Cohort Profile: The Epidemiology of Chronic Diseases and Multimorbidity. The EpiChron Cohort Study

Prados‐Torres, Alexandra; Poblador‐Plou, Beatriz; Gimeno-Miguel, Antonio; Calderón‐Larrañaga, Amaia; Poncel-Falcó, Antonio; Gimeno-Feliu, Luis Andrés; González-Rubio, Francisca; Laguna-Berna, Clara; Marta-Moreno, Javier; Clerencia-Sierra, Mercedes; Aza-Pascual-Salcedo, Mercedes; Bandrés-Liso, Ana Cristina; Coscollar-Santaliestra, Carlos; Pico-Soler, Victoria; Díez, José María Abad

doi:10.1093/ije/dyx259

Cited by 67 publications

(71 citation statements)

References 33 publications

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“…ELGH has multiple strengths as a large, population-based study, and its novel, pragmatic design offers opportunities to combine genomic investigation with longitudinal and cross-sectional description of health and disease, and reflects a trend away from traditional epidemiological cohort design 25 .…”

Section: What Are the Main Strengths And Weaknesses?mentioning

confidence: 99%

Cohort Profile: East London Genes & Health (ELGH), a community based population genomics and health study of British-Bangladeshi and British-Pakistani people

Finer

Martin

Khan

et al. 2018

Preprint

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Why was the cohort set up?East London Genes & Health (ELGH) is a community based, long-term study of health and disease in British-Bangladeshi and British-Pakistani people in east London. ELGH has a population-based design incorporating cutting-edge genomics with electronic health record (EHR) data linkage and targeted recall-by-genotype (RbG) studies. ELGH currently has >34,000 volunteers with funding to expand to 100,000 volunteers by 2023. ELGH is an open access data resource, and its research will impact a population at high need and redress the poor representation of non-White ethnic groups in existing population genomic cohorts 1 .Almost a quarter of the world's population, and 5% of the UK population, are of South Asian origin 2 .The risk of coronary heart disease is 3-4 times higher, and type 2 diabetes (T2D) 2-4 times higher in UK South Asians compared with Europeans 3,4 . East London incorporates one of the UK's largest South Asian communities (29% of 1.95 million people), of which 70% are British-Bangladeshi and British-Pakistani, and its population live in high levels of deprivation (Tower Hamlets, Hackney, Barking and Dagenham are the 9 th , 10 th and 11 th most deprived local authorities in England) 5 . Compared to White Europeans, South Asians living in east London have a two-fold greater risk of developing T2D 6 , nearly double the risk of non-alcoholic liver disease 7 , and over double the risk of multimorbidity 8 , with the onset of cardiovascular disease occurring 8 years earlier in men 8 . Determinants of poor cardiometabolic health start early in the life course, with higher rates of overweight and obese children in east London compared to the UK average 5 .Recent genomic advances offer exciting potential to better understand the genetic causation of disease 9 , and to direct pharmacotherapy to rare loss-of-function gene variants 10 . Genetic variation relevant to British-Bangladeshi and British-Pakistani populations, such as autozygosity arising from parental relatedness, is under-researched with regards to potential effects on complex adult phenotypes at a population level 11,12 .ELGH fosters authentic, inclusive, long-term engagement in its research, to deliver future health benefits to the population it represents. Community involvement in ELGH helps prioritise areas for

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Section: What Are the Main Strengths And Weaknesses?mentioning

confidence: 99%

Cohort Profile: East London Genes & Health (ELGH), a community based population genomics and health study of British-Bangladeshi and British-Pakistani people

Finer

Martin

Khan

et al. 2018

Preprint

View full text Add to dashboard Cite

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“…This cohort was conformed in 2011 including 1.25 million people at baseline (approximately 95% of the total inhabitants of the region). A description of the cohort and of the data sources was published elsewhere [20]. We selected for this study all prevalent patients with a diagnosis of HF in their primary or hospital EHRs on 1 January 2015 (i.e., 17,516 patients), and analyzed their demographic and clinical information corresponding to the year of study.…”

Section: Methodsmentioning

confidence: 99%

Sex Differences in Comorbidity, Therapy, and Health Services’ Use of Heart Failure in Spain: Evidence from Real-World Data

