Vascular and metabolic risk factor differences prior to dementia diagnosis: a multidatabase case–control study using European electronic health records

Abstract

ObjectiveThe objective of the study is to compare body mass index (BMI), systolic/diastolic blood pressure (SBP/DBP) and serum total cholesterol levels between dementia cases and controls at multiple time intervals prior to dementia onset, and to test time interval as a modifying factor for these associations.DesignCase–control study.SettingSix European electronic health records databases.Participants291 780 cases at the date of first-recorded dementia diagnosis, compared with 29 170 549 controls randomly selected from the same databases, age matched and sex matched at this index date.ExposureThe following measures were extracted whenever recorded within each dataset: BMI (kg/m2), SBP and DBP (mm Hg) and serum total cholesterol (mmol/L). Levels for each of these variables were defined within six 2-year time intervals over the 12 years prior to the index date.Main outcomesCase–control differences in exposures of interest were modelled for each time period and adjusted for demographic and clinical factors (ischaemic/unspecified stroke, type 2 diabetes mellitus, acute myocardial infarction, hypertension diagnosis, antihypertensive medication, cholesterol-lowering medication). Coefficients and interactions with time period were meta-analysed across the six databases.ResultsMean BMI (coefficient −1.16 kg/m2; 95% CI –1.38 to 0.93) and SBP (−2.83 mm Hg; 95% CI –4.49 to –1.16) were lower in cases at diagnosis, and case–control differences were greater in more recent time periods, as indicated by significant case-x-time interaction and case-x-time-squared interaction terms. Time variations in coefficients for cholesterol levels were less consistent between databases and those for DBP were largely not significant.ConclusionRoutine clinical data show emerging divergence in levels of BMI and SBP prior to the diagnosis of dementia but less evidence for DBP or total cholesterol levels. These divergences should receive at least some consideration in routine dementia risk screening, although underlying mechanisms still require further investigation.

An Italian individual-level data study investigating on the association between air pollution exposure and Covid-19 severity in primary-care setting

“…Currently, about 900 Italian GPs contribute to the IQVIA® LPD, providing data from routinely collected records of ~ 1.2 million patients. The Italian IQVIA® LPD database, established in 1998 by the Italian College of General Practitioners (Società Italiana di Medicina Generale - SIMG), was found to be representative of the Italian general population [ 48 – 50 ] and a reliable source of information in numerous previous studies for several disease areas [ 51 – 57 ].…”

The Genetic Architecture of Alzheimer’s Disease Risk: A Genomic Structural Equation Modelling Study

“…Factor 3 included positive loadings for AD and a subset of risk factors that have complex relationships with AD in that they have all been hypothesised to be disease prodromes as well as causal risk factors [6][7][8][9]38]. Moreover, systolic blood pressure negatively loaded onto this factor, and whereas risk of dementia is associated with higher blood pressure in mid-life, blood pressure declines during the period prior to cognitive symptoms and dementia diagnosis [39][40][41][42]. It is therefore possible that Factor 3 reflects AD prodromes, and hence reverse causality between AD and these traits.…”

“…The only trait that did not pass inclusion into this model was systolic blood pressure due to its lack of communality with the other traits. This may partly be due to the complex relationship with blood pressure at the different stages of AD [39][40][41][42]. AD loaded positively onto the Common Factor but did not display positive loadings for any of the 3 subfactors after the Common Factor was added to the model.…”

An Italian individual-level data study investigating on the association between air pollution exposure and Covid-19 severity in primary-care setting

“…The Italian IQVIA® database, established in 1998 by the Italian College of General Practitioners (Società Italiana di Medicina Generale -SIMG), was found to be representative of the Italian general population (48)- (50) and a reliable source of information in numerous previous studies for several disease areas. ( 51)-( 57) PM 10 daily concentration data detected by the o cial air quality monitoring stations located on the entire Italian territory were retrieved from ARPA Regional websites for the period January 2020 -June 2020 and are publicly available.…”