Evidence map›Paper›PMID 33662324›Full record

Observational studyThe Lancet. Infectious diseases2021

Non-communicable disease, sociodemographic factors, and risk of death from infection: a UK Biobank observational cohort study.

Michael Drozd, Mar Pujades-Rodriguez, Patrick J Lillie, Sam Straw, Ann W Morgan, Mark T Kearney, Klaus K Witte, Richard M Cubbon

Open access · hybridAbstract readObservational Study
In one paragraph

Observational study in The Lancet. Infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
16.5field-weighted citation impact, top 1% 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

31 citing papers in PubMed, 69 citations in OpenAlex.

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  4. Association between Broad-Spectrum Antibiotic Use and Risk of Early-Onset Colorectal Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 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 1 country.

Michael DrozdLeeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, UK.
Mar Pujades-RodriguezLeeds Institute of Health Sciences, School of Medicine, University of Leeds, Leeds, UK; IQVIA, London, UK.
Patrick J LillieDepartment of Infection, Castle Hill Hospital, Hull University Hospitals NHS Trust, Kingston Upon Hull, UK.
Sam StrawLeeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, UK.
Ann W MorganLeeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, UK; NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Mark T KearneyLeeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, UK.
Klaus K WitteLeeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, UK.
Richard M CubbonLeeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, UK. Electronic address: r.cubbon@leeds.ac.uk.
University of Leeds · GBCastle Hill Hospital · GB

Funding

British Heart Foundation CH/13/1/30086British Heart Foundation FS/12/80/29821British Heart Foundation FS/18/44/33792British Heart Foundation FS/CRTF/20/24071British Heart Foundation RG/09/010/28087Medical Research Council MC_PC_17228Medical Research Council MC_PC_19042Medical Research Council MC_QA137853Medical Research Council MR/K015346/1Medical Research Council MR/N011775/1
6 · The paper itself

Abstract

backgroundNon-communicable diseases (NCDs) have been highlighted as important risk factors for COVID-19 mortality. However, insufficient data exist on the wider context of infectious diseases in people with NCDs. We aimed to investigate the association between NCDs and the risk of death from any infection before the COVID-19 pandemic (up to Dec 31, 2019).

methodsFor this observational study, we used data from the UK Biobank observational cohort study to explore factors associated with infection death. We excluded participants if data were missing for comorbidities, body-mass index, smoking status, ethnicity, and socioeconomic deprivation, and if they were lost to follow-up or withdrew consent. Deaths were censored up to Dec 31, 2019. We used Poisson regression models including NCDs present at recruitment to the UK Biobank (obesity [defined by use of body-mass index] and self-reported hypertension, chronic heart disease, chronic respiratory disease, diabetes, cancer, chronic liver disease, chronic kidney disease, previous stroke or transient ischaemic attack, other neurological disease, psychiatric disorder, and chronic inflammatory and autoimmune rheumatological disease), age, sex, ethnicity, smoking status, and socioeconomic deprivation. Separate models were constructed with individual NCDs replaced by the total number of prevalent NCDs to define associations with multimorbidity. All analyses were repeated with non-infection-related death as an alternate outcome measure to establish differential associations of infection death and non-infection death. Associations are reported as incidence rate ratios (IRR) accompanied by 95% CIs.

findingsAfter exclusion of 9210 (1·8%) of the 502 505 participants in the UK Biobank cohort, our study sample comprised 493 295 individuals. During 5 273 731 person-years of follow-up (median 10·9 years [IQR 10·1-11·6] per participant), 27 729 deaths occurred, of which 1385 (5%) were related to infection. Advancing age, male sex, smoking, socioeconomic deprivation, and all studied NCDs were independently associated with the rate of both infection death and non-infection death. Compared with White ethnicity, a pooled Black, Asian, and minority ethnicity group was associated with a reduced risk of infection death (IRR 0·64, 95% CI 0·46-0·87) and non-infection death (0·80, 0·75-0·86). Stronger associations with infection death than with non-infection death were observed for advancing age (age 65 years vs 45 years: 7·59, 95% CI 5·92-9·73, for infection death vs 5·21, 4·97-5·48, for non-infection death), current smoking (vs never smoking: 3·69, 3·19-4·26, vs 2·52, 2·44-2·61), socioeconomic deprivation (most vs least deprived quintile: 2·13, 1·78-2·56, vs 1·38, 1·33-1·43), class 3 obesity (vs non-obese: 2·21, 1·74-2·82, vs 1·55, 1·44-1·66), hypertension (1·36, 1·22-1·53, vs 1·15, 1·12-1·18), respiratory disease (2·21, 1·96-2·50, vs 1·28, 1·24-1·32), chronic kidney disease (5·04, 4·28-7·31, vs 2·50, 2·20-2·84), psychiatric disease (1·56, 1·30-1·86, vs 1·23, 1·18-1·29), and chronic inflammatory and autoimmune rheumatological disease (2·45, 1·99-3·02, vs 1·41, 1·32-1·51). Accrual of multimorbidity was also more strongly associated with risk of infection death (five or more comorbidities vs none: 9·53, 6·97-13·03) than of non-infection death (5·26, 4·84-5·72).

interpretationSeveral NCDs are associated with an increased risk of infection death, suggesting that some of the reported associations with COVID-19 mortality might be non-specific. Only a subset of NCDs, together with the accrual of multimorbidity, advancing age, smoking, and socioeconomic deprivation, were associated with a greater IRR for infection death than for other causes of death. Further research is needed to define why these risk factors are more strongly associated with infection death, so that more effective preventive strategies can be targeted to high-risk groups.

fundingBritish Heart Foundation.

Indexed as

Biological Specimen BanksNoncommunicable DiseasesSARS-CoV-2AdultAgedCOVID-19FemaleHumansMaleMiddle AgedRisk FactorsSocioeconomic Factors

Identifiers

PMID33662324
PMCPMC8323124
OpenAlexW3134996577

What OpenQuestion holds

Textmetadata
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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.