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3. Temporal patterns of cancer burden in Asia, 1990–2019: a systematic examination for the Global Burden of Disease 2019 study

Author

Sharma, Rajesh, Abbastabar, Hedayat, Abdulah, Deldar Morad, Abidi, Hassan, Abolhassani, Hassan, Abrehdari-Tafreshi, Zahra, Absalan, Abdorrahim, Ali, Hiwa Abubaker, Abu-Gharbieh, Eman, Acuna, Juan Manuel, Adib, Nasrin, Sakilah Adnani, Qorinah Estiningtyas, Aghaei, Abbas, Ahmad, Aqeel, Ahmad, Sajjad, Ahmadi, Ali, Ahmadi, Sepideh, Ahmed, Luai A., Ajami, Marjan, Al Hamad, Hanadi, Al Hasan, Syed Mahfuz, Alanezi, Fahad Mashhour, Saeed Al-Gheethi, Adel Ali, Al-Hanawi, Mohammed Khaled, Ali, Abid, Ali, Beriwan Abdulqadir, Alimohamadi, Yousef, Aljunid, Syed Mohamed, Ali Al-Maweri, Sadeq Ali, Alqahatni, Saleh A., AlQudah, Mohammad, Al-Raddadi, Rajaa M., Al-Tammemi, Ala'a B., Ansari-Moghaddam, Alireza, Anwar, Sumadi Lukman, Anwer, Razique, Aqeel, Muhammad, Arabloo, Jalal, Arab-Zozani, Morteza, Ariffin, Hany, Artaman, Al, Arulappan, Judie, Ashraf, Tahira, Askari, Elaheh, Athar, Mohammad, Wahbi Atout, Maha Moh'd, Azadnajafabad, Sina, Badar, Muhammad, Badiye, Ashish D., Baghcheghi, Nayereh, Bagherieh, Sara, Bai, Ruhai, Bajbouj, Khuloud, Baliga, Shrikala, Bardhan, Mainak, Bashiri, Azadeh, Baskaran, Pritish, Basu, Saurav, Belgaumi, Uzma Iqbal, Nazer C Bermudez, Amiel, Bhandari, Bharti, Bhardwaj, Nikha, Bhat, Ajay Nagesh, Bitaraf, Saeid, Boloor, Archith, Hashemi, Milad Bonakdar, Butt, Zahid A., Chadwick, Joshua, Kai Chan, Jeffrey Shi, Chattu, Vijay Kumar, Chaturvedi, Pankaj, Cho, William C.S., Darwesh, Aso Mohammad, Dash, Nihar Ranjan, Dehghan, Amin, Dhali, Arkadeep, Dianatinasab, Mostafa, Dibas, Mahmoud, Dixit, Abhinav, Dixit, Shilpi Gupta, Dorostkar, Fariba, Dsouza, Haneil Larson, Elbarazi, Iffat, Elemam, Noha Mousaad, El-Huneidi, Waseem, Elkord, Eyad, Abdou Elmeligy, Omar Abdelsadek, Emamian, Mohammad Hassan, Erkhembayar, Ryenchindorj, Ezzeddini, Rana, Fadoo, Zehra, Faiz, Razana, Fakhradiyev, Ildar Ravisovich, Fallahzadeh, Aida, Faris, MoezAlIslam Ezzat Mahmoud, Farrokhpour, Hossein, Fatehizadeh, Ali, Fattahi, Hamed, Fekadu, Ginenus, Fukumoto, Takeshi, Gaidhane, Abhay Motiramji, Galehdar, Nasrin, Garg, Priyanka, Ghadirian, Fataneh, Ghafourifard, Mansour, Ghasemi, MohammadReza, Nour, Mohammad Ghasemi, Ghassemi, Fariba, Gholamalizadeh, Maryam, Gholamian, Asadollah, Ghotbi, Elena, Golechha, Mahaveer, Goleij, Pouya, Goyal, Sahil, Mohialdeen Gubari, Mohammed Ibrahim, Gunasekera, D Sanjeeva, Gunawardane, Damitha Asanga, Gupta, Sapna, Habibzadeh, Parham, Haeri Boroojeni, Helia Sadat, Halboub, Esam S., Hamadeh, Randah R., Hamoudi, Rifat, Harorani, Mehdi, Hasanian, Mohammad, Hassan, Treska S., Hay, Simon I., Heidari, Mohammad, Heidari-Foroozan, Mahsa, Hessami, Kamran, Hezam, Kamal, Hiraike, Yuta, Holla, Ramesh, Hoseini, Mohammad, Hossain, Md Mahbub, Hossain, Sahadat, Hsieh, Vivian Chia-rong, Huang, Junjie, Hussein, Nawfal R., Hwang, Bing-Fang, Iravanpour, Farideh, Ismail, Nahlah Elkudssiah, Iwagami, Masao, Merin J, Linda, Jadidi-Niaragh, Farhad, Jafarinia, Morteza, Jahani, Mohammad Ali, Jahrami, Haitham, Jaiswal, Abhishek, Jakovljevic, Mihajlo, Jalili, Mahsa, Jamshidi, Elham, Jayarajah, Umesh, Jayaram, Shubha, Jha, Sweety Suman, Jokar, Mohammad, Joseph, Nitin, Kabir, Ali, Kabir, Md. Awal, Kadir, Dler Hussein, Kakodkar, Pradnya Vishal, Kalankesh, Laleh R., Kalankesh, Leila R., Kalhor, Rohollah, Kaliyadan, Feroze, Kamal, Vineet Kumar, Kamal, Zul, Kamath, Ashwin, Kar, Sitanshu Sekhar, Karimi, Hanie, Kaur, Navjot, Keikavoosi-Arani, Leila, Keykhaei, Mohammad, Khader, Yousef Saleh, Khajuria, Himanshu, Khan, Ejaz Ahmad, Khan, M Nuruzzaman, Khan, Maseer, Khan, Moien A.B., Khan, Yusra H., Khanmohammadi, Shaghayegh, Khatatbeh, Moawiah Mohammad, Khateri, Sorour, Khayamzadeh, Maryam, Khayat Kashani, Hamid Reza, Kim, Min Seo, Kompani, Farzad, Koohestani, Hamid Reza, Koulmane Laxminarayana, Sindhura Lakshmi, Krishan, Kewal, Kumar, Narinder, Kumar, Naveen, Kutluk, Tezer, Kuttikkattu, Ambily, Ching Lai, Daphne Teck, Lal, Dharmesh Kumar, Lami, Faris Hasan, Lasrado, Savita, Lee, Sang-Woong, Lee, Seung Won, Lee, Yeong Yeh, Lee, Yo Han, Leong, Elvynna, Li, Ming-Chieh, Liu, Jue, Madadizadeh, Farzan, Mafi, Ahmad R., Mahjoub, Soleiman, Malekzadeh, Reza, Malik, Ahmad Azam, Malik, Iram, Mallhi, Tauqeer Hussain, Mansournia, Mohammad Ali, Martini, Santi, Mathews, Elezebeth, Mathur, Manu Raj, Meena, Jitendra Kumar, Menezes, Ritesh G., Mirfakhraie, Reza, Mirinezhad, Seyed Kazem, Mirza-Aghazadeh-Attari, Mohammad, Mithra, Prasanna, Mohamadkhani, Ashraf, Mohammadi, Soheil, Mohammadzadeh, Maryam, Mohan, Syam, Mokdad, Ali H., Al Montasir, Ahmed, Montazeri, Fateme, Moradi, Maryam, Sarabi, Mostafa Moradi, Moradpour, Farhad, Moradzadeh, Maliheh, Moraga, Paula, Mosapour, Abbas, Motaghinejad, Majid, Mubarik, Sumaira, Muhammad, Jibran Sualeh, Murray, Christopher J.L., Nagarajan, Ahamarshan Jayaraman, Naghavi, Mohsen, Nargus, Shumaila, Natto, Zuhair S., Nayak, Biswa Prakash, Nejadghaderi, Seyed Aria, Nguyen, Phuong The, Niazi, Robina Khan, Noroozi, Nafise, Okati-Aliabad, Hassan, Okekunle, Akinkunmi Paul, Ong, Sokking, Oommen, Anu Mary, Padubidri, Jagadish Rao, Pandey, Ashok, Park, Eun-Kee, Park, Seoyeon, Pati, Siddhartha, Patil, Shankargouda, Paudel, Rajan, Paudel, Uttam, Pirestani, Majid, Podder, Indrashis, Pourali, Ghazaleh, Pourjafar, Mona, Pourshams, Akram, Syed, Zahiruddin Quazi, Radhakrishnan, Raghu Anekal, Radhakrishnan, Venkatraman, Rahman, Mosiur, Rahmani, Shayan, Rahmanian, Vahid, Ramesh, Pushkal Sinduvadi, Rana, Juwel, Rao, Indu Ramachandra, Rao, Sowmya J., Rashedi, Sina, Rashidi, Mohammad-Mahdi, Rezaei, Nazila, Rezaei, Negar, Rezaei, Nima, Rezaei, Saeid, Rezaeian, Mohsen, Roshandel, Gholamreza, Chandan, S.N., Saber-Ayad, Maha Mohamed, Sabour, Siamak, Sabzmakan, Leila, Saddik, Basema, Saeed, Umar, Safi, Sher Zaman, Sharif-Askari, Fatemeh Saheb, Sahebkar, Amirhossein, Sahoo, Harihar, Sajedi, Seyed Aidin, Sajid, Mirza Rizwan, Salehi, Mohammad Amin, Farrokhi, Amir Salek, Sarasmita, Made Ary, Sargazi, Saman, Sarode, Gargi Sachin, Sarode, Sachin C., Sathian, Brijesh, Satpathy, Maheswar, Semwal, Prabhakar, Senthilkumaran, Subramanian, Sepanlou, Sadaf G., Shafeghat, Melika, Shahabi, Saeed, Shahbandi, Ataollah, Shahraki-Sanavi, Fariba, Shaikh, Masood Ali, Shannawaz, Mohammed, Sheikhi, Rahim Ali, Shobeiri, Parnian, Shorofi, Seyed Afshin, Shrestha, Sunil, Siabani, Soraya, Singh, Garima, Singh, Paramdeep, Singh, Surjit, Sinha, Dhirendra Narain, Siwal, Samarjeet Singh, Sreeram, Saraswathy, Suleman, Muhammad, Abdulkader, Rizwan Suliankatchi, Sultan, Iyad, Sultana, Abida, Tabish, Mohammad, Tabuchi, Takahiro, Taheri, Majid, Talaat, Iman M., Tehrani-Banihashemi, Arash, Temsah, Mohamad-Hani, Thangaraju, Pugazhenthan, Thomas, Nihal, Thomas, Nikhil Kenny, Tiyuri, Amir, Tobe-Gai, Ruoyan, Toghroli, Razie, Tovani-Palone, Marcos Roberto, Ullah, Sana, Unnikrishnan, Bhaskaran, Upadhyay, Era, Tahbaz, Sahel Valadan, Valizadeh, Rohollah, Varthya, Shoban Babu, Waheed, Yasir, Wang, Song, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Xiao, Hong, Yonemoto, Naohiro, Younis, Mustafa Z., Yu, Chuanhua, Zahir, Mazyar, Zaki, Nazar, Zamanian, Maryam, Zhang, Zhi-Jiang, Zhao, Hanqing, Zitoun, Osama A., and Zoladl, Mohammad

