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Your search keyword '"Jahangiry, Leila"' showing total 269 results
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269 results on '"Jahangiry, Leila"'

10. Framingham risk scores for determination the 10-year risk of cardiovascular disease in participants with and without the metabolic syndrome: results of the Fasa Persian cohort study.

Author

Dehghan, Azizallah, Jahangiry, Leila, Khezri, Rozhan, Jafari, Alireza, Pezeshki, Babak, Rezaei, Fatemeh, and Aune, Dagfinn

Subjects
*CARDIOVASCULAR disease prevention, *RISK assessment, *CROSS-sectional method, *HIGH density lipoproteins, *CARDIOVASCULAR diseases, *RESEARCH funding, *SEX distribution, *SMOKING, *MULTIPLE regression analysis, *CARDIOVASCULAR diseases risk factors, *AGE distribution, *DESCRIPTIVE statistics, *LONGITUDINAL method, *WAIST circumference, *METABOLIC syndrome, *CHOLESTEROL, *SYSTOLIC blood pressure, *TRIGLYCERIDES, *DIABETES
Abstract

Background: Metabolic syndrome (MetS) is a cluster of risk factors and the Framingham risk score (FRS) is a useful metric for measuring the 10-year cardiovascular disease (CVD) risk of the population. The present study aimed to determine the 10-year risk of cardiovascular disease using the Framingham risk score in people with and without MetS in a large Iranian cohort study. Methods: This cross-sectional study was done using the Fasa cohort. Participants aged ≥ 35 years old were recruited to the study from 2015 to 2016. The FRS was calculated using age, sex, current smoking, diabetes, systolic blood pressure (SBP), total cholesterol, and high-density lipoprotein (HDL) cholesterol. MetS was defined as the presence of three or more of the MetS risk factors including triglyceride (TG) level ≥ 150 mg dl− 1, HDL level < 40 mg dl− 1 in men and < 50 mg dl− 1 in women, systolic/diastolic blood pressure ≥ 130/≥85 mmHg or using medicine for hypertension, fasting blood sugar (FBS) level ≥ 100 mg dl− 1 or using diabetes medication and abdominal obesity considered as waist circumference (WC) ≥ 88 cm for women and ≥ 102 cm for men. Multiple logistic regressions were applied to estimate the 10- year CVD risk among people with and without MetS. Results: Of 8949 participants, 1928 people (21.6%) had MetS. The mean age of the participants with and without Mets was 50.4 ± 9.2 years and 46.9 ± 9.1 years respectively. In total 15.3% of participants with MetS and 8.0% of participants without MetS were in the high-risk category of 10-year CVD risk. Among participants with MetS gender, TG, SBP, FBS and in people without MetS gender, TG, SBP, FBS, and HDL showed strong associations with the predicted 10-year CVD risk. Conclusion: Male sex and increased SBP, TG, and FBS parameters were strongly associated with increased 10-year risk of CVD in people with and without MetS. In people without MetS, reduced HDL-cholestrol was strongly associated with increased 10-year risk of CVD. The recognition of participant's TG, blood pressure (BP), FBS and planning appropriate lifestyle interventions related to these characteristics is an important step towards prevention of CVD. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Association between nutritional risk status and health related quality of life: An investigation on the aging patients with cardiovascular disease.

Author

Gavgani, Leili Faraji, Alipour, Somayeh, Khabiri, Roghayeh, Laghousi, Delara, Sarbakhsh, Parvin, Farajiazad, Haniyeh, Farhangi, Mahdieh Abbasalizad, and Jahangiry, Leila

Subjects
NUTRITIONAL assessment, ACADEMIC medical centers, CROSS-sectional method, AGE distribution, CARDIOVASCULAR diseases, REGRESSION analysis, RISK assessment, SEX distribution, QUALITY of life, MALNUTRITION, RESEARCH funding, DESCRIPTIVE statistics, SOCIODEMOGRAPHIC factors, STATISTICAL sampling, EDUCATIONAL attainment, DISEASE risk factors, OLD age
Abstract

