An overview of the nitrite and nitrate contents in meat products in Estonia

Saabunud / Received 08.12.2020 ; Aktsepteeritud / Accepted 30.12.2020 ; Avaldatud veebis / Published online 31.12.2020 ; Vastutav autor / Corresponding author: Terje Elias [email protected] study examined the nitrite and nitrate content in processed meat products in Estonia. The study shows the levels of nitrites and nitrates in meat products and compares the results with data from the previous study periods. All meat products, which needed heat treatment according to the manufacturer's instructions, were heat-treated prior analyses. Among analysed meat products (n=164), the highest nitrite concentration was 93.1 mg kg–1 and it was determined in uncooked meat preparation product. The overall mean nitrite concentration among nitrite contained meat products varied from 9.7–30.3 mg kg–1 depending on the meat product category. The highest mean nitrite concentrations were found in sausages and pates. There were large differences in the nitrite content of the products of different producers, ranging from the detection limit to 93.1 mg kg–1. The largest differences in nitrite contents were observed in the cooked sausages of one manufacturer, in which the nitrite content was from the detection limit up to 61.5 mg kg–1 in the product. The nitrite and nitrate contents of different meat products also varied widely between producers and were different for each product group. By the Regulation (EC 1333/2008) taking into account the maximum levels for nitrites and nitrates allowed to be added to the meat products, there were no exceedances detected. In the comparison of previous and present study periods, it can be summarised that sodium nitrite (NaNO2) levels are lower in cooked sausages, smoked sausages and wieners, and the content of sodium nitrate (NaNO3) in various meat products is considerably decreased

Valmistoidu nakatamiskatsed Listeria monocytogenes´ga : [poster]

Listeria monocytogenes´t peetakse jahutatud valmistoitude puhul üheks kõige ohtlikumaks toidupatogeeniks, kuna ta on võimeline kasvama ka külmkapi temperatuuridel ning võib põhjustada inimestel raskekujulist haigust - listerioosi. Tingituna L. monocytogenes´e olulisusest valmistoitude toiduohutust mõjutava tegurina ning toidukäitlejate toiduohutuse tagamise kohustusest on vajadus hinnata toidu sisemiste, väliste ja kaudsete tegurite mõju L. monocytogenes´e kasvule selles, eriti valmistoitudes, millel on pikk säilimisaeg ning mille koostis võib võimaldada patogeeni kasvu. Uurimustööd finantseeris Eesti Teadusagentuur (projekt PRG1441). Projekti TAIMLOOMTOIT (F200143PKPA) elluviimist toetavad Euroopa Regionaalarengu Fond ja Eesti Teadusagentuur läbi „Ressursside väärindamise alase TA-tegevuse toetamise” programmi ResTA14.Konverentsi "Terve loom ja tervislik toit 2023" posterettekanne

Microbial Growth Dynamics in Minced Meat Enriched with Plant Powders

Plant powders with antimicrobial properties can be used in food manufacturing and must comply with the demands of consumers regarding microbiological safety, nutritional value, and sensory properties of foods. The present study aimed to assess the microbial growth inhibitory ability of different plant powders, including by-products of horticultural primary processing (e.g., pomace) in raw and cooked minced pork. The total counts of aerobic mesophilic bacteria, pseudomonads, yeasts, and moulds were studied to assess the microbial growth dynamics in meat samples. Additionally, for the plant powders, which were able to suppress the microbial growth in a total counts dynamics study, the growth potential of Listeria monocytogenes in ready-to-eat (RTE) minced meat samples was estimated by challenge testing. The results showed that the most effective combinations of plant powders in raw minced pork, in relation to the total counts of microorganisms, were 3% apple+1% onion+2% blackcurrant berries (Apple+On+BCber); 3% apple+1% garlic+2% tomato (Apple+Ga+Tom); and 3% apple+2% tomato+1% rhubarb petioles (Apple+Tom+Rhub). However, challenge tests revealed that some plant powders were unable to inhibit the growth of L. monocytogenes. The lowest L. monocytogenes growth potential (δ = 2.74 log cfu/g) was determined for cooked minced pork samples enriched with 2% rhubarb petioles, followed by Apple+On+BCber (δ = 3.63 log cfu/g) and Apple+Tom+Rhub (δ = 3.74 log cfu/g). In minced pork samples without plant additives, the L. monocytogenes growth potential was 7.30 log cfu/g. In conclusion, blends of plant powders may have good potential for developing meat products with acceptable microbiological quality

