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Background: Biological ageing is known to vary among different organs within an individual, but the extent to which advanced ageing of specific organs increases the risk of age-related diseases in the same and other organs remains poorly understood., Methods: In this observational cohort study, to assess the biological age of an individual's organs relative to those of same-aged peers, ie, organ age gaps, we collected plasma samples from 6235 middle-aged (age 45-69 years) participants of the Whitehall II prospective cohort study in London, UK, in 1997-99. Age gaps of nine organs were determined from plasma proteins via SomaScan (SomaLogic; Boulder, CO, USA) using the Python package organage. Following this assessment, we tracked participants for 20 years through linkage to national health records. Study outcomes were 45 individual age-related diseases and multimorbidity., Findings: Over 123 712 person-years of observation (mean follow-up 19·8 years [SD 3·6]), after excluding baseline disease cases and adjusting for age, sex, ethnicity, and age gaps in organs other than the one under investigation, individuals with large organ age gaps showed an increased risk of 30 diseases. Six diseases were exclusively associated with accelerated ageing of their respective organ: liver failure (hazard ratio [HR] per SD increment in the organ age gap 2·13 [95% CI 1·41-3·22]), dilated cardiomyopathy (HR 1·65 [1·28-2·12]), chronic heart failure (HR 1·52 [1·40-1·65]), lung cancer (HR 1·29 [1·04-1·59]), agranulocytosis (HR 1·27 [1·07-1·51]), and lymphatic node metastasis (HR 1·23 [1·06-1·43]). 24 diseases were associated with more than one organ age gap or with organ age gaps not directly related to the disease location. Larger age gaps were also associated with elevated HRs of developing two or more diseases affecting different organs within the same individual (ie, multiorgan multimorbidity): 2·03 (1·51-2·74) for the arterial age gap, 1·78 (1·48-2·14) for the kidney age gap, 1·52 (1·38-1·68) for the heart age gap, 1·52 (1·12-2·06) for the brain age gap, 1·43 (1·16-1·78) for the pancreas age gap, 1·37 (1·17-1·61) for the lung age gap, 1·36 (1·26-1·46) for the immune system age gap, and 1·30 (1·18-1·42) for the liver age gap., Interpretation: Advanced proteomic organ ageing is associated with the long-term risk of age-related diseases. In most cases, faster ageing of a specific organ increases susceptibility to morbidity affecting multiple organs., Funding: Wellcome Trust, UK Medical Research Council, National Institute for Aging, Academy of Finland., Competing Interests: Declaration of interests We declare no competing interests. Hamilton Se-Hwee is Co-founder and Scientific Advisor of Tealomics., (Copyright © 2025 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objectives: Rheumatic diseases may impair reproductive success and pregnancy outcomes, but systematic evaluations across diseases are lacking. We conducted a nationwide cohort study to examine the impact of rheumatic diseases on reproductive health measures, comparing the impacts with those of other immune-mediated diseases (IMDs)., Methods: Out of all of the 5 339 804 Finnish citizens, individuals born 1964-1984 and diagnosed with any of the 19 IMDs before age 30 (women) or 35 (men) were matched with 20 controls by birth year, sex, and education. We used data from nationwide health registers to study the impact of IMDs on reproductive health measures, such as reproductive success and, for women, ever having experienced adverse maternal and perinatal outcomes., Results: Several of the rheumatic diseases, particularly SLE, JIA, and seropositive RA, were associated with higher rates of childlessness and fewer children. The risks for pre-eclampsia, newborns being small for gestational age, preterm delivery, non-elective Caesarean sections, and need of neonatal intensive care were increased in many IMDs. Particularly, SLE, SS, type 1 diabetes, and Addison's disease showed >2-fold risks for some of these outcomes. In most rheumatic diseases, moderate (1.1-1.5-fold) risk increases were observed for diverse adverse pregnancy outcomes, with similar effects in IBD, celiac disease, asthma, ITP, and psoriasis., Conclusion: Rheumatic diseases have a broad impact on reproductive health, with effects comparable with that of several other IMDs. Of the rheumatic diseases, SLE and SS conferred the largest risk increases on perinatal adverse event outcomes., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Infections have been associated with the incidence of Alzheimer disease and related dementias, but the mechanisms responsible for these associations remain unclear. Using a multicohort approach, we found that influenza, viral, respiratory, and skin and subcutaneous infections were associated with increased long-term dementia risk. These infections were also associated with region-specific brain volume loss, most commonly in the temporal lobe. We identified 260 out of 942 immunologically relevant proteins in plasma that were differentially expressed in individuals with an infection history. Of the infection-related proteins, 35 predicted volumetric changes in brain regions vulnerable to infection-specific atrophy. Several of these proteins, including PIK3CG, PACSIN2, and PRKCB, were related to cognitive decline and plasma biomarkers of dementia (Aβ 42/40 , GFAP, NfL, pTau-181). Genetic variants that influenced expression of immunologically relevant infection-related proteins, including ITGB6 and TLR5, predicted brain volume loss. Our findings support the role of infections in dementia risk and identify molecular mediators by which infections may contribute to neurodegeneration., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background: Ageing hallmarks, characterising features of cellular ageing, have a role in the pathophysiology of many age-related diseases. We examined whether obesity is associated with an increased risk of developing such hallmark-related diseases., Methods: In this multicohort study, we included people aged 38-72 years with data on weight, height, and waist circumference measured during a clinical examination at baseline between March 13, 2006, and Oct 1, 2010, from the UK Biobank with follow-up until Nov 12, 2021. To test reproducibility of the findings (replication analysis), we used data from people aged 40 years or older included in the Finnish Public Sector study and the Finnish Health and Social Support study who responded to the study surveys, had data on BMI, and were successfully linked to electronic health records from national registers up to Dec 31, 2016. Obesity and clinical characteristics were assessed at baseline. Via linkage to national health records, participants were followed up for 83 diseases related to nine ageing hallmarks (genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication). Outcomes were the first instance of hallmark-related disease, in addition to co-occurrence of three or more hallmark-related diseases and mortality., Findings: 496 530 adults (mean age 57·0 years [SD 8·1]) from the UK Biobank were included in the primary analysis, and 83 249 (mean age 48·2 years [6·4]) adults from the Finnish cohorts were included in the replication analysis. Median follow-up was 12·7 years (IQR 12·0-13·4) in the UK Biobank and 14·0 years (8·0-15·0) in the Finnish cohorts. After adjusting for demographic characteristics, lifestyle factors, and depression, UK Biobank participants with obesity (BMI ≥30·0 kg/m 2 ) had a 1·40 (95% CI 1·38-1·41) times higher hazard ratio for the first hallmark-related disease than those with a healthy weight (BMI 18·5-24·9 kg/m 2 ). The corresponding hazard ratios for three co-occurring diseases were 2·92 (95% CI 2·64-3·22) for deregulated nutrient sensing, 2·73 (2·46-3·02) for telomere attrition, 2·33 (2·10-2·60) for epigenetic alterations, 2·30 (2·14-2·48) for mitochondrial dysfunction, 2·23 (2·04-2·45) for stem cell exhaustion, 2·02 (1·89-2·16) for altered intercellular communication, 2·01 (1·89-2·15) for cellular senescence, 1·83 (1·67-2·00) for loss of proteostasis, and 1·39 (1·27-1·52) for genomic instability. These findings were replicated in the Finnish cohorts. In both studies, the associations between other risk factors (low education, unhealthy dietary factors [available only in the UK Biobank], smoking, high alcohol consumption, physical inactivity, and depression) and hallmark-related diseases were weaker than those with obesity. 45-60% of the excess mortality in people with obesity was attributable to hallmark-related diseases., Interpretation: Obesity might have an important role in the development of diseases associated with cellular ageing. Tackling ageing mechanisms could potentially help to reduce the disease and mortality burden resulting from the obesity epidemic., Funding: Wellcome Trust, UK Medical Research Council, US National Institute on Aging, Academy of Finland, and Finnish Foundation for Cardiovascular Research., Translations: For the German and Finnish translations of the abstract see Supplementary Materials section., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p < 4.9E-5, n up to 7289). Of these, 45 were replicated using SomaScan data, and three were replicated using Olink data at Bonferroni-corrected significance. Enrichment analysis linked the proteins associated with general cognitive function to cell signaling pathways and synapse architecture. Mendelian randomization analysis implicated higher levels of NECTIN2, a protein mediating viral entry into neuronal cells, with higher Alzheimer's disease (AD) risk (p = 2.5E-26). Levels of 14 other protein measures were implicated as consequences of AD susceptibility (p < 2.0E-4). Proteins implicated as causes or consequences of AD susceptibility may provide new insight into the potential relationship between immunity and AD susceptibility as well as potential therapeutic targets., (© 2023. The Author(s).)