Published
2024
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4. Indicators for maternal near miss: an observational study, India/ Indicateurs de deces maternels evites de justesse: etude d'observation en Inde/Indicadores de morbilidad materna extrema: un estudio observacional en la India

Author

Balachandran, Divya Mecheril, Karuppusamy, Dhamotharan, Maurya, Dilip Kumar, Kar, Sitanshu Sekhar, and Keepanasseril, Anish

Subjects
Pregnancy, Mothers -- Patient outcomes, Blood transfusion, Health
Abstract

Objective To compare the incidence of maternal near miss using the World Health Organization (WHO) near-miss tool and six other criteria sets, including criteria designed for low-resource settings or specifically for India. Methods In a cohort study we used WHO severity indicators to identify women with potentially life-threatening conditions during pregnancy or childbirth admitted to a referral hospital in Puducherry, India, from May 2018 to April 2021. We analysed sociodemographic, clinical and laboratory data for each woman and calculated the incidence of maternal near miss and other process indicators for each set of criteria. Findings We analysed data on 37 590 live births; 1833 (4.9%) women were identified with potentially life- threatening conditions, 380 women had severe maternal outcomes and 57 died. Applying the different sets of criteria to the same data, we found the incidence of maternal near miss ranged from 7.6 to 15.6 per 1000 live births. Only the Global Network criteria (which exclude laboratory data that may not be available in low-resource settings) and the WHO criteria could identify all women who died. Applying the criterion of any number of units of blood transfusion increased the overall number of women identified with near miss. Conclusion The WHO and Global Network criteria may be used to detect maternal near miss in low-resource settings. Future studies could assess the usefulness of blood transfusion as an indicator for maternal near miss, especially in low- to middle- income countries where the indicator may not reflect severe maternal morbidity if the number of units received is not specified. Objectif Etablir une comparaison de I'incidence des deces maternels evites de justesse en utilisant l'outil mis au point par l'Organisation mondiale de la Sante (OMS) ainsi que six autres ensembles de criteres, notamment ceux conpus pour les milieux a faibles ressources ou, plus specifiquement, pour l'Inde. Methodes Dans le cadre d'une etude de cohorte, nous avons applique les indicateurs de gravite de l'OMS afin d'identifier les femmes dont l'etat de sante pouvait s'averer potentiellement mortel durant la grossesse ou l'accouchement, admises dans un hopital de reference a Pondichery, en Inde, entre mai 2018 et avril 2021. Nous avons examine les donnees sociodemographiques, cliniques et de laboratoire relatives a chacune de ces femmes. Nous avons ensuite calcule l'incidence des deces maternels evites de justesse et d'autres indicateurs de processus pour chaque ensemble de criteres. Resultats Notre analyse portait sur 37 590 naissances vivantes; 1833 femmes (4,9%) ont ete considerees comme presentant des risques eleves, 380 femmes ont connu de graves problemes de sante, et 57 sont decedees. En etudiant les memes donnees a travers le prisme des dfferents ensembles de criteres, nous avons decouvert que l'incidence des deces maternels evites de justesse etait comprise entre 7,6 et 15,6 pour 1000 naissances vivantes. Seuls les criteres du Reseau mondial (qui ne reprend pas les donnees de laboratoire non disponibles dans les milieux a faibles ressources) et de l'OMS ont permis d'identifier toutes les femmes n'ayant pas survecu. Appliquer le critere tenant compte du nombre d'unites de sang transfuse, quel qu'il soit, a fait augmenter le nombre total de femmes considerees comme ayant echappe de justesse a un deces. Conclusion Les criteres de l'OMS et du Reseau mondial peuvent servir a detecter les deces maternels evites de justesse dans les milieux a faibles ressources. Les futures etudes sur le sujet pourraient evaluer l'utilite de la transfusion sanguine en tant qu'indicateur, en particulier dans les pays a revenu faible et intermediate ou cet indicateur pourrait ne pas refleter la morbidite maternelle grave si le nombre d'unites transfusees n'est pas precise. Objetivo Comparar la tasa de incidencia de la morbilidad materna extrema mediante la herramienta de morbilidad extrema de la Organizacion Mundial de la Salud (OMS) y otros seis conjuntos de criterios, incluidos los criterios elaborados para entornos de bajos recursos o especificos para la India. Metodos A traves de un estudio de cohortes, se utilizaron los indicadores de gravedad de la OMS para identificar a las mujeres con afecciones potencialmente mortales durante el embarazo o el parto ingresadas en un hospital de referencia en Puducherry, India, desde mayo de 2018 hasta abril de 2021. Se analizaron los datos sociodemograficos, clinicos y de laboratorio de cada mujer y se calculo la tasa de incidencia de la morbilidad materna extrema y otros indicadores de proceso para cada conjunto de criterios. Resultados Se analizaron los datos de 37 590 nacidos vivos; se identificaron 1833 (4,9 %) mujeres con afecciones potencialmente mortales, 380 mujeres presentaron desenlaces maternos graves y 57 murieron. Al aplicar los diferentes conjuntos de criterios a los mismos datos, se observo que la tasa de incidencia de la morbilidad materna extrema oscilaba entre 7,6 y 15,6 por cada 1000 nacidos vivos. Solo los criterios de la Red Mundial (que excluyen los datos de laboratorio que podrian no estar disponibles en entornos de bajos recursos) y los criterios de la OMS pudieron identificar a todas las mujeres que murieron. La aplicacion del criterio de cualquier numero de unidades de transfusion de sangre aumento el numero total de mujeres identificadas con morbilidad extrema. Conclusion Los criterios de la OMS y de la Red Mundial se podrian utilizar para detectar la morbilidad materna extrema en entornos de bajos recursos. En futuros estudios, se podria evaluar la utilidad de la transfusion de sangre como indicador para detectar la morbilidad materna extrema, en especial en los paises de ingresos bajos y medios, donde el indicador podria no reflejar la morbilidad materna grave si no se especifica el numero de unidades de transfusion recibidas., Introduction Maternal mortality refers to the 'death of a woman whilst pregnant or within 42 days of delivery or termination of pregnancy, from any cause related to, or aggravated by [...]