Content of reducing sugars in mostly grown vegetables in Estonia after harvesting and after storage

Saabunud / Received 21.02.2022 ; Aktsepteeritud / Accepted 01.04.2022 ; Avaldatud veebis / Published online 01.04.2022 ; Vastutav autor / Corresponding author: Terje Elias; [email protected] study examined the content of reducing sugars in various varieties of potato, beetroot, turnip and pumpkin most commonly grown in Estonia. This study aimed to determine the varieties of vegetables with the lowest levels of reducing sugars after harvesting and after storage at two different temperatures (3 and 8 C). In the present study it was found that the potato variety with the lowest content of reducing sugars after harvesting and after six months of storage was potato variety 'Birgit' with 0.19 g 100 g–1after harvesting, 0.98 g 100 g–1 after storage at 3 C and 0.38 g 100 g–1 after storage at 8 C, respectively. All three varieties of the beetroot, after harvest, contained a similar amount of reducing sugars. After six months of storage, the lowest content of reducing sugars was determined for variety 'Boro' with 1.22 g 100 g–1 at 3 C and 0.96 g 100 g–1 at 8 C, respectively. The lowest average concentrations of reducing sugars from turnips were after harvest in the variety 'Kohalik sinine' with 3.38 g 100 g–1. Also after storage, the same variety had the lowest content of reducing sugars with 8.36 g 100 g–1 at 3 C and 3.76 g 100 g–1 at 8 C, respectively. From the pumpkin varieties, the lowest reducing sugars contents were determined for variety 'Gold Medal' with 2.64 g 100 g–1after harvesting, 2.40 g 100 g–1 after storage at 3 C and 1.90 g 100 g–1 after storage at 8 C. It can be concluded that all studied vegetables stored at 3 °C contained higher amounts of reducing sugars than those stored at 8 °C

Salmonella enterica prevalence, serotype diversity, antimicrobial resistance and control in the European pork production chain

Background: A risk assessment conducted by EFSA identified Salmonella enterica (Salmonella) as a high-risk hazard at the EU level in the context of meat inspection of swine. Despite pork being considered an important source of S. Typhimurium and its monophasic variant, Regulation (EC) No 2073/2005 does not set criteria for specific Salmonella serotypes. Enforcing specific criteria for Salmonella target serotypes could result in a reduction in the prevalence of Salmonella in the pork production chain, as has happened in broiler flocks. Scope and approach: This study gives an overview of Salmonella enterica in the European pork chain, discussing prevalence, serotype diversity, antimicrobial resistance and epidemiological importance during the last 20 years. Additionally, future trends and recommendations regarding control of Salmonella in the European pork production chain are introduced. Key findings and conclusions: The highest proportions of Salmonella-positive samples were observed at the fattening pig farm level, whereas the prevalence of Salmonella on pig carcasses was much lower. Among epidemiologically important serotypes, isolates of S. Typhimurium, and its monophasic variant were found to be resistant to ampicillin, sulfamethoxazole, streptomycin and tetracycline. Future Salmonella control in the pork production chain can preferably be conducted through a risk-based meat safety assurance system. In conclusion, a fit-for-purpose strategy applied to the pork production chain and adapted to the national epidemiological situation can deliver acceptable consumer safety

Taimsete lisandite mõju verivorstide säilivusele ja kvaliteedile : [poster]

Verivorstid on eestlaste toidulaual olulisel kohal. Seda enam pakub huvi verivorstide koostise edasiarendus tervislikumate ja naturaalsemate toodete suunas. Üks võimalus on kasutada selleks taimseid lisandeid, et anda verivorstidele lisandväärtus tervisliku, stabiilse mikrobioloogilise kvaliteedi ja heade organoleptiliste omadustega lõpptoote saamiseks.Konverentsi "Terve loom ja tervislik toit 2023" posterettekanne.Projekti TAIMLOOMTOIT (F200143PKPA) elluviimist toetasid Euroopa Regionaalarengu Fond ja Eesti Teadusagentuur läbi „Ressursside väärindamise alase TA-tegevuse toetamise" programmi ResTA14. Uurimistööd on finantseerinud Eesti Teadusagentuuri projekt (PRG1441).Projekti TAIMLOOMTOIT (F200143PKPA) elluviimist toetasid Euroopa Regionaalarengu Fond ja Eesti Teadusagentuur läbi „Ressursside väärindamise alase TA-tegevuse toetamise" programmi ResTA14. Uurimistööd on finantseerinud Eesti Teadusagentuuri projekt (PRG1441)

