Emily Johnson

Scopus Publications

Lasting Income Costs of Mental and Physical Illness
Emily K. Johnson, Harsh Parikh, Catherine K. Ettman, Ge Ge, Liza Sopina, Angela Y. Chang
JAMA Health Forum, 2026
Importance Income losses following a hospital diagnosis can dampen career trajectories, slow social mobility, and worsen health states. Few cost-of-illness studies examine individual income loss across diseases, life stages, and socioeconomic characteristics. Objective To estimate long-term personal income losses following hospital diagnosis for selected mental and physical disorders. Design, Setting, and Participants This observational population-based matched cohort study used prospectively collected Danish register data. All nonretired Danish residents aged 18 to 65 years from 2000 to 2018 were eligible for inclusion. Exposed individuals were matched to controls by year, age, sex, marital status, household size, immigration status, baseline personal income, education level, labor market attachment, and hospitalization and comorbidity history. Data were analyzed from January 2025 to January 2026. Exposure Incident hospital diagnosis of depression, alcohol use disorder (AUD), stroke, or breast cancer. Hospital contacts for identification included inpatient and outpatient encounters at general and psychiatric treatment facilities. Main Outcomes and Measures The outcome of interest was personal disposable income for 10 years after inclusion. The difference between the average exposed and control incomes was measured, and standardized losses were estimated to compare across disease populations. Results Among 4 925 341 Danish residents included, there were 125 769 individuals with hospital diagnoses of depression, 77 206 with AUD, 82 151 with stroke, and 36 868 with breast cancer who were successfully matched to controls. In the third year after hospital diagnosis, income losses for male individuals were 11.8% (95% CI, 11.6%-12.0%) of control income in the same year for depression, 8.3% (95% CI, 8.1%-8.5%) for AUD, and 3.2% (95% CI, 3.0%-3.4%) for stroke. Losses for female individuals in the same year were 7.3% (95% CI, 7.2%-7.5%) of control income for depression, 5.5% (95% CI, 5.3%-5.7%) for AUD, 1.2% (95% CI, 1.1%-1.4%) for stroke, and 0.7% (95% CI, 0.5%-0.9%) for breast cancer. In the 10th year after exposure, losses totaled 13.7% (95% CI, 13.4%-14.0%), 10.4% (95% CI, 10.1%-10.7%), and 4.3% (95% CI, 4.0%-4.6%) for male individuals and 10.2% (95% CI, 10.0%-10.4%), 6.7% (95% CI, 6.4%-7.0%), 2.4% (95% CI, 2.1%-2.6%), and 0.6% (95% CI, 0.3%-0.9%) for female individuals for depression, AUD, stroke, and breast cancer, respectively. Income losses for those with mental disorders started in the 2 years preceding hospital diagnosis. Differences in loss magnitude between individuals with mental and physical conditions were not explained by differential disease risk. Income losses were greatest among those 30 to 50 years old but grew disproportionately for younger individuals and for those outside of the labor market. Some subgroups, including male individuals 25 to 29 years old with depression and female individuals with AUD receiving welfare benefits, were particularly vulnerable, with losses 5 years after diagnosis of 19.6% (95% CI, 18.9%-20.4%) and 6.1% (95% CI, 5.6%-6.6%), respectively. Conclusions and Relevance In this cohort study, income loss after disease diagnosis appeared to shape long-term income trajectories. Increased attention on the younger population and those outside of the workforce is warranted.
Exploring State-Level Change in Health Care Value Over Three Decades in the United States, 1991–2020
Haley Lescinsky, Maitreyi Sahu, Meera Beauchamp, Sawyer Crosby, Emily Johnson, Theresa A. McHugh, John W. Scott, Kevin Schulman, Azalea Thomson, Maxwell Weil, Joseph L. Dieleman, Arnold Milstein
Health Services Research, 2026
ObjectiveTo examine trends in state‐level health care value over three decades, defined using statewide health care spending and cause‐specific mortality, and to explore its associations with potentially modifiable state attributes.Study Setting and DesignWe use stochastic frontier analysis to identify the “inefficiency” of each state's delivery system in converting health care spending into lower mortality–incidence or mortality–prevalence rates, adjusting for underlying population risk (age, smoking, obesity, etc.). We combine these inefficiency scores to score and compare delivery system value for each state and track change over three decades. Then, we use linear regression to look across states and identify state‐level attributes significantly associated with greater health care value.Data Sources and Analytic SampleFor each US state and year from 1991 to 2020, we extracted mortality–incidence or mortality–prevalence rates for 67 high‐mortality health conditions from the Global Burden of Disease 2021 Study and state health care spending from the State Health Expenditure Accounts.Principal FindingsAcross US states, value on average increased from 1991 to 2000, remained relatively constant from 2001 to 2010, and then declined from 2011 to 2020 by 16.7% (95% uncertainty interval [UI]: 14.7–20.1) or 13.6 (95% UI: 11.3–15.9) value points. The percentage of state populations with insurance was positively associated with health delivery system value. In contrast, market consolidation among hospitals and among health insurers of small and large groups, and increased for‐profit hospital ownership were each associated with a lower health care value. The net effect of these associations was a reduction in the national value score for the decade ending in 2020.ConclusionsIn contrast to the prior two decades, health care delivery system value scores declined over the last decade. This decline was associated with reduced competition among hospitals and health insurers, increased for‐profit hospital ownership, and was partly mitigated by wider insurance coverage.
Comparing the predictive performance of diabetes complications using administrative health data and clinical data
Anders Aagaard, Richard Röttger, Emily K. Johnson, Kim Rose Olsen
Scientific Reports, 2025
When predicting adverse complications due to Type 2 Diabetes, often two different approaches are taken: predictions based on clinical data or those using administrative health data. No studies have assessed whether these two approaches reach comparable predictions. This study compares the predictive performance of these two data sources and examines the algorithmic fairness of the developed models. We developed XGBoost models to predict the two-year risk of nephropathy, tissue infection, and cardiovascular events in Type 2 Diabetes patients. The models using only clinical data achieved an average AUC of 0.78, while the models using administrative health data alone achieved 0.77. A hybrid model combining both data types resulted in an average AUC of 0.80, across complications. The models showed that laboratory data were key for predicting nephropathy, whereas comorbidity and diabetes age were most important for tissue infection. For cardiovascular events, age and a history of congestive heart failure was the most important predictors. Our analysis identified bias on the feature sex in all three outcomes: models tended to underestimate risk for females and overestimate it for males, indicating a need to address fairness in these applications. This study demonstrates the effectiveness of ML models using both data types for predicting diabetes complications. However, the presence of sex bias highlights the importance of improving model fairness for reliable clinical use.
