@article{MTMT:34804298, title = {Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021. a systematic analysis for the Global Burden of Disease Study 2021.}, url = {https://m2.mtmt.hu/api/publication/34804298}, doi = {10.1016/S0140-6736(24)00757-8}, journal-iso = {LANCET}, journal = {LANCET}, unique-id = {34804298}, issn = {0140-6736}, abstract = {Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic.The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic.Global DALYs increased from 2·63 billion (95% UI 2·44-2·85) in 2010 to 2·88 billion (2·64-3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7-17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8-6·3) in 2020 and 7·2% (4·7-10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0-234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7-198·3]), neonatal disorders (186·3 million [162·3-214·9]), and stroke (160·4 million [148·0-171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3-51·7) and for diarrhoeal diseases decreased by 47·0% (39·9-52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54-1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5-9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0-19·8]), depressive disorders (16·4% [11·9-21·3]), and diabetes (14·0% [10·0-17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7-27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6-63·6) in 2010 to 62·2 years (59·4-64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6-2·9) between 2019 and 2021.Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades.Bill & Melinda Gates Foundation.}, year = {2024}, eissn = {1474-547X}, orcid-numbers = {Joó, Tamás/0000-0002-3551-6125; Lám, Judit/0000-0001-9621-1563; Palicz, Tamás Gyula/0000-0003-3676-2878} } @article{MTMT:34754562, title = {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.}, url = {https://m2.mtmt.hu/api/publication/34754562}, doi = {10.1016/S0140-6736(24)00550-6}, journal-iso = {LANCET}, journal = {LANCET}, unique-id = {34754562}, issn = {0140-6736}, abstract = {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.}, year = {2024}, eissn = {1474-547X}, orcid-numbers = {Gaál, Péter/0000-0002-6815-9021; Joó, Tamás/0000-0002-3551-6125; Lám, Judit/0000-0001-9621-1563; Pollner, Péter/0000-0003-0464-4893; Szócska, Miklós/0000-0003-0648-9778} } @article{MTMT:34750478, title = {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.}, url = {https://m2.mtmt.hu/api/publication/34750478}, doi = {10.1016/S0140-6736(24)00476-8}, journal-iso = {LANCET}, journal = {LANCET}, unique-id = {34750478}, issn = {0140-6736}, abstract = {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.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.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.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.Bill & Melinda Gates Foundation.}, year = {2024}, eissn = {1474-547X}, orcid-numbers = {Gaál, Péter/0000-0002-6815-9021; Joó, Tamás/0000-0002-3551-6125; Lám, Judit/0000-0001-9621-1563; Palicz, Tamás Gyula/0000-0003-3676-2878; Pollner, Péter/0000-0003-0464-4893; Szócska, Miklós/0000-0003-0648-9778} } @article{MTMT:34694205, title = {A multimodal deep learning architecture for smoking detection with a small data approach}, url = {https://m2.mtmt.hu/api/publication/34694205}, author = {Lakatos, Róbert and Pollner, Péter and Hajdu, András and Joó, Tamás}, doi = {10.3389/frai.2024.1326050}, journal-iso = {FRONTI ARTIF INTELL}, journal = {FRONTIERS IN ARTIFICIAL INTELLIGENCE}, volume = {7}, unique-id = {34694205}, abstract = {Covert tobacco advertisements often raise regulatory measures. This paper presents that artificial intelligence, particularly deep learning, has great potential for detecting hidden advertising and allows unbiased, reproducible, and fair quantification of tobacco-related media content. We propose an integrated text and image processing model based on deep learning, generative methods, and human reinforcement, which can detect smoking cases in both textual and visual formats, even with little available training data. Our model can achieve 74% accuracy for images and 98% for text. Furthermore, our system integrates the possibility of expert intervention in the form of human reinforcement. Using the pre-trained multimodal, image, and text processing models available through deep learning makes it possible to detect smoking in different media even with few training data.