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

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 2·5 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. Findings 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. 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

Silicon crosstalk with reactive oxygen species, phytohormones and other signaling molecules

Exogenous applications of silicon (Si) can initiate cellular defence pathways to enhance plant resistance to abiotic and biotic stresses. Plant Si accumulation is regulated by several transporters of silicic acid (e.g. Lsi1, Lsi2, and Lsi6), but the precise mechanisms involved in overall Si transport and its beneficial effects remains unclear. In stressed plants, the accumulation of Si leads to a defence mechanism involving the formation of amorphous or hydrated silicic acid caused by their polymerization and interaction with other organic substances. Silicon also regulates plant ionic homeostasis, which involves the nutrient acquisition, availability, and replenishment in the soil through biogeochemical cycles. Furthermore, Si is implicated in modulating ethylene-dependent and jasmonate pathways, as well as other phytohormones, particularly under stress conditions. Crosstalk between Si and phytohormones could lead to improvements in Si-mediated crop growth, especially when plants are exposed to stress. The integration of Si with reactive oxygen species (ROS) metabolism appears to be a part of the signaling cascade that regulates plant phytohormone homeostasis, as well as morphological, biochemical, and molecular responses. This review aims to provide an update on Si interplays with ROS, phytohormones, and other signaling molecules that regulate plant development under stress conditions

Metal/Metalloid-Based Nanomaterials for Plant Abiotic Stress Tolerance: An Overview of the Mechanisms

In agriculture, abiotic stress is one of the critical issues impacting the crop productivity and yield. Such stress factors lead to the generation of reactive oxygen species, membrane damage, and other plant metabolic activities. To neutralize the harmful effects of abiotic stress, several strategies have been employed that include the utilization of nanomaterials. Nanomaterials are now gaining attention worldwide to protect plant growth against abiotic stresses such as drought, salinity, heavy metals, extreme temperatures, flooding, etc. However, their behavior is significantly impacted by the dose in which they are being used in agriculture. Furthermore, the action of nanomaterials in plants under various stresses still require understanding. Hence, with this background, the present review envisages to highlight beneficial role of nanomaterials in plants, their mode of action, and their mechanism in overcoming various abiotic stresses. It also emphasizes upon antioxidant activities of different nanomaterials and their dose-dependent variability in plants’ growth under stress. Nevertheless, limitations of using nanomaterials in agriculture are also presented in this review

Tolerance and Reduction of Chromium(VI) by Bacillus sp. MNU16 Isolated from Contaminated Coal Mining Soil

The bacterium MNU16 was isolated from contaminated soils of coal mine and subsequently screened for different plant growth promoting (PGP) activities. The isolate was further identified by 16S rRNA sequencing as Bacillus subtilis MNU16 with IAA concentration (56.95 ± 0.43 6μg/ml), siderophore unit (9.73 ± 2.05%), phosphate solubilization (285.13 ± 1.05 μg/ml) and ACC deaminase activity (116.79 ± 0.019 μmoles α-ketobutyrate/mg/24 h). Further, to evaluate the metal resistance profile of bacterium, the isolate was screened for multi-metal resistance (viz. 900 mg/L for Cr, 600 mg/L for As, 700 mg/L for Ni and 300 mg/L for Hg). Additionally, the resistance pattern of B. subtilis MNU16 against Cr(VI) (from 50 to 300 mg/L) treatments were evaluated. An enriched population was observed at 0–200 mg/L Cr(VI) concentration while slight reductions were observed at 250 and 300 mg/L Cr(VI). Further, the chromium reduction ability at 50 mg/L of Cr(VI) highlighted that the bacterium B. subtilis MNU16 reduced 75% of Cr(VI) to 13.23 mg/L within 72 h. The localization of electron dense precipitates was observed in the TEM images of B. subtilis MNU16 which is might be due to the reduction of Cr(VI) to Cr(III). The data of fluorescence microscopy and flow cytometry with respect to Cr(VI) treatments (50–300 mg/L) showed a similar pattern and clearly revealed the less toxic effect of hexavalent chromium upto 200 mg/L Cr(VI) concentration. However, toxicity effects were more pronounced at 300 mg/L Cr(VI). Therefore, the present study suggests that the plant growth promoting potential and resistance efficacy of B. subtilis MNU16 will go a long way in developing an effective bioremediation approach for Cr(VI) contaminated soils

Differential Phytotoxic Impact of Plant Mediated Silver Nanoparticles (AgNPs) and Silver Nitrate (AgNO3) on Brassica sp.

Continuous formation and utilization of nanoparticles (NPs) have resulted into significant discharge of nanosized particles into the environment. NPs find applications in numerous products and agriculture sector, and gaining importance in recent years. In the present study, silver nanoparticles (AgNPs) were biosynthesized from silver nitrate (AgNO3) by green synthesis approach using Aloe vera extract. Mustard (Brassica sp.) seedlings were grown hydroponically and toxicity of both AgNP and AgNO3 (as ionic Ag+) was assessed at various concentrations (1 and 3 mM) by analyzing shoot and root length, fresh mass, protein content, photosynthetic pigments and performance, cell viability, oxidative damage, DNA degradation and enzyme activities. The results revealed that both AgNPs and AgNO3 declined growth of Brassica seedlings due to enhanced accumulation of AgNPs and AgNO3 that subsequently caused severe inhibition in photosynthesis. Further, the results showed that both AgNPs and AgNO3 induced oxidative stress as indicated by histochemical staining of superoxide radical and hydrogen peroxide that was manifested in terms of DNA degradation and cell death. Activities of antioxidants, i.e., ascorbate peroxidase (APX) and catalase (CAT) were inhibited by AgNPs and AgNO3. Interestingly, damaging impact of AgNPs was lesser than AgNO3 on Brassica seedlings which was due to lesser accumulation of AgNPs and better activities of APX and CAT, which resulted in lesser oxidative stress, DNA degradation and cell death. The results of the present study showed differential impact of AgNPs and AgNO3 on Brassica seedlings, their mode of action, and reasons for their differential impact. The results of the present study could be implied in toxicological research for designing strategies to reduce adverse impact of AgNPs and AgNO3 on crop plants