Breast cancer and income loss in Denmark: heterogeneous outcomes and longitudinal effects
Emily K. Johnson, Harsh Parikh, Kim Rose Olsen, Angela Y. Chang, Liza Sopina
Nature Communications, 2025
Income loss after breast cancer is an important area of research, but long-term impacts and heterogeneous effects are understudied. Here, we measure the effect of breast cancer on personal and household equivalized income of females in Denmark from 2000-2018 using Danish register data. We perform a cohort study and match on age, income, employment, comorbidities, healthcare utilization, and other socioeconomic and demographic variables at cohort entry, to investigate impacts across subpopulations over 10 years. We also perform an event study difference-in-difference analysis over the same period. Our study finds personal income loss averaging €7138 over 10 years in the non-retired population. The working population, students, and those in worse health suffer disproportionate loss. Household income losses are smaller and recover within 10 years. Overall, the Danish economic protections are effective in mitigating long-term economic impact of breast cancer, though there is room for improvement in protection of the most vulnerable. Breast cancer has been associated with long term negative personal and household level economical impact in survivors. Here the authors find that while financial losses exist across the population, they are mitigated by robust social safety nets however, certain subgroups including students and individuals with poor baseline health, experience a disproportionate economic burden that persists long after diagnosis.
From sex differences to sex inequalities in life expectancy: A cross-country observational benchmarking analysis
Angela Y. Chang, Emily K. Johnson, Sarah Bolongaita, Kent Buse, Sarah J. Hawkes, Omar Karlsson, Felicia M. Knaul, Margaret E. Kruk, Ole F. Norheim, Osondu Ogbuoji, David Watkins, Dean T. Jamison
Plos Medicine, 2025
Background The answer to whether females or males have better health, and which sex is the more disadvantaged, has depended in part on the metric and how the inequality is measured. This study introduces a new method for analyzing and interpreting sex inequalities in health outcomes—defined as the avoidable sex differences in health outcomes—that is systematic and potentially more objective. For this paper, we focus on life expectancy at different ages. Methods and findings We introduce the adjusted sex ratio as a measure of sex inequalities and determining sex disadvantage. First, we calculated the sex ratio of life expectancy at ages 0, 5, 15, 35, 50, and 70. To understand what is achievable under favorable conditions, we identified countries in the 5th percentile of the highest life expectancy for each sex and used these values as benchmarks, and calculated the sex ratio of these best-performing countries (“frontier”). We calculated the country- and age-specific adjusted sex ratio by dividing country sex ratios by frontier sex ratios. This assumes that theoretically, under the current risk and healthcare environments, females all over the world have the potential to live up to the life expectancy of the females in the frontier countries, and separately, all males to their male-specific frontier. An adjusted ratio of greater than one indicates male disadvantage, while below one indicates female disadvantage. To avoid overinterpreting small differences, we defined a narrow range around equality (ratio of 1) within which we do not label either sex as disadvantaged. Before adjustment, males in all countries (except two) and at all ages had lower life expectancy than females. After adjustment, between 13% (at age 0) and 33% (at age 70) of the 237 countries shift from male to female disadvantage in life expectancy. More than half of the countries remain male-disadvantaged, indicating that males are generally disadvantaged in terms of life expectancy in most countries, even after our adjustments. India and approximately half of the countries in the Middle East and North Africa, North Atlantic, sub-Saharan Africa, and Western Pacific and Southeast Asia show female disadvantage. The number of countries with female disadvantage rises with age, especially in sub-Saharan Africa and Western Pacific and Southeastern Asia. Central and Eastern Europe show substantial male disadvantage across nearly all ages, even with adjustment. Our frontier selection and buffer range are empirical choices, and other definitions could be equally valid. Although our sex-specific benchmarks use the best-performing countries for each sex, they are not meant to represent purely biological differences, as observed sex gaps in life expectancy may also reflect unmeasured genetic variation, environmental exposures, and their interactions with sex. Conclusion This study provides a novel, potentially more objective method for assessing sex inequalities in health outcomes, and presents the trends across countries, age, and time.
Burden of 375 diseases and injuries, risk-attributable burden of 88 risk factors, and healthy life expectancy in 204 countries and territories, including 660 subnational locations, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023
