Evidence map›Paper›PMID 29481008›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2018

Joint Families and Cancer Diagnosis in Rural India

Sushant Koirala

Abstract read
In one paragraph

Article in Asian Pacific journal of cancer prevention : APJCP, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

1 author.

Sushant KoiralaSchool of Arts and Science, University of Pennsylvania, Philadelphia, United States. Email:kois@sas.upenn.edu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Each year, there are over a million new cases of cancer in India, which causes many untimely deaths and increases the economic burden to households. By focusing on preventative measures and finding socioeconomic and behavioral contributors to cancer, steps can be taken to help alleviate this burden. This study aims to find the effect living in a joint family can have on being diagnosed with cancer in rural India. Methods: The study estimates the effect living in a joint family, along with other demographic information, has on being diagnosed with cancer using a logit estimation model. The data for the study was collected from a survey was conducted on the households of the Handiganur village (N=251) comprising of several demographic, social, and medical questions. Results: The study found that living in a joint family lowers the odds of having cancer. The results indicate that living in a joint family reduces the probability of being diagnosed by 7.23 percentage points and is significant at a 5% level. Furthermore, among the other tested variables, eating habit is negatively significant at 5% level, suggesting that if a person eats 3 to 4 times a day his or her likelihood of suffering from cancer will be lowered by 6.55 percentage points. Access to public wells and drinking alcohol both increase the likelihood of being diagnosed with cancer by 7.90 (p<0.1) percentage points and 11.90 (p<0.05) percentage points respectively. Conclusions: The negative effect of joint family could be due to two possible reasons. The first is that there is in fact a biological reason. The second reason for this result could be a false negative, as it could be because people in joint families are not getting the necessary check-ups required to diagnose cancer.

Indexed as

Family CharacteristicsFeeding BehaviorFemaleHumansIndiaLife StyleMaleNeoplasmsRural PopulationSocioeconomic Factorscancereating habitsJoint familieslogit

Identifiers

PMID29481008
PMCPMC5980948

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.