Published
2022
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6. Community health workers willingness to participate in COVID-19 vaccine trials and intention to vaccinate: A cross-sectional survey in India

Author

Goel, Kapil, Sen, Arunima, Goel, Parul, Satapathy, Prakasini, Jain, Lovely, Vij, Jatina, Patro, Binod Kumar, Kar, Sitanshu Sekhar, Chakrapani, Venkatesan, Singh, Ritesh, Pala, Star, Sankhe, Lalit, Modi, Bhavesh, Bali, Surya, Rustagi, Neeti, Nadda, Anuradha, Rajagopal, Vineeth, Kiran, Tanvi, Aggarwal, Arun Kumar, Gupta, Madhu, and Padhi, Bijaya Kumar

Published
2022
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8. Effectiveness of BBV152/Covaxin and AZD1222/Covishield vaccines against severe COVID-19 and B.1.617.2/Delta variant in India, 2021: a multi-centric hospital-based case-control study

Author

Bhatnagar, Tarun, Chaudhuri, Sirshendu, Ponnaiah, Manickam, Yadav, Pragya D, Sabarinathan, R, Sahay, Rima R, Ahmed, Faheem, Aswathy, S, Bhardwaj, Pankaj, Bilimale, Anil, Kumar, M Santhosh, Logaraj, M., Narlawar, Uday, Palanivel, C, Patel, Prakash, Rai, Sanjay K, Saxena, Vartika, Singh, Arvind, Thangaraj, Jeromie WV, Agarwal, Ashwini, Alvi, Yasir, Amoghashree, Ashok, P, Babu, Dinesh, Bahurupi, Yogesh, Bhalavi, Sangita, Behera, Priyamadhaba, Biswas, Priyanka Pandit, Charan, Jaykaran, Chauhan, Nishant Kumar, Chetak, KB, Dar, Lalit, Das, Ayan, Deepashree, R, Dhar, Minakshi, Dhodapkar, Rahul, Dipu, TS, Dudeja, Mridu, Dudhmal, Manisha, Gadepalli, Ravisekhar, Garg, Mahendra Kumar, Gayathri, AV, Goel, Akhil Dhanesh, Gowdappa, H Basavana, Guleria, Randeep, Gupta, Manoj Kumar, Islam, Farzana, Jain, Mannu, Jain, Vineet, Jawahar, M Lanord Stanley, Joshi, Rajendra, Kant, Shashi, Kar, Sitanshu Sekhar, Kalita, Deepjyoti, Khapre, Meenakshi, Khichar, Satyendra, Kombade, Sarika Prabhakar, Kohli, Sunil, Kumar, Abhinendra, Kumar, Anil, Kumar, Deepak, Kulirankal, Kiran G, Leela, KV, Majumdar, Triparna, Mishra, Baijayantimala, Misra, Puneet, Misra, Sanjeev, Mohapatra, Prasanta Raghab, Murthy, M Narayana, Nyayanit, Dimpal A, Patel, Manish, Pathania, Monika, Patil, Savita, Patro, Binod Kumar, Jalandra, Ramniwas, Rathod, Pragati, Shah, Naimesh, Shete, Anita, Shukla, Deepak, Shwethashree, M, Sinha, Smita, Sumana, MN, Surana, Ashish, Trikha, Anjan, Tejashree, A, Venkateshan, Mahalingam, Vijaykrishnan, G, Wadhava, Sarita, Wig, Naveet, Gupta, Nivedita, Abraham, Priya, and Murhekar, Manoj V

Published
2022
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11. Understanding Critical Thinking to Create Better Doctors

Author

Zayapragassarazan, Zayabalaradjane, Menon, Vikas, Kar, Sitanshu Sekhar, and Batmanabane, Gitanjali

Abstract

Medical students master an enormous body of knowledge, but lack systematic problem solving ability and effective clinical decision making. High profile reports have called for reforms in medical education to create a better generation of doctors who can cope with the system based problems they would encounter in an interdisciplinary and collaborative environment and make better reasoned decisions for quality patient care. To achieve this critical thinking is at the very heart of development of new medical knowledge. Critical thinking (CT) can be defined as the ability to identify and analyse problems as well as seek and evaluate relevant information in order to reach an appropriate conclusion. Medical academics and practitioners have raised concerns about the low levels of critical thinking and stress the need for fostering critical thinking among medical practitioners. This article attempts to provide a conceptual analysis of critical thinking with reference to medical education along with measures to foster critical thinking through relevant teaching learning and assessment methods.

Published
2016

15. Correlates of diabetes mellitus and hypertension in India: Change as evidenced from NFHS- 4 and 5 during 2015–2021.

Author

Rana, Rishabh Kumar, Jha, Ravi Ranjan, Sinha, Ratnesh, Kumar, Dewesh, Jaiswal, Richa, Patel, Urvish, Prasad, Jang Bahadur, Kar, Sitanshu Sekhar, and Goel, Sonu

Subjects
DIABETES, AGE groups, HYPERTENSION, LOGISTIC regression analysis, AGE factors in disease, TRENDS
Abstract

Both diabetes mellitus (DM) and hypertension (HTN) have been on the rise in recent decades all over the world more remarkably in developing countries like India. We intend to measure the prevalence of DM and HTN in the Indian population and to compare the trends and various correlates of these diseases in NFHS (National Family Health Survey)-4 and 5. Data of NFHS-4 and 5 were accessed from dhs program website. All statistical analyses were done in SAS (version 9.4). Mixed effects survey logistic regression models were used for estimating odds ratio (OR).p-values <0.05 were considered significant.1,637,762 individual case entries were evaluated. Both the diseases showed an increasing trend as per the advancing age in both sexes. The highest prevalence of DM is seen in the age group of 45–49 years (7.8%) in females and > 50 years (11.9%) in males as per NFHS-5. Similarly, the highest prevalence of HTN was seen in the age group of45–49 years (31.2%) in females and > 50 years (41.4%) in males as per NFHS-5. The OR (95% CI) of prevalence of DM, HTN and both the diseases in age group >50 years was 14.46 (13.14–15.7), 16.65 (15.78–17.6), 79.5 (64.76–97.73) respectively when compared to reference age group15-19 years. Highest odds for having both DM, HTN concurrently was in age >50 years with aOR(95% CI) 65.32 (52.26–72.63) in NFHS 4 and 35.57 (97.47–45.53) in NFHS 5.Rise in prevalence of DM, HTN and concurrent presence is noted with an apparent increase in cases. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Prevalence and Time Trend of SARS-CoV-2 Infection in Puducherry, India, August-October 2020

Author

Kar, Sitanshu Sekhar, Sarkar, Sonali, Murali, Sharan, Dhodapkar, Rahul, Joseph, Noyal Mariya, and Aggarwal, Rakesh

Subjects
Medical research, Medicine, Experimental, Time trends (Statistics) -- Methods, Prevalence studies (Epidemiology) -- Methods, Company distribution practices, Health
Abstract

The magnitude of the ongoing pandemic of coronavirus disease (COVID-19), caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has not been fully assessed because most those infected [...]