Gutiérrez

Poblador‐Plou

Prados‐Torres

et al. 2020

IJERPH

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Heart failure (HF) is becoming increasingly prevalent and affects both men and women. However, women have traditionally been underrepresented in HF clinical trials. In this study, we aimed to analyze sex differences in the comorbidity, therapy, and health services’ use of HF patients. We conducted a cross-sectional study in Aragón (Spain) and described the characteristics of 17,516 patients with HF. Women were more frequent (57.4 vs. 42.6%, p < 0.001) and older (83 vs. 80 years, p < 0.001) than men, and presented a 33% lower risk of 1-year mortality (p < 0.001). Both sexes showed similar disease burdens, and 80% suffered six or more diseases. Some comorbidities were clearly sex-specific, such as arthritis, depression, and hypothyroidism in women, and arrhythmias, ischemic heart disease, and COPD in men. Men were more frequently anti-aggregated and anti-coagulated and received more angiotensin-converting-enzyme (ACE) inhibitors and beta-blockers, whereas women had more angiotensin II antagonists, antiinflammatories, antidepressants, and thyroid hormones dispensed. Men were admitted to specialists (79.0 vs. 70.6%, p < 0.001), hospital (47.0 vs. 38.1%, p < 0.001), and emergency services (57.6 vs. 52.7%, p < 0.001) more frequently than women. Our results highlight the need to conduct future studies to confirm the existence of these differences and of developing separate HF management guidelines for men and women that take into account their sex-specific comorbidity.

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“…Three of five databases participating in the agomelatine PASS were amenable for direct validation of cases within the respective database. [39][40][41] The PPVs ranged from 60% to 84% for the primary PASS outcome (specific end point after exclusion of cases with known competing causes of ALI). 31,42 Case numbers in two of these databases were very small, explaining in part the large variability in observed PPVs.…”

Section: Interpretation Of the Ppv As Compared With Other Workmentioning

confidence: 99%

Validity of hospital ICD‐10‐GM codes to identify acute liver injury in Germany

Timmer

Sordi

Kappen

et al. 2019

Pharmacoepidemiology and Drug

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Purpose Acute liver injury (ALI) is an important adverse drug reaction. We estimated the positive predictive values (PPVs) of ICD‐10‐GM codes of ALI used in an international postauthorisation safety study (PASS). Methods Analyses used routine data (2007 to 2016, adults) from a German academic hospital in a cross‐sectional design. Two algorithms from the PASS were applied to extract potential cases from the hospital information system: specific end point (A) (discharge diagnosis of liver disease–specific codes) and less specific end point (B) (discharge and outpatient‐specific and nonspecific codes suggestive of liver injury). ALI cases were confirmed on the basis of plasma liver enzyme activity elevation. Secondary analysis was performed following exclusion of cases with known cancer, chronic liver, biliary and pancreatic disease, heart failure, and alcohol‐related disorders, as applied in the PASS. Results On the basis of ICD codes: outcome A, 154 cases (143 with case notes and lab data for case verification); outcome B, 485 cases (357 with case notes and lab data). ALI was confirmed in 71 outcome A cases, PPV of 49.7% (95% confidence interval [CI], 41.2%‐58.1%), and 100 outcome B cases, PPV of 28.0% (95% CI, 23.4%‐33.0%). Applying exclusion criteria increased PPV (95% CI) to 62.7% (50.0%‐74.2%) for outcome A and 45.7% (37.2%‐54.3%) for outcome B. Conclusions In safety studies on hepatotoxicity based on routine data using ICD‐10‐GM discharge codes and when validation of potential cases is not feasible, only the more specific codes should be used to describe ALI, and competing diagnoses for liver injury should be excluded to avoid substantial misclassification.

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Cohort Profile: The Epidemiology of Chronic Diseases and Multimorbidity. The EpiChron Cohort Study

Cited by 67 publications

References 33 publications

Cohort Profile: East London Genes & Health (ELGH), a community based population genomics and health study of British-Bangladeshi and British-Pakistani people

Cohort Profile: East London Genes & Health (ELGH), a community based population genomics and health study of British-Bangladeshi and British-Pakistani people

Sex Differences in Comorbidity, Therapy, and Health Services’ Use of Heart Failure in Spain: Evidence from Real-World Data

Validity of hospital ICD‐10‐GM codes to identify acute liver injury in Germany

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