Introduction: Acknowledging the considerable influence of undernutrition on health outcomes and HRQOL, this study sought to appraise the nutritional risk status of elderly patients with cardiovascular diseases (CVD) through the utilization of the Nutritional Risk Screening (NRS). Additionally, the investigation aimed to evaluate the correlation between NRS status and HRQOL within the context of patients referred to a cardiac hospital in Tabriz, Iran. Methods: This cross-sectional study was conducted in Tabriz, Iran. The participants were selected randomly from patients referring to Shahid Madani Heart Hospital, a comprehensive university hospital during July to December 2018. A linear regression was used for control of confounding variables (age, gender, education level, marital status, and income levels) and predict the relationship between nutrition risk status and HQRL. Results: Of the 200 patients with CVD participated in this study, 68 (34%) of participants had normal nutrition status, 108 (54%) were at risk for undernutrition, and 24 (12%) had undernutrition. A total of 24 aging patients with undernutrition, 13 (54%) were divorced or widowed. 86% of patients with diabetes were at risk for undernutrition and 13.9% had undernutrition. There were statistically significant relationship between undernutrition and HRQOL dimensions, age, gender, and marital status. Conclusion: The study revealed a correlation between elevated undernutrition scores in patients and factors such as older age, female gender, and marital status of being divorced or widowed. Furthermore, the results imply that a notable elevation in the risk score for undernutrition in patients is significantly linked to impaired HRQOL among elderly individuals with CVD. [ABSTRACT FROM AUTHOR]

Published
2023
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25. Risk perception and preventive behaviors related to brucellosis among Iranian livestock farmers.

Author

Moslehi, Shandiz, Jahangiry, Leila, Narimani, Sajjad, Maleki, Ali, Zarehoseinzade, Elham, and Shaker, HamidReza

Subjects
RISK perception, BRUCELLOSIS, ZOONOSES, LIVESTOCK, INFECTIOUS disease transmission
Abstract

Background and Aims: Brucellosis is one of the zoonotic diseases that endanger the health of the population, particularly in developing countries. This study aimed to assess risk perception and behaviors of livestock farmers on brucellosis based on PRECEDE model in a rural area in the northwest of Iran. Methods: This was a cross‐sectional study conducted with 365 livestock farmers in rural areas of Germi, Iran. Participants were selected random sampling method. Data were gathered using a PRECEDE model based questionnaire consisted of five sections including demographic characteristics, predisposing factors (knowledge and attitudes), reinforcing factors, enabling factors, and brucellosis preventive behaviors. Results: The mean ± SD of age of participants was 47.1 ± 14.7 years. The state of knowledge about preventive behaviors and ways of disease transmission was evaluated as appropriate (with 87% and 81% of the maximum score, respectively). Three aspects of attitude in participants were desirable. Predisposing factors including knowledge of prevention ways, knowledge of transmission ways, and attitudes toward prevention, reinforcing factors, as well as education were significant predictors of brucellosis preventive behaviors. R2 and adjusted R2 were 0.312 and 0.310, respectively, according to which, about 31% of the changes in the brucellosis preventive behaviors explained by significant dependent variables. Conclusions: Given that farmers are at particular high risk of exposing brucellosis, improving their knowledge and desirable attitudes of brucellosis is crucial to increasing control the disease. [ABSTRACT FROM AUTHOR]

Published
2023
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35. Screen Time and Body Mass Index Among Children and Adolescents: A Systematic Review and Meta-Analysis

Author

Wu, Yiling, Amirfakhraei, Azita, Ebrahimzadeh, Farnoosh, Jahangiry, Leila, and Abbasalizad-Farhangi, Mahdieh

