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|Year : 2019 | Volume
| Issue : 1 | Page : 5-6
Noncommunicable diseases in India: Challenges and the way forward
Department of Community Medicine, Dr DY Patil Medical College, Hospital and Research Centre, Dr DY Patil Vidyapeeth, Pune, Maharashtra, India
|Date of Web Publication||28-Jan-2019|
Dr. A Banerjee
Department of Community Medicine, Dr DY Patil Medical College, Hospital and Research Centre, Dr DY Patil Vidyapeeth, Pune, Maharashtra
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Banerjee A. Noncommunicable diseases in India: Challenges and the way forward. J Postgrad Med 2019;65:5-6
India like most rapidly growing economies is facing a looming epidemic of noncommunicable diseases (NCDs). Market forces promote junk foods, sugar sweetened beverages (SSBs), tobacco, and alcohol. Increasing automobiles on the roads lead to air pollution. Changing work environments with long hours in front of computers lead to a sedentary lifestyle. Young and old choose games on their computers or smartphone over outdoor sports. Facebook friends are replacing the warmth of genuine human contacts leading to social isolation. While unhealthy diet, tobacco, alcohol, and sedentary lifestyle are known determinants of NCDs, a meta-analysis suggests social isolation as a risk factor for coronary heart disease (CHD) and stroke.
India is one of the first countries to respond to these challenges and set specific targets and indicators to bring down the burden of NCDs mortality by 25% by the year 2025—the so-called 25 × 25 target. The present study has to be viewed in this context.
The authors in the present study have used data available in the public domain such as census 2001 and 2013 Sample Registration Systems and causes of death reports, to calculate the unconditional probability of dying between 30 and 70 years of age from 2001 to 2013. The paper has analyzed mortality trends for selected NCDs. This is the first step as mortality data are easier to compile. It has also provided a rough estimate of knowing how far we are from the goal of reducing mortality by 25% by the year 2025. The authors conclude that, although there has been a declining trend in premature mortality due to NCDs in this period, the rate of decrease is not sufficient to meet the goal of “25 × 25 ”target. The present study has also found that mortality in males due to NCDs was higher than in females.
Such data mining technique is an emerging concept in public health practice. Surveillance, particularly of NCDs which have complex etiologies both at individual and environmental levels, can benefit from such an approach. We can attempt to unravel the convoluted associations of NCDs risk factors by linking epidemiology and informatics through data mining applied across environmental, individual, economic, and biologic data sources.
India being a vast country; there are regional differences in trends of NCDs, which the present study has not captured. Improving population health in a vast and diverse country like India requires reliable and state level estimates of disease trends and risk factors. Moreover, while allocating resources, NCDs cannot be considered in isolation. Competing priorities of communicable, maternal, neonatal, and nutritional diseases [CMNND] have to be taken into account.
India is one country with stories of many states. Focused actions together with intersectoral long-term policies will be required across all states. This will require state level segregation of NCDs trends vis-à-vis CMNND trends.
This picture has been captured for the first time by an Indian team comprising more than 200 experts from over 100 institutions. The group used all available data sources and compiled trends for both NCDs and CMNNDs from 1990 to 2016. The states of India were divided into four epidemiological transition level [ETL] groups based on the ratio of burden from CMNNDs to those from NCDs.
Although this exhaustive study brought out that the burden of NCDs and injuries exceeded those due to CMNNDs in 2003 this transition had a wide variation ranging almost quarter of a century among the four ETL state groups. As the burden of NCDs and injuries exceeds CMNNDs, the degree varies widely. The implications for policy are that as interventions to control NCDs and injuries are indicated, the burden of CMNNDs needs to be addressed commensurate with its share in each state. This will reduce the inequities in health status among the states of India.
Data integration and creation of large social, environmental, and clinical data sets will increasingly play an important role of surveillance and monitoring as well as health technology assessment (HTA) in India. There are concerns however, that the completeness and quality of vital registration data for mortality in India are inadequate. A recent evaluation of the civil registration and vital statistics system found that recorded data were incomplete and of poor quality, with a proper cause of death recorded in only 16% of the total deaths registered. In order to overcome these deficiencies, the ICMR plans to undertake a thorough verbal autopsy study in 2018. In times to come we will have more robust databases in the public domain for monitoring and surveillance of NCDs and CMNNDs to enable strengthening of the Indian health system to cope with the rising burden of NCDs and tackle the unfinished agenda of CMNNDs.
| :: References|| |
Kontis V, Mathers CD, Bonita R, Stevens GA, Rehm J, Shield KD, et al
. Regional Contribution of Six Preventable Risk Factors to achieving the 25 × 25 non-communicable disease mortality reduction targets: A modeling study. Lancet Glob Health 2015;3:e746-57.
Valtorta N K, Kanaan M, Gilbody S, Ronzi S, Hanratty B. Loneliness and social isolation as risk factors for coronary heart disease and stroke: A systematic review and meta-analysis of longitudinal observational studies. Heart 2016;102:1009-16.
Reddy MM, Kar SS. Unconditional probability of dying and age-specific mortality rate because of major non-communicable diseases in India: Time trends from 2001 to 2013. J Postgrad Med 2019;65:11-7.
] [Full text]
Lynch SM, Moore JH. A call for biological data mining approaches in epidemiology. BioData Mining 2016;9:1.
Anonymous. Editorial: India – A tale of one country, but stories of many states. Lancet 2017;390:2413.
India State-Level Disease Burden Initiative Collaborators. Nations within a nation: variations in epidemiological transition across states of India, 1990–2016 in the Global Burden of Disease Study. Lancet 2017;390:2437-60.
Downey L, Rao N, Guinness L, Asaria M, Prinja S, Sinha A, et al
. Identification of publicly available data sources to inform the conduct of Health Technology Assessment in India. F1000Research 2018;7:245.