org/10.1093/ije/dyh091
Chiang, C.L. (1991). Competing risks in mortality analysis. Annual Review of Public Health, 12(1), 281-307. https://doi.org/10.1146/annurev.pu.12.050191.001433
Conti, S., Farchi, G., Masocco, M., & Toccaceli, V. (1999). The impact of the major causes of death on life expectancy in Italy. International Journal of Epidemiology, 28: 905-910. https://doi.org/10.1093/ije/28.5.905
Gaylin, D.S., & Kates, J. (1997). Refocusing the lens: Epidemiologic transition theory, mortality differentials, and the AIDS pandemic. Social Science and Medicine, 44(5), 609-621. https://doi.org/10.1016/s0277-9536(96)00212-2
Kahn, K., Garenne, M.L., Collinson, M.A., & Tollman, S.M. (2007). Mortality trends in a new South Africa: hard to make a fresh start. Scandinavian Journal of Public Health Supplements, 69, 26-34. https://doi.org/10.1080/14034950701355668
Klenk, J., Keil, U., & Jaensch, A. (2016). Changes in life expectancy 1950–2010: contributions from age- and disease-specific mortality in selected countries. Population  Health Metrics 14, 20: 2-11. https://doi.org/10.1186/s12963-016-0089-x
Lee, R.D., & Carter, L.R. (1992). Modeling and forecasting US mortality. Journal of the American Statistical Association, 87(419), 659-671. https://doi.org/10.1080/01621459.1992.10475265
McNicoll, G. (2002). World Population Ageing 1950-2050. Population and Development Review, 28(4): 814-816. https://digitallibrary.un.org/record/461899?ln=en
Olshansky, S.J., & Ault, E.B. (1986). The fourth stage of the epidemiologic transition: the age of delayed degenerative diseases. Milbank Memorial Fund Quarterly, 64, 355-391. https://pubmed.ncbi.nlm.nih.gov/3762504
Omran, A.R (1971). The epidemiologic transition: A theory of the epidemiology of population change. Milbank Memorial Fund Quarterly, 49(4), 509-538. https://doi.org/10.1111/j.1468-0009.2005.00398.x
Preston, S.H., Heuvline, P., & Guillot, M (2001). Demography: Measuring and Modeling Population Processes, USA: Blackwell. https://archive.org/details/demographymeasur0000pres/page/n7/mode/2up
Raleigh, V.S. (1999). World population and health in transition. British Medical Journal, 319, 981-984. https://doi.org/10.1136/bmj.319.7215.981
Razeghi Nasrabad, H.B., & Sasanipour, M. (2022). Effect of COVID-19 Epidemic on Life Expectancy and Years of Life Lost in Iran: A Secondary Data Analysis. Iran Journal of Medical Sciences, 47(3), 210-218. https://doi.org/10.30476/ijms.2021.90269.2111
Santosa, A., Wall, S., Fottrell, E., Högberg, U., & Byass, P. (2014). The development and experience of epidemiological transition theory over four decades: a systematic review. Global Health Action, 7(1), 23574. https://doi.org/10.3402/gha.v7.23574
Sasanipour, M. (2022). The Role of Age Groups in Improving Life Expectancy of Iran During 1976-2016. Epidemiology and Health System Journal, 9(2), 80-85. https://doi.org/10.34172/ijer.2022.14
Schoen R. (1975). Constructing increment-decrement life tables. Demography, 12(2), 313-24. https://pubmed.ncbi.nlm.nih.gov/1157991/
Setel, P., Saker, W.L., Unwin, N.C., Hemed, Y., Whiting D.R., Kitange, H. (2004). Is it time to reassess the categorization of disease burdens in low-income countries? American Journal of Public Health, 94, 384–388. https://doi.org/10.2105/ajph.94.3.384
United Nations Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024: Summary of Results (UN DESA/POP/2024/TR/NO. 9). https://population.un.org/wpp/
United Nations, Department of Economic and Social Affairs, Population Division (2019). World Mortality 2019: Highlights (ST/ESA/SER.A/432). https://www.un.org/development/desa/pd/content/world-mortality-2019-highlights
دوره 9، شماره 1 - شماره پیاپی 17
تاریخ انتشار: دی‌ماه 1404
خرداد 1402
صفحه 17-33

  • تاریخ دریافت 08 تیر 1404
  • تاریخ بازنگری 19 مرداد 1404
  • تاریخ پذیرش 28 مرداد 1404
  • تاریخ انتشار 01 خرداد 1402