Evidence map›Paper›PMID 31650125›Full record

ArticleThe Lancet. Digital health2019

A chronological map of 308 physical and mental health conditions from 4 million individuals in the English National Health Service.

Valerie Kuan, Spiros Denaxas, Arturo Gonzalez-Izquierdo, Kenan Direk, Osman Bhatti, Shanaz Husain, Shailen Sutaria, Melanie Hingorani, Dorothea Nitsch, Constantinos A Parisinos and 7 more

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Digital health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 196 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
196citing papers in PubMed, 5 pooled it
21.9field-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

196 citing papers in PubMed, 5 syntheses or guidelines pooled it, 343 citations in OpenAlex.

  1. Pooled it
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  19. Personality disorder diagnoses in UK Autistic people: Evidence from a matched cohort study.Autism : the international journal of research and practice · 2026
    Article
  20. Article

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 10 institutions in 4 countries.

Valerie KuanInstitute of Cardiovascular Science, London.
Spiros DenaxasHealth Data Research UK London.
Arturo Gonzalez-IzquierdoHealth Data Research UK London.
Kenan DirekHealth Data Research UK London.
Osman BhattiChrisp Street Health Centre, London, UK.
Shanaz HusainStratford Village Surgery, London, UK.
Shailen SutariaClinical Effectiveness Group, Queen Mary University of London, London, UK.
Melanie HingoraniMoorfields Eye Hospital, London, UK.
Dorothea NitschDepartment of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
Constantinos A ParisinosInstitute of Health Informatics, University College London, London, UK.
R Thomas LumbersHealth Data Research UK London.
Rohini MathurDepartment of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
Reecha SofatHealth Data Research UK London.
Juan P CasasInstitute of Health Informatics, University College London, London, UK.
Ian C K WongSchool of Pharmacy, University College London, London, UK.
Harry HemingwayHealth Data Research UK London.
Aroon D HingoraniInstitute of Cardiovascular Science, London.
University College London · GBHealth Data Research UK · GBLondon School of Hygiene & Tropical Medicine · GBBritish Heart Foundation · GBCardiovascular Institute Hospital · JPLondon Borough of Tower Hamlets · GBMoorfields Eye Hospital · GBQueen Mary University of London · GBStratford Hospital · GBVA Boston Healthcare System · US

Funding

Arthritis Research UKBritish Heart Foundation RG/10/12/28456Cancer Research UKChief Scientist OfficeDepartment of HealthMedical Research Council MR/K006584/1Medical Research Council MR/S003754/1Wellcome Trust 110284/Z/15/ZWellcome Trust 201375/Z/16/ZWellcome Trust 206274/Z/17/Z
6 · The paper itself

Abstract

Background: To effectively prevent, detect, and treat health conditions that affect people during their lifecourse, health-care professionals and researchers need to know which sections of the population are susceptible to which health conditions and at which ages. Hence, we aimed to map the course of human health by identifying the 50 most common health conditions in each decade of life and estimating the median age at first diagnosis. Methods: We developed phenotyping algorithms and codelists for physical and mental health conditions that involve intensive use of health-care resources. Individuals older than 1 year were included in the study if their primary-care and hospital-admission records met research standards set by the Clinical Practice Research Datalink and they had been registered in a general practice in England contributing up-to-standard data for at least 1 year during the study period. We used linked records of individuals from the CALIBER platform to calculate the sex-standardised cumulative incidence for these conditions by 10-year age groups between April 1, 2010, and March 31, 2015. We also derived the median age at diagnosis and prevalence estimates stratified by age, sex, and ethnicity (black, white, south Asian) over the study period from the primary-care and secondary-care records of patients. Findings: We developed case definitions for 308 disease phenotypes. We used records of 2 784 138 patients for the calculation of cumulative incidence and of 3 872 451 patients for the calculation of period prevalence and median age at diagnosis of these conditions. Conditions that first gained prominence at key stages of life were: atopic conditions and infections that led to hospital admission in children (<10 years); acne and menstrual disorders in the teenage years (10-19 years); mental health conditions, obesity, and migraine in individuals aged 20-29 years; soft-tissue disorders and gastro-oesophageal reflux disease in individuals aged 30-39 years; dyslipidaemia, hypertension, and erectile dysfunction in individuals aged 40-59 years; cancer, osteoarthritis, benign prostatic hyperplasia, cataract, diverticular disease, type 2 diabetes, and deafness in individuals aged 60-79 years; and atrial fibrillation, dementia, acute and chronic kidney disease, heart failure, ischaemic heart disease, anaemia, and osteoporosis in individuals aged 80 years or older. Black or south-Asian individuals were diagnosed earlier than white individuals for 258 (84%) of the 308 conditions. Bone fractures and atopic conditions were recorded earlier in male individuals, whereas female individuals were diagnosed at younger ages with nutritional anaemias, tubulointerstitial nephritis, and urinary disorders. Interpretation: We have produced the first chronological map of human health with cumulative-incidence and period-prevalence estimates for multiple morbidities in parallel from birth to advanced age. This can guide clinicians, policy makers, and researchers on how to formulate differential diagnoses, allocate resources, and target research priorities on the basis of the knowledge of who gets which diseases when. We have published our phenotyping algorithms on the CALIBER open-access Portal which will facilitate future research by providing a curated list of reusable case definitions. Funding: Wellcome Trust, National Institute for Health Research, Medical Research Council, Arthritis Research UK, British Heart Foundation, Cancer Research UK, Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Department of Health and Social Care (England), Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), Economic and Social Research Council, Engineering and Physical Sciences Research Council, National Institute for Social Care and Health Research, and The Alan Turing Institute.

Indexed as

Age of OnsetForecastingHealth StatusMental DisordersAdolescentAdultAgedAged, 80 and overAlgorithmsChildDatabases, FactualElectronic Health RecordsEnglandFemaleHumansMale

Identifiers

PMID31650125
PMCPMC6798263
OpenAlexW2944890781

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.