Evidence map›Paper›PMID 23667455›Full record

ArticlePloS one2013

Age and sex pattern of cardiovascular mortality, hospitalisation and associated cost in India.

Akanksha Srivastava, Sanjay K Mohanty

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Akanksha SrivastavaInternational Institute for Population Sciences, Mumbai, India. akankshaleo@gmail.com
Sanjay K Mohanty

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextThough the cardiovascular diseases are the leading cause of mortality in India, little is known about the human and economic loss attributed to the disease. The aim of this paper is to account the age and sex pattern of mortality, hospitalisation and the cost of hospitalisation for cardiovascular diseases in India. DATA AND

methodsData for the present study has been drawn from multiple sources; 52(nd) and 60(th) rounds of the National Sample Survey, Special Survey of Death, 2001-03 and the Sample Registration System 2004-2010. Under the changing demographics and constant assumptions of mortality, hospitalisation and cost of hospitalisation, we have estimated the deaths, hospitalisation and cost of hospitalisation for cardiovascular diseases in India during 2004 to 2021. Descriptive analyses and multivariate techniques were used to understand the socio-economic differentials in cost of hospitalisation for cardiovascular diseases in India.

findingsIn India, the cardiovascular diseases accounted for an estimated 1.4 million deaths in 2004 and it is likely to be 2.1 million in 2021. An estimated 6.7 million people were hospitalised for cardiovascular diseases in 2004, and projected to be 10.9 million by 2021. Unlike mortality, majority of the hospitalisation due to cardiovascular diseases will be in the prime working age group (25-59). The estimated cost of hospitalisation for cardiovascular diseases was 94/- billion rupees in 2004 and expected to be 152/- billion rupees by 2021, at 2004 prices. The cost of hospitalisation for cardiovascular diseases was significantly high in private health centres, high fertility states and among high socio-economic groups.

conclusionThe cardiovascular mortality and hospitalisation will be largely concentrated in the prime working age group and the cost of hospitalisation is expected to increase substantially in coming years. This calls for mobilising resources, increasing access to health insurance and devising strategies for the prevention, control and treatment of cardiovascular diseases in India.

Indexed as

Cost of IllnessAdultAge DistributionBudgetsCardiovascular DiseasesFemaleHospitalizationHumansIndiaMaleMiddle AgedSex DistributionSocioeconomic FactorsYoung Adult

Identifiers

PMID23667455
PMCPMC3646767

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