Occurence of Eserichia coli O157:H7 in Estonian dairy farms and beef production chain in 2005–2014

Escherichia coli O157:H7 human infections are mostly associated with consumption of raw or undercooked beef and raw milk. Ruminants, especially cattle are the main reservoir of the pathogen. The main aim of the present study was to evaluate the occurrence of E. coli O157:H7 in cattle dairy farm and beef production level in Estonia. It was found that E. coli O157:H7 is present at both the dairy farm and slaughterhouse level. The occurrence of the pathogen at Estonian dairy farm level was 1.2% from 1312 cattle's sampled. At slaughterhouse level 744 hide swabs were taken from which 30 (4.0%) were positive to E. coli O157:H7. Both stx1 and stx2 genes were determined from isolates and often the combination of both genes was found to be present. Minimal inhibitory concentration was determined for 30 E. coli O157:H7 isolates which revealed 26.7% of multiresistant isolates. In 2009–2010 in a total of 188 beef samples were analysed, which all were negative for O157:H7

Ühise põllumajanduspoliitika strateegiakava 2023‒2027 eelhindamine : lõpparuanne

Maaeluministeeriumi (edaspidi MeM) juhtimisel koostatakse Euroopa Liidu (edaspidi EL) ühise põllumajanduspoliitika strateegiakava aastateks 2023–2027 (edaspidi ÜPP strateegiakava). ÜPP strateegiakava koondab senised esimese samba (otsetoetused ja varasemad programmiti rakendatud turukorraldusmeetmed, nagu mesindusprogramm Euroopa Põllumajanduse Tagatisfondist, edaspidi EAGF) ja teise samba tegevused (nagu maaelu arengu investeeringu- ja arengutoetused Euroopa Maaelu Arengu Põllumajandusfondist, edaspidi EAFRD). Koostatava ÜPP strateegiakava aluseks on Euroopa Parlamendi ja nõukogu määrus3 (edaspidi ÜPP strateegiakava määrus). Määruses toodud peamised ÜPP eesmärgid on keskkonna- ja kliimameetmete asjus varasemast ambitsioonikamad, suunavad toetusi paremini ning tuginevad kindlamalt uuringute, innovatsiooni ja nõustamise vahelistele seostele. ÜPP tulemuslikkuse parandamiseks on ette nähtud uus ÜPP rakendamise mudel, et nihutada poliitika kese nõuetele vastavuse jälgimisest tulemuslikkuse jälgimisele ning suurema subsidiaarsuse abil tasakaalustada ELi ja liikmesriikide tasandite vahelist vastutust. Uue mudeli abil soovitakse edukamalt saavutada ELi eesmärgid, mis põhinevad strateegilisel kavandamisel, laialdastel poliitilistel sekkumistel ning ühtsetel tulemusnäitajatel, parandades seeläbi poliitikavaldkondade sidusust kogu tulevase ÜPP ulatuses ning ELi teiste eesmärkidega. Uuendatud ÜPP üldeesmärgid perioodil 2023‒2027 on järgmised. ● Tõhustada arukat, vastupidavat ja mitmekesist põllumajandussektorit, mis tagab toiduga kindlustatuse. ● Edendada keskkonnahoidu ja kliimameetmeid ning panustada liidu keskkonna- ja kliimaeesmärkidesse. ● Parandada maapiirkondade sotsiaal-majanduslikku olukorda. Üldeesmärkide saavutamiseks on püstitatud üheksa erieesmärki. ● Erieesmärk 1: toetada põllumajandustootja elujõulisust tagavat sissetulekut ja vastupanuvõimet kogu liidus, et tagada toiduga kindlustatus. ● Erieesmärk 2: suurendada konkurentsivõimet ja turule orienteeritust, pöörates erilist tähelepanu teadusuuringutele, tehnoloogiale ja digiüleminekule. ● Erieesmärk 3: parandada põllumajandustootjate positsiooni väärtusahelas. ● Erieesmärk 4: panustada kliimamuutuste leevendamisse ja nendega kohanemisse ning säästvasse energiasse. ● Erieesmärk 5: edendada säästvat arengut ja selliste loodusvarade tõhusat majandamist nagu vesi, muld ja õhk. 18 ● Erieesmärk 