Published
2021
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20. Anti-SARS-CoV-2 antibody kinetics up to 6 months of follow-up: Result from a nation-wide population-based, age stratified sero-epidemiological prospective cohort study in India

Author

Misra, Puneet, primary, Singh, Arvind Kumar, additional, Mishra, Baijayantimala, additional, Behera, Bijayini, additional, Patro, Binod Kumar, additional, Medigeshi, Guruprasad R., additional, Joshi, Hari Shanker, additional, Ahmad, Mohammad, additional, Chaturvedi, Pradeep Kumar, additional, Chinnakali, Palanivel, additional, Haldar, Partha, additional, Bairwa, Mohan, additional, Kharya, Pradeep, additional, Dhodapkar, Rahul, additional, Rath, Ramashankar, additional, Guleria, Randeep, additional, Rai, Sanjay Kumar, additional, Kar, Sitanshu Sekhar, additional, Kant, Shashi, additional, Sarkar, Sonali, additional, Baidya, Subrata, additional, Meena, Suneeta, additional, Mandal, Suprakash, additional, Kishore, Surekha, additional, Majumder, Tapan, additional, and Hada, Vivek, additional

Published
2023
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21. Global Burden of Cardiovascular Diseases and Risks, 1990-2022

Author

Mensah, George A., primary, Fuster, Valentin, additional, Murray, Christopher J.L., additional, Roth, Gregory A., additional, Mensah, George A., additional, Abate, Yohannes Habtegiorgis, additional, Abbasian, Mohammadreza, additional, Abd-Allah, Foad, additional, Abdollahi, Ashkan, additional, Abdollahi, Mohammad, additional, Abdulah, Deldar Morad, additional, Abdullahi, Auwal, additional, Abebe, Ayele Mamo, additional, Abedi, Aidin, additional, Abedi, Armita, additional, Abiodun, Olugbenga Olusola, additional, Ali, Hiwa Abubaker, additional, Abu-Gharbieh, Eman, additional, Abu-Rmeileh, Niveen M.E., additional, Aburuz, Salahdein, additional, Abushouk, Abdelrahman I., additional, Abu-Zaid, Ahmed, additional, Adane, Tigist Demssew, additional, Adderley, Nicola J., additional, Adebayo, Oladimeji M., additional, Aden, Bashir, additional, Adeyeoluwa, Temitayo Esther, additional, Adeyomoye, Olorunsola Israel, additional, Sakilah Adnani, Qorinah Estiningtyas, additional, Afrashteh, Fatemeh, additional, Afyouni, Shadi, additional, Afzal, Saira, additional, Agasthi, Pradyumna, additional, Agodi, Antonella, additional, Aguilera Arriagada, Constanza Elizabeth, additional, Agyemang-Duah, Williams, additional, Ahinkorah, Bright Opoku, additional, Ahmad, Aqeel, additional, Ahmad, Danish, additional, Ahmad, Firdos, additional, Ahmad, Muayyad M., additional, Ahmed, Ayman, additional, Ahmed, Haroon, additional, Ahmed, Muktar Beshir, additional, Ahmed, Syed Anees, additional, Ajami, Marjan, additional, Akinosoglou, Karolina, additional, Ala, Moein, additional, Ali AL-Ahdal, Tareq Mohammed, additional, Alalalmeh, Samer O., additional, Al-Aly, Ziyad, additional, Alam, Nazmul, additional, Al-amer, Rasmieh Mustafa, additional, Alashi, Alaa, additional, Albashtawy, Mohammed, additional, AlBataineh, Mohammad T., additional, Alema, Haileselasie Berhane, additional, Alemi, Sharifullah, additional, Alemu, Yihun Mulugeta, additional, Saeed Al-Gheethi, Adel Ali, additional, Alhabib, Khalid F., additional, Naji Alhalaiqa, Fadwa Alhalaiqa, additional, Ali, Mohammed Usman, additional, Ali, Rafat, additional, pursuing, PhD., additional, Shujait Ali, Syed Shujait, additional, Alicandro, Gianfranco, additional, Alikhani, Reyhaneh, additional, Aljunid, Syed Mohamed, additional, Alla, François, additional, Almahmeed, Wael, additional, Al-Marwani, Sabah, additional, Alonso, Jordi, additional, Al-Raddadi, Rajaa M., additional, Alvi, Farrukh Jawad, additional, Alvis-Guzman, Nelson, additional, Alvis-Zakzuk, Nelson J., additional, Alwafi, Hassan, additional, Aly, Hany, additional, Amegbor, Prince M., additional, Amin, Tarek Tawfik, additional, Amindarolzarbi, Alireza, additional, Amini-Rarani, Mostafa, additional, Amiri, Sohrab, additional, Ammirati, Enrico, additional, Anand, Tanu, additional, Ancuceanu, Robert, additional, Anderlini, Deanna, additional, Anil, Abhishek, additional, Ansari, Golnoosh, additional, Anyanwu, Philip Emeka, additional, Anyasodor, Anayochukwu Edward, 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additional, Zeng, Youjie, additional, Zhai, Chunxia, additional, Zhang, Chen, additional, Zhang, Haijun, additional, Zhang, Hongwei, additional, Zhang, Liqun, additional, Zhang, Ning, additional, Zhang, Yunquan, additional, Zhao, Hanqing, additional, Zheng, Peng, additional, Zhong, Chenwen, additional, Zhou, Shuduo, additional, Zhu, Bin, additional, Zhu, Lei, additional, Zielińska, Magdalena, additional, Zikarg, Yossef Teshome, additional, Zmaili, Mohammad, additional, Zoeckler, Leo Zucker, additional, Zou, Zhiyong, additional, Zumla, Alimuddin, additional, Zweck, Elric, additional, and Zyoud, Samer H., additional

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2023
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32. Protocol for estimating the willingness-to-pay-based value for a quality-adjusted life year to aid health technology assessment in India: a cross-sectional study

Author

Chugh, Yashika, primary, Jyani, Gaurav, additional, Trivedi, Mayur, additional, Albert, Sandra, additional, Kar, Sitanshu Sekhar, additional, Patro, Binod, additional, Raman, Swati, additional, Rajsekar, Kavitha, additional, Baker, Rachel Mairi, additional, Donaldson, Cam, additional, and Prinja, Shankar, additional

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2023
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34. Trends in willingness to receive COVID-19 vaccines among healthcare workers in India: Findings from repeated cross-sectional national surveys

Author

Padhi, Bijaya Kumar, primary, Chakrapani, Venkatesan, additional, Gupta, Madhu, additional, Sharma, Nikita, additional, Patro, Binod Kumar, additional, Kar, Sitanshu Sekhar, additional, Singh, Ritesh, additional, Pala, Star, additional, Sankhe, Lalit, additional, Modi, Bhavesh, additional, Bali, Surya, additional, Rustagi, Neeti, additional, Jain, Lovely, additional, Vij, Jatina, additional, Satapathy, Prakasini, additional, Goel, Kapil, additional, Rajagopal, Vineeth, additional, Kiran, Tanvi, additional, and Aggarwal, Arun Kumar, additional

Published
2022
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35. a systematic analysis for the Global Burden of Disease Study 2019