A diverse set of biological processes have been implicated in the pathophysiology of Alzheimer's disease (AD) and related dementias. However, there is limited understanding of the peripheral biological mechanisms relevant in the earliest phases of the disease. Here, we used a large-scale proteomics platform to examine the association of 4877 plasma proteins with 25-year dementia risk in 10,981 middle-aged adults. We found 32 dementia-associated plasma proteins that were involved in proteostasis, immunity, synaptic function, and extracellular matrix organization. We then replicated the association between 15 of these proteins and clinically relevant neurocognitive outcomes in two independent cohorts. We demonstrated that 12 of these 32 dementia-associated proteins were associated with cerebrospinal fluid (CSF) biomarkers of AD, neurodegeneration, or neuroinflammation. We found that eight of these candidate protein markers were abnormally expressed in human postmortem brain tissue from patients with AD, although some of the proteins that were most strongly associated with dementia risk, such as GDF15, were not detected in these brain tissue samples. Using network analyses, we found a protein signature for dementia risk that was characterized by dysregulation of specific immune and proteostasis/autophagy pathways in adults in midlife ~20 years before dementia onset, as well as abnormal coagulation and complement signaling ~10 years before dementia onset. Bidirectional two-sample Mendelian randomization genetically validated nine of our candidate proteins as markers of AD in midlife and inferred causality of SERPINA3 in AD pathogenesis. Last, we prioritized a set of candidate markers for AD and dementia risk prediction in midlife.

Background: High-sensitivity cardiac troponin testing is a promising tool for cardiovascular risk prediction, but whether serial testing can dynamically predict risk is uncertain. We evaluated the trajectory of cardiac troponin I in the years prior to a cardiovascular event in the general population, and determine whether serial measurements could track risk within individuals., Methods: In the Whitehall II cohort, high-sensitivity cardiac troponin I concentrations were measured on three occasions over a 15-year period. Time trajectories of troponin were constructed in those who died from cardiovascular disease compared to those who survived or died from other causes during follow up and these were externally validated in the HUNT Study. A joint model that adjusts for cardiovascular risk factors was used to estimate risk of cardiovascular death using serial troponin measurements., Results: In 7,293 individuals (mean 58 ± 7 years, 29.4% women) cardiovascular and non-cardiovascular death occurred in 281 (3.9%) and 914 (12.5%) individuals (median follow-up 21.4 years), respectively. Troponin concentrations increased in those dying from cardiovascular disease with a steeper trajectory compared to those surviving or dying from other causes in Whitehall and HUNT (P interaction  < 0.05 for both). The joint model demonstrated an independent association between temporal evolution of troponin and risk of cardiovascular death (HR per doubling, 1.45, 95% CI,1.33-1.75)., Conclusions: Cardiac troponin I concentrations increased in those dying from cardiovascular disease compared to those surviving or dying from other causes over the preceding decades. Serial cardiac troponin testing in the general population has potential to track future cardiovascular risk., (© 2023. The Author(s).)