Subjects
Pediatrics, Perinatology and Child Health
Abstract

BackgroundThere is no summative quantitative study that report the difference in BMI in high screen user children and adolescents or give a difference in screen time in children and adolescents with obesity vs. children and adolescents without obesity. In the current meta-analysis we systematically summarized the association between obesity and screen time and meta-analyzed the results.MethodsA systematic search from Scopus, PubMed and Embase electronic databases. Studies that evaluated the association between screen time and obesity up to June 2021.ResultsResults revealed that those at the highest screen time category had 0.7 kg/m2 higher BMI (WMD = 0.703; CI = 0.128, 1.278; P < 0.016; I2 = 95.8%). Moreover, children and adolescents with obesity had a mean value of 0.313 h higher screen time compared with children and adolescents without obesity (WMD: 0.313; OR = 0.219, 0.407; P < 0.001; I2 = 96%). The results of subgrouping showed that study quality, continent and sample size could reduce the heterogeneity values. No evidence of publication bias was reported according to visual asymmetry of funnel plots and the results of Begg’s and Egger’s tests.ConclusionFor the first time, the current systematic review and meta-analysis revealed a positive association between screen time and obesity among children and adolescents. Due to the cross-sectional design of the included studies, causal inference is impossible, therefore, further studies in separate analysis of both genders are suggested to better elucidate gender-specific results.Systematic Review Registration[www.ClinicalTrials.gov], identifier [CRD4202123 3899].

Published
2022

37. Setting research priorities to achieve long-term national road safety goals in Iran

Author

Sadeghi-Bazargani, Homayoun, primary, Razzaghi, Alireza, additional, Atabak, Ali, additional, Bazargani-Hejazi, Shahrzad, additional, Basirat, Shahriar Behzad, additional, Doshmangir, Leila, additional, Ebrahiminejad, Salman, additional, Farahbakhsh, Mostafa, additional, Benekohal, Rahim Farahnak, additional, Ghaffarifar, Saiedeh, additional, Golestani, Mina, additional, Hamidi, Mohammad Hossein, additional, Heydari, Seyed Taghi, additional, Jahani, Einollah, additional, Jahangiry, Leila, additional, Imani, Ali, additional, Khabiri, Mohammad Mehdi, additional, Khishdari, Abolfazl, additional, Marouf, Hamed, additional, Masoumi, Gholamreza, additional, Mazloumi, Adel, additional, Mehmandar, Mohammad Reza, additional, Mortazavi-Tabatabaei, Seyed Abdolreza, additional, Pourebrahim, Khalil, additional, Rahmanian, Nasir Baradaran, additional, Rezapur-Shahkolai, Forouzan, additional, Rezaei, Mahdi, additional, Saadati, Mohammad, additional, Sarbazi, Ehsan, additional, Samadipour, Ezat, additional, Sehat, Mojtaba, additional, Shafieian, Mehdi, additional, Mohaymany, Afshin Shariat, additional, Soori, Hamid, additional, Sheikhi, Saeedeh, additional, Tabibi, Masoud, additional, Tabrizi, Jafar Sadegh, additional, Kashani, Ali Tavakoli, additional, Vahabzadeh, Ibrahim, additional, Veisi, Salah, additional, and Yazdani, Mirbahador, additional

Published
2022
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41. The effect of the herbal medicine on severity of cyclic mastalgia: a systematic review and meta-analysis.

Author

Osouli Tabrizi, Shirin, Meedya, Shahla, Ghassab-Abdollahia, Nafiseh, Ghorbani, Zahra, Jahangiry, Leila, and Mirghafourvand, Mojgan

Subjects
PAIN management, HERBAL medicine, META-analysis, MEDICAL information storage & retrieval systems, MEDICINAL plants, CONFIDENCE intervals, MENSTRUAL cycle, SYSTEMATIC reviews, SEVERITY of illness index, TREATMENT effectiveness, PLACEBOS, BREAST, DESCRIPTIVE statistics, MEDLINE, ALTERNATIVE medicine, ODDS ratio, REPRODUCTIVE health
Abstract

