Journal article
Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
The Lancet (British edition), Vol.403(10440), pp.2057-2099
05/18/2024
DOI: 10.1016/S0140-6736(24)00550-6
PMCID: PMC11122687
PMID: 38521087
Abstract
Background Accurate assessments of current and future fertility-including overall trends and changing population age structures across countries and regions-are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios.
Methods To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10-54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates ( female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2 center dot 5 and 97 center dot 5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values-a metric assessing gain in forecasting accuracy-by comparing predicted versus observed ASFRs from the past 15 years (2007-21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline.
Findings During the period from 1950 to 2021, global TFR more than halved, from 4 center dot 84 (95% UI 4 center dot 63-5 center dot 06) to 2 center dot 23 (2 center dot 09-2 center dot 38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137-147), declining to 129 million (121-138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2 center dot 1-canonically considered replacement-level fertility-in 94 (46 center dot 1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29 center dot 2% [28 center dot 7-29 center dot 6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1 center dot 83 (1 center dot 59-2 center dot 08) in 2050 and 1 center dot 59 (1 center dot 25-1 center dot 96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24 center dot 0%) in 2050 and only six (2 center dot 9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41 center dot 3% (39 center dot 6-43 center dot 1) in 2050 and 54 center dot 3% (47 center dot 1-59 center dot 5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions-decreasing, for example, in south Asia from 24 center dot 8% (23 center dot 7-25 center dot 8) in 2021 to 16 center dot 7% (14 center dot 3-19 center dot 1) in 2050 and 7 center dot 1% (4 center dot 4-10 center dot 1) in 2100-but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1 center dot 65 (1 center dot 40-1 center dot 92) in 2050 and 1 center dot 62 (1 center dot 35-1 center dot 95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction.
Interpretation Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world.
Details
- Title: Subtitle
- Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
- Creators
- Natalia V. Bhattacharjee - Institute for Health Metrics and EvaluationAustin E. Schumacher - University of WashingtonAmirali Aali - Institute for Health Metrics and EvaluationYohannes Habtegiorgis Abate - Institute for Health Metrics and EvaluationRouzbeh Abbasgholizadeh - Institute for Health Metrics and EvaluationMohammadreza Abbasian - Institute for Health Metrics and EvaluationMohsen Abbasi-Kangevari - Institute for Health Metrics and EvaluationHedayat Abbastabar - Institute for Health Metrics and EvaluationSamar Abd ElHafeez - Alexandria UniversitySherief Abd-Elsalam - University of WashingtonMohammad Abdollahi - University of WashingtonMohammad-Amin Abdollahifar - University of SaskatchewanMeriem Abdoun - Institute for Health Metrics and EvaluationAuwal Abdullahi - Institute for Health Metrics and EvaluationMesfin Abebe - Institute for Health Metrics and EvaluationSamrawit Shawel Abebe - University of WashingtonOlumide Abiodun - University of WashingtonHassan Abolhassani - Institute for Health Metrics and EvaluationMeysam Abolmaali - Institute for Health Metrics and EvaluationMohamed Abouzid - Institute for Health Metrics and EvaluationGirma Beressa Aboye - Madda Walabu UniversityLucas Guimaraes Abreu - Institute for Health Metrics and EvaluationWoldu Aberhe Abrha - Aksum UniversityMichael R. M. Abrigo - Institute for Health Metrics and EvaluationDariush Abtahi - Institute for Health Metrics and EvaluationHasan Abualruz - Institute for Health Metrics and EvaluationBilyaminu Abubakar - Institute for Health Metrics and EvaluationEman Abu-Gharbieh - Institute for Health Metrics and EvaluationNiveen M. E. Abu-Rmeileh - Institute for Health Metrics and EvaluationTadele Girum Girum Adal - Institute for Health Metrics and EvaluationMesafint Molla Adane - Institute for Health Metrics and EvaluationOluwafemi Atanda Adeagbo Adeagbo - University of South CarolinaRufus Adesoji Adedoyin - Institute for Health Metrics and EvaluationVictor Adekanmbi - Institute for Health Metrics and EvaluationBashir Aden - Institute for Health Metrics and EvaluationAbiola Victor Adepoju - HIV & Infect Dis