}, year = {2024}, eissn = {2624-8212}, orcid-numbers = {Pollner, Péter/0000-0003-0464-4893; Joó, Tamás/0000-0002-3551-6125} } @article{MTMT:34521945, title = {Impact of regulatory tightening of the Hungarian tobacco retail market on availability, access and cigarette smoking prevalence of adolescents.}, url = {https://m2.mtmt.hu/api/publication/34521945}, author = {Joó, Tamás and Foley, Kristie and Brys, Zoltán and Rogers, Todd and Szócska, Miklós and Bodrogi, József and Gaál, Péter and Pénzes, Melinda}, doi = {10.1136/tc-2023-058232}, journal-iso = {TOB CONTROL}, journal = {TOBACCO CONTROL}, volume = {In press}, unique-id = {34521945}, issn = {0964-4563}, abstract = {Policies that reduce tobacco retail density to decrease tobacco use among the youth are critical for the tobacco endgame. This paper reviews a Hungarian tobacco regulatory measure, which, since 2013, has confined the sale of tobacco products exclusively to so-called National Tobacco Shops, summarises the changes in the national tobacco retail marketplace and reports on analyses of the impact of this intervention on illegal sales to minors and adolescent smoking behaviour.We reviewed the available national statistical data on the structure and dynamics of the tobacco retail market. Changes in lifetime and current (past 30 days) use of cigarettes among Hungarian adolescents aged 13-17 years were assessed using data from international youth surveys on health behaviours collected in 2010-2020.Since the start of policy implementation, the density of tobacco shops in Hungary decreased by 85%, from 4.1 to 0.6 per 1000 persons. The prevalence of lifetime and current cigarette smoking among adolescents declined by 13-24 percentage points (pp) and by 4.8-15 pp, respectively. The rate of illegal sales of tobacco products to minors decreased by 27.6 pp, although the prevalence of compensatory access strategies, especially asking others to buy cigarettes for minors, increased.After a significant decrease in the nationwide availability of licensed tobacco retailers, Hungary experienced short-term reductions in youth smoking prevalence. However, the sporadic implementation of complementary, evidence-based tobacco control strategies might limit further declines in youth smoking initiation and tobacco product use.}, keywords = {Public Policy; surveillance and monitoring; End game}, year = {2024}, eissn = {1468-3318}, orcid-numbers = {Joó, Tamás/0000-0002-3551-6125; Brys, Zoltán/0000-0002-3324-2255; Szócska, Miklós/0000-0003-0648-9778; Gaál, Péter/0000-0002-6815-9021; Pénzes, Melinda/0000-0001-7396-4028} } @article{MTMT:34520558, title = {Az egészségkárosodás társadalmi költségei a munkaképes korú lakosság körében 2019-ben Magyarországon}, url = {https://m2.mtmt.hu/api/publication/34520558}, author = {Joó, Tamás and Fadgyas-Freyler, Petra and Vitrai, József and Kollányi, Zsófia Katalin}, doi = {10.1556/650.2024.32955}, journal-iso = {ORV HETIL}, journal = {ORVOSI HETILAP}, volume = {165}, unique-id = {34520558}, issn = {0030-6002}, abstract = {Bevezetés: Hazánkban a várható egészséges életévek száma alacsonyabb, mint a nyugdíjkorhatár, vagyis a 30 és 64 éves kor közötti magyar lakosság megromlott egészségi állapota jelentős termeléskiesést okoz. A gazdasági szempontokon túl a munkaképes korú korosztály romlott egészségi állapotát más társadalmi szereplő nézőpontjából is lehet vizsgálni, a közvetett költségeket az emberitőke-megközelítésnek megfelelően kalkulálva. Célkitűzés: Becslésünk célja az volt, hogy megvilágítsuk, mekkora veszteségeket okoz Magyarország számára évről évre az, hogy lakosai jelentősen rövidebb és betegebb életre számíthatnak, mint más országok hasonló helyzetű lakosai. Módszer: Az elemzés első részében a 30–64 éves korosztályra vonatkozóan 2019-re összesítettük a megromlott egészség és a betegségek okozta