Importance: The clinical value of current multifactorial algorithms for individualized assessment of dementia risk remains unclear., Objective: To evaluate the clinical value associated with 4 widely used dementia risk scores in estimating 10-year dementia risk., Design, Setting, and Participants: This prospective population-based UK Biobank cohort study assessed 4 dementia risk scores at baseline (2006-2010) and ascertained incident dementia during the following 10 years. Replication with a 20-year follow-up was based on the British Whitehall II study. For both analyses, participants who had no dementia at baseline, had complete data on at least 1 dementia risk score, and were linked to electronic health records from hospitalizations or mortality were included. Data analysis was conducted from July 5, 2022, to April 20, 2023., Exposures: Four existing dementia risk scores: the Cardiovascular Risk Factors, Aging and Dementia (CAIDE)-Clinical score, the CAIDE-APOE-supplemented score, the Brief Dementia Screening Indicator (BDSI), and the Australian National University Alzheimer Disease Risk Index (ANU-ADRI)., Main Outcomes and Measures: Dementia was ascertained from linked electronic health records. To evaluate how well each score predicted the 10-year risk of dementia, concordance (C) statistics, detection rate, false-positive rate, and the ratio of true to false positives were calculated for each risk score and for a model including age alone., Results: Of 465 929 UK Biobank participants without dementia at baseline (mean [SD] age, 56.5 [8.1] years; range, 38-73 years; 252 778 [54.3%] female participants), 3421 were diagnosed with dementia at follow-up (7.5 per 10 000 person-years). If the threshold for a positive test result was calibrated to achieve a 5% false-positive rate, all 4 risk scores detected 9% to 16% of incident dementia and therefore missed 84% to 91% (failure rate). The corresponding failure rate was 84% for a model that included age only. For a positive test result calibrated to detect at least half of future incident dementia, the ratio of true to false positives ranged between 1 to 66 (for CAIDE-APOE-supplemented) and 1 to 116 (for ANU-ADRI). For age alone, the ratio was 1 to 43. The C statistic was 0.66 (95% CI, 0.65-0.67) for the CAIDE clinical version, 0.73 (95% CI, 0.72-0.73) for the CAIDE-APOE-supplemented, 0.68 (95% CI, 0.67-0.69) for BDSI, 0.59 (95% CI, 0.58-0.60) for ANU-ADRI, and 0.79 (95% CI, 0.79-0.80) for age alone. Similar C statistics were seen for 20-year dementia risk in the Whitehall II study cohort, which included 4865 participants (mean [SD] age, 54.9 [5.9] years; 1342 [27.6%] female participants). In a subgroup analysis of same-aged participants aged 65 (±1) years, discriminatory capacity of risk scores was low (C statistics between 0.52 and 0.60)., Conclusions and Relevance: In these cohort studies, individualized assessments of dementia risk using existing risk prediction scores had high error rates. These findings suggest that the scores were of limited value in targeting people for dementia prevention. Further research is needed to develop more accurate algorithms for estimation of dementia risk.

Background: The excess risk of cardiovascular disease associated with a wide array of infectious diseases is unknown. We quantified the short- and long-term risk of major cardiovascular events in people with severe infection and estimated the population-attributable fraction., Methods: We analyzed data from 331 683 UK Biobank participants without cardiovascular disease at baseline (2006-2010) and replicated our main findings in an independent population from 3 prospective cohort studies comprising 271 329 community-dwelling participants from Finland (baseline 1986-2005). Cardiovascular risk factors were measured at baseline. We diagnosed infectious diseases (the exposure) and incident major cardiovascular events after infections, defined as myocardial infarction, cardiac death, or fatal or nonfatal stroke (the outcome) from linkage of participants to hospital and death registers. We computed adjusted hazard ratios (HRs) and 95% CIs for infectious diseases as short- and long-term risk factors for incident major cardiovascular events. We also calculated population-attributable fractions for long-term risk., Results: In the UK Biobank (mean follow-up, 11.6 years), 54 434 participants were hospitalized for an infection, and 11 649 had an incident major cardiovascular event at follow-up. Relative to participants with no record of infectious disease, those who were hospitalized experienced increased risk of major cardiovascular events, largely irrespective of the type of infection. This association was strongest during the first month after infection (HR, 7.87 [95% CI, 6.36-9.73]), but remained elevated during the entire follow-up (HR, 1.47 [95% CI, 1.40-1.54]). The findings were similar in the replication cohort (HR, 7.64 [95% CI, 5.82-10.03] during the first month; HR, 1.41 [95% CI, 1.34-1.48] during mean follow-up of 19.2 years). After controlling for traditional cardiovascular risk factors, the population-attributable fraction for severe infections and major cardiovascular events was 4.4% in the UK Biobank and 6.1% in the replication cohort., Conclusions: Infections severe enough to require hospital treatment were associated with increased risks for major cardiovascular disease events immediately after hospitalization. A small excess risk was also observed in the long-term, but residual confounding cannot be excluded., Competing Interests: Disclosures Dr Sipilä reports grant support during the conduct of the study from NordForsk (75021), Academy of Finland (311492 and 329202), Helsinki Institute of Life Science, Emil Aaltonen Foundation, and Finnish Medical Foundation. Dr Lindbohm reports grant support during the conduct of the study from the Academy of Finland (339568) and Päivikki and Sakari Sohlberg Foundation. Dr Batty reports grant support from the UK Medical Research Council (MR/P023444/1) and US National Institute on Aging (1R56AG052519-01 and 1R01AG052519-01A1). Dr Vahtera reports grant support from the Academy of Finland (321409 and 329240) and NordForsk (75021). Dr Nyberg reports grant support from NordForsk (75021). Dr Warren-Gash reports support from Wellcome Fellowship (201440/Z/16/Z). Dr Kivimäki reports grant support during the conduct of the study from NordForsk (75021), UK Medical Research Council (MRC S011676/1 and R024227/1), US National Institute on Aging (R01AG056477), Academy of Finland (329202 and 350426), Finnish Foundation for Cardiovascular Research (a86898), Finnish Work Environment Fund (190424), and Wellcome Trust (221854/Z/20/Z). The other authors report no conflicts.