Author

Tran, Khanh Bao, Lang, Justin J, Compton, Kelly, Xu, Rixing, Acheson, Alistair R, Henrikson, Hannah Jacqueline, Kocarnik, Jonathan M, Penberthy, Louise, Aali, Amirali, Abbas, Qamar, Abbasi, Behzad, Abbasi-kangevari, Mohsen, Abbasi-kangevari, Zeinab, Abbastabar, Hedayat, Abdelmasseh, Michael, Abd-elsalam, Sherief, Abdelwahab, Ahmed Abdelwahab, Abdoli, Gholamreza, Abdulkadir, Hanan Abdulkadir, Abedi, Aidin, Abegaz, Kedir Hussein, Abidi, Hassan, Aboagye, Richard Gyan, Abolhassani, Hassan, Absalan, Abdorrahim, Abtew, Yonas Derso, Abubaker Ali, Hiwa, Abu-gharbieh, Eman, Achappa, Basavaprabhu, Acuna, Juan Manuel, Addison, Daniel, Addo, Isaac Yeboah, Adegboye, Oyelola A, Adesina, Miracle Ayomikun, Adnan, Mohammad, Adnani, Qorinah Estiningtyas Sakilah, Advani, Shailesh M, Afrin, Sumia, Afzal, Muhammad Sohail, Aggarwal, Manik, Ahinkorah, Bright Opoku, Ahmad, Araz Ramazan, Ahmad, Rizwan, Ahmad, Sajjad, Ahmad, Sohail, Ahmadi, Sepideh, Ahmed, Haroon, Ahmed, Luai A, Ahmed, Muktar Beshir, Ahmed Rashid, Tarik, Aiman, Wajeeha, Ajami, Marjan, Akalu, Gizachew Taddesse, Akbarzadeh-khiavi, Mostafa, Aklilu, Addis, Akonde, Maxwell, Akunna, Chisom Joyqueenet, Al Hamad, Hanadi, Alahdab, Fares, Alanezi, Fahad Mashhour, Alanzi, Turki M, Alessy, Saleh Ali, Algammal, Abdelazeem M, Al-hanawi, Mohammed Khaled, Alhassan, Robert Kaba, Ali, Beriwan Abdulqadir, Ali, Liaqat, Ali, Syed Shujait, Alimohamadi, Yousef, Alipour, Vahid, Aljunid, Syed Mohamed, Alkhayyat, Motasem, Al-maweri, Sadeq Ali Ali, Almustanyir, Sami, Alonso, Nivaldo, Alqalyoobi, Shehabaldin, Al-raddadi, Rajaa M, Al-rifai, Rami H Hani, Al-sabah, Salman Khalifah, Al-tammemi, Ala'a B, Altawalah, Haya, Alvis-guzman, Nelson, Amare, Firehiwot, Ameyaw, Edward Kwabena, Aminian Dehkordi, Javad Javad, Amirzade-iranaq, Mohammad Hosein, Amu, Hubert, Amusa, Ganiyu Adeniyi, Ancuceanu, Robert, Anderson, Jason A, Animut, Yaregal Animut, Anoushiravani, Amir, Anoushirvani, Ali Arash, Ansari-moghaddam, Alireza, Ansha, Mustafa Geleto, Antony, Benny, Antwi, Maxwell Hubert, Anwar, Sumadi Lukman, Anwer, Razique, Anyasodor, Anayochukwu Edward, Arabloo, Jalal, Arab-zozani, Morteza, Aremu, Olatunde, Argaw, Ayele Mamo, Ariffin, Hany, Aripov, Timur, Arshad, Muhammad, Artaman, Al, Arulappan, Judie, Aruleba, Raphael Taiwo, Aryannejad, Armin, Asaad, Malke, Asemahagn, Mulusew A, Asemi, Zatollah, Asghari-jafarabadi, Mohammad, Ashraf, Tahira, Assadi, Reza, Athar, Mohammad, Athari, Seyyed Shamsadin, Atout, Maha Moh'd Wahbi, Attia, Sameh, Aujayeb, Avinash, Ausloos, Marcel, Avila-burgos, Leticia, Awedew, Atalel Fentahun, Awoke, Mamaru Ayenew, Awoke, Tewachew, Ayala Quintanilla, Beatriz Paulina, Ayana, Tegegn Mulatu, Ayen, Solomon Shitu, Azadi, Davood, Azadnajafabad, Sina, Azami-aghdash, Saber, Azanaw, Melkalem Mamuye, Azangou-khyavy, Mohammadreza, Azari Jafari, Amirhossein, Azizi, Hosein, Azzam, Ahmed Y Y, Babajani, Amirhesam, Badar, Muhammad, Badiye, Ashish D, Baghcheghi, Nayereh, Bagheri, Nader, Bagherieh, Sara, Bahadory, Saeed, Baig, Atif Amin, Baker, Jennifer L, Bakhtiari, Ahad, Bakshi, Ravleen Kaur, Banach, Maciej, Banerjee, Indrajit, Bardhan, Mainak, Barone-adesi, Francesco, Barra, Fabio, Barrow, Amadou, Bashir, Nasir Z, Bashiri, Azadeh, Basu, Saurav, Batiha, Abdul-monim Mohammad, Begum, Aeysha, Bekele, Alehegn Bekele, Belay, Alemayehu Sayih, Belete, Melaku Ashagrie, Belgaumi, Uzma Iqbal, Bell, Arielle Wilder, Belo, Luis, Benzian, Habib, Berhie, Alemshet Yirga, Bermudez, Amiel Nazer C, Bernabe, Eduardo, Bhagavathula, Akshaya Srikanth, Bhala, Neeraj, Bhandari, Bharti Bhandari, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhattacharyya, Krittika, Bhojaraja, Vijayalakshmi S, Bhuyan, Soumitra S, Bibi, Sadia, Bilchut, Awraris Hailu, Bintoro, Bagas Suryo, Biondi, Antonio, Birega, Mesfin Geremaw Birega, Birhan, Habitu Eshetu, Bjørge, Tone, Blyuss, Oleg, Bodicha, Belay Boda Abule, Bolla, Srinivasa Rao, Boloor, Archith, Bosetti, Cristina, Braithwaite, Dejana, Brauer, Michael, Brenner, Hermann, Briko, Andrey Nikolaevich, Briko, Nikolay Ivanovich, Buchanan, Christina Maree, Bulamu, Norma B, Bustamante-teixeira, Maria Teresa, Butt, Muhammad Hammad, Butt, Nadeem Shafique, Butt, Zahid A, Caetano Dos Santos, Florentino Luciano, Cámera, Luis Alberto, Cao, Chao, Cao, Yin, Carreras, Giulia, Carvalho, Márcia, Cembranel, Francieli, Cerin, Ester, Chakraborty, Promit Ananyo, Charalampous, Periklis, Chattu, Vijay Kumar, Chimed-ochir, Odgerel, Chirinos-caceres, Jesus Lorenzo, Cho, Daniel Youngwhan, Cho, William C S, Christopher, Devasahayam J, Chu, Dinh-toi, Chukwu, Isaac Sunday, Cohen, Aaron J, Conde, Joao, Cortés, Sandra, Costa, Vera Marisa, Cruz-martins, Natália, Culbreth, Garland T, Dadras, Omid, Dagnaw, Fentaw Teshome, Dahlawi, Saad M A, Dai, Xiaochen, Dandona, Lalit, Dandona, Rakhi, Daneshpajouhnejad, Parnaz, Danielewicz, Anna, Dao, An Thi Minh, Darvishi Cheshmeh Soltani, Reza, Darwesh, Aso Mohammad, Das, Saswati, Davitoiu, Dragos Virgil, Davtalab Esmaeili, Elham, De La Hoz, Fernando Pio, Debela, Sisay Abebe, Dehghan, Azizallah, Demisse, Biniyam, Demisse, Fitsum Wolde, Denova-gutiérrez, Edgar, Derakhshani, Afshin, Derbew Molla, Meseret, Dereje, Diriba, Deribe, Kalkidan Solomon, Desai, Rupak, Desalegn, Markos Desalegn, Dessalegn, Fikadu Nugusu, Dessalegni, Samuel Abebe A, Dessie, Gashaw, Desta, Abebaw Alemayehu, Dewan, Syed Masudur Rahman, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Dianatinasab, Mostafa, Diao, Nancy, Diaz, Daniel, Digesa, Lankamo Ena, Dixit, Shilpi Gupta, Doaei, Saeid, Doan, Linh Phuong, Doku, Paul Narh, Dongarwar, Deepa, Dos Santos, Wendel Mombaque, Driscoll, Tim Robert, Dsouza, Haneil Larson, Durojaiye, Oyewole Christopher, Edalati, Sareh, Eghbalian, Fatemeh, Ehsani-chimeh, Elham, Eini, Ebrahim, Ekholuenetale, Michael, Ekundayo, Temitope Cyrus, Ekwueme, Donatus U, El Tantawi, Maha, Elbahnasawy, Mostafa Ahmed, Elbarazi, Iffat, Elghazaly, Hesham, Elhadi, Muhammed, El-huneidi, Waseem, Emamian, Mohammad Hassan, Engelbert Bain, Luchuo, Enyew, Daniel Berhanie, Erkhembayar, Ryenchindorj, Eshetu, Tegegne, Eshrati, Babak, Eskandarieh, Sharareh, Espinosa-montero, Juan, Etaee, Farshid, Etemadimanesh, Azin, Eyayu, Tahir, Ezeonwumelu, Ifeanyi Jude, Ezzikouri, Sayeh, Fagbamigbe, Adeniyi Francis, Fahimi, Saman, Fakhradiyev, Ildar Ravisovich, Faraon, Emerito Jose A, Fares, Jawad, Farmany, Abbas, Farooque, Umar, Farrokhpour, Hossein, Fasanmi, Abidemi Omolara, Fatehizadeh, Ali, Fatima, Wafa, Fattahi, Hamed, Fekadu, Ginenus, Feleke, Berhanu Elfu, Ferrari, Allegra Allegra, Ferrero, Simone, Ferro