korlátozottság miatt elvesztett, egészségben eltöltött időt. A vizsgált korosztályra vonatkozó magyar értékeket a visegrádi országok, Ausztria és az Európai Unió megfelelő értékeivel vetettük össze. Az elemzés második részében a betegségben töltött időhöz kapcsolódó társadalmi költségeket mutattuk be, melyek között megkülönböztettünk közvetlen, pénzmozgással járó költségeket, valamint közvetett, az elmaradt bevételekben vagy termelésben megtestesülő költségeket. Eredmények: Az eredmények alapján megállapítható, hogy 2019-ben Magyarországon a munkanapok egyhetedében az egészségproblémák miatt csökkent a termelékenység és a teljesített munkaidő. Átlagosan 51 naptári nap, ennek megfelelően 35 munkanap elveszett egészséges idő jutott minden 30–64 éves munkaképes magyarra. A közvetlen költségek, vagyis az Egészségbiztosítási Alap természetbeni kiadásainak, valamint a betegek és az önkéntes (magán)biztosítás által finanszírozott kiadásainak összege 1446 milliárd Ft-ot tett ki. A közvetett költségek, amelyek a korai halálozásnak és a betegségeknek betudható munkaévveszteség következtében fellépő kiadásokat jelentik, további 2279 milliárd Ft terhet jelentettek. Következtetés: A 30–64 évesek közvetlen és közvetett kiadásainak összege 2019-ben 3425 milliárd Ft-ot tett ki, a GDP 7,21%-át. Jól ismert, hogy a fejlett országokban, így Magyarországon is azok a nem fertőző, krónikus betegségek okozzák a legnagyobb egészségveszteséget, amelyek egészséges életmóddal megelőzhetők. Az ország versenyképességének javításához emiatt elengedhetetlen az egészséges életmód előmozdítása és az azt elősegítő fizikai és szociális környezet kialakítása. Orv Hetil. 2024; 165(3): 110–120.}, keywords = {társadalmi költség; munkaévveszteség; munkaképes korú; jövedelemveszteség}, year = {2024}, eissn = {1788-6120}, pages = {110-120}, orcid-numbers = {Joó, Tamás/0000-0002-3551-6125; Fadgyas-Freyler, Petra/0000-0002-0858-8924; Vitrai, József/0000-0001-9267-806X; Kollányi, Zsófia Katalin/0000-0003-1261-6745} } @{MTMT:34569456, title = {A nemzeti egészségügyi adatvagyon gazdasági jelentősége}, url = {https://m2.mtmt.hu/api/publication/34569456}, author = {Szócska, Miklós and Joó, Tamás and Gaál, Péter}, booktitle = {Medicina évkönyv 2023. A magyar egészségügy számokban: ellátás, gazdaság, innováció}, unique-id = {34569456}, year = {2023}, pages = {44-47}, orcid-numbers = {Szócska, Miklós/0000-0003-0648-9778; Joó, Tamás/0000-0002-3551-6125; Gaál, Péter/0000-0002-6815-9021} } @article{MTMT:34518238, title = {Röviden az Év Medikusa díjról}, url = {https://m2.mtmt.hu/api/publication/34518238}, author = {Lőrincz, Orsolya and Joó, Tamás and Gaál, Péter}, journal-iso = {IME}, journal = {IME}, volume = {22}, unique-id = {34518238}, issn = {1588-6387}, year = {2023}, eissn = {1789-9974}, pages = {51-51}, orcid-numbers = {Lőrincz, Orsolya/0000-0003-2294-2405; Joó, Tamás/0000-0002-3551-6125; Gaál, Péter/0000-0002-6815-9021} } @article{MTMT:34486659, title = {Global Burden of Cardiovascular Diseases and Risks, 1990-2022}, url = {https://m2.mtmt.hu/api/publication/34486659}, author = {Mensah, George A and Fuster, Valentin and Murray, Christopher J L and Roth, Gregory A}, doi = {10.1016/j.jacc.2023.11.007}, journal-iso = {J AM COLL CARDIOL}, journal = {JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY}, volume = {82}, unique-id = {34486659}, issn = {0735-1097}, year = {2023}, eissn = {1558-3597}, pages = {2350-2473}, orcid-numbers = {Bikov, András/0000-0002-8983-740X; Gaál, Péter/0000-0002-6815-9021; Joó, Tamás/0000-0002-3551-6125; Palicz, Tamás Gyula/0000-0003-3676-2878} } @article{MTMT:34216612, title = {Could TikTok be a promising platform for anti-tobacco communication? – Experiences from Hungary}, url = {https://m2.mtmt.hu/api/publication/34216612}, author = {Kulja, András and Joó, Tamás and Pénzes, Melinda}, doi = {10.18332/tpc/172688}, journal-iso = {Tobacco Prevention and Cessation}, journal = {Tobacco Prevention and Cessation}, volume = {9}, unique-id = {34216612}, year = {2023}, eissn = {2459-3087}, pages = {28-29}, orcid-numbers = {Joó, Tamás/0000-0002-3551-6125; Pénzes, Melinda/0000-0001-7396-4028} }