Parents' alcohol use is associated with alcohol use of their adolescent offspring, but does this association extend to the adulthood of the offspring? We examined associations of paternal and maternal problem drinking with lifetime problem drinking of their adult offspring prospectively assessed in a population-based Finnish twin-family cohort (FinnTwin16). Problem drinking (Malmö-modified Michigan Alcoholism Screening Test) was self-reported separately by mothers and fathers when their children were 16. The children reported on an extended lifetime version of the same measure during their mid-twenties (21-28 years) and mid-thirties (31-37 years). 1235 sons and 1461 daughters in mid-twenties and 991 sons and 1278 daughters in mid-thirties had complete data. Correlations between fathers' and their adult children's problem drinking ranged from .12 to .18. For mothers and their adult children, these correlations ranged from .09 to .14. In multivariate models, adjustment for potential confounders had little effect on the observed associations. In this study, parental problem drinking was modestly associated with lifetime problem drinking of their adult children. This association could be detected even when the children had reached the fourth decade of life.

Family history is the standard indirect measure of inherited susceptibility in clinical care, whereas polygenic risk scores (PRSs) have more recently demonstrated potential for more directly capturing genetic risk in many diseases. Few studies have systematically compared how these overlap and complement each other across common diseases. Within FinnGen (N = 306,418), we leverage family relationships, up to 50 years of nationwide registries, and genome-wide genotyping to examine the interplay of family history and genome-wide PRSs. We explore the dynamic for three types of family history across 24 common diseases: first- and second-degree family history and parental causes of death. Covering a large proportion of the burden of non-communicable diseases in adults, we show that family history and PRS are independent and not interchangeable measures, but instead provide complementary information on inherited disease susceptibility. The PRSs explained on average 10% of the effect of first-degree family history, and first-degree family history 3% of PRSs, and PRS effects were independent of both early- and late-onset family history. The PRS stratified the risk similarly in individuals with and without family history. In most diseases, including coronary artery disease, glaucoma, and type 2 diabetes, a positive family history with a high PRS was associated with a considerably elevated risk, whereas a low PRS compensated completely for the risk implied by positive family history. This study provides a catalogue of risk estimates for both family history of disease and PRSs and highlights opportunities for a more comprehensive way of assessing inherited disease risk across common diseases., Competing Interests: Declaration of interests A.P. is a member of the Pfizer Genetics Scientific Advisory Panel., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

The implementation of recommendations for type 2 diabetes (T2D) screening and diagnosis focuses on the measurement of glycated hemoglobin (HbA1c) and fasting glucose. This approach leaves a large number of individuals with isolated impaired glucose tolerance (iIGT), who are only detectable through oral glucose tolerance tests (OGTTs), at risk of diabetes and its severe complications. We applied machine learning to the proteomic profiles of a single fasted sample from 11,546 participants of the Fenland study to test discrimination of iIGT defined using the gold-standard OGTTs. We observed significantly improved discriminative performance by adding only three proteins (RTN4R, CBPM and GHR) to the best clinical model (AUROC = 0.80 (95% confidence interval: 0.79-0.86), P = 0.004), which we validated in an external cohort. Increased plasma levels of these candidate proteins were associated with an increased risk for future T2D in an independent cohort and were also increased in individuals genetically susceptible to impaired glucose homeostasis and T2D. Assessment of a limited number of proteins can identify individuals likely to be missed by current diagnostic strategies and at high risk of T2D and its complications., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

A 27-protein signature has been proposed to predict cardiovascular disease, but its applicability in clinical decision-making remains unclear.

Immune system and blood-brain barrier dysfunction are implicated in the development of Alzheimer's and other dementia-causing diseases, but their causal role remains unknown. We performed Mendelian randomization for 1,827 immune system- and blood-brain barrier-related biomarkers and identified 127 potential causal risk factors for dementia-causing diseases. Pathway analyses linked these biomarkers to amyloid-β, tau and α-synuclein pathways and to autoimmunity-related processes. A phenome-wide analysis using Mendelian randomization-based polygenic risk score in the FinnGen study (n = 339,233) for the biomarkers indicated shared genetic background for dementias and autoimmune diseases. This association was further supported by human leukocyte antigen analyses. In inverse-probability-weighted analyses that simulate randomized controlled drug trials in observational data, anti-inflammatory methotrexate treatment reduced the incidence of Alzheimer's disease in high-risk individuals (hazard ratio compared with no treatment, 0.64, 95% confidence interval 0.49-0.88, P = 0.005). These converging results from different lines of human research suggest that autoimmunity is a modifiable component in dementia-causing diseases., (© 2022. The Author(s).)