Desideri, Lorenzo, Filip, Irina, Fischer, Florian, Foroumadi, Roham, Foroutan, Masoud, Fukumoto, Takeshi, Gaal, Peter Andras, Gad, Mohamed M, Gadanya, Muktar A, Gaipov, Abduzhappar, Galehdar, Nasrin, Gallus, Silvano, Garg, Tushar, Gaspar Fonseca, Mariana, Gebremariam, Yosef Haile, Gebremeskel, Teferi Gebru, Gebremichael, Mathewos Alemu, Geda, Yohannes Fikadu, Gela, Yibeltal Yismaw, Gemeda, Belete Negese Belete, Getachew, Melaku, Getachew, Motuma Erena, Ghaffari, Kazem, Ghafourifard, Mansour, Ghamari, Seyyed-hadi, Ghasemi Nour, Mohammad, Ghassemi, Fariba, Ghimire, Ajnish, Ghith, Nermin, Gholamalizadeh, Maryam, Gholizadeh Navashenaq, Jamshid, Ghozy, Sherief, Gilani, Syed Amir, Gill, Paramjit Singh, Ginindza, Themba G, Gizaw, Abraham Tamirat T, Glasbey, James C, Godos, Justyna, Goel, Amit, Golechha, Mahaveer, Goleij, Pouya, Golinelli, Davide, Golitaleb, Mohamad, Gorini, Giuseppe, Goulart, Bárbara Niegia Garcia, Grosso, Giuseppe, Guadie, Habtamu Alganeh, Gubari, Mohammed Ibrahim Mohialdeen, Gudayu, Temesgen Worku, Guerra, Maximiliano Ribeiro, Gunawardane, Damitha Asanga, Gupta, Bhawna, Gupta, Sapna, Gupta, Veer Bala, Gupta, Vivek Kumar, Gurara, Mekdes Kondale, Guta, Alemu, Habibzadeh, Parham, Haddadi Avval, Atlas, Hafezi-nejad, Nima, Hajj Ali, Adel, Haj-mirzaian, Arvin, Halboub, Esam S, Halimi, Aram, Halwani, Rabih, Hamadeh, Randah R, Hameed, Sajid, Hamidi, Samer, Hanif, Asif, Hariri, Sanam, Harlianto, Netanja I, Haro, Josep Maria, Hartono, Risky Kusuma, Hasaballah, Ahmed I, Hasan, S M Mahmudul, Hasani, Hamidreza, Hashemi, Seyedeh Melika, Hassan, Abbas M, Hassanipour, Soheil, Hayat, Khezar, Heidari, Golnaz, Heidari, Mohammad, Heidarymeybodi, Zahra, Herrera-serna, Brenda Yuliana, Herteliu, Claudiu, Hezam, Kamal, Hiraike, Yuta, Hlongwa, Mbuzeleni Mbuzeleni, Holla, Ramesh, Holm, Marianne, Horita, Nobuyuki, Hoseini, Mohammad, Hossain, Md Mahbub, Hossain, Mohammad Bellal Hossain, Hosseini, Mohammad-salar, Hosseinzadeh, Ali, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Househ, Mowafa, Huang, Junjie, Hugo, Fernando N, Humayun, Ayesha, Hussain, Salman, Hussein, Nawfal R, Hwang, Bing-fang, Ibitoye, Segun Emmanuel, Iftikhar, Pulwasha Maria, Ikuta, Kevin S, Ilesanmi, Olayinka Stephen, Ilic, Irena M, Ilic, Milena D, Immurana, Mustapha, Innos, Kaire, Iranpour, Pooya, Irham, Lalu Muhammad, Islam, Md Shariful, Islam, Rakibul M, Islami, Farhad, Ismail, Nahlah Elkudssiah, Isola, Gaetano, Iwagami, Masao, J, Linda Merin, Jaiswal, Abhishek, Jakovljevic, Mihajlo, Jalili, Mahsa, Jalilian, Shahram, Jamshidi, Elham, Jang, Sung-in, Jani, Chinmay T, Javaheri, Tahereh, Jayarajah, Umesh Umesh, Jayaram, Shubha, Jazayeri, Seyed Behzad, Jebai, Rime, Jemal, Bedru, Jeong, Wonjeong, Jha, Ravi Prakash, Jindal, Har Ashish, John-akinola, Yetunde O, Jonas, Jost B, Joo, Tamas, Joseph, Nitin, Joukar, Farahnaz, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kabir, Ali, Kacimi, Salah Eddine Oussama, Kadashetti, Vidya, Kahe, Farima, Kakodkar, Pradnya Vishal, Kalankesh, Laleh R, Kalankesh, Leila R, Kalhor, Rohollah, Kamal, Vineet Kumar, Kamangar, Farin, Kamath, Ashwin, Kanchan, Tanuj, Kandaswamy, Eswar, Kandel, Himal, Kang, Hyejung, Kanno, Girum Gebremeskel, Kapoor, Neeti, Kar, Sitanshu Sekhar, Karanth, Shama D, Karaye, Ibraheem M, Karch, André, Karimi, Amirali, Kassa, Bekalu Getnet, Katoto, Patrick Dmc, Kauppila, Joonas H, Kaur, Harkiran, Kebede, Abinet Gebremickael, Keikavoosi-arani, Leila, Kejela, Gemechu Gemechu, Kemp Bohan, Phillip M, Keramati, Maryam, Keykhaei, Mohammad, Khajuria, Himanshu, Khan, Abbas, Khan, Abdul Aziz Khan, Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Md Nuruzzaman, Khan, Moien Ab, Khanali, Javad, Khatab, Khaled, Khatatbeh, Moawiah Mohammad, Khatib, Mahalaqua Nazli, Khayamzadeh, Maryam, Khayat Kashani, Hamid Reza, Khazeei Tabari, Mohammad Amin, Khezeli, Mehdi, Khodadost, Mahmoud, Kim, Min Seo, Kim, Yun Jin, Kisa, Adnan, Kisa, Sezer, Klugar, Miloslav, Klugarová, Jitka, Kolahi, Ali-asghar, Kolkhir, Pavel, Kompani, Farzad, Koul, Parvaiz A, Koulmane Laxminarayana, Sindhura Lakshmi, Koyanagi, Ai, Krishan, Kewal, Krishnamoorthy, Yuvaraj, Kucuk Bicer, Burcu, Kugbey, Nuworza, Kulimbet, Mukhtar, Kumar, Akshay, Kumar, G Anil, Kumar, Narinder, Kurmi, Om P, Kuttikkattu, Ambily, La Vecchia, Carlo, Lahiri, Arista, Lal, Dharmesh Kumar, Lám, Judit, Lan, Qing, Landires, Iván, Larijani, Bagher, Lasrado, Savita, Lau, Jerrald, Lauriola, Paolo, Ledda, Caterina, Lee, Sang-woong, Lee, Shaun Wen Huey, Lee, Wei-chen, Lee, Yeong Yeh, Lee, Yo Han, Legesse, Samson Mideksa, Leigh, James, Leong, Elvynna, Li, Ming-chieh, Lim, Stephen S, Liu, Gang, Liu, Jue, Lo, Chun-han, Lohiya, Ayush, Lopukhov, Platon D, Lorenzovici, László, Lotfi, Mojgan, Loureiro, Joana A, Lunevicius, Raimundas, Madadizadeh, Farzan, Mafi, Ahmad R, Magdeldin, Sameh, Mahjoub, Soleiman, Mahmoodpoor, Ata, Mahmoudi, Morteza, Mahmoudimanesh, Marzieh, Mahumud, Rashidul Alam, Majeed, Azeem, Majidpoor, Jamal, Makki, Alaa, Makris, Konstantinos Christos, Malakan Rad, Elaheh, Malekpour, Mohammad-reza, Malekzadeh, Reza, Malik, Ahmad Azam, Mallhi, Tauqeer Hussain, Mallya, Sneha Deepak, Mamun, Mohammed A, Manda, Ana Laura, Mansour-ghanaei, Fariborz, Mansouri, Borhan, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Martini, Santi, Martorell, Miquel, Masoudi, Sahar, Masoumi, Seyedeh Zahra, Matei, Clara N, Mathews, Elezebeth, Mathur, Manu Raj, Mathur, Vasundhara, Mckee, Martin, Meena, Jitendra Kumar, Mehmood, Khalid, Mehrabi Nasab, Entezar, Mehrotra, Ravi, Melese, Addisu, Mendoza, Walter, Menezes, Ritesh G, Mengesha, Sisay Derso, Mensah, Laverne G, Mentis, Alexios-fotios A, Mera-mamián, Andry Yasmid Mera, Meretoja, Tuomo J, Merid, Mehari Woldemariam, Mersha, Amanual Getnet, Meselu, Belsity Temesgen, Meshkat, Mahboobeh, Mestrovic, Tomislav, Miao Jonasson, Junmei, Miazgowski, Tomasz, Michalek, Irmina Maria, Mijena, Gelana Fekadu Worku, Miller, Ted R, Mir, Shabir Ahmad, Mirinezhad, Seyed Kazem, Mirmoeeni, Seyyedmohammadsadeq, Mirza-aghazadeh-attari, Mohammad, Mirzaei, Hamed, Mirzaei, Hamid Reza, Misganaw, Abay Sisay, Misra, Sanjeev, Mohammad, Karzan Abdulmuhsin, Mohammadi, Esmaeil, Mohammadi, Mokhtar, Mohammadian-hafshejani, Abdollah, Mohammadpourhodki, Reza, Mohammed, Arif, Mohammed, Shafiu, Mohan, Syam, Mohseni, Mohammad, Moka, Nagabhishek, Mokdad, Ali H, Molassiotis, Alex, Molokhia, Mariam, Momenzadeh, Kaveh, Momtazmanesh, Sara, Monasta, Lorenzo, Mons, Ute, Montasir, Ahmed Al, Montazeri, Fateme, Montero, Arnulfo, Moosavi, Mohammad Amin, Moradi, Abdolvahab, Moradi, Yousef, Moradi