National noncommunicable disease monitoring survey (NNMS) in India: Estimating risk factor prevalence in adult population

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Abstract

Background

The primary objective of National NCD monitoring survey (NNMS) was to generate national-level estimates of key NCD indicators identified in the national NCD monitoring framework. This paper describes survey study protocol and prevalence of risk factors among adults (18–69 years).

Materials and methods

NNMS was a national level cross-sectional survey conducted during 2017–18. The estimated sample size was 12,000 households from 600 primary sampling units. One adult (18–69 years) per household was selected using the World Health Organization-KISH grid. The study tools were adapted from WHO-STEPwise approach to NCD risk factor surveillance, IDSP-NCD risk factor survey and WHO-Global adult tobacco survey. Total of 8/10 indicators of adult NCD risk factors according to national NCD disease monitoring framework was studied. This survey for the first time estimated dietary intake of salt intake of population at a national level from spot urine samples.

Results

Total of 11139 households and 10659 adults completed the survey. Prevalence of tobacco and alcohol use was 32.8% (95% CI: 30.8–35.0) and 15.9% (95% CI: 14.2–17.7) respectively. More than one-third adults were physically inactive [41.3% (95% CI: 39.4–43.3)], majority [98.4% (95% CI: 97.8–98.8)] consumed less than 5 servings of fruits and / or vegetables per day and mean salt intake was 8 g/day (95% CI: 7.8–8.2). Proportion with raised blood pressure and raised blood glucose were 28.5% (95% CI: 27.0–30.1) and 9.3% (95% CI: 8.3–10.5) respectively. 12.8% (95% CI: 11.2–14.5) of adults (40–69 years) had ten-year CVD risk of ≥30% or with existing CVD.

Conclusion

NNMS was the first comprehensive national survey providing relevant data to assess India’s progress towards targets in National NCD monitoring framework and NCD Action Plan. Established methodology and findings from survey would contribute to plan future state-based surveys and also frame policies for prevention and control of NCDs.

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Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

Mohammad Forouzanfar, Ashkan Afshin, Lily T Alexander … (2017)

Summary Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation.

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Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4·4 million participants

Emily Sonestedt (2016)

Summary Background One of the global targets for non-communicable diseases is to halt, by 2025, the rise in the age-standardised adult prevalence of diabetes at its 2010 levels. We aimed to estimate worldwide trends in diabetes, how likely it is for countries to achieve the global target, and how changes in prevalence, together with population growth and ageing, are affecting the number of adults with diabetes. Methods We pooled data from population-based studies that had collected data on diabetes through measurement of its biomarkers. We used a Bayesian hierarchical model to estimate trends in diabetes prevalence—defined as fasting plasma glucose of 7·0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs—in 200 countries and territories in 21 regions, by sex and from 1980 to 2014. We also calculated the posterior probability of meeting the global diabetes target if post-2000 trends continue. Findings We used data from 751 studies including 4 372 000 adults from 146 of the 200 countries we make estimates for. Global age-standardised diabetes prevalence increased from 4·3% (95% credible interval 2·4–7·0) in 1980 to 9·0% (7·2–11·1) in 2014 in men, and from 5·0% (2·9–7·9) to 7·9% (6·4–9·7) in women. The number of adults with diabetes in the world increased from 108 million in 1980 to 422 million in 2014 (28·5% due to the rise in prevalence, 39·7% due to population growth and ageing, and 31·8% due to interaction of these two factors). Age-standardised adult diabetes prevalence in 2014 was lowest in northwestern Europe, and highest in Polynesia and Micronesia, at nearly 25%, followed by Melanesia and the Middle East and north Africa. Between 1980 and 2014 there was little change in age-standardised diabetes prevalence in adult women in continental western Europe, although crude prevalence rose because of ageing of the population. By contrast, age-standardised adult prevalence rose by 15 percentage points in men and women in Polynesia and Micronesia. In 2014, American Samoa had the highest national prevalence of diabetes (>30% in both sexes), with age-standardised adult prevalence also higher than 25% in some other islands in Polynesia and Micronesia. If post-2000 trends continue, the probability of meeting the global target of halting the rise in the prevalence of diabetes by 2025 at the 2010 level worldwide is lower than 1% for men and is 1% for women. Only nine countries for men and 29 countries for women, mostly in western Europe, have a 50% or higher probability of meeting the global target. Interpretation Since 1980, age-standardised diabetes prevalence in adults has increased, or at best remained unchanged, in every country. Together with population growth and ageing, this rise has led to a near quadrupling of the number of adults with diabetes worldwide. The burden of diabetes, both in terms of prevalence and number of adults affected, has increased faster in low-income and middle-income countries than in high-income countries. Funding Wellcome Trust.