Cyclic mastalgia is one of the most prevalent problems in women of reproductive age and sometimes it is so severe that it influences their activities and requires treatment. The available drug treatments for mastalgia are not satisfactory and most patients have inclined towards complementary and alternative medicine including herbal medicines. Therefore, in order to evaluate the effectiveness and side effects of herbal medicines conducting systematic review studies and meta-analysis seems essential, thus this systematic review was conducted with the aim of determining the effect of herbal medicines on cyclic mastalgia and its probable side effects. The databases of Pubmed, Medline, Embase, ProQuest, Scopus, Web of science, Complementary Medicine Database, SID (Scientific information database), Magiran and Iranmedex were searched from 1997 to 2020 and limited only for English and Persian languages. The studies were appraised according to the Cochrane Collaboration's tool. Meta-analysis was conducted using RevMan software. Standardized mean difference (SMD) was calculated to assess an overall estimate of effectiveness for the continuous data. Odds ratio (OR) was calculated for dichotomous data. Thirty papers were included in the study. Meta-analysis of data demonstrated that herbal medicine was an effective method in reducing the severity of mastalgia compared to the placebo (SMD: −3.26, 95% CI: −5.05 to −1.46, p=0.00004). Subanalysis of data showed no difference between the effectiveness of herbal medicine on the severity of mastalgia compared to the pharmacologic treatment. This research demonstrated efficacy of herbal medicines in alleviating cyclic mastalgia. Therefore, these herbal medicines can be regarded as an alternative treatment for women suffering from cyclic mastalgia. However, due to the limited number of studies in relation to each specific herbal treatment, conducting further studies in this area is recommended. [ABSTRACT FROM AUTHOR]

Published
2022
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47. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Author