Simon I Hay, Kanyin Liane Ong, Damian F Santomauro, Bhoomadevi A, Mohammad Amin Aalipour, Hasan Aalruz, Hazim S Ababneh, Ukachukwu O Abaraogu, Biruk Beletew Abate, Cristiana Abbafati, Nasir Abbas, Mitra Abbasifard, Mohsen Abbasi-Kangevari, Samar Abd ElHafeez, Ashraf Nabiel Abdalla, Mohammed Altigani Abdalla, Emad M Abdallah, Barkhad Aden Abdeeq, Nadin M I Abdel Razeq, Ahmed Abdelrahman Abdelgalil, Reda Abdel-Hameed, Michael Abdelmasseh, Mahmoud Abdelnabi, Wael M Abdel-Rahman, Sherief Abd-Elsalam, Sepideh Abdi, Mohammad Abdollahi, Meriem Abdoun, Arman Abdous, Jeza Muhamad Abdul Aziz, Deldar Morad Abdulah, Rizwan Suliankatchi Abdulkader, Adam Abdullahi, Auwal Abdullahi, Toufik Abdul-Rahman, Kulmira Abdykerimova, Habtamu Abebe Getahun, Aidin Abedi, Armita Abedi, Asrat Agalu Abejew, Roberto Ariel Abeldaño Zuñiga, E S Abhilash, Shehab Uddin Al Abid, Syed Hani Abidi, Alemwork Abie, Olugbenga Olusola Abiodun, Olumide Abiodun, Richard Gyan Aboagye, Shady Abohashem, Hassan Abolhassani, Ulric Sena Abonie, Nagah M Abourashed, Mohamed Abouzid, Dmitry Abramov, Lucas Guimarães Abreu, Dariush Abtahi, Rana Kamal Abu Farha, Fuad Hamdi A Abuadas, Aminu Kende Abubakar, Bilyaminu Abubakar, Eman Abu-Gharbieh, Sawsan Abuhammad, Ahmad Y Abuhelwa, Hana J Abukhadijah, Niveen ME Abu-Rmeileh, Salahdein Aburuz, Dina Abushanab, Raghu Ram Achar, Anirudh Balakrishna Acharya, Apurba Acharya, Ilana N Ackerman, Juan Manuel Acuna, Ousman Adal, Lisa C Adams, Lawan Hassan Adamu, Mesafint Molla Adane, Zenaw Debasu Addisu, Isaac Yeboah Addo, Oluwafemi Atanda Adeagbo, Tajudeen Adesanmi Adebisi, Isaac Akinkunmi Adedeji, David Adedia, Kamoru Ademola Adedokun, Rufus Adesoji Adedoyin, Oluwatobi E Adegbile, Oyelola A Adegboye, Nurudeen A Adegoke, Olumide Thomas Adeleke, Isaac Ayodeji Adesina, Miracle Ayomikun Adesina, Habeeb Omoponle Adewuyi, Temitayo Esther Adeyeoluwa, Olorunsola Israel Adeyomoye, Kishor Adhikari, Ripon Kumar Adhikary, Usha Adiga, Mohd Adnan, Qorinah Estiningtyas Sakilah Adnani, Prince Owusu Adoma, Leticia Akua Adzigbli, David Adzrago, Giuseppina Affinito, Ahmed M Afifi, Aanuoluwapo Adeyimika Afolabi, Rotimi Felix Afolabi, Saira Afzal, Gizachew Beykaso Agafari, Suneth Buddhika Agampodi, Temesgen Anjulo Ageru, Navidha Aggarwal, Mahdi Aghaalikhani, Sepehr Aghajanian, Seyed Mohammad Kazem Aghamir, César Agostinis Sobrinho, Anurag Agrawal, Williams Agyemang-Duah, Mahsa Ahadi, Bright Opoku Ahinkorah, Aqeel Ahmad, Danish Ahmad, Faisal Ahmad, Khabir Ahmad, Khurshid Ahmad, Muayyad M Ahmad, Noah Ahmad, Rabbiya Ahmad, Sajjad Ahmad, Tauseef Ahmad, Waqas Ahmad, Negar Sadat Ahmadi, Amir Mahmoud Ahmadzade, Mohadese Ahmadzade, Akeem Olayiwola Ahmed, Anisuddin Ahmed, Ayman Ahmed, Gasha Salih Ahmed, Haroon Ahmed, Junaid Ahmed, Luai A Ahmed, Mehrunnisha Sharif Ahmed, Meqdad Saleh Ahmed, Muktar Beshir Ahmed, Mushood Ahmed, Oli Ahmed, Shabbir Ahmed, Sindew Mahmud Ahmed, Gulzhanat Aimagambetova, Ahmed AJ Jabbar, Dolapo Emmanuel Ajala, Marjan Ajami, Azeezat Oluwafunmilayo Ajose, Hossein Akbarialiabad, Saeid Akbarifard, Oluwasefunmi Akeju, Roland Eghoghosoa Akhigbe, Olufemi Ambrose Akinkuotu, Karolina Akinosoglou, Mohammed Ahmed Akkaif, Sreelatha Akkala, Wole Akosile, Hammad Akram, Ashley E Akrami, Ralph Kwame Akyea, Alaa Al Amiry, Salah Al Awaidy, Syed Mahfuz Al Hasan, Omar Al Omari, Mohammad Al Qadire, Omar Al Ta'ani, Wasan A M Al Taie, Yazan Al Thaher, Omar Ali Mohammed Al Zaabi, Mohammad Ahmmad Mahmoud Al Zoubi, Mousa Ali Al-Abbadi, Yazan Al-Ajlouni, Tariq A Alalwan, Ziyad Al-Aly, Khurshid Alam, Manjurul Alam, Mohammad Khursheed Alam, Mostafa Alam, Rasmieh Mustafa Al-Amer, Abebaw Alamrew, Amani Alansari, Turki M Alanzi, Fahmi Y Al-Ashwal, Rahmeh Al-Asmar, Seyed Mohammad Amin Alavi, Mohammed Albashtawy, Astefanos Al-Dalakta, Khalifah A Aldawsari, Wafa A Aldhaleei, Mohammed S Aldossary, Robert W Aldridge, Raouf Alebshehy, Shereen M Aleidi, Bezawit Abeje Alemayehu, Tekletsadik Tekleslassie Alemayehu, Fentahun Alemnew, Melaku Birhanu Alemu, Ayman Al-Eyadhy, Ali M Alfalki, Fahad D Algahtani, Abdelazeem M Algammal, Mohammed Ridha Algethami, Adel Ali Saeed Al-Gheethi, Khairat Al-Habbal, Khalid F Alhabib, Nma Bida Alhaji, Samar Al-Hajj, Fadwa Naji Alhalaiqa, Mohammed Khaled Al-Hanawi, Aminu Alhassan Ibrahim, Ashraf Alhumaidi, Fahad A Alhumaydhi, Dari Alhuwail, Abid Ali, Haroon Muhammad Ali, Irfan Ali, Maratab Ali, Mohammad Daud Ali, Mohammed Usman Ali, Rafat Ali, Shahid Ali, Syed Shujait Ali, Syed Yusuf Ali, Waad Ali, Akram Al-Ibraheem, Gianfranco Alicandro, Montaha Al-Iede, Sheikh Mohammad Alif, Morteza Alipour, Samah W Al-Jabi, Mohammad A Aljasir, Mohamad Aljofan, Adel Al-Jumaily, Syed Mohamed Aljunid, Ahmad Alkhatib, Mayson H Alkhatib, Mustafa Alkhawam, Atefeh Allahbakhshian, Khaled S Allemailem, Mohammed Z Allouh, Wesam Taher Almagharbeh, Wael Almahmeed, Sabah Al-Marwani, Nihad A Almasri, Joseph Uy Almazan, Hesham M Al-Mekhlafi, Omar Almidani, Amr Almobayed, Khaldoon Aied Alnawafleh, Hasan Yaser Alniss, Margret Beaula Alocious Sukumar, Mahmoud A Alomari, Mohammad R Alosta, Jaber S Alqahtani, Saleh A Alqahtani, Mohammad R Alqudimat, Ahmad Rajeh Al-Qudimat, Ahmad Alrawashdeh, Intima Alrimawi, Sahel Majed Alrousan, Salman Khalifah Al-Sabah, Mohammed A Alsabri, Najim Z Alshahrani, Mansour Abdullah Alshehri, Zaid Altaany, Awais Altaf, Alaa B Al-Tammemi, Jaffar A Al-Tawfiq, Malik A Althobiani, Khalid A Altirkawi, Javier Alvarez-Galvez, Vera L Alves Carneiro, Nelson Alvis-Guzman, Nelson J Alvis-Zakzuk, Hassan Alwafi, Mohammad Al-Wardat, Yaser Mohammed Al-Worafi, Hany Aly, Mohammad Sharif Ibrahim Alyahya, Amal