Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study. Issue 10111 (2nd December 2017)
- Record Type:
- Journal Article
- Title:
- Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study. Issue 10111 (2nd December 2017)
- Main Title:
- Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study
- Authors:
- Dandona, Lalit
Dandona, Rakhi
Kumar, G Anil
Shukla, D K
Paul, Vinod K
Balakrishnan, Kalpana
Prabhakaran, Dorairaj
Tandon, Nikhil
Salvi, Sundeep
Dash, A P
Nandakumar, A
Patel, Vikram
Agarwal, Sanjay K
Gupta, Prakash C
Dhaliwal, R S
Mathur, Prashant
Laxmaiah, Avula
Dhillon, Preet K
Dey, Subhojit
Mathur, Manu R
Afshin, Ashkan
Fitzmaurice, Christina
Gakidou, Emmanuela
Gething, Peter
Hay, Simon I
Kassebaum, Nicholas J
Kyu, Hmwe
Lim, Stephen S
Naghavi, Mohsen
Roth, Gregory A
Stanaway, Jeffrey D
Whiteford, Harvey
Chadha, Vineet K
Khaparde, Sunil D
Rao, Raghuram
Rade, Kirankumar
Dewan, Puneet
Furtado, Melissa
Dutta, Eliza
Varghese, Chris M
Mehrotra, Ravi
Jambulingam, P
Kaur, Tanvir
Sharma, Meenakshi
Singh, Shalini
Arora, Rashmi
Rasaily, Reeta
Anjana, Ranjit M
Mohan, Viswanathan
Agrawal, Anurag
Chopra, Arvind
Mathew, Ashish J
Bhardwaj, Deeksha
Muraleedharan, Pallavi
Mutreja, Parul
Bienhoff, Kelly
Glenn, Scott
Abdulkader, Rizwan S
Aggarwal, Ashutosh N
Aggarwal, Rakesh
Albert, Sandra
Ambekar, Atul
Arora, Monika
Bachani, Damodar
Bavdekar, Ashish
Beig, Gufran
Bhansali, Anil
Bhargava, Anurag
Bhatia, Eesh
Camara, Bilali
Christopher, D J
Das, Siddharth K
Dave, Paresh V
Dey, Sagnik
Ghoshal, Aloke G
Gopalakrishnan, N
Guleria, Randeep
Gupta, Rajeev
Gupta, Subodh S
Gupta, Tarun
Gupte, M D
Gururaj, G
Harikrishnan, Sivadasanpillai
Iyer, Veena
Jain, Sudhir K
Jeemon, Panniyamamkal
Joshua, Vasna
Kant, Rajni
Kar, Anita
Kataki, Amal C
Katoch, Kiran
Khanna, Tripti
Khera, Ajay
Kinra, Sanjay
Koul, Parvaiz A
Krishnan, Anand
Kumar, Avdhesh
Kumar, Raman K
Kumar, Rashmi
Kurpad, Anura
Ladusingh, Laishram
Lodha, Rakesh
Mahesh, P A
Malhotra, Rajesh
Mathai, Matthews
Mavalankar, Dileep
Mohan BV, Murali
Mukhopadhyay, Satinath
Murhekar, Manoj
Murthy, G V S
Nair, Sanjeev
Nair, Sreenivas A
Nanda, Lipika
Nongmaithem, Romi S
Oommen, Anu M
Pandian, Jeyaraj D
Pandya, Sapan
Parameswaran, Sreejith
Pati, Sanghamitra
Prasad, Kameshwar
Prasad, Narayan
Purwar, Manorama
Rahim, Asma
Raju, Sreebhushan
Ramji, Siddarth
Rangaswamy, Thara
Rath, Goura K
Roy, Ambuj
Sabde, Yogesh
Sachdeva, K S
Sadhu, Harsiddha
Sagar, Rajesh
Sankar, Mari J
Sharma, Rajendra
Shet, Anita
Shirude, Shreya
Shukla, Rajan
Shukla, Sharvari R
Singh, Gagandeep
Singh, Narinder P
Singh, Virendra
Sinha, Anju
Sinha, Dhirendra N
Srivastava, R K
Srividya, A
Suri, Vanita
Swaminathan, Rajaraman
Sylaja, P N
Tandale, Babasaheb
Thakur, J S
Thankappan, Kavumpurathu R
Thomas, Nihal
Tripathy, Srikanth
Varghese, Mathew
Varughese, Santosh
Venkatesh, S
Venugopal, K
Vijayakumar, Lakshmi
Xavier, Denis
Yajnik, Chittaranjan S
Zachariah, Geevar
Zodpey, Sanjay
Rao, J V R Prasada
Vos, Theo
Reddy, K Srinath
Murray, Christopher J L
Swaminathan, Soumya
… (more) - Abstract:
- Summary: Background: 18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016. Methods: Using all available data sources, the India State-Level Disease Burden Initiative estimated burden (metrics were deaths, disability-adjusted life-years [DALYs], prevalence, incidence, and life expectancy) from 333 disease conditions and injuries and 84 risk factors for each state of India from 1990 to 2016 as part of GBD 2016. We divided the states of India into four epidemiological transition level (ETL) groups on the basis of the ratio of DALYs from communicable, maternal, neonatal, and nutritional diseases (CMNNDs) to those from non-communicable diseases (NCDs) and injuries combined in 2016. We assessed variations in the burden of diseases and risk factors between ETL state groups and between states to inform a more specific health-system response in the states and for India as a whole. Findings: DALYs due to NCDs and injuries exceeded those due to CMNNDs in 2003 for India, but this transition had a rangeSummary: Background: 18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016. Methods: Using all available data sources, the India State-Level Disease Burden Initiative estimated burden (metrics were deaths, disability-adjusted life-years [DALYs], prevalence, incidence, and life expectancy) from 333 disease conditions and injuries and 84 risk factors for each state of India from 1990 to 2016 as part of GBD 2016. We divided the states of India into four epidemiological transition level (ETL) groups on the basis of the ratio of DALYs from communicable, maternal, neonatal, and nutritional diseases (CMNNDs) to those from non-communicable diseases (NCDs) and injuries combined in 2016. We assessed variations in the burden of diseases and risk factors between ETL state groups and between states to inform a more specific health-system response in the states and for India as a whole. Findings: DALYs due to NCDs and injuries exceeded those due to CMNNDs in 2003 for India, but this transition had a range of 24 years for the four ETL state groups. The age-standardised DALY rate dropped by 36·2% in India from 1990 to 2016. The numbers of DALYs and DALY rates dropped substantially for most CMNNDs between 1990 and 2016 across all ETL groups, but rates of reduction for CMNNDs were slowest in the low ETL state group. By contrast, numbers of DALYs increased substantially for NCDs in all ETL state groups, and increased significantly for injuries in all ETL state groups except the highest. The all-age prevalence of most leading NCDs increased substantially in India from 1990 to 2016, and a modest decrease was recorded in the age-standardised NCD DALY rates. The major risk factors for NCDs, including high systolic blood pressure, high fasting plasma glucose, high total cholesterol, and high body-mass index, increased from 1990 to 2016, with generally higher levels in higher ETL states; ambient air pollution also increased and was highest in the low ETL group. The incidence rate of the leading causes of injuries also increased from 1990 to 2016. The five leading individual causes of DALYs in India in 2016 were ischaemic heart disease, chronic obstructive pulmonary disease, diarrhoeal diseases, lower respiratory infections, and cerebrovascular disease; and the five leading risk factors for DALYs in 2016 were child and maternal malnutrition, air pollution, dietary risks, high systolic blood pressure, and high fasting plasma glucose. Behind these broad trends many variations existed between the ETL state groups and between states within the ETL groups. Of the ten leading causes of disease burden in India in 2016, five causes had at least a five-times difference between the highest and lowest state-specific DALY rates for individual causes. Interpretation: Per capita disease burden measured as DALY rate has dropped by about a third in India over the past 26 years. However, the magnitude and causes of disease burden and the risk factors vary greatly between the states. The change to dominance of NCDs and injuries over CMNNDs occurred about a quarter century apart in the four ETL state groups. Nevertheless, the burden of some of the leading CMNNDs continues to be very high, especially in the lowest ETL states. This comprehensive mapping of inequalities in disease burden and its causes across the states of India can be a crucial input for more specific health planning for each state as is envisioned by the Government of India's premier think tank, the National Institution for Transforming India, and the National Health Policy 2017. Funding: Bill & Melinda Gates Foundation; Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India; and World Bank … (more)
- Is Part Of:
- Lancet. Volume 390:Issue 10111(2017)
- Journal:
- Lancet
- Issue:
- Volume 390:Issue 10111(2017)
- Issue Display:
- Volume 390, Issue 10111 (2017)
- Year:
- 2017
- Volume:
- 390
- Issue:
- 10111
- Issue Sort Value:
- 2017-0390-10111-0000
- Page Start:
- 2437
- Page End:
- 2460
- Publication Date:
- 2017-12-02
- Subjects:
- Medicine -- Periodicals
Medicine -- Periodicals
Medicine
Medicine
Electronic journals
Periodicals
610.5 - Journal URLs:
- http://www.thelancet.com/ ↗
http://www.sciencedirect.com/science/journal/01406736 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/S0140-6736(17)32804-0 ↗
- Languages:
- English
- ISSNs:
- 0140-6736
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