8 research outputs found

    The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

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    Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

    Demand of and Access to Health Messages Through Mass Media in the Rural Community of Eastern Ethiopia: A Mixed Method Study

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    Bushra Aliyi,1 Yadeta Dassie,2 Alemayehu Deressa,2 Adera Debella,3 Abdi Birhanu,4 Mulugeta Gamachu,4,5 Addis Eyeberu,3 Gelana Mamo Ayana,2 Hamdi Fekredin,2 Ibsa Mussa2 1Zonal Health Office, Eastern Hararghe, Oromia, Ethiopia; 2School of Public Health, CHMS, Haramaya University, Harar, Ethiopia; 3School of Nursing and Midwifery, CHMS, Haramaya University, Harar, Ethiopia; 4School of Medicine, CHMS, Haramaya University, Harar, Ethiopia; 5Departments of Public Health, Rift Valley University, Harar, EthiopiaCorrespondence: Alemayehu Deressa, School of Public Health, CHMS, Haramaya University, PO Box 235, Harar, Ethiopia, Tel +251917841709, Fax +251256668081, Email [email protected]: The demand for health-related information has increased dramatically in recent years. Media is crucial in reaching health messages to audiences, especially those who are distant and rural. Therefore, the study aimed to assess demands, access, and factors associated with access to health messages through mass media in the rural community of Kersa District of East Hararghe, Eastern Ethiopia.Methods: A mixed-methods study was conducted from October 15 to November 20, 2020. A quantitative cross-sectional and a qualitative phenomenological study design were applied. A total of 578 participants were included by using a systematic sampling technique. Collected data were entered into Epidata version 3.1 and analyzed using SPSS version 22.0. A multivariate logistic regression analysis model was used and reported using an adjusted odds ratio (AOR) with a 95% confidence interval (CI). Statistical significance was set at p < 0.05. For qualitative, six-focused group discussions (FGDs) were used and then analyzed thematically.Results: Overall, the demand of and access to health messages through mass media was 32.5% (95% CI=28.5– 34.2%) and 26.6% (95% CI=24.6– 28.7%), respectively. Factors such as having electric services (AOR=2.36, 95% CI=2.13– 5.41), having a mobile phone (AOR=4.56, 95% CI=4.32– 8.73), exposure to TV (AOR=4.73, 95% CI=1.03– 11.62), and exposure to social media and printed media (AOR=5.24, 95% CI=1.07– 15.63), a preference for programs such as news, current affairs, entertainment, health and educational were 2.37, 9.47, 4.75 and 7.55 times more likely to access health messages (AOR=2.37, 95% CI=1.00– 5.61; AOR=9.47, 95% CI=3.54– 25.34; AOR=4.75, 95% CI=1.23– 18.38; and AOR=7.55, 95% CI=3.12– 8.66, respectively). Qualitative findings, participants demand for health messages from health workers, radio, and the main source for accessing the message was the radio.Conclusion: Approximately one in every three and one in every four rural communities in the study area had demand, and access to health messages through mass media, respectively. As a result, all stakeholders should emphasize and strengthen expanding methods of reaching health messages using mass media.Keywords: health message, media, access, rural community, Eastern Ethiopi

    Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019

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    Background Reducing the burden of death due to infection is an urgent global public health priority. Previous studies have estimated the number of deaths associated with drug-resistant infections and sepsis and found that infections remain a leading cause of death globally. Understanding the global burden of common bacterial pathogens (both susceptible and resistant to antimicrobials) is essential to identify the greatest threats to public health. To our knowledge, this is the first study to present global comprehensive estimates of deaths associated with 33 bacterial pathogens across 11 major infectious syndromes. Methods We estimated deaths associated with 33 bacterial genera or species across 11 infectious syndromes in 2019 using methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, in addition to a subset of the input data described in the Global Burden of Antimicrobial Resistance 2019 study. This study included 343 million individual records or isolates covering 11 361 study-location-years. We used three modelling steps to estimate the number of deaths associated with each pathogen: deaths in which infection had a role, the fraction of deaths due to infection that are attributable to a given infectious syndrome, and the fraction of deaths due to an infectious syndrome that are attributable to a given pathogen. Estimates were produced for all ages and for males and females across 204 countries and territories in 2019. 95% uncertainty intervals (UIs) were calculated for final estimates of deaths and infections associated with the 33 bacterial pathogens following standard GBD methods by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. Findings From an estimated 13·7 million (95% UI 10·9–17·1) infection-related deaths in 2019, there were 7·7 million deaths (5·7–10·2) associated with the 33 bacterial pathogens (both resistant and susceptible to antimicrobials) across the 11 infectious syndromes estimated in this study. We estimated deaths associated with the 33 bacterial pathogens to comprise 13·6% (10·2–18·1) of all global deaths and 56·2% (52·1–60·1) of all sepsis-related deaths in 2019. Five leading pathogens—Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa—were responsible for 54·9% (52·9–56·9) of deaths among the investigated bacteria. The deadliest infectious syndromes and pathogens varied by location and age. The age-standardised mortality rate associated with these bacterial pathogens was highest in the sub-Saharan Africa super-region, with 230 deaths (185–285) per 100 000 population, and lowest in the high-income super-region, with 52·2 deaths (37·4–71·5) per 100 000 population. S aureus was the leading bacterial cause of death in 135 countries and was also associated with the most deaths in individuals older than 15 years, globally. Among children younger than 5 years, S pneumoniae was the pathogen associated with the most deaths. In 2019, more than 6 million deaths occurred as a result of three bacterial infectious syndromes, with lower respiratory infections and bloodstream infections each causing more than 2 million deaths and peritoneal and intra-abdominal infections causing more than 1 million deaths. Interpretation The 33 bacterial pathogens that we investigated in this study are a substantial source of health loss globally, with considerable variation in their distribution across infectious syndromes and locations. Compared with GBD Level 3 underlying causes of death, deaths associated with these bacteria would rank as the second leading cause of death globally in 2019; hence, they should be considered an urgent priority for intervention within the global health community. Strategies to address the burden of bacterial infections include infection prevention, optimised use of antibiotics, improved capacity for microbiological analysis, vaccine development, and improved and more pervasive use of available vaccines. These estimates can be used to help set priorities for vaccine need, demand, and development

