Evidence map›Paper›PMID 33318117›Full record

ArticleBMJ open2020

Population-based comparison of chronic kidney disease prevalence and risk factors among adults living in the Punjab, Northern India and the USA (2013-2015).

Jennifer Bragg-Gresham, J S Thakur, Gursimer Jeet, Sanjay Jain, Arnab Pal, Rajendra Prasad, Subramaniam Pennathur, Rajiv Saran

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 14% of its field
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Global health inequalities of chronic kidney disease: a meta-analysis.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
    Pooled it
  2. Long Term Exposure to Ambient Particulate MatterKidney international reports · 2026
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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

8 authors at 2 institutions in 2 countries.

Jennifer Bragg-GreshamInternal Medicine-Division of Nephrology, University of Michigan Medical School, Ann Arbor, Michigan, USA.ORCID 0000-0002-9069-9489
J S ThakurSchool of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, Chandigarh, India.ORCID 0000-0003-1339-1429
Gursimer JeetSchool of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, Chandigarh, India.ORCID 0000-0003-3727-9941
Sanjay JainSchool of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, Chandigarh, India.
Arnab PalSchool of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, Chandigarh, India.ORCID 0000-0002-0850-3118
Rajendra PrasadSchool of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, Chandigarh, India.
Subramaniam PennathurInternal Medicine and Molecular and Integrative Physiology, Division of Nephrology, University of Michigan School of Public Health, Ann Arbor, India.
Rajiv SaranInternal Medicine-Division of Nephrology, University of Michigan Medical School, Ann Arbor, Michigan, USA rsaran@med.umich.edu.
Post Graduate Institute of Medical Education and Research · INUniversity of Michigan · US

Funding

WICONI UNKI TAWAPI-HEALING OUR LIVESU58DP001624 · DP · SANTEE SIOUX NATION · PI BICKERSTAFF, YVONNE · 2008 to 2012
$491k
NCCDPHP CDC HHS U58 DP001624
6 · The paper itself

Abstract

objectivesIndia is witnessing a disturbing growth in non-communicable diseases (NCDs), including chronic kidney disease (CKD). Recently, a WHO STEPS survey was conducted in the state of Punjab, India to collect data from the adult population on NCD risk factors. We sought to compare the prevalence of CKD and its risk factors between this large state in northern India and the USA.

settingSamples were drawn from both locations, Punjab, India and the USA, using multistage stratified sampling designs to collect data representative of the general population.

participantsData from 2002 participants in the Punjab survey (2014-2015) and 5057 in the USA (National Health and Nutrition Examination Survey (NHANES; 2013-2014), between the ages of 18-69 years were examined. PRIMARY AND SECONDARY OUTCOME MEASURES: Modified Poisson regression was employed to compare prevalence between the two samples for markers of CKD and its risk factors. All analyses used sampling weights.

resultsThe average age in the Punjab sample was significantly lower than the USA (38.3 vs 42.5 years, p<0.0001). While smoking and obesity were higher in the USA, hypertension was much more common in Punjab (48.2% vs 33.4%, p<0.0001). Significant differences were seen in the prevalence of CKD, with lower prevalence of eGFR <60 mL/min/1.73 m

conclusionsWe report a strikingly high prevalence of albuminuria in Punjab, India, compared with the USA. This requires further study and may have enormous public health implications for future burden of progressive CKD, end-stage kidney disease, morbidity, mortality and specifically for elevated risk or presence of cardiovascular disease in the northern state of Punjab, India.Funding came from the National Health Mission, Punjab, India, JST and the Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

Indexed as

Renal Insufficiency, ChronicAdolescentAdultAgedCross-Sectional StudiesGeorgiaHumansIndiaMiddle AgedNutrition SurveysPrevalenceRisk FactorsYoung Adultadult nephrologyepidemiologynephrology

Identifiers

PMID33318117
PMCPMC7737106
OpenAlexW3111761193

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.