Evidence map›Paper›PMID 16354108›Full record

ArticlePLoS medicine2006

Prospective study of one million deaths in India: rationale, design, and validation results.

Prabhat Jha, Vendhan Gajalakshmi, Prakash C Gupta, Rajesh Kumar, Prem Mony, Neeraj Dhingra, Richard Peto, RGI-CGHR Prospective Study Collaborators

Abstract read
In one paragraph

Article in PLoS medicine, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 152 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
152citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

152 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Trial
  7. Trial
  8. Trial
  9. Trial
  10. Trial
  11. Quality of Medical Certification of Cause of Death in a City of Assam.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2026
    Article
  12. Article
  13. Tuberculosis: An Ongoing Global Threat.Advances in experimental medicine and biology · 2026
    Review
  14. Article
  15. Article
  16. Article
  17. Observational
  18. Article
  19. Article
  20. Cohort Profile: Indian Study of Healthy Ageing (ISHA-Barshi).International journal of epidemiology · 2024
    Article

92 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Prabhat JhaCentre for Global Health Research, Public Health Sciences, St Michael's Hospital, McLaughlin Centre for Molecular Medicine, University of Toronto, Toronto, Canada. prabhat.jha@utoronto.ca
Vendhan Gajalakshmi
Prakash C Gupta
Rajesh Kumar
Prem Mony
Neeraj Dhingra
Richard Peto
RGI-CGHR Prospective Study Collaborators

Funding

Strengthening monitoring of Indian tobacco mortalityR01TW005991 · FIC · ST. MICHAEL'S HOSPITAL · PI JHA, PRABHAT · 2002 to 2006
$862k
FIC NIH HHS R01 TW005991FIC NIH HHS R01 TW05991-01
6 · The paper itself

Abstract

backgroundOver 75% of the annual estimated 9.5 million deaths in India occur in the home, and the large majority of these do not have a certified cause. India and other developing countries urgently need reliable quantification of the causes of death. They also need better epidemiological evidence about the relevance of physical (such as blood pressure and obesity), behavioral (such as smoking, alcohol, HIV-1 risk taking, and immunization history), and biological (such as blood lipids and gene polymorphisms) measurements to the development of disease in individuals or disease rates in populations. We report here on the rationale, design, and implementation of the world's largest prospective study of the causes and correlates of mortality. METHODS AND

findingsWe will monitor nearly 14 million people in 2.4 million nationally representative Indian households (6.3 million people in 1.1 million households in the 1998-2003 sample frame and 7.6 million people in 1.3 million households in the 2004-2014 sample frame) for vital status and, if dead, the causes of death through a well-validated verbal autopsy (VA) instrument. About 300,000 deaths from 1998-2003 and some 700,000 deaths from 2004-2014 are expected; of these about 850,000 will be coded by two physicians to provide causes of death by gender, age, socioeconomic status, and geographical region. Pilot studies will evaluate the addition of physical and biological measurements, specifically dried blood spots. Preliminary results from over 35,000 deaths suggest that VA can ascertain the leading causes of death, reduce the misclassification of causes, and derive the probable underlying cause of death when it has not been reported. VA yields broad classification of the underlying causes in about 90% of deaths before age 70. In old age, however, the proportion of classifiable deaths is lower. By tracking underlying demographic denominators, the study permits quantification of absolute mortality rates. Household case-control, proportional mortality, and nested case-control methods permit quantification of risk factors.

conclusionsThis study will reliably document not only the underlying cause of child and adult deaths but also key risk factors (behavioral, physical, environmental, and eventually, genetic). It offers a globally replicable model for reliably estimating cause-specific mortality using VA and strengthens India's flagship mortality monitoring system. Despite the misclassification that is still expected, the new cause-of-death data will be substantially better than that available previously.

Indexed as

Cause of DeathPopulation SurveillanceAdultAgedAlcohol DrinkingCase-Control StudiesData CollectionFemaleHumansIndiaMaleMiddle AgedMolecular EpidemiologyMortalityProspective StudiesQuality Control

Identifiers

PMID16354108
PMCPMC1316066

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.