Lozano, Rafael, Fullman, Nancy, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshari, Mahdi, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Monika, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Assadi, Reza, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banerjee, Amitava, Banoub, Joseph Adel Mattar, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Barthelemy, Celine M, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Battista, Robert J, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Benzian, Habib, Berhane, Adugnaw, Berhe, Abadi Kidanemariam, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhansali, Anil, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Biehl, Molly H, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bitew, Helen, Bizuneh, Hailemichael, Bjertness, Espen, Bobasa, Eshetu Mulisa, Boufous, Soufiane, Bourne, Rupert, Bozorgmehr, Kayvan, Bragazzi, Nicola Luigi, Brainin, Michael, Brant, Luisa C, Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Bukhman, Gene, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Callender, Charlton SKH, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Josip, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carter, Austin, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Causey, Kate, Çavlin, Alanur, Cercy, Kelly M, Cerin, Ester, Chaiah, Yazan, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chattu, Vijay Kumar, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J, Chung, Sheng-Chia, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Claßen, Thomas Khaled Dwayne, Cohen, Aaron J, Collado-Mateo, Daniel, Cooper, Cyrus, Cooper, Leslie Trumbull, Cornaby, Leslie, Cortinovis, Monica, Costa, Megan, Cousin, Ewerton, Cromwell, Elizabeth A, Crowe, Christopher Stephen, Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I, Daryani, Ahmad, Das, Siddharth K, Das Gupta, Rajat, das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C, Davitoiu, Dragos Virgil, Davletov, Kairat, Dayama, Anand, de Courten, Barbora, De Leo, Diego, De Neve, Jan-Walter, De Steur, Hans, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta Tilahun, Deiparine, Selina, Dellavalle, Robert P, Demoz, Gebre Teklemariam, Demtsu, Balem, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Dessie, Getenet Ayalew, Dey, Subhojit, Dharmaratne, Samath D, Dhimal, Meghnath, Dicker, Daniel, Dinberu, Mesfin Tadese, Ding, Eric L, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Douwes-Schultz, Dirk, Driscoll, Tim Robert, Duan, Leilei, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B, Duraes, Andre R, Ebrahimpour, Soheil, Edvardsson, David, El Bcheraoui, Charbel, Eldrenkamp, Erika, El-Khatib, Ziad, Elyazar, Iqbal RF, Enayati, Ahmadali, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Esteghamati, Sadaf, Estep, Kara, Fakhar, Mahdi, Fakhim, Hamed, Fanzo, Jessica, Faramarzi, Mahbobeh, Fareed, Mohammad, Farhadi, Farzaneh, Farid, Talha A, Farinha, Carla Sofia e Sá, Farioli, Andrea, Faro, Andre, Farvid, Maryam S, Farzadfar, Farshad, Farzaei, Mohammad Hosein, Farzam, Hossein, Fazaeli, Ali Akbar, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Fekadu, Wubalem, Feldman, Rachel, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C, Feyissa, Garumma Tolu, Fijabi, Daniel Obadare, Filip, Irina, Finegold, Samuel, Finger, Jonas David, Fischer, Florian, Fitzmaurice, Christina, Flor, Luisa Sorio, Foigt, Nataliya A, Foreman, Kyle J, Frank, Tahvi D, Franklin, Richard Charles, Fukumoto, Takeshi, Fukutaki, Kai, Fuller, John E, Fürst, Thomas, Furtado, João M, Gakidou, Emmanuela, Gallus, Silvano, Gankpe, Fortune Gbetoho, Gansevoort, Ron T, Garcia, Ana Cristina, Garcia-Basteiro, Alberto L, Garcia-Gordillo, Miguel A, Gardner, William M, Gebre, Abadi Kahsu, Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gebremichael, Bereket, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijnse, Johanna M, Geramo, Yilma Chisha Dea, Getachew, Sefonias, Gething, Peter W, Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi-Kasman, Maryam, Ghiasvand, Hesam, Ghimire, Mamata, Ghoshal, Aloke Gopal, Giampaoli, Simona, Gill, Paramjit Singh, Gill, Tiffany K, Giussani, Giorgia, Gnedovskaya, Elena V, Goldberg, Ellen M, Goli, Srinivas, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Gorman, Taren M, Goto, Atsushi, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Griswold, Max G, Grosso, Giuseppe, Gugnani, Harish Chander C, Guillemin, Francis, Guimaraes, Andre Luiz Sena, Guo, Yuming, Gupta, Prakash C, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Ha, Giang Hai, Haagsma, Juanita A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Haghparast Bidgoli, Hassan, Hagos, Tekleberhan B, Haile, Michael Tamene, Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randah R, Hamidi, Samer, Hankey, Graeme J, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haririan, Hamidreza, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid Yimam, Havmoeller, Rasmus, Hawley, Caitlin N, Hay, Simon I, He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I, Heibati, Behzad, Heidari, Behnam, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Heredia-Pi, Ileana, Herteliu, Claudiu, Heydarpour, Behzad, Heydarpour, Fatemeh, Heydarpour, Sousan, Hibstu, Desalegn T, Híjar, Martha, Hoek, Hans W, Hoffman, Daniel J, Hole, Michael K, Homaie Rad, Enayatollah, Hoogar, Praveen, Horita, Nobuyuki, Hosgood, H Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hotez, Peter J, Hoy, Damian G, Hsairi, Mohamed, Hsiao, Thomas, Hu, Guoqing, Huang, John J, Hughes, Caitlyn, Huynh, Chantal K, Igumbor, Ehimario U, Ikeda, Chad Thomas, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Ivers, Rebecca Q, Izadi, Neda, Jacobsen, Kathryn H, Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, Jalu, Moti Tolera, Jamal, Amr A, James, Spencer L, Jassal, Simerjot K, Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Johnson, Catherine O, Johnson, Sarah C, Jonas, Jost B, Jonnagaddala, Jitendra, Jorjoran Shushtari, Zahra, Joshi, Ankur, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jürisson, Mikk, K, Madhanraj, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kahssay, Molla, Kalani, Rizwan, Kapil, Umesh, Karami, Manoochehr, Karami Matin, Behzad, Karanikolos, Marina, Karimi, Narges, Karimi, Seyed M, Karimi-Sari, Hamidreza, Kasaeian, Amir, Kassa, Dessalegn H, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassa, Zemenu Yohannes, Kassebaum, Nicholas J, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazemi, Zhila, Karyani, Ali Kazemi, Kazi, Dhruv Satish, KC, Prakash, Kebede, Seifu, Keiyoro, Peter Njenga, Kemmer, Laura, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khafaei, Behzad, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A, Khan, Ejaz Ahmad, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khanna, Tripti, Khater, Mona M, Khatony, Alireza, Khazaeipour, Zahra, Khazaie, Habibolah, Khoja, Abdullah T, Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kiadaliri, Aliasghar A, Kiarie, Helen W, Kibret, Getiye D, Kiirithio, Daniel N, Kim, Daniel, Kim, 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Subjects
GENDER-DIFFERENCES, SUICIDE, Medicine (all), Burden of Disease Study 2017, SDG, CONSUMPTION, 11 Medical And Health Sciences, GBD, Sustainable Development Goals, PREVENTION, ALCOHOL-USE, CARDIOVASCULAR-DISEASE, SMOKING PREVALENCE, General & Internal Medicine, factors risk, Medicine and Health Sciences, Human medicine, CESSATION, PERSPECTIVE, TRANSITION
Abstract

Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health -related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related S DG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2.5th percentile and 100 as the 97.5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings The global median health-related SDG index in 2017 was 59.4 (IQR 35.4-67.3), ranging from a low of 11.6 (95% uncertainty interval 9.6-14.0) to a high of 84.9 (83.1-86.7). SDG index values in countries assessed at the subnational level varied substantially particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attaimnent by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation The GBD study offers a unique, robust platform for monitoring the health -related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health -related SDG indicators, NCDs, NCD-related risks, and violence -related indicators will require a concerted shift away from what might have driven past gains curative interventions in the case of NCDs towards multisectoral, prevention -oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the S DGs. What is clear is that our actions or inaction today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

Published
2018

48. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017

Author

Roth, Gregory A., Collaborotors, G. B. D.Causes Death, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M., Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Load, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adamu, Abdu A., Adebayo, Oladimeji, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adookunboh, Olatunii, Adhena, Beyene Meressa, Adib, Mina G., Admasie, Aniha, Afshin, Ashkan, Agarwal, Gina, Agesa, Karelia M., Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Melidi, Ahmed, Muktar Beshir, Ahmed, Sayent, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Fddine, Akbari, Mohammad Esmaeil, Akinyeniti, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M., Alandab, Fares, Alam, Khurshid, Alam, Tahiya, Alebel, Animut, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, Francois, Allebeck, Peter, Alonso, Jordi, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T., Aminde, Leopold N., Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampern, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Aniha, Mustafa Geleto, Antonio, Carl Abelardo T., Anwari, Palwasha, Aremu, Olatunde, Arnlov, Johan, Arora, Amit, Arora, Monika, Artaman, Al, Aryal, Krishna K., Asayesh, Hamid, Asfaw, Ephremi Tsegay, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R., Ausloos, Marcel, Avokpaho, Euripide F. 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Subjects
Adult, Male, Adolescent, national age-sex-specific mortality, UNITED-STATES, Global Health, Socioeconomic Factor, Global Burden of Disease, GBD, causes of death, Young Adult, Age Distribution, Life Expectancy, General & Internal Medicine, Cause of Death, PUBLIC-HEALTH PROBLEM, mortality, 282 causes global burden of disease, Sex Distribution, Child, Aged, Aged, 80 and over, BARRIERS, DEMENTIA, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, TRENDS, PREVENTION, PREVALENCE, ALZHEIMERS-DISEASE, INDIVIDUALS, 3121 General medicine, internal medicine and other clinical medicine, Child, Preschool, REGISTRATION, Female, Human medicine, Human
Abstract

Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.

Published
2018

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