Background: It is unclear whether replacing oral glucose tolerance test (OGTT) with hemoglobin A1c (HbA1c) measurement for diagnosing diabetes is justified. We aimed to assess the proportion of OGTT-diagnosed diabetes cases that can be confirmed by HbA1c and to examine whether individuals with OGTT diagnosis but nondiagnostic HbA1c are at higher risk of macrovascular and microvascular disease., Methods: Participants were 5773 men and women from the population-based Whitehall II prospective cohort study in the United Kingdom. New OGTT diabetes cases diagnosed in clinical examinations in 2002 to 2004 and 2007 to 2009 were assessed for HbA1c confirmation (≥6.5%) in these and subsequent clinical examinations in 2012 to 2013 and 2015 to 2016. All participants were followed up for major cardiovascular events through linkage to electronic health records until 2017 and for incident chronic kidney disease (estimated glomerular filtration rate <60 mL·min -1 ·1.73 m -2 ) until the last clinical examination. In analysis of vascular disease risk, new OGTT-diagnosed diabetes cases with and without diagnostic HbA1c and preexisting diabetes cases were compared with diabetes-free participants., Results: Of the 378 (59.3%) participants with OGTT-diagnosed diabetes, 224 were confirmed by HbA1c during 4.1 years (SD, 4.1 years) of follow-up. We recorded 942 cardiovascular events over 12.1 years. After adjustment for nonmodifiable risk factors and compared with the 4997 diabetes-free participants, 371 participants with new HbA1c-confirmed diabetes and 405 participants with preexisting diabetes had increased risk of cardiovascular disease (hazard ratio, 1.53 [95% CI, 1.12-2.10] and 1.85 [95% CI, 1.50-2.28], respectively). The corresponding hazard ratios in the analysis of incident chronic kidney disease (487 cases; follow-up, 6.6 years) were 1.69 (95% CI, 1.09-2.62) for 282 participants with new HbA1c-confirmed diabetes and 1.67 (95% CI, 1.22-2.28) for 276 participants with preexisting diabetes. In both analyses, OGTT cases with nondiagnostic HbA1c (n=149 and 107) had a risk (hazard ratio, 0.99-1.07) similar to that of the diabetes-free population., Conclusions: More than 40% of OGTT-diagnosed diabetes cases were not confirmed by HbA1c during an extended follow-up. However, because these individuals have a risk of cardiovascular disease and chronic kidney disease similar to that of the diabetes-free population, replacement of OGTT with HbA1c-based diagnosis appears justified.

Hypertension is the main modifiable risk factor for cardiovascular morbidity and mortality but discovering molecular mechanisms for targeted treatment has been challenging. Here we investigate associations of blood metabolite markers with hypertension by integrating data from nine intercontinental cohorts from the COnsortium of METabolomics Studies. We included 44,306 individuals with circulating metabolites (up to 813). Metabolites were aligned and inverse normalised to allow intra-platform comparison. Logistic models adjusting for covariates were performed in each cohort and results were combined using random-effect inverse-variance meta-analyses adjusting for multiple testing. We further conducted canonical pathway analysis to investigate the pathways underlying the hypertension-associated metabolites. In 12,479 hypertensive cases and 31,827 controls without renal impairment, we identified 38 metabolites, associated with hypertension after adjusting for age, sex, body mass index, ethnicity, and multiple testing. Of these, 32 metabolite associations, predominantly lipid (steroids and fatty acyls) and organic acids (amino-, hydroxy-, and keto-acids) remained after further adjusting for comorbidities and dietary intake. Among the identified metabolites, 5 were novel, including 2 bile acids, 2 glycerophospholipids, and ketoleucine. Pathway analysis further implicates the role of the amino-acids, serine/glycine, and bile acids in hypertension regulation. In the largest cross-sectional hypertension-metabolomics study to date, we identify 32 circulating metabolites (of which 5 novel and 27 confirmed) that are potentially actionable targets for intervention. Further in-vivo studies are needed to identify their specific role in the aetiology or progression of hypertension.

Background: Heavy alcohol consumption increases the risk of several chronic diseases. In this multicohort study, we estimated the number of life-years without major chronic diseases according to different characteristics of alcohol use., Methods: In primary analysis, we pooled individual-level data from up to 129,942 adults across 12 cohort studies with baseline data collection on alcohol consumption, drinking patterns, and history between 1986 and 2005 (the IPD-Work Consortium). Self-reported alcohol consumption was categorised according to UK guidelines - non-drinking (never or former drinkers); moderate consumption (1-14 units); heavy consumption (>14 units per week). We further subdivided moderate and heavy drinkers by binge drinking pattern (alcohol-induced loss of consciousness). In addition, we assessed problem drinking using linked data on hospitalisations due to alcohol abuse or poisoning. Follow-up for chronic diseases for all participants included incident type 2 diabetes, coronary heart disease, stroke, cancer, and respiratory disease (asthma and chronic obstructive pulmonary disease) as ascertained via linkage to national morbidity and mortality registries, repeated medical examinations, and/or self-report. We estimated years lived without any of these diseases between 40 and 75 years of age according to sex and characteristics of alcohol use. We repeated the main analyses using data from 427,621 participants in the UK Biobank cohort study., Findings: During 1·73 million person-years at risk, 22,676 participants in IPD-Work cohorts developed at least one chronic condition. From age 40 to 75 years, never-drinkers [men: 29·3 (95%CI 27·9-30·8) years, women 29·8 (29·2-30·4) years)] and moderate drinkers with no binge drinking habit [men 28·7 (28·4-29·0) years, women 29·6 (29·4-29·7) years] had the longest disease-free life span. A much shorter disease-free life span was apparent in participants who experienced alcohol poisoning [men 23·4 (20·9-26·0) years, women 24·0 (21·4-26·5) years] and those with self-reported heavy overall consumption and binge drinking [men: 26·0 (25·3-26·8), women 27·5 (26·4-28·5) years]. The pattern of results for alcohol poisoning and self-reported alcohol consumption was similar in UK Biobank. In IPD-Work and UK Biobank, differences in disease-free years between self-reported moderate drinkers and heavy drinkers were 1·5 years or less., Interpretation: Individuals with alcohol poisonings or heavy self-reported overall consumption combined with a binge drinking habit have a marked 3- to 6-year loss in healthy longevity. Differences in disease-free life between categories of self-reported weekly alcohol consumption were smaller., Funding: Medical Research Council, National Institute on Aging, NordForsk, Academy of Finland, Finnish Work Environment Fund., Competing Interests: No disclosures were reported., (© 2022 The Author(s).)