    Age–sex differences in the global burden of lower respiratory infections and risk factors, 1990–2019: results from the Global Burden of Disease Study 2019

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    Background: The global burden of lower respiratory infections (LRI) and corresponding risk factors in children older than five years and adults has not been studied as comprehensively as in children under five years old. We assessed the burden and trends of LRI and risk factors across all age groups by sex for 204 countries and territories. Methods: We used clinician-diagnosed pneumonia or bronchiolitis as our case definition for lower respiratory infections. We included ICD9 codes 073.0-073.6, 079.82, 466-469, 480-489, 513.0, and 770.0 and ICD10 codes A48.1, J09-J22, J85.1, P23-P23.9, and U04. We used the Cause of Death Ensemble modelling strategy to analyse 23,109 site-years of vital registration data, 825 site-years of sample vital registration data, 1766 site-years of verbal autopsy data, and 681 site-years of mortality surveillance data. We used DisMod-MR 2.1, a Bayesian meta-regression tool, to analyse age-sex-specific incidence and prevalence data identified via systematic review, population-based surveys, and claims and inpatient data. Additionally, we estimated age-sex-specific LRI mortality that is attributable to the independent effects of 14 risk factors.Results: Globally, we estimated LRI episodes of 257 million (95% UI 240–275) for males and 232 million (217–248) for females in 2019. In the same year, LRI accounted for 1.3 million (1.2–1.4) deaths among males and 1.2 million (1.1–1.3) deaths among females. Age-standardised incidence and mortality rates were 1.2 times and 1.3 times greater in males than in females in 2019. Between 1990 and 2019, LRI incidence and mortality rates declined at different rates across age groups while an increase in LRI episodes and deaths was estimated among all adult age groups, with males aged 70 years and older experiencing the highest increase in LRI episodes (126.0% [121.4–131.1]) and deaths (100.0% [83.4–115.9]). During the same period, LRI episodes and deaths in children younger than 15 years were estimated to have decreased, and the greatest decline was observed for mortality among males under the age of five (70.7% [61.8–77.3]). The leading risk factors for LRI mortality varied across age groups and sex. More than half of global LRI deaths among males and females younger than five years were attributable to child wasting, and more than a quarter of LRI deaths among those aged 5–14 years were attributable to household air pollution in 2019. For males aged 15–49, 50–69, and 70 years and older, 20.4 (15.4-25.2), 30.5% (24.1–36.9), and 21.9% (16.8–27.3), respectively, of estimated LRI deaths were attributable to smoking in the same year. For females aged 15–49 and 50–69 years, 21.1% (14.5–27.9) and 7.9% (5.5–10.5) of estimated LRI deaths were attributable to household air pollution in 2019. For females aged 70 years and older, the leading risk factor, ambient particulate matter, was responsible for 11.7% (8.2–15.8) of LRI deaths in the same year.Interpretation: The patterns and progress in reducing the burden of LRI and key risk factors varied across age groups and sexes.. The progress seen in under five children was clearly a result of targeted interventions, such as vaccination and reduction of exposure to risk factors. Similar interventions for other age groups could contribute to achieving multiple Sustainable Development Goals targets, including promoting well-being at all ages and reducing inequalities. Interventions, including addressing risk factors such as child wasting, smoking, ambient particulate matter pollution, and household air pollution, would mean preventable deaths and millions of lives saved, as well as reduced health disparities

    The global burden of cancer attributable to risk factors, 2010-19: a systematic analysis for the Global Burden of Disease Study 2019

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    Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% 47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% 32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% 27.9-42.8] and 33.3% 25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
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