Sarabi, Mostafa, Moraga, Paula, Morawska, Lidia, Morrison, Shane Douglas, Morze, Jakub, Mosapour, Abbas, Mostafavi, Ebrahim, Mousavi, Seyyed Meysam, Mousavi Isfahani, Haleh, Mousavi Khaneghah, Amin, Mpundu-kaambwa, Christine, Mubarik, Sumaira, Mulita, Francesk, Munblit, Daniel, Munro, Sandra B, Murillo-zamora, Efrén, Musa, Jonah, Nabhan, Ashraf F, Nagarajan, Ahamarshan Jayaraman, Nagaraju, Shankar Prasad, Nagel, Gabriele, Naghipour, Mohammadreza, Naimzada, Mukhammad David, Nair, Tapas Sadasivan, Naqvi, Atta Abbas, Narasimha Swamy, Sreenivas, Narayana, Aparna Ichalangod, Nassereldine, Hasan, Natto, Zuhair S, Nayak, Biswa Prakash, Ndejjo, Rawlance, Nduaguba, Sabina Onyinye, Negash, Wogene Wogene, Nejadghaderi, Seyed Aria, Nejati, Kazem, Neupane Kandel, Sandhya, Nguyen, Huy Van Nguyen, Niazi, Robina Khan, Noor, Nurulamin M, Noori, Maryam, Noroozi, Nafise, Nouraei, Hasti, Nowroozi, Ali, Nuñez-samudio, Virginia, Nzoputam, Chimezie Igwegbe, Nzoputam, Ogochukwu Janet, Oancea, Bogdan, Odukoya, Oluwakemi Ololade, Oghenetega, Onome Bright, Ogunsakin, Ropo Ebenezer, Oguntade, Ayodipupo Sikiru, Oh, In-hwan, Okati-aliabad, Hassan, Okekunle, Akinkunmi Paul, Olagunju, Andrew T, Olagunju, Tinuke O, Olakunde, Babayemi Oluwaseun, Olufadewa, Isaac Iyinoluwa, Omer, Emad, Omonisi, Abidemi E Emmanuel, Ong, Sokking, Onwujekwe, Obinna E, Orru, Hans, Otstavnov, Stanislav S, Oulhaj, Abderrahim, Oumer, Bilcha, Owopetu, Oluwatomi Funbi, Oyinloye, Babatunji Emmanuel, P A, Mahesh, Padron-monedero, Alicia, Padubidri, Jagadish Rao, Pakbin, Babak, Pakshir, Keyvan, Pakzad, Reza, Palicz, Tamás, Pana, Adrian, Pandey, Anamika, Pandey, Ashok, Pant, Suman, Pardhan, Shahina, Park, Eun-cheol, Park, Eun-kee, Park, Seoyeon, Patel, Jay, Pati, Siddhartha, Paudel, Rajan, Paudel, Uttam, Paun, Mihaela, Pazoki Toroudi, Hamidreza, Peng, Minjin, Pereira, Jeevan, Pereira, Renato B, Perna, Simone, Perumalsamy, Navaraj, Pestell, Richard G, Pezzani, Raffaele, Piccinelli, Cristiano, Pillay, Julian David, Piracha, Zahra Zahid, Pischon, Tobias, Postma, Maarten J, Pourabhari Langroudi, Ashkan, Pourshams, Akram, Pourtaheri, Naeimeh, Prashant, Akila, Qadir, Mirza Muhammad Fahd, Quazi Syed, Zahiruddin, Rabiee, Mohammad, Rabiee, Navid, Radfar, Amir, Radhakrishnan, Raghu Anekal, Radhakrishnan, Venkatraman, Raeisi, Mojtaba, Rafiee, Ata, Rafiei, Alireza, Raheem, Nasiru, Rahim, Fakher, Rahman, Md Obaidur, Rahman, Mosiur, Rahman, Muhammad Aziz, Rahmani, Amir Masoud, Rahmani, Shayan, Rahmanian, Vahid, Rajai, Nazanin, Rajesh, Aashish, Ram, Pradhum, Ramezanzadeh, Kiana, Rana, Juwel, Ranabhat, Kamal, Ranasinghe, Priyanga, Rao, Chythra R, Rao, Sowmya J, Rashedi, Sina, Rashidi, Amirfarzan, Rashidi, Mahsa, Rashidi, Mohammad-mahdi, Ratan, Zubair Ahmed, Rawaf, David Laith, Rawaf, Salman, Rawal, Lal, Rawassizadeh, Reza, Razeghinia, Mohammad Sadegh, Rehman, Ashfaq Ur, Rehman, Inayat Ur, Reitsma, Marissa B, Renzaho, Andre M N, Rezaei, Maryam, Rezaei, Nazila, Rezaei, Negar, Rezaei, Nima, Rezaei, Saeid, Rezaeian, Mohsen, Rezapour, Aziz, Riad, Abanoub, Rikhtegar, Reza, Rios-blancas, Maria, Roberts, Thomas J, Rohloff, Peter, Romero-rodríguez, Esperanza, Roshandel, Gholamreza, Rwegerera, Godfrey M, S, Manjula, Saber-ayad, Maha Mohamed, Saberzadeh-ardestani, Bahar, Sabour, Siamak, Saddik, Basema, Sadeghi, Erfan, Saeb, Mohammad Reza, Saeed, Umar, Safaei, Mohsen, Safary, Azam, Sahebazzamani, Maryam, Sahebkar, Amirhossein, Sahoo, Harihar, Sajid, Mirza Rizwan, Salari, Hedayat, Salehi, Sana, Salem, Marwa Rashad, Salimzadeh, Hamideh, Samodra, Yoseph Leonardo, Samy, Abdallah M, Sanabria, Juan, Sankararaman, Senthilkumar, Sanmarchi, Francesco, Santric-milicevic, Milena M, Saqib, Muhammad Arif Nadeem, Sarveazad, Arash, Sarvi, Fatemeh, Sathian, Brijesh, Satpathy, Maheswar, Sayegh, Nicolas, Schneider, Ione Jayce Ceola, Schwarzinger, Michaël, Šekerija, Mario, Senthilkumaran, Subramanian, Sepanlou, Sadaf G, Seylani, Allen, Seyoum, Kenbon, Sha, Feng, Shafaat, Omid, Shah, Pritik A, Shahabi, Saeed, Shahid, Izza, Shahrbaf, Mohammad Amin, Shahsavari, Hamid R, Shaikh, Masood Ali, Shaka, Mohammed Feyisso, Shaker, Elaheh, Shannawaz, Mohammed, Sharew, Mequannent Melaku Sharew, Sharifi, Azam, Sharifi-rad, Javad, Sharma, Purva, Shashamo, Bereket Beyene, Sheikh, Aziz, Sheikh, Mahdi, Sheikhbahaei, Sara, Sheikhi, Rahim Ali, Sheikhy, Ali, Shepherd, Peter Robin, Shetty, Adithi, Shetty, Jeevan K, Shetty, Ranjitha S, Shibuya, Kenji, Shirkoohi, Reza, Shirzad-aski, Hesamaddin, Shivakumar, K M, Shivalli, Siddharudha, Shivarov, Velizar, Shobeiri, Parnian, Shokri Varniab, Zahra, Shorofi, Seyed Afshin, Shrestha, Sunil, Sibhat, Migbar Mekonnen, Siddappa Malleshappa, Sudeep K, Sidemo, Negussie Boti, Silva, Diego Augusto Santos, Silva, Luís Manuel Lopes Rodrigues, Silva Julian, Guilherme, Silvestris, Nicola, Simegn, Wudneh, Singh, Achintya Dinesh, Singh, Ambrish, Singh, Garima, Singh, Harpreet, Singh, Jasvinder A, Singh, Jitendra Kumar, Singh, Paramdeep, Singh, 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Ticoalu, Jansje Henny Vera, Tiyuri, Amir, Tollosa, Daniel Nigusse, Topor-madry, Roman, Touvier, Mathilde, Tovani-palone, Marcos Roberto, Traini, Eugenio, Tran, Mai Thi Ngoc, Tripathy, Jaya Prasad, Ukke, Gebresilasea Gendisha, Ullah, Irfan, Ullah, Saif, Ullah, Sana, Unnikrishnan, Bhaskaran, Vacante, Marco, Vaezi, Maryam, Valadan Tahbaz, Sahel, Valdez, Pascual R, Vardavas, Constantine, Varthya, Shoban Babu, Vaziri, Siavash, Velazquez, Diana Zuleika, Veroux, Massimiliano, Villeneuve, Paul J, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vo, Bay, Vu, Linh Gia, Wadood, Abdul Wadood, Waheed, Yasir, Walde, Mandaras Tariku, Wamai, Richard G, Wang, Cong, Wang, Fang, Wang, Ning, Wang, Yu, Ward, Paul, Waris, Abdul, Westerman, Ronny, Wickramasinghe, Nuwan Darshana, Woldemariam, Melat, Woldu, Berhanu, Xiao, Hong, Xu, Suowen, Xu, Xiaoyue, Yadav, Lalit, Yahyazadeh Jabbari, Seyed Hossein, Yang, Lin, Yazdanpanah, Fereshteh, Yeshaw, Yigizie, Yismaw, Yazachew, Yonemoto, Naohiro, Younis, Mustafa Z, Yousefi, Zabihollah, Yousefian, Fatemeh, Yu, Chuanhua, Yu, Yong, Yunusa, Ismaeel, Zahir, Mazyar, Zaki, Nazar, Zaman, Burhan Abdullah, Zangiabadian, Moein, Zare, Fariba, Zare, Iman, Zareshahrabadi, Zahra, Zarrintan, Armin, Zastrozhin, Mikhail Sergeevich, Zeineddine, Mohammad A, Zhang, Dongyu, Zhang, Jianrong, Zhang, Yunquan, Zhang, Zhi-jiang, Zhou, Linghui, Zodpey, Sanjay, Zoladl, Mohammad, Vos, Theo, Hay, Simon I, Force, Lisa M, Murray, Christopher J L, NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM), and DCM - Departamento de Ciência dos Materiais