AlZahmi, Hosam Alzahrani, Karem H Alzoubi, Md Akib Al-Zubayer, Uchenna Anderson Amaechi, Ekiyor Joseph Amafah, Joy Amafah, Masoud Aman Mohammadi, Reza Amani-Beni, Adeladza Kofi Amegah, Faten Amer, Bardia Amidi, Amr Amin, Tarek Tawfik Amin, Alireza Amindarolzarbi, Saeed Amini, Ehsan Amini-Salehi, Nafiu Aminu, Majid Aminzare, Sohrab Amiri, Joanne O Amlag, Dickson A Amugsi, Jimoh Amzat, Filippos Anagnostakis, Roshan A Ananda, Robert Ancuceanu, Deanna Anderlini, David B Anderson, Jason A Anderson, Sofia Androudi, Susan C Anenberg, Song Peng Ang, Colin Angus, Nguyen Hoang Anh, Samuel Egyakwa Ankomah, Kabilan Annadurai, Amir Anoushiravani, Iman Ansari, Sumbul Ansari, Umair Ansari, Rahel Mulatie Anteneh, Josep M Antó, Catherine M Antony, Ernoiz Antriyandarti, Boluwatife Stephen Anuoluwa, Saleha Anwar, Sumadi Lukman Anwar, Razique Anwer, Shahnawaz Anwer, Anayochukwu Edward Anyasodor, Geminn Louis Carace Apostol, Juan Pablo Arab, Hossein Arabi, Jalal Arabloo, Mosab Arafat, Aleksandr Y Aravkin, Demelash Areda, Jorge Arias de la Torre, Hany Ariffin, Benedetta Armocida, Johan Ärnlöv, Jesu Arockiaraj, Mahwish Arooj, Anton A Artamonov, Kurnia Dwi Artanti, Raphael Taiwo Aruleba, Deepavalli Arumuganainar, Nurila Aryntayeva, Mahsa Asadi Anar, Muhammad Asaduzzaman, Syed Mohammed Basheeruddin Asdaq, Shewatatek Melaku Asefa, Mulu Tiruneh Asemu, Saeed Asgary, Mohammad Asghari-Jafarabadi, Charlie Ashbaugh, Syed Amir Ashraf, Tahira Ashraf, Mitra Ashrafi, Milad Ashrafizadeh, Bernard Kwadwo Yeboah Asiamah-Asare, Muhammad Shahzad Aslam, Saeed Aslani, Yuni Asri, Batyrbek Assembekov, Thomas Astell-Burt, Mahshid Ataei, Mirbahador Athari, Seyyed Shamsadin Athari, Maha Moh'd Wahbi Atout, Sachin R Atre, Alok Atreya, Julie Alaere Atta, Zeenah A Atwan, Zaure Maratovna Aumoldaeva, Marcel Ausloos, Abolfazl Avan, Núbia Carelli Pereira Avelar, Sana Javaid Awan, Babafela B Awosile, Adedapo Wasiu Awotidebe, Lemessa Assefa A Ayana, Seyyed HamidReza Ayatizadeh, Olatunde O Ayinde, Yusuf Oloruntoyin Ayipo, Seyed Mohammad Ayyoubzadeh, Davood Azadi, Sina Azadnajafabad, Alireza Azarboo, Ali Azargoonjahromi, Masood Azhar, Farya Azimi, Mohd Yusmaidie Aziz, Sadat Abdulla Aziz, Amin Azizan, Ahmed Y Azzam, Domenico Azzolino, Zaharaddeen Shuaibu Babandi, Rasha Babiker, Giridhara Rathnaiah Babu, Israel Tadesse Bacha, Muhammad Badar, Ashish D Badiye, Alaa Aboelnour Badran, Youngoh Bae, Arvind Bagga, Soroush Baghdadi, Nasser Bagheri, Sara Bagheri, Elahe Baghizadeh, Fereshteh Baghizadeh, Sana Baghizadeh, Khlood K Baghlaf, Najmeh Bahmanziari, Mohammad Amin Bahrami, Razieh Bahreini, Ruhai Bai, Atif Amin Baig, Vali Baigi, Shankar M Bakkannavar, Abdulaziz T Bako, Senthilkumar Balakrishnan, Wondu Feyisa Balcha, Maher Balkis, Jose Balmori-de-la-Miyar, Mohammadreza Balooch Hasankhani, Ovidiu Constantin Baltatu, Shatha Bamashmous, Maciej Banach, Morteza Banakar, Palash Chandra Banik, Rajon Banik, Shirin Barati, Noel C Barengo, Suzanne Lyn Barker-Collo, Hiba Jawdat Barqawi, Ismael A Barreras Beltran, Amadou Barrow, Sandra Barteit, Lingkan Barua, MD Abu Bashar, Zarrin Basharat, Shahid Bashir, Guido Basile, Pritish Baskaran, Rehana Basri, Quique Bassat, Mohammad-Mahdi Bastan, Sanjay Basu, Saurav Basu, Kavita Batra, Bernhard T Baune, Mahdis Bayat, Mohammad Amin Bayat Tork, Mulat Tirfie Bayih, Feyisa Shasho Bayisa, Nebiyou Simegnew Bayleyegn, Thomas Beaney, Neeraj Bedi, Narasimha M Beeraka, Priyamadhaba Behera, Jina Behjati, Babak Behnam, Amir Hossein Behnoush, Bezawit K Bekele, Asnake Gashaw Belayneh, Melesse Belayneh, Abel Cherkos Belete, Gokce Belge Bilgin, Michael Belingheri, Muhammad Bashir Bello, Olorunjuwon Omolaja Bello, Luis Belo, Apostolos Beloukas, Salaheddine Bendak, Riyad Bendardaf, Corina Benjet, Derrick A Bennett, Isabela M Bensenor, Samiun Nazrin Bente Kamal Tune, Habib Benzian, Zombor Berezvai, Maria Bergami, Alemshet Yirga Berhie, Abiye Assefa Berihun, Amiel Nazer C Bermudez, Eduardo Bernabe, Robert S Bernstein, Paulo J G Bettencourt, Ajeet Singh Bhadoria, Akshaya Srikanth Bhagavathula, Neeraj Bhala, Jeetendra Bhandari, Kayleigh Bhangdia, Ravi Bharadwaj, Sonu Bhaskar, Ajay Nagesh Bhat, Anup Bhat, Vivek Bhat, Priyadarshini Bhattacharjee, Shuvarthi Bhattacharjee, Gurjit Kaur Bhatti, Jasvinder Singh Bhatti, Manpreet Singh Bhatti, Rajbir Bhatti, Soumitra S Bhuyan, Sibhatu Kassa Biadgilign, Raluca Bievel-Radulescu, Can Bilgin, Cem Bilgin, Saeed Biroudian, Catherine Bisignano, Atanu Biswas, Bijit Biswas, Raaj Kishore Biswas, Ahmad Naoras Bitar, Molalegne Bitew, Bruno Bizzozero-Peroni, Espen Bjertness, Fiona M Blyth, Trupti Bodhare, Virginia Bodolica, Mahmut Bodur, Lucimere Bohn, Rachael Bokota, Obasanjo Afolabi Bolarinwa, Srinivasa Rao Bolla, Paria Bolourinejad, Aime Bonny, Sri Harsha Boppana, Berrak Bora Basara, Sanaz Bordbar, Hamed Borhany, Alejandro Botero Carvajal, Souad Bouaoud, Soufiane Boufous, Rupert R A Bourne, Christopher Boxe, Marija M Bozic, Jyoti Brahmaiah, Dejana Braithwaite, Nicholas J K Breitborde, Hermann Brenner, Edmond D Brewer, Gabrielle Britton, Julie Brown, Annie J Browne, Traolach Brugha, Claudia Buchweitz, Raffaele Bugiardini, Linh Phuong Bui, Norma B Bulamu, Tsion Samuel Bunare, Danilo Buonsenso, Asmat Burhan, Katrin Burkart, Richard A Burns, Felix Busch, Reinhard Busse, Yasser Bustanji, Zahid A Butt, Channa Buxbaum, Sanjay C J, Jack Cagney, Tianji Cai, Rose Cairns, Mehtap Çakmak Barsbay, Daniela Calina, Luis Alberto Cámera, Luciana Aparecida Campos, Ismael Campos-Nonato, Fan Cao, Yuchen Cao, Angelo Capodici, Rosario Cárdenas, Sinclair Carr, Giulia Carreras, Juan Jesus Carrero, Austin Carter, Andrea Carugno, Andre F Carvalho, Ana Paula Carvalho-e-Silva, Joao Mauricio Castaldelli-Maia, Carlos A Castañeda-Orjuela, Giulio Castelpietra, Alberico L Catapano, Maria Sofia Cattaruzza, Arthur Caye, Christopher R Cederroth, Luca Cegolon, Francieli Cembranel, Muthia Cenderadewi, Kelly M Cercy, Ester Cerin, Sonia Cerrai, Muge Cevik, Madhu Chakkere Shivamadhu, Chiranjib Chakraborty, Promit Ananyo Chakraborty, Sandip Chakraborty, Joht Singh Chandan, Rama Mohan Chandika, Miyuru Chandradasa, Eeshwar K Chandrasekar, Jung-Chen Chang, Vijay Kumar Chattu, Victoria Chatzimavridou-Grigoriadou, Lam Duc Chau, Sirshendu Chaudhuri, Akhilanand Chaurasia, Galmesa Bekana Chemeda, An-Tian Chen, Catherine S Chen, Guangjin Chen, Hana Chen, Haowei Chen, Hui Chen, Junhao Chen, Meng Xuan Chen, Shanquan Chen, Simiao Chen, Xiang Chen, Yifan Chen, Haojin Cheng, Ka Ching Cheung, Nicholas WS Chew, Gerald Chi, Ju-Huei Chien, Odgerel Chimed-Ochir, Patrick R Ching, Jesus Lorenzo Chirinos-Caceres, Clara G Chisari, William C S Cho, Bryan Chong, Yuen Yu Chong, Hou In Chou, Enayet Karim Chowdhury, Mohiuddin Ahsanul Kabir Chowdhury, Hanne Christensen, Steffan Wittrup McPhee Christensen, Dinh-Toi Chu, Isaac Sunday Chukwu, Eric Chung, Erin Chung, Sheng-Chia Chung, Sunghyun Chung, Muhammad Chutiyami, Arrigo Francesco Giuseppe Cicero, Liliana G Ciobanu, Rebecca M Cogen, Aaron J Cohen, Alyssa Columbus, Joao Conde, Stephen E Congly, Nathalie Conrad, Sara Conti, Mariana Oliveira Corda, Alexandru Corlateanu, Samuele Cortese, Paolo Angelo Cortesi, Claudia Cosma, Ewerton Cousin, Emma Johnson Cowart, Michael H Criqui, Andrew Crist, Jessica A Cruz, Natalia Cruz-Martins, Xiaolin Cui, Garland T Culbreth, Nour Dababo, Ali Dabbagh, Omid Dadras, Tukur Dahiru, Xiaochen Dai, Zhaoli Dai, Mayank Dalakoti, Koustuv Dalal, Gloria Dalla Costa, Giovanni Damiani, Emanuele D'Amico, Yohannes Tefera Damtew, Roy Arokiam Arokiam Daniel, Lucio D'Anna, Pojsakorn Danpanichkul, Samuel Demissie Darcho, Latefa Ali Dardas, Bahar Darouei, Reza Darvishi Cheshmeh Soltani, Anna Dastiridou, Gail Davey, Claudio Alberto Dávila-Cervantes, Nicole Davis Weaver, Dimash Davletov, Kairat Davletov, Elham Davoudi, Fernando Pio De la Hoz, Katie de Luca, Nicole K DeCleene, Edward Christopher Dee, Orla Deegan, Sindhura Deekonda, Amanda Deen, Louisa Degenhardt, Paria Dehesh, Lee Deitesfeld, Tadesse Asmamaw Dejenie, Pouria Delbari, Mohammad Delsoz, Dessalegn Demeke, Andreas K Demetriades, Desalegn Getnet Demsie, Edgar Denova-Gutiérrez, Tadios Niguss Derese, Ismail Dergaa, Hunegnaw Almaw Derseh, Emina Dervišević, Abraham Aregay Desta, Vinoth Gnana Chellaiyan Devanbu, Pradeep Kumar Devarakonda, Syed Masudur Rahman Dewan, Arkadeep Dhali, Kuldeep Dhama, Rajinder K Dhamija, Amol S Dhane, Narender K Dhania, Mandira Lamichhane Dhimal, Meghnath Dhimal, Sameer Dhingra, Bibha Dhungel, Marcello Di Pumpo, 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Lancet, 2025
BACKGROUND: For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. METHODS: The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010-23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. FINDINGS: Total numbers of global DALYs grew 6·1% (95% UI 4·0-8·1), from 2·64 billion (2·46-2·86) in 2010 to 2·80 billion (2·57-3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0-14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31-1·61) global DALYs in 2010, increasing to 1·80 billion (1·63-2·03) in 2023, alongside a concurrent 4·1% (1·9-6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176-209] DALYs), stroke (157 million [141-172]), and diabetes (90·2 million [75·2-107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0-107·5]), depressive disorders (26·3% [11·6-42·9]), and diabetes (14·9% [7·5-25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837-917) in 2010 to 681 million (642-736) in 2023, and a 25·8% (22·6-28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7-61·0) for diarrhoeal diseases, 42·9% (38·0-48·0) for HIV/AIDS, and 42·2% (23·6-56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6-22·0) and 24·8% (7·4-36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7-19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18-1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation-with high SBP accounting for 8·4% (6·9-10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories-behavioural, metabolic, and environmental and occupational-risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8-37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0-11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023-eg, declining by 54·4% (38·7-65·3) for unsafe sanitation, 50·5% (33·3-63·1) for unsafe water source, and 45·2% (25·6-72·0) for no access to handwashing facility, and by 44·9% (37·3-53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [-2·7 to 15·6]; non-significant). INTERPRETATION: Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors-eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG-including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic-the complex interaction of multiple health risks, social determinants, and systemic challenges-will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. FUNDING: Gates Foundation and Bloomberg Philanthropies.
Tracking US Health Care Spending by Health Condition and County
Joseph L. Dieleman, Meera Beauchamp, Sawyer W. Crosby, Drew DeJarnatt, Emily K. Johnson, Haley Lescinsky, Theresa McHugh, Ian Pollock, Maitreyi Sahu, Vivianne Swart, Kayla V. Taylor, Azalea Thomson, Golsum Tsakalos, Maxwell Weil, Lauren B. Wilner, Anthony L. Bui, Herbert C. Duber, Annie Haakenstad, Bulat Idrisov, Ali Mokdad, Mohsen Naghavi, Gregory Roth, John W. Scott, Tara Templin, Christopher J. L. Murray
JAMA, 2025
ImportanceUnderstanding health conditions with the most spending and variation across locations and over time is important for identifying trends, highlighting inequalities, and developing strategies for lowering health spending.ObjectiveTo estimate US health care spending for each of 3110 US counties, across 4 payers (Medicare, Medicaid, private insurance, and out-of-pocket payments), and according to 148 health conditions, 38 age/sex groups, and 7 types of care from 2010 to 2019.Design, Setting, and ParticipantsObservational analysis using more than 40 billion insurance claims and nearly 1 billion facility records.ExposuresAmbulatory care, dental care, emergency department care, home health care, hospital inpatient care, nursing facility care, and purchase of prescribed retail pharmaceuticals.Main Outcomes and MeasuresHealth care spending and utilization (eg, number of visits, admissions, or prescriptions) estimates from 2010 through 2019.ResultsBetween 2010 and 2019, 76.6% of personal health care spending was captured by this study. More spending was on type 2 diabetes ($143.9 billion [95% CI, $140 billion-$147.2 billion]) than on any other health condition, followed by other musculoskeletal disorders, which includes joint pain and osteoporosis ($108.6 billion [95% CI, $106.4 billion-$110.3 billion]), oral disorders ($93 billion [95% CI, $92.7 billion-$93.3 billion]), and ischemic heart disease ($80.7 billion [95% CI, $79 billion-$82.4 billion]). Of total spending, 42.2% (95% CI, 42.2%-42.2%) was on ambulatory care, while 23.8% (95% CI, 23.8%-23.8%) was on hospital inpatient care and 13.7% (95% CI, 13.7%-13.7%) was on prescribed retail pharmaceuticals. At the county level, age-standardized spending per capita ranged from $3410 (95% CI, $3281-$3529) in Clark County, Idaho, to $13 332 (95% CI, $13 177-$13 489) in Nassau County, New York. Across counties, the greatest variation was in age-standardized out-of-pocket spending, followed by private insurance spending. Cross-county variation was driven more by variation in utilization rates than variation in price and intensity of care, although both types of variation were substantial for all payers but Medicare.Conclusions and RelevanceBroad variation in health care spending was observed across US counties. Understanding this variation by health condition, sex, age, type of care, and payer is valuable for identifying outliers, highlighting inequalities, and assessing health care gaps.
Halving premature death and improving quality of life at all ages: cross-country analyses of past trends and future directions
Ole F Norheim, Angela Y Chang, Sarah Bolongaita, Mariana Barraza-Lloréns, Ayodamope Fawole, Lia Tadesse Gebremedhin, Eduardo González-Pier, Prabhat Jha, Emily K Johnson, Omar Karlsson, Mizan Kiros, Sarah Lewington, Wenhui Mao, Osondu Ogbuoji, Muhammad Pate, Jennifer L Sargent, Xuyang Tang, David Watkins, Gavin Yamey, Dean T Jamison, Richard Peto
Lancet, 2024
BACKGROUND: Although death in old age is unavoidable, premature death-defined here as death before age 70 years-is not. To assess whether halving premature mortality by 2050 is feasible, we examined the large variation in premature death rates before age 70 years and trends over the past 50 years (1970-2019), covering ten world regions and the 30 most-populous nations. This analysis was undertaken in conjunction with the third report of The Lancet Commission on Investing in Health: Global Health 2050: the path to halving premature death by mid-century. METHODS: In this cross-country analysis of past mortality trends and future directions, all analyses on the probability of premature death (PPD) were conducted using life tables from the UN World Population Prospects 2024. For each sex, country, and year, probability of death was calculated from these life tables with 1-year age-specific mortality rates. FINDINGS: Globally, PPD decreased from 56% in 1970 to 31% in 2019, although some countries saw reversals because of conflict, social instability, or HIV and AIDS. Child mortality has decreased faster than adult mortality. Among all countries, 34 halved their PPD over three decades between 1970 and 2019. Among the 30 most-populous countries, seven countries, with varying levels of baseline PPD and income, halved their PPD in the past half century. Seven of the most-populous countries had average annual rates of improvement in the period 2010-19 that, if sustained, could lead to a halving of PPD by 2050, including Korea (3·9%), Bangladesh (2·8%), Russia (2·7%), Ethiopia (2·4%), Iran (2·4%), South Africa (2·4%), and Türkiye (2·3%). INTERPRETATION: Halving premature death by 2050 is feasible, although substantial investments in child and adult health are needed to sustain or accelerate the rate of improvement for high-performing and medium-performing countries. Particular attention must be paid to countries with very low or a worsening rate of improvement in PPD. By reducing premature mortality, more people will live longer and more healthy lives. However, as people live longer, the absolute number of years lived with chronic disease will increase and investments in services reducing chronic disease morbidity are needed. FUNDING: The Norwegian Agency for Development Cooperation, the Bill & Melinda Gates Foundation, and a Norwegian Research Council Centre of Excellence grant.
The burden of diseases, injuries, and risk factors by state in the USA, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
Masayuki Teramoto, Catherine Bisignano, Johnathan M Hsu, Hazim S Ababneh, Rouzbeh Abbasgholizadeh, et al.
Lancet, 2024
BACKGROUND: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides a comprehensive assessment of health and risk factor trends at global, regional, national, and subnational levels. This study aims to examine the burden of diseases, injuries, and risk factors in the USA and highlight the disparities in health outcomes across different states. METHODS: GBD 2021 analysed trends in mortality, morbidity, and disability for 371 diseases and injuries and 88 risk factors in the USA between 1990 and 2021. We used several metrics to report sources of health and health loss related to specific diseases, injuries, and risk factors. GBD 2021 methods accounted for differences in data sources and biases. The analysis of levels and trends for causes and risk factors within the same computational framework enabled comparisons across states, years, age groups, and sex. GBD 2021 estimated years lived with disability (YLDs) and disability-adjusted life-years (DALYs; the sum of years of life lost to premature mortality and YLDs) for 371 diseases and injuries, years of life lost (YLLs) and mortality for 288 causes of death, and life expectancy and healthy life expectancy (HALE). We provided estimates for 88 risk factors in relation to 155 health outcomes for 631 risk-outcome pairs and produced risk-specific estimates of summary exposure value, relative health risk, population attributable fraction, and risk-attributable burden measured in DALYs and deaths. Estimates were produced by sex (male and female), age (25 age groups from birth to ≥95 years), and year (annually between 1990 and 2021). 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws (ie, 500 random samples from the estimate's distribution). Uncertainty was propagated at each step of the estimation process. FINDINGS: We found disparities in health outcomes and risk factors across US states. Our analysis of GBD 2021 highlighted the relative decline in life expectancy and HALE compared with other countries, as well as the impact of COVID-19 during the first 2 years of the pandemic. We found a decline in the USA's ranking of life expectancy from 1990 to 2021: in 1990, the USA ranked 35th of 204 countries and territories for males and 19th for females, but dropped to 46th for males and 47th for females in 2021. When comparing life expectancy in the best-performing and worst-performing US states against all 203 other countries and territories (excluding the USA as a whole), Hawaii (the best-ranked state in 1990 and 2021) dropped from sixth-highest life expectancy in the world for males and fourth for females in 1990 to 28th for males and 22nd for females in 2021. The worst-ranked state in 2021 ranked 107th for males (Mississippi) and 99th for females (West Virginia). 14 US states lost life expectancy over the study period, with West Virginia experiencing the greatest loss (2·7 years between 1990 and 2021). HALE ranking declines were even greater; in 1990, the USA was ranked 42nd for males and 32nd for females but dropped to 69th for males and 76th for females in 2021. When comparing HALE in the best-performing and worst-performing US states against all 203 other countries and territories, Hawaii ranked 14th highest HALE for males and fifth for females in 1990, dropping to 39th for males and 34th for females in 2021. In 2021, West Virginia-the lowest-ranked state that year-ranked 141st for males and 137th for females. Nationally, age-standardised mortality rates declined between 1990 and 2021 for many leading causes of death, most notably for ischaemic heart disease (56·1% [95% UI 55·1-57·2] decline), lung cancer (41·9% [39·7-44·6]), and breast cancer (40·9% [38·7-43·7]). Over the same period, age-standardised mortality rates increased for other causes, particularly drug use disorders (878·0% [770·1-1015·5]), chronic kidney disease (158·3% [149·6-167·9]), and falls (89·7% [79·8-95·8]). We found substantial variation in mortality rates between states, with Hawaii having the lowest age-standardised mortality rate (433·2 per 100 000 [380·6-493·4]) in 2021 and Mississippi having the highest (867·5 per 100 000 [772·6-975·7]). Hawaii had the lowest age-standardised mortality rates throughout the study period, whereas Washington, DC, experienced the most improvement (a 40·7% decline [33·2-47·3]). Only six countries had age-standardised rates of YLDs higher than the USA in 2021: Afghanistan, Lesotho, Liberia, Mozambique, South Africa, and the Central African Republic, largely because the impact of musculoskeletal disorders, mental disorders, and substance use disorders on age-standardised disability rates in the USA is so large. At the state level, eight US states had higher age-standardised YLD rates than any country in the world: West Virginia, Kentucky, Oklahoma, Pennsylvania, New Mexico, Ohio, Tennessee, and Arizona. Low back pain was the leading cause of YLDs in the USA in 1990 and 2021, although the age-standardised rate declined by 7·9% (1·8-13·0) from 1990. Depressive disorders (56·0% increase [48·2-64·3]) and drug use disorders (287·6% [247·9-329·8]) were the second-leading and third-leading causes of age-standardised YLDs in 2021. For females, mental health disorders had the highest age-standardised YLD rate, with an increase of 59·8% (50·6-68·5) between 1990 and 2021. Hawaii had the lowest age-standardised rates of YLDs for all sexes combined (12 085·3 per 100 000 [9090·8-15 557·1]), whereas West Virginia had the highest (14 832·9 per 100 000 [11 226·9-18 882·5]). At the national level, the leading GBD Level 2 risk factors for death for all sexes combined in 2021 were high systolic blood pressure, high fasting plasma glucose, and tobacco use. From 1990 to 2021, the age-standardised mortality rates attributable to high systolic blood pressure decreased by 47·8% (43·4-52·5) and for tobacco use by 5·1% (48·3%-54·1%), but rates increased for high fasting plasma glucose by 9·3% (0·4-18·7). The burden attributable to risk factors varied by age and sex. For example, for ages 15-49 years, the leading risk factors for death were drug use, high alcohol use, and dietary risks. By comparison, for ages 50-69 years, tobacco was the leading risk factor for death, followed by dietary risks and high BMI. INTERPRETATION: GBD 2021 provides valuable information for policy makers, health-care professionals, and researchers in the USA at the national and state levels to prioritise interventions, allocate resources effectively, and assess the effects of health policies and programmes. By addressing socioeconomic determinants, risk behaviours, environmental influences, and health disparities among minority populations, the USA can work towards improving health outcomes so that people can live longer and healthier lives. FUNDING: Bill & Melinda Gates Foundation.
Global and national influenza-associated hospitalisation rates: Estimates for 40 countries and administrative regions
John Paget, Lisa Staadegaard, Xin Wang, You Li, Tayma van Pomeren, Jojanneke van Summeren, Michel Dückers, Sandra S Chaves, Emily K Johnson, Cédric Mahé, Harish Nair, Cecile Viboud, Peter Spreeuwenberg
Journal of Global Health, 2023
Background WHO estimates that seasonal influenza epidemics result in three to five million cases of severe illness (hospitalisations) every year. We aimed to improve the understanding of influenza-associated hospitalisation estimates at a national and global level. Methods We performed a systematic literature review of English- and Chinese-language studies published between 1995 and 2020 estimating influenza-associated hospitalisation. We included a total of 127 studies (seven in Chinese) in the meta-analysis and analyzed their data using a logit-logistic regression model to understand the influence of five study factors and produce national and global estimates by age groups. The five study factors assessed were: 1) the method used to calculate the influenza-associated hospitalisation estimates (rate- or time series regression-based), 2) the outcome measure (divided into three envelopes: narrow, medium, or wide), 3) whether every case was laboratory-confirmed or not, 4) whether the estimates were national or sub-national, 5) whether the rates were based on a single year or multiple years. Results The overall pooled influenza-associated hospitalisation rate was 40.5 (95% confidence interval (CI) = 24.3-67.4) per 100 000 persons, with rates varying substantially by age: 224.0 (95% CI = 118.8-420.0) in children aged 0-4 years and 96.8 (95% CI = 57.0-164.3) in the elderly aged >65 years. The overall pooled hospitalisation rates varied by calculation method; for all ages, the rates were significantly higher when they were based on rate-based methods or calculated on a single season and significantly lower when cases were laboratory-confirmed. The national hospitalisation rates (all ages) varied considerably, ranging from 11.7 (95% CI = 3.8-36.3) per 100 000 in New Zealand to 122.1 (95% CI = 41.5-358.4) per 100 000 in India (all age estimates). Conclusions Using the pooled global influenza-associated hospitalisation rate, we estimate that seasonal influenza epidemics result in 3.2 million cases of severe illness (hospitalisations) per annum. More extensive analyses are required to assess the influence of other factors on the estimates (e.g. vaccination and dominant virus (sub)types) and efforts to harmonize the methods should be encouraged. Our study highlights the high rates of influenza-associated hospitalisations in children aged 0-4 years and the elderly aged 65+ years.
Global mortality of snakebite envenoming between 1990 and 2019
, Nicholas L. S. Roberts, Emily K. Johnson, Scott M. Zeng, Erin B. Hamilton, Amir Abdoli, Fares Alahdab, Vahid Alipour, Robert Ancuceanu, Catalina Liliana Andrei, Davood Anvari, Jalal Arabloo, Marcel Ausloos, Atalel Fentahun Awedew, Ashish D. Badiye, Shankar M. Bakkannavar, Ashish Bhalla, Nikha Bhardwaj, Pankaj Bhardwaj, Soumyadeep Bhaumik, Ali Bijani, Archith Boloor, Tianji Cai, Felix Carvalho, Dinh-Toi Chu, Rosa A. S. Couto, Xiaochen Dai, Abebaw Alemayehu Desta, Hoa Thi Do, Lucas Earl, Aziz Eftekhari, Firooz Esmaeilzadeh, Farshad Farzadfar, Eduarda Fernandes, Irina Filip, Masoud Foroutan, Richard Charles Franklin, Abhay Motiramji Gaidhane, Birhan Gebresillassie Gebregiorgis, Berhe Gebremichael, Ahmad Ghashghaee, Mahaveer Golechha, Samer Hamidi, Syed Emdadul Haque, Khezar Hayat, Claudiu Herteliu, Olayinka Stephen Ilesanmi, M. Mofizul Islam, Jagnoor Jagnoor, Tanuj Kanchan, Neeti Kapoor, Ejaz Ahmad Khan, Mahalaqua Nazli Khatib, Roba Khundkar, Kewal Krishan, G. Anil Kumar, Nithin Kumar, Iván Landires, Stephen S. Lim, Mohammed Madadin, Venkatesh Maled, Navid Manafi, Laurie B. Marczak, Ritesh G. Menezes, Tuomo J. Meretoja, Ted R. Miller, Abdollah Mohammadian-Hafshejani, Ali H. Mokdad, Francis N. P. Monteiro, Maryam Moradi, Vinod C. Nayak, Cuong Tat Nguyen, Huong Lan Thi Nguyen, Virginia Nuñez-Samudio, Samuel M. Ostroff, Jagadish Rao Padubidri, Hai Quang Pham, Marina Pinheiro, Majid Pirestani, Zahiruddin Quazi Syed, Navid Rabiee, Amir Radfar, Vafa Rahimi-Movaghar, Sowmya J. Rao, Prateek Rastogi, David Laith Rawaf, Salman Rawaf, Robert C. Reiner, Amirhossein Sahebkar, Abdallah M. Samy, Monika Sawhney, David C. Schwebel, Subramanian Senthilkumaran, Masood Ali Shaikh, Valentin Yurievich Skryabin, Anna Aleksandrovna Skryabina, Amin Soheili, Mark A. Stokes, Rekha Thapar, Marcos Roberto Tovani-Palone, Bach Xuan Tran, Ravensara S. Travillian, Diana Zuleika Velazquez, Zhi-Jiang Zhang, Mohsen Naghavi, Rakhi Dandona, Lalit Dandona, Spencer L. James, David M. Pigott, Christopher J. L. Murray, Simon I. Hay, Theo Vos, Kanyin Liane Ong
Nature Communications, 2022
Varied Health Spending Growth Across US States Was Associated With Incomes, Price Levels, And Medicaid Expansion, 2000–19
Emily K. Johnson, Matthew A. Wojtesta, Sawyer W. Crosby, Herbert C. Duber, Eunice Jun, Haley Lescinsky, Phong Nguyen, Maitreyi Sahu, Azalea Thomson, Golsum Tsakalos, Maxwell S. Weil, Annie Haakenstad, Ali H. Mokdad, Christopher J. L. Murray, Joseph L. Dieleman
Health Affairs, 2022
Hospital utilization rates for influenza and RSV: a novel approach and critical assessment
Emily K. Johnson, Dillon Sylte, Sandra S. Chaves, You Li, Cedric Mahe, Harish Nair, John Paget, Tayma van Pomeren, Ting Shi, Cecile Viboud, Spencer L. James
Population Health Metrics, 2021
National burden estimates of hospitalisations for acute lower respiratory infections due to respiratory syncytial virus in young children in 2019 among 58 countries: a modelling study
You Li, Emily K Johnson, Ting Shi, Harry Campbell, Sandra S Chaves, Catherine Commaille-Chapus, Izzie Dighero, Spencer L James, Cédric Mahé, Yujing Ooi, John Paget, Tayma van Pomeren, Cécile Viboud, Harish Nair
Lancet Respiratory Medicine, 2021

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