Dept, Abuja, NigeriaOlatunji O. AdetokunbohJuliana Bunmi Adetunji - Institute for Health Metrics and EvaluationDaniel Adedayo Adeyinka - Institute for Health Metrics and EvaluationOlorunsola Israel Adeyomoye - Institute for Health Metrics and EvaluationQorinah Estiningtyas Sakilah Adnani - Institute for Health Metrics and EvaluationSaryia Adra - Institute for Health Metrics and EvaluationRotimi Felix Afolabi - Institute for Health Metrics and EvaluationShadi Afyouni - Institute for Health Metrics and EvaluationMuhammad Sohail Afzal - Univ Management & Technol, Dept Life Sci, Lahore, PakistanSaira Afzal - Institute for Health Metrics and EvaluationShahin Aghamiri - Institute for Health Metrics and EvaluationAntonella Agodi - Institute for Health Metrics and EvaluationWilliams Agyemang-Duah - Institute for Health Metrics and EvaluationBright Opoku Ahinkorah - Institute for Health Metrics and EvaluationAustin J. Ahlstrom - Institute for Health Metrics and EvaluationAqeel Ahmad - University of WashingtonDanish Ahmad - Institute for Health Metrics and EvaluationFirdos Ahmad - Institute for Health Metrics and EvaluationMuayyad M. Ahmad - Institute for Health Metrics and EvaluationSajjad Ahmad - Institute for Health Metrics and EvaluationTauseef Ahmad - Institute for Health Metrics and EvaluationAli Ahmed - Institute for Health Metrics and EvaluationAyman Ahmed - Institute for Health Metrics and EvaluationHaroon Ahmed - University of WashingtonLuai A. Ahmed - University of WashingtonMeqdad Saleh Ahmed - Institute for Health Metrics and EvaluationSyed Anees Ahmed - Institute for Health Metrics and EvaluationMarjan Ajami - Institute for Health Metrics and EvaluationBudi Aji - Institute for Health Metrics and EvaluationGizachew Taddesse Akalu - Institute for Health Metrics and EvaluationHossein Akbarialiabad - Institute for Health Metrics and EvaluationRufus Olusola Akinyemi - University of IbadanMohammed Ahmed Akkaif - Institute for Health Metrics and EvaluationSreelatha Akkala - University of WashingtonHanadi Al Hamad - Institute for Health Metrics and EvaluationSyed Mahfuz Al Hasan - Institute for Health Metrics and EvaluationMohammed Al Qadire - Institute for Health Metrics and EvaluationTareq Mohammed Ali Al-Ahdal - Institute for Health Metrics and EvaluationSamer O. Alalalmeh - Institute for Health Metrics and EvaluationTariq A. Alalwan - University of WashingtonZiyad Al-Aly - Institute for Health Metrics and EvaluationKhurshid Alam - Institute for Health Metrics and EvaluationRasmieh Mustafa Al-Amer - University of WashingtonFahad Mashhour Alanezi - University of WashingtonTurki M. Alanzi - Institute for Health Metrics and EvaluationAlmaza Albakri - University of WashingtonMohammed Albashtawy - Institute for Health Metrics and EvaluationMohammad T. AlBataineh - Institute for Health Metrics and EvaluationHediyeh Alemi - Institute for Health Metrics and EvaluationSharifullah Alemi - Institute for Health Metrics and EvaluationYihun Mulugeta Alemu - Bahir Dar UniversityAyman Al-Eyadhy - Institute for Health Metrics and EvaluationAdel Ali Saeed Al-Gheethi - Univ Newcastle, Global Ctr Environm Remediat, Newcastle, NSW, AustraliaKhalid F. Alhabib - University of WashingtonNoora Alhajri - Institute for Health Metrics and EvaluationFadwa Naji Alhalaiqa Alhalaiqa - Qatar UniversityRobert Kaba Alhassan - Institute for Health Metrics and EvaluationAbid Ali - Institute for Health Metrics and EvaluationBeriwan Abdulqadir Ali - Institute for Health Metrics and EvaluationLiaqat Ali - Institute for Health Metrics and EvaluationMohammed Usman Ali - Institute for Health Metrics and EvaluationRafat Ali - Institute for Health Metrics and EvaluationSyed Shujait Shujait Ali - University of WashingtonSheikh Mohammad Alif - Institute for Health Metrics and EvaluationGBD 2021 Fertility Forecasting CollaboratorsDavid C Schwebel (Contributor) - Research Administration
- Resource Type
- Journal article
- Publication Details
- The Lancet (British edition), Vol.403(10440), pp.2057-2099
- DOI
- 10.1016/S0140-6736(24)00550-6
- PMID
- 38521087
- PMCID
- PMC11122687
- NLM abbreviation
- Lancet
- ISSN
- 0140-6736
- eISSN
- 1474-547X
- Publisher
- Elsevier
- Number of pages
- 43
- Grant note
- 21K01093; 20K10425; 21H03203 / Grants-in-Aid for Scientific Research; Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT); Japan Society for the Promotion of Science; Grants-in-Aid for Scientific Research (KAKENHI) Bill AMP; Melinda Gates Foundation; CGIAR
- Language
- English
- Date published
- 05/18/2024
- Academic Unit
- Research Administration
- Record Identifier
- 9984949471702771
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