6: panustada elurikkuse kaitsesse, edendada ökosüsteemi teenuseid ning säilitada elupaiku ja maastikke. ● Erieesmärk 7: olla atraktiivne noorte põllumajandustootjate jaoks ja soodustada ettevõtluse arengut maapiirkondades. ● Erieesmärk 8: edendada tööhõivet, majanduskasvu, sotsiaalset kaasatust ja maapiirkondade arengut, sh biomajandust ja säästvat metsamajandust. ● Erieesmärk 9: parandada ELi põllumajanduse reageerimist ühiskonna nõudlusele toidu ja tervise vallas (hõlmab nii ohutut, toitvat ja säästvalt toodetud toitu, toidu raiskamise vähendamist kui ka loomade heaolu tagamist). Neile erieesmärkidele lisandub horisontaalse eesmärgina põllumajanduse ja maapiirkondade elu kaasajastamine, edendades ja jagades teadmisi, toetades innovatsiooni ja digiüleminekut ning ergutades nende kasutuselevõttu. Erieesmärke täites peavad liikmesriigid tagama ÜPP toetuste lihtsuse ja tulemuslikkuse. Erieesmärgid saavutab liikmesriik oma valitud sekkumiste kaudu. Peale ÜPP prioriteetide on ÜPP strateegiakava koostamise aluseks MeMi eestvedamisel valminud Põllumajanduse ja kalanduse valdkonna arengukava aastani 2030 (edaspidi PõKa 2030). PõKa 2030 eesmärk on aidata kaasa Eesti põllumajanduse, kalanduse, vesiviljeluse ja toidutööstuse arengule ning konkurentsivõime kasvule, toidujulgeolekule, maa- ja rannapiirkondade tasakaalustatud arengule, samuti taimede ja loomade heale tervisele, muldade seisundi paranemisele, toiduohutusele ning puhta keskkonna ja liigilise mitmekesisuse säilimisele. Metsandust puudutavas osas on ÜPP strateegiakava koostamise aluseks Keskkonnaministeeriumi eestvedamisel koostatav Eesti metsanduse arengukava aastani 2030 (edaspidi MAK2030) eelnõu. Peale eespool nimetatud strateegiliste dokumentide on ÜPP strateegiakaval seos EL-üleste strateegiatega ning Eesti muude asjakohaste strateegiatega, valdkondlike arengukavade ja programmidega, millega eelhindamisel arvestati. ÜPP strateegiakava koostamisse kaasati riigiasutuste ja valdkondlike huvigruppide esindajad 15 eri töörühma vormis, eesmärgiga luua selline strateegiline dokument, mis aitaks edendada põllumajandus- ja toidutootmise ning maapiirkondade kestlikku arengut. Lisaks töögruppidele moodustati 2019. a juunis Eesti ÜPP strateegiakava 2021–2027 ettevalmistav juhtkomisjon (edaspidi ÜPP juhtkomisjon), kelle ülesanne on kujundada Eesti seisukohad ÜPP maaelu arengu toetuste andmist korraldavate õigusaktide kohta ning koordineerida ÜPP strateegiakava koostamist, teha ettepanekuid ja kujundada seisukoht ÜPP strateegiakava kohta enne kava esitamist Vabariigi Valitsusele. Rööbiti ÜPP strateegiakava koostamisega viidi läbi ÜPP strateegiakava EAFRD vahenditest planeeritava rahastamisvahendi eelhindamine turutõrgete väljaselgitamiseks (uuring valmis aprillis 2020) ning käimas on ÜPP strateegiakava keskkonnamõju strateegiline hindamine (edaspidi KSH, millega alustati oktoobris 2019), mis võimaldavad ÜPP strateegiakava koostades arvesse võtta hindamisel leitut.Ühise põllumajanduspoliitika strateegiakava 2023‒2027 eelhinnati Maaeluministeeriumi tellimusel ja seda rahastatakse Eesti maaelu arengukava 2014‒2020 tehnilise abi vahenditest. Eelhindajaks oli Eesti Maaülikooli hindamis- ja valdkondlike ekspertide töörühm.Ühise põllumajanduspoliitika strateegiakava 2023‒2027 eelhinnati Maaeluministeeriumi tellimusel ja seda rahastatakse Eesti maaelu arengukava 2014‒2020 tehnilise abi vahenditest. Eelhindajaks oli Eesti Maaülikooli hindamis- ja valdkondlike ekspertide töörühm

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic