Nafsiah Mboi, Ruri Syailendrawati, Samuel M. Ostroff, Iqbal R. F. Elyazar, Scott D. Glenn, Tety Rachmawati, Wahyu Pudji Nugraheni, Pungkas Bahjuri Ali, Laksono Trisnantoro, Qorinah Estiningtyas Sakilah Adnani, Rozana Ika Agustiya, Agung Dwi Laksono, Budi Aji, Luna Amalia, Ansariadi Ansariadi, Ernoiz Antriyandarti, Irfan Ardani, Ratih Ariningrum, Ni Ketut Aryastami, Djunaedi Djunaedi, Ferry Efendi, Nelsensius Klau Fauk, Ghozali Ghozali, Nariyah Handayani, Harapan Harapan, Arief Hargono, Agus D. W I. Harso, Hartanti Dian Ikawati, Endang Indriasih, Karlina Karlina, Soewarta Kosen, Asep Kusnali, Dian Kusuma, Melyana Lumbantoruan, Merry Lusiana, Santi Martini, Meilinda Meilinda, Rofingatul Mubasyiroh, Dede Anwar Musadad, Dina Nur Anggraini Ningrum, Syarifah Nuraini, Ni�matun Nurlaela, Helena Ullyartha Pangaribuan, Indah Pawitaningtyas, Agung Purnomo, Herti Windya Puspasari, Nurul Puspasari, Setyaningrum Rahmawaty, Hasnani Rangkuti, Betty Roosihermiatie, Tita Rosita, Rustika Rustika, Yoseph Leonardo Samodra, Jenny Veronika Samosir, Siswanto Siswanto, Karen Houston Smith, Agus Sudaryanto, Sugianto Sugianto, Suparmi Suparmi, Ni Ketut Susilarini, Ingan Ukur Tarigan, Jansje Henny Vera Ticoalu, Indang Trihandini, Mugi Wahidin, Tati Suryati Warouw, Retno Widyastuti, Ratna D. W. I. Wulandari, Simon I. Hay, Christopher J. L. Murray, Ali H. Mokdad
Background: Analysing trends and levels of the burden of disease at the national level can mask inequalities in health-related progress in lower administrative units such as provinces and districts. We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to analyse health patterns in Indonesia at the provincial level between 1990 and 2019. Long-term analyses of disease burden provide insights on Indonesia's advance to universal health coverage and its ability to meet the United Nations Sustainable Development Goals by 2030. Methods: We analysed GBD 2019 estimated cause-specific mortality, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), life expectancy at birth, healthy life expectancy, and risk factors for 286 causes of death, 369 causes of non-fatal health loss, and 87 risk factors by year, age, and sex for Indonesia and its 34 provinces from 1990 to 2019. To generate estimates for Indonesia at the national level, we used 138 location-years of data to estimate Indonesia-specific demographic indicators, 317 location-years of data for Indonesia-specific causes of death, 689 location-years of data for Indonesia-specific non-fatal outcomes, 250 location-years of data for Indonesia-specific risk factors, and 1641 location-years of data for Indonesia-specific covariates. For subnational estimates, we used the following source counts: 138 location-years of data to estimate Indonesia-specific demographic indicators; 5848 location-years of data for Indonesia-specific causes of death; 1534 location-years of data for Indonesia-specific non-fatal outcomes; 650 location-years of data for Indonesia-specific risk factors; and 16 016 location-years of data for Indonesia-specific covariates. We generated our GBD 2019 estimates for Indonesia by including 1 915 207 total source metadata rows, and we used 821 total citations. Findings: Life expectancy for males across Indonesia increased from 62·5 years (95% uncertainty interval 61·3–63·7) to 69·4 years (67·2–71·6) between 1990 and 2019, a positive change of 6·9 years. For females during the same period, life expectancy increased from 65·7 years (64·5–66·8) to 73·5 years (71·6–75·6), an increase of 7·8 years. There were large disparities in health outcomes among provinces. In 2019, Bali had the highest life expectancy at birth for males (74·4 years, 70·90–77·9) and North Kalimantan had the highest life expectancy at birth for females (77·7 years, 74·7–81·2), whereas Papua had the lowest life expectancy at birth for males (64·5 years, 60·9–68·2) and North Maluku had the lowest life expectancy at birth for females (64·0 years, 60·7–67·3). The difference in life expectancy for males between the highest-ranked and lowest-ranked provinces was 9·9 years and the difference in life expectacy for females between the highest-ranked and lowest-ranked provinces was 13·7 years. Age-standardised death, YLL, and YLD rates also varied widely among the provinces in 2019. High systolic blood pressure, tobacco, dietary risks, high fasting plasma glucose, and high BMI were the five leading risks contributing to health loss measured as DALYs in 2019. Interpretation: Our findings highlight that Indonesia faces a double burden of communicable and non-communicable diseases that varies across provinces. From 1990 to 2019, Indonesia witnessed a decline in the infectious disease burden, although communicable diseases such as tuberculosis, diarrhoeal diseases, and lower respiratory infections have remained a main source of DALYs in Indonesia. During that same period, however, all-ages death and disability rates from non-communicable diseases and exposure to their risk factors accounted for larger shares of health loss. The differences in health outcomes between the highest-performing and lowest-performing provinces have also widened since 1990. Our findings support a comprehensive process to revisit current health policies, examine the root causes of variation in the burden of disease among provinces, and strengthen programmes and policies aimed at reducing disparities across the country. Funding: The Bill & Melinda Gates Foundation and the Government of Indonesia. Translation: For the Bahasa Indonesia translation of the abstract see Supplementary Materials section. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
Centre for Strategic and International Studies, Jakarta, Indonesia; The National Commission on Tobacco Control, Jakarta, Indonesia; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, United States; Henry M Jackson School of International Studies, University of Washington, Seattle, WA, United States; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, United States; Eijkman-Oxford Clinical Research Unit, Eijkman Institute for Molecular Biology, Jakarta, Indonesia; Research Organization for Public Health and Nutrition, Jakarta, Indonesia; National Research and Innovation Agency, Jakarta, Indonesia; Directorate for Health and Nutrition, National Development Planning Agency, Jakarta, Indonesia; Center for Health Policy and Management, Gadjah Mada University, Yogyakarta, Indonesia; Faculty of Medicine, Universitas Padjadjaran (Padjadjaran University), Bandung, Indonesia; Research Department, The Airlangga Centre for Health Policy (ACeHAP), Surabaya, Indonesia; Faculty of Medicine and Public Health, Jenderal Soedirman University, Purwokerto, Indonesia; Data and Information, National Institute of Health Research & Development, Jakarta, Indonesia; School of Public Health, Hasanuddin University, Makassar, Indonesia; Agribusiness Study Program, Sebelas Maret University, Surakarta, Indonesia; Directorate of People Welfare Statistics, BPS-Statistics Indonesia, DKI, Jakarta, Indonesia; Research and Development Center for Humanities and Health Management, Jakarta Pusat, Indonesia; Biomedical Research and Development Center for Basic Health Technology, Jakarta Pusat, Indonesia; Department of Nutrition Science, Muhammadiyah University of Surakarta, Surakarta, Indonesia; National Institute of Health Research and Development, Ministry of Health, Jakarta Pusat, Indonesia; Puslitbang Biomedis dan Teknologi Dasar Kesehatan, Ministry of Health, Jakarta Pusat, Indonesia; Community Health Nursing, Universitas Airlangga (Airlangga University), Surabaya, Indonesia; Department of Epidemiology, Universitas Airlangga (Airlangga University), Surabaya, Indonesia; Faculty of Public Health, Universitas Airlangga (Airlangga University), Surabaya, Indonesia; Management Department, Universitas Airlangga (Airlangga University), Surabaya, Indonesia; School of Nursing and Midwifery, La Trobe University, Melbourne, VIC, Australia; Torrens University Australia, Adelaide, SA, Australia; Institute of Resource Governance and Social Change, Kupang, Indonesia; Department of Public Health, University of Muhammadiyah Kalimantan Timur, Samarinda, Indonesia; Medical Research Unit, Universitas Syiah Kuala (Syiah Kuala University), Banda Aceh, Indonesia; Health Research Organization, Jakarta, Indonesia; Faculty of Public Health, Universitas Sam Ratulangi, Manado, Indonesia; Entrepreneurship Department, Bina Nusantara University, Jakarta, Indonesia; Department of Nursing, Muhammadiyah University of Surakarta, Surakarta, Indonesia; Imperial College Business School, Imperial College London, London, United Kingdom; Faculty of Public Health, University of Indonesia, Depok, Indonesia; School of Public Health, Taipei Medical University, Taipei, Taiwan; Indonesian Public Health Association, Surabaya, Indonesia; Public Health Department, Universitas Negeri Semarang (State University of Semarang), Kota Semarang, Indonesia; Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan