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Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19·1 million participants

José Huerta, Kim Overvad (2017)

Summary Background Raised blood pressure is an important risk factor for cardiovascular diseases and chronic kidney disease. We estimated worldwide trends in mean systolic and mean diastolic blood pressure, and the prevalence of, and number of people with, raised blood pressure, defined as systolic blood pressure of 140 mm Hg or higher or diastolic blood pressure of 90 mm Hg or higher. Methods For this analysis, we pooled national, subnational, or community population-based studies that had measured blood pressure in adults aged 18 years and older. We used a Bayesian hierarchical model to estimate trends from 1975 to 2015 in mean systolic and mean diastolic blood pressure, and the prevalence of raised blood pressure for 200 countries. We calculated the contributions of changes in prevalence versus population growth and ageing to the increase in the number of adults with raised blood pressure. Findings We pooled 1479 studies that had measured the blood pressures of 19·1 million adults. Global age-standardised mean systolic blood pressure in 2015 was 127·0 mm Hg (95% credible interval 125·7–128·3) in men and 122·3 mm Hg (121·0–123·6) in women; age-standardised mean diastolic blood pressure was 78·7 mm Hg (77·9–79·5) for men and 76·7 mm Hg (75·9–77·6) for women. Global age-standardised prevalence of raised blood pressure was 24·1% (21·4–27·1) in men and 20·1% (17·8–22·5) in women in 2015. Mean systolic and mean diastolic blood pressure decreased substantially from 1975 to 2015 in high-income western and Asia Pacific countries, moving these countries from having some of the highest worldwide blood pressure in 1975 to the lowest in 2015. Mean blood pressure also decreased in women in central and eastern Europe, Latin America and the Caribbean, and, more recently, central Asia, Middle East, and north Africa, but the estimated trends in these super-regions had larger uncertainty than in high-income super-regions. By contrast, mean blood pressure might have increased in east and southeast Asia, south Asia, Oceania, and sub-Saharan Africa. In 2015, central and eastern Europe, sub-Saharan Africa, and south Asia had the highest blood pressure levels. Prevalence of raised blood pressure decreased in high-income and some middle-income countries; it remained unchanged elsewhere. The number of adults with raised blood pressure increased from 594 million in 1975 to 1·13 billion in 2015, with the increase largely in low-income and middle-income countries. The global increase in the number of adults with raised blood pressure is a net effect of increase due to population growth and ageing, and decrease due to declining age-specific prevalence. Interpretation During the past four decades, the highest worldwide blood pressure levels have shifted from high-income countries to low-income countries in south Asia and sub-Saharan Africa due to opposite trends, while blood pressure has been persistently high in central and eastern Europe. Funding Wellcome Trust.

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Author and article information

Contributors

Prashant Mathur:

ORCID: https://orcid.org/0000-0002-9271-1373

Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing

Vaitheeswaran Kulothungan: Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Sravya Leburu: Role: ConceptualizationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Anand Krishnan: Role: ConceptualizationRole: InvestigationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing

Himanshu Kumar Chaturvedi: Role: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – review & editing

Harshal Ramesh Salve: Role: InvestigationRole: ResourcesRole: SupervisionRole: VisualizationRole: Writing – review & editing

Ritvik Amarchand: Role: InvestigationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – review & editing

Baridalyne Nongkynrih: Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

P. Ganesh Kumar:

ORCID: https://orcid.org/0000-0001-7466-7965

Role: InvestigationRole: ResourcesRole: SoftwareRole: SupervisionRole: Validation

Vinay Urs K. S.: Role: ResourcesRole: SoftwareRole: Supervision

Lakshmy Ramakrishnan: Role: InvestigationRole: ResourcesRole: SupervisionRole: Validation

A. Laxmaiah: Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

Manjit Boruah: Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

Sanjeev Kumar:

ORCID: https://orcid.org/0000-0003-2730-2378

Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

Binod Kumar Patro:

ORCID: https://orcid.org/0000-0003-0019-4522

Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

Pankaja Ravi Raghav:

ORCID: https://orcid.org/0000-0002-4209-3829

Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

Prabu Rajkumar: Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

P. Sankara Sarma: Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

Rinku Sharma: Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

Muralidhar Tambe: Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

K. R. Thankappan:

ORCID: https://orcid.org/0000-0002-4536-2684

Role: InvestigationRole: Supervision

N. Arlappa: Role: InvestigationRole: Supervision

Tulika Goswami Mahanta: Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

Rajnish P. Joshi: Role: InvestigationRole: Supervision

Neeti Rustagi: Role: InvestigationRole: Supervision

Sonia Gupta: Role: InvestigationRole: Supervision

Binod Kumar Behera:

ORCID: https://orcid.org/0000-0001-8113-5289

Role: InvestigationRole: Supervision

Sangita Chandrakant Shelke: Role: InvestigationRole: Supervision

Abhiruchi Galhotra: Role: InvestigationRole: Supervision

Pranab Jyoti Bhuyan: Role: InvestigationRole: Supervision

Abhijit P. Pakhare: Role: InvestigationRole: Supervision

Dewesh Kumar: Role: InvestigationRole: Supervision

Roshan K. Topno:

ORCID: https://orcid.org/0000-0003-1412-7566

Role: InvestigationRole: Supervision

Manoj Kumar Gupta: Role: InvestigationRole: Supervision

Atulkumar V. Trivedi: Role: InvestigationRole: Supervision

Suneela Garg: Role: InvestigationRole: Supervision

Fernando C. Wehrmeister: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS One

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 2 March 2021

Publication date Collection: 2021

Volume: 16

Issue: 3

Electronic Location Identifier: e0246712

Affiliations

[1 ] Indian Council Medical Research–National Centre for Disease Informatics and Research, Bengaluru, Karnataka, India

[2 ] Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India

[3 ] Indian Council Medical Research—National Institute of Medical Statistics, New Delhi, India

[4 ] Indian Council Medical Research—National Institute of Epidemiology, Chennai, Tamil Nadu, India

[5 ] Department of Cardiac Biochemistry, All India Institute of Medical Sciences, New Delhi, India

[6 ] Division of Community Studies, Indian Council Medical Research—National Institute of Nutrition, Hyderabad, Telangana, India

[7 ] Department of Community Medicine, Assam Medical College, Dibrugarh, Assam, India

[8 ] Department of Community and Family Medicine, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India

[9 ] Department of Community and Family Medicine, All India Institute of Medical Sciences, Bhubaneshwar, Odisha, India

[10 ] Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India

[11 ] Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India

[12 ] Centre for Noncommunicable Diseases, National Centre for Disease Control, Directorate General of Health Services, New Delhi, India

[13 ] Department of Community Medicine, B J Govt. Medical College, Pune, Maharashtra, India

[14 ] Department of Public Health and Community Medicine, Central University Kerala, Kasaragod, Kerala, India

[15 ] Department of Community Medicine/Prevention & Social Medicine, Tezpur Medical College, Tezpur, Assam, India

[16 ] Department of Community and Family Medicine, All India Institute of Medical Sciences, Raipur, Chhattisgarh, India

[17 ] Regional Director Office, Ministry of Health and Family Welfare, Guwahati, Assam, India

[18 ] Department of Preventive and Social Medicine, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India

[19 ] Department of Epidemiology, Indian Council Medical Research—Rajendra Memorial Research Institute of Medical Sciences, Patna, Bihar, India

[20 ] Department of Community Medicine, Government Medical College, Bhavnagar, Gujarat, India

[21 ] Department of Community Medicine, Maulana Azad Medical College and Associated Hospitals, New Delhi, India

Federal University of Pelotas, BRAZIL

Author notes

Competing Interests: The authors have declared that no competing interests exist.

¶ Member of the ICMR-NNMS investigator group. Co-investigators and Collaborators.

* E-mail: ncdir@ 123456ncdirindia.org

Author information

Prashant Mathur https://orcid.org/0000-0002-9271-1373

P. Ganesh Kumar https://orcid.org/0000-0001-7466-7965

Sanjeev Kumar https://orcid.org/0000-0003-2730-2378

Binod Kumar Patro https://orcid.org/0000-0003-0019-4522

Pankaja Ravi Raghav https://orcid.org/0000-0002-4209-3829

K. R. Thankappan https://orcid.org/0000-0002-4536-2684

Binod Kumar Behera https://orcid.org/0000-0001-8113-5289

Roshan K. Topno https://orcid.org/0000-0003-1412-7566

Article

Publisher ID: PONE-D-20-15698

DOI: 10.1371/journal.pone.0246712

PMC ID: 7924800

PubMed ID: 33651825

SO-VID: 747df175-a035-48ad-ae53-bf695dae9e45

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 25 May 2020

Date accepted : 25 January 2021

Page count

Figures: 2, Tables: 5, Pages: 17

Funding

Funded by: Ministry of Health and Family Welfare, Government of India

Award ID: C-707

Award Recipient :

ORCID: https://orcid.org/0000-0002-9271-1373

Prashant Mathur

1.1 Sources of funding: This study was funded by the Ministry of Health and Family Welfare (MoHFW), Govt of India. 1.2 Role of sponsors or funders (other than the named authors): The funders only provided the funds and no role in the study planning and implementation, and preparation of the manuscript.”

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Data Availability All relevant data are within the paper and its Supporting Information files.

National noncommunicable disease monitoring survey (NNMS) in India: Estimating risk factor prevalence in adult population

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Most cited references 39

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4·4 million participants

Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19·1 million participants

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