Egészségbiztonság Nemzeti Laboratórium(RRF-2.3.1-21-2022-00006) Támogató: NKFIH
(TKP2021-NVA-11)
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.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 2·5 and 97·5 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.During
the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63-5·06)
to 2·23 (2·09-2·38). 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 2·1-canonically
considered replacement-level fertility-in 94 (46·1%) 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 (29·2% [28·7-29·6]). 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 1·83 (1·59-2·08) in 2050
and 1·59 (1·25-1·96) in 2100 under the reference scenario. The number of countries
and territories with fertility rates remaining above replacement was forecast to be
49 (24·0%) in 2050 and only six (2·9%) 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 41·3%
(39·6-43·1) in 2050 and 54·3% (47·1-59·5) 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 24·8% (23·7-25·8) in 2021 to 16·7% (14·3-19·1) in
2050 and 7·1% (4·4-10·1) 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 1·65 (1·40-1·92) in 2050 and 1·62 (1·35-1·95) 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.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.Bill
& Melinda Gates Foundation.