Background: The accumulation of disparate diseases in complex multimorbidity makes prevention difficult if each disease is targeted separately. We aimed to examine obesity as a shared risk factor for common diseases, determine associations between obesity-related diseases, and examine the role of obesity in the development of complex multimorbidity (four or more comorbid diseases)., Methods: We did an observational study and used pooled prospective data from two Finnish cohort studies (the Health and Social Support Study and the Finnish Public Sector Study) comprising 114 657 adults aged 16-78 years at study entry (1998-2013). A cohort of 499 357 adults (aged 38-73 years at study entry; 2006-10) from the UK Biobank provided replication in an independent population. BMI and clinical characteristics were assessed at baseline. BMIs were categorised as obesity (≥30·0 kg/m 2 ), overweight (25·0-29·9 kg/m 2 ), healthy weight (18·5-24·9 kg/m 2 ), and underweight (<18·5 kg/m 2 ). Via linkage to national health records, participants were followed-up for death and diseases diagnosed according to the International Classification of Diseases 10th Revision (ICD-10). Hazard ratios (HRs) with 95% CIs and population attributable fractions (PAFs) for associations between BMI and multimorbidity were calculated., Findings: Mean follow-up duration was 12·1 years (SD 3·8) in the Finnish cohorts and 11·8 years (1·7) in the UK Biobank cohort. Obesity was associated with 21 non-overlapping cardiometabolic, digestive, respiratory, neurological, musculoskeletal, and infectious diseases after Bonferroni multiple testing adjustment and ignoring HRs of less than 1·50. Compared with healthy weight, the confounder-adjusted HR for obesity was 2·83 (95% CI 2·74-2·93; PAF 19·9% [95% CI 19·3-20·5]) for developing at least one obesity-related disease, 5·17 (4·84-5·53; 34·4% [33·2-35·5]) for two diseases, and 12·39 (9·26-16·58; 55·2% [50·9-57·5]) for complex multimorbidity. The proportion of participants of healthy weight with complex multimorbidity by age 75 years was observed by age 55 years in participants with obesity, and degree of obesity was associated with complex multimorbidity in a dose-response relationship. Compared with obesity, the association between overweight and complex multimorbidity was more modest (HR 2·67, 95% CI 1·94-3·68; PAF 13·3% [95% CI 9·6-16·3]). The same pattern of results was observed in the UK Biobank cohort., Interpretation: Obesity is associated with diverse, increasing disease burdens, and might represent an important target for multimorbidity prevention that avoids the complexities of multitarget preventive regimens., Funding: Wellcome Trust, Medical Research Council, National Institute on Aging., Competing Interests: Declaration of interests TS reports cooperation (consultative, educational, research) with companies and entities interested in cardiovascular prevention and diabetes (not directly obesity), including Amgen, Pfizer, MSD, Orion Pharma, Sanofi, Sankyo, and NovoNordisk. All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Plasma proteins affect biological processes and are common drug targets but their role in the development of Alzheimer's disease and related dementias remains unclear. We examined associations between 4953 plasma proteins and cognitive decline and risk of dementia in two cohort studies with 20-year follow-ups., Methods: In the Whitehall II prospective cohort study proteins were measured using SOMAscan technology. Cognitive performance was tested five times over 20 years. Linkage to electronic health records identified incident dementia. The results were replicated in the Atherosclerosis Risk in Communities (ARIC) study., Results: Fifteen non-amyloid/non-tau-related proteins were associated with cognitive decline and dementia, were consistently identified in both cohorts, and were not explained by known dementia risk factors. Levels of six of the proteins are modifiable by currently approved medications for other conditions., Discussion: This study identified several plasma proteins in dementia-free people that are associated with long-term risk of cognitive decline and dementia., (© 2021 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Aortic pulse wave velocity is a noninvasive measure of aortic stiffness and arterial aging. Its current value in cardiovascular risk estimation practice is unknown. We aimed to establish whether aortic pulse wave velocity identified individuals with higher risk of incident major adverse cardiovascular events and improved performance of the American Heart Association/American College of Cardiology atherosclerotic cardiovascular disease risk score., Methods: This prospective analysis included 3837 Whitehall II cohort participants screened in 2008 to 2009, and followed for 11.7 years (mean=10.3, SD=1.81), without history of stroke, myocardial infarction, or coronary heart disease., Results: Mean age of the sample was 65.0 years (SD=5.6), 2831 participants (73.8%) were male and mean atherosclerotic cardiovascular disease risk score was 13.8%. At the end of follow-up, 411 individuals (10.7%) had suffered a major cardiovascular event. Those in the highest aortic pulse wave velocity quartile were at high risk (hazard ratio, 2.99 [95% CI, 2.25-3.97]) and reached the threshold for statin medication (7.5% risk) after 5 years whereas others reached it after 10 years (difference P <0.001). The addition of aortic pulse wave velocity to the risk score improved the C statistic (0.68 versus 0.67, P =0.03) and net reclassification index (4.6%, P =0.04 and 11.3%, P =0.02)., Conclusions: Our results show that aortic stiffness predicted major adverse cardiovascular events in a cohort of elderly individuals, improving the performance of a widely used cardiovascular disease risk estimator. Aortic pulse wave velocity measurement is scalable, radiation-free, and easy to perform. Further studies on its applicability in cardiovascular disease risk assessment in primary care settings are needed.