Subjects
SDG 3 - Good Health and Well-being
Abstract

Funding: J A Loureiro reports support for the present manuscript from Scientific Employment Stimulus (FCT; CEECINST/00049/2018) as support to their salary and from UIDB/00511/2020 of the LEPABE, funded by national funds through the FCT/MCTES (PIDDAC) as research support. 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. FUNDING: Bill & Melinda Gates Foundation. publishersversion published

Published
2022

37. What is the out-of-pocket expenditure on medicines in India? An empirical assessment using a novel methodology

Author

Prinja, Shankar, primary, Kumar, Sumit, additional, Sharma, Atul, additional, Kar, Sitanshu Sekhar, additional, Tripathi, Narayan, additional, Dumka, Neha, additional, Sharma, Sandeep, additional, Mukhopadhyay, Indranil, additional, Rana, Saroj Kumar, additional, Garg, Samir, additional, Kotwal, Atul, additional, and Aggarwal, Arun Kumar, additional

Published
2022
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39. Sociodemographic Determinants of Willingness and Extent to Pay for COVID-19 Vaccine in India

Author

Kiran, Tanvi, primary, Junaid, K. P., additional, Sharma, Divya, additional, Jain, Lovely, additional, Vij, Jatina, additional, Satapathy, Prakasini, additional, Chakrapani, Venkatesan, additional, Patro, Binod Kumar, additional, Kar, Sitanshu Sekhar, additional, Singh, Ritesh, additional, Pala, Star, additional, Bali, Surya, additional, Rustagi, Neeti, additional, Goel, Kapil, additional, Sankhe, Lalit, additional, Modi, Bhavesh, additional, Gupta, Madhu, additional, Aggarwal, Arun Kumar, additional, Rajagopal, Vineeth, additional, and Padhi, Bijaya Kumar, additional

Published
2022
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41. High prevalence of abdominal obesities and metabolically unhealthy individuals in a highly urbanized district of India: findings of a cross-sectional survey in Puducherry.

Author

Sivanantham, Parthibane, Sahoo, Jaya Prakash, Lakshminarayanan, Subitha, Bobby, Zachariah, and Kar, Sitanshu Sekhar

Subjects
ABDOMINAL adipose tissue, BODY mass index, CITY dwellers, INDIANS (Asians), WAIST circumference
Abstract

Background Abdominal obesities are better markers for predicting cardiovascular abnormalities than risk stratification based only on body mass index (BMI). We aimed to estimate the prevalence of abdominal adiposities using predictive equations for Asian Indian adults and to determine the prevalence of metabolically healthy subjects among those overweight/obese and with normal BMI. Methods A community-based survey was conducted among those aged 18–69 years in the district of Puducherry between February 2019 and February 2020. We surveyed 2,560 individuals selected through multi-stage cluster random sampling from urban and rural areas (50 wards and 50 villages, respectively) of the district. Anthropometric measurements, such as height, weight, waist circumference, and blood pressure were recorded from each participant. Fasting blood sample was collected from each alternate participant to estimate metabolic risk factors. Results Over four-fifths (85.6%; 95% CI: 84.2–86.9) and two-thirds (69.7%; 95% CI: 67.9–71.6) of the population in the district had high levels of intra-abdominal adipose tissue (IAAT) and total abdominal fat (TAF), respectively. Both the risk factors were significantly higher among women and urban population. About 43% (95% CI: 41–44.9) of the population had high abdominal subcutaneous adipose tissue (SCAT) with a significantly higher prevalence among the urban population. Among those overweight/obese (n  = 773), almost all 99.4% (95% CI: 98.7–99.9) were metabolically unhealthy. Among subjects with normal BMI (n  = 314), only about 2.9% (95% CI: 1.3–4.8) were metabolically healthy. Conclusion We highlight the substantially high prevalence of IAAT, TAF, and SCAT in the district of Puducherry. Almost all the study population was metabolically unhealthy irrespective of their BMI levels. [ABSTRACT FROM AUTHOR]

Published
2023
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42. Parents' Perceptions and Intention to Vaccinate Their Children Against COVID-19: Results From a Cross-Sectional National Survey in India

Author

Padhi, Bijaya Kumar, primary, Satapathy, Prakasini, additional, Rajagopal, Vineeth, additional, Rustagi, Neeti, additional, Vij, Jatina, additional, Jain, Lovely, additional, Chakrapani, Venkatesan, additional, Patro, Binod Kumar, additional, Kar, Sitanshu Sekhar, additional, Singh, Ritesh, additional, Pala, Star, additional, Sankhe, Lalit, additional, Modi, Bhavesh, additional, Bali, Surya, additional, Kiran, Tanvi, additional, Goel, Kapil, additional, Aggarwal, Arun Kumar, additional, and Gupta, Madhu, additional

Published
2022
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44. Factors Influencing COVID-19 Vaccination Intentions Among College Students: A Cross-Sectional Study in India

Author

Jain, Lovely, primary, Vij, Jatina, additional, Satapathy, Prakasini, additional, Chakrapani, Venkatesan, additional, Patro, Binod, additional, Kar, Sitanshu Sekhar, additional, Singh, Ritesh, additional, Pala, Star, additional, Sankhe, Lalit, additional, Modi, Bhavesh, additional, Bali, Surya, additional, Rustagi, Neeti, additional, Rajagopal, Vineeth, additional, Kiran, Tanvi, additional, Goel, Kapil, additional, Aggarwal, Arun Kumar, additional, Gupta, Madhu, additional, and Padhi, Bijaya Kumar, additional

Published
2021
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49. Additional file 2 of Evidence on article 5.3 of FCTC (tobacco industry interference in tobacco control activities) in India- a qualitative scoping study

Author

Goel, Sonu, Kar, Sitanshu Sekhar, Verma, Madhur, Sivanantham, Parthibane, Naik, Bijay Nanda, and Gupta, Deepti

Subjects
InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, Data_FILES
Abstract

Additional file 2. Supplementary File 2: Ranking Sheet: Perception of study participants regarding Tobacco Industry using ‘Power Ranking Methodology’.

Published
2021
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50. Additional file 3 of Evidence on article 5.3 of FCTC (tobacco industry interference in tobacco control activities) in India- a qualitative scoping study

Author

Goel, Sonu, Kar, Sitanshu Sekhar, Verma, Madhur, Sivanantham, Parthibane, Naik, Bijay Nanda, and Gupta, Deepti

Abstract

Additional file 3. Supplementary File 3: Questionnaire: Perception of study participants regarding involvement of “Tobacco industry role players” in various identified themes. Instruction: Prioritize (1 to 17) the role players of tobacco industry under each theme of industry’s interferences. Rank the role players from 1 to 17 such that 1 represents least involvement and 17 correspond to most involvement under a particular theme of TII.

Published
2021
Full Text
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