Background: Infections have been hypothesised to increase the risk of dementia. Existing studies have included a narrow range of infectious diseases, relied on short follow-up periods, and provided little evidence for whether the increased risk is limited to specific dementia subtypes or attributable to specific microbes rather than infection burden. We aimed to compare the risk of Alzheimer's disease and other dementias across a wide range of hospital-treated bacterial and viral infections in two large cohorts with long follow-up periods., Methods: In this large, multicohort, observational study, the analysis was based on a primary cohort consisting of pooled individual-level data from three prospective cohort studies in Finland (the Finnish Public Sector study, the Health and Social Support study, and the Still Working study) and an independent replication cohort from the UK Biobank. Community-dwelling adults (≥18 years) with no dementia at study entry were included. Follow-up was until Dec 31, 2012, in the Health and Social Support study, Dec 31, 2016, in the public sector study and the Still Working study, and Feb 7, 2018, in the replication cohort. Through record linkage to national hospital inpatient registers, we ascertained exposure to 925 infectious diseases (using the International Classification of Diseases 10th Revision codes) before dementia onset, and identified incident dementia from hospital records, medication reimbursement entitlements, and death certificates. Hazard ratios (HRs) for the associations of each infectious disease or disease group (index infection) with incident dementia were assessed by use of Cox proportional hazards models. We then repeated the analysis after excluding incident dementia cases that occurred during the first 10 years after initial hospitalisation due to the index infection., Findings: From March 1, 1986, to Jan 1, 2005, 260 490 people were included in the primary cohort, and from Dec 19, 2006, to Oct 1, 2010, 485 708 people were included in the replication cohort. In the primary cohort analysis based on 3 947 046 person-years at risk (median follow-up 15·4 years [IQR 9·8-21·0]), 77 108 participants had at least one hospital-treated infection before dementia onset and 2768 developed dementia. Hospitalisation for any infectious disease was associated with increased dementia risk in the primary cohort (adjusted HR [aHR] 1·48 [95% CI 1·37-1·60]) and replication cohort (2·60 [2·38-2·83]). The association remained when analyses were restricted to new dementia cases that occurred more than 10 years after infection (aHR 1·22 [95% CI 1·09-1·36] in the primary cohort, the replication cohort had insufficient follow-up data for this analysis), and when comorbidities and other dementia risk factors were considered. There was evidence of a dose-response association between the number of episodes of hospital-treated infections and dementia risk in both cohorts (p trend =0·0007). Although the greatest dementia risk was seen for central nervous system (CNS) infections versus no infection (aHR 3·01 [95% CI 2·07-4·37]), excess risk was also evident for extra-CNS infections (1·47 [1·36-1·59]). Although we found little difference in the infection-dementia association by type of infection, associations were stronger for vascular dementia than for Alzheimer's disease (aHR 2·09 [95% CI 1·59-2·75] versus aHR 1·20 [1·08-1·33] in the primary cohort and aHR 3·28 [2·65-4·04] versus aHR 1·80 [1·53-2·13] in the replication cohort)., Interpretation: Severe infections requiring hospital treatment are associated with long-term increased risk of dementia, including vascular dementia and Alzheimer's disease. This association is not limited to CNS infections, suggesting that systemic effects are sufficient to affect the brain. The absence of infection specificity combined with evidence of dose-response relationships between infectious disease burden and dementia risk support the hypothesis that increased dementia risk is driven by general inflammation rather than specific microbes., Funding: UK Medical Research Council, US National Institute on Aging, Wellcome Trust, NordForsk, Academy of Finland, and Helsinki Institute of Life Science., Competing Interests: Declaration of interests PNS reports funding from the Helsinki Institute of Life Science, NordForsk, and the Academy of Finland during the conduct of the study, and from the Finnish Foundation for Alcohol Studies outside of the submitted work. JVL reports funding from the Academy of Finland during the conduct of the study. STN reports funding from NordForsk during the conduct of the study. TES reports funding from the Academy of Finland; consultation fees from Servier, Orion, and Novartis outside the submitted work; and is a member of the European Geriatric Medicine Society special interest group on Cardiovascular Medicine in Older People and Diabetes in older people. MK reports funding from the Helsinki Institute of Life Science, the Academy of Finland, NordForsk, UK Medical Research Council, the US National Institute on Aging, and the Wellcome Trust during the conduct of the study. CH, JV, and ME report funding from the Academy of Finland. All other authors declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objective: To study whether the incidence of subarachnoid hemorrhage (SAH) varies between geographic regions of Finland., Methods: By utilizing the nationwide Causes of Death and Hospital Discharge Registers, we identified all first-ever, hospitalized, and sudden-death (dying before hospitalization) SAH events in Finland between 1998 and 2017. Based on the patients' home residence, we divided SAHs into 5 geographic regions: southern, central, western, eastern, and northern Finland. We calculated crude and European age-standardized (European Standard Population [ESP] 2013) SAH incidence rates for each region and used a Poisson regression model to calculate age-, sex-, and calendar year-adjusted incidence rate ratios (IRRs) and 95% confidence intervals for regional and time-dependent differences., Results: During the total 106,510,337 cumulative person-years, we identified 9,443 first-ever SAH cases, of which 24% resulted in death before hospitalization. As compared to western Finland, where the SAH incidence was the lowest (7.4 per 100,000 persons), the ESP-standardized SAH incidence was 1.4 times higher in eastern (10.2 per 100,000 persons; adjusted IRR, 1.37 [1.27-1.47]) and northern Finland (10.4 per 100,000 persons; adjusted IRR, 1.40 [1.30-1.51]). These differences were similar when men and women were analyzed independently. Although SAH incidence rates decreased in all 5 regions over 2 decades, the rate of decrease varied significantly by region., Conclusion: SAH incidence appears to vary substantially by region in Finland. Our results suggest that regional SAH studies can identify high-risk subpopulations, but can also considerably over- or underestimate incidence on a nationwide level., (© 2021 American Academy of Neurology.)

Background: Evaluation of cardiovascular disease risk in primary care, which is recommended every 5 years in middle-aged and older adults (typical age range 40-75 years), is based on risk scores, such as the European Society of Cardiology Systematic Coronary Risk Evaluation (SCORE) and American College of Cardiology/American Heart Association Atherosclerotic Cardiovascular Disease (ASCVD) algorithms. This evaluation currently uses only the most recent risk factor assessment. We aimed to examine whether 5-year changes in SCORE and ASCVD risk scores are associated with future cardiovascular disease risk., Methods: We analysed data from the Whitehall II longitudinal, prospective cohort study for individuals with no history of stroke, myocardial infarction, coronary artery bypass graft, percutaneous coronary intervention, definite angina, heart failure, or peripheral artery disease. Participants underwent clinical examinations in 5-year intervals between Aug 7, 1991, and Dec 6, 2016, and were followed up for incident cardiovascular disease until Oct 2, 2019. Levels of, and 5-year changes in, cardiovascular disease risk were assessed using the SCORE and ASCVD risk scores and were analysed as predictors of cardiovascular disease. Harrell's C index, continuous net reclassification improvement, the Akaike information criterion, and calibration analysis were used to assess whether incorporating change in risk scores into a model including only a single risk score assessment improved the predictive performance. We assessed the levels of, and 5-year changes in, SCORE and ASCVD risk scores as predictors of cardiovascular disease and disease-free life-years using Cox proportional hazards and flexible parametric survival models., Findings: 7574 participants (5233 [69·1%] men, 2341 [30·9%] women) aged 40-75 years were included in analyses of risk score change between April 24, 1997, and Oct 2, 2019. During a mean follow-up of 18·7 years (SD 5·5), 1441 (19·0%; 1042 [72·3%] men and 399 [27·7%] women) participants developed cardiovascular disease. Adding 5-year change in risk score to a model that included only a single risk score assessment improved model performance according to Harrell's C index (from 0·685 to 0·690, change 0·004 [95% CI 0·000 to 0·008] for SCORE; from 0·699 to 0·700, change 0·001 [0·000 to 0·003] for ASCVD), the Akaike information criterion (from 17 255 to 17 200, change -57 [95% CI -97 to -13] for SCORE; from 14 739 to 14 729, change -10 [-28 to 7] for ASCVD), and the continuous net reclassification index (0·353 [95% CI 0·234 to 0·447] for SCORE; 0·232 [0·030 to 0·344] for ASCVD). Both favourable and unfavourable changes in SCORE and ASCVD were associated with cardiovascular disease risk and disease-free life-years. The associations were seen in both sexes and all age groups up to the age of 75 years. At the age of 45 years, each 2-unit improvement in risk scores was associated with an additional 1·3 life-years (95% CI 0·4 to 2·2) free of cardiovascular disease for SCORE and an additional 0·9 life-years (95% CI 0·5 to 1·3) for ASCVD. At age 65 years, this same improvement was associated with an additional 0·4 life-years (95% CI 0·0 to 0·7) free of cardiovascular disease for SCORE and 0·3 life-years (95% CI 0·1 to 0·5) for ASCVD. These models were developed into an interactive calculator, which enables estimation of the number of cardiovascular disease-free life-years for an individual as a function of two risk score measurements., Interpretation: Changes in the SCORE and ASCVD risk scores over time inform cardiovascular disease risk prediction beyond a single risk score assessment. Repeat data might allow more accurate cardiovascular risk stratification and strengthen the evidence base for decisions on preventive interventions., Funding: UK Medical Research Council, British Heart Foundation, Wellcome Trust, and US National Institute on Aging., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Observational studies have identified a link between unfavourable neighbourhood characteristics and increased risk of morbidity, but it is unclear whether changes in neighbourhoods affect future disease risk. We used a data-driven approach to assess the impact of neighbourhood modification on 79 health outcomes., Methods: In this prospective cohort study, we used pooled, individual-level data from two Finnish cohort studies: the Health and Social Support study and the Finnish Public Sector study. Neighbourhood characteristics (mean educational level, median income, and employment rate of residents, and neighbourhood green space) and individual lifestyle factors of community-dwelling individuals were assessed at baseline (at different waves starting between 1998 and 2013). We repeated assessment of neighbourhood characteristics and lifestyle factors approximately 5 years from each baseline assessment, after which follow-up began for health conditions diagnosed according to the WHO International Classification of Diseases for 79 common health conditions using linkage to electronic health records. We used Cox proportional hazard regression models to compute adjusted hazard ratios (HRs) of incident disease associated with neighbourhood characteristics and changes in neighbourhood characteristics over time and logistic regression analysis to compute adjusted odds of association between changes in neighbourhood characteristics and individual lifestyle factors., Findings: 114 786 individuals (87 012 [75·8%] women; mean age 44·4 years [SD 11·1]) had complete data and were included in this cohort study. During 1·17 million person-years at risk, we recorded 164 368 new-onset health conditions and 3438 deaths. Favourable changes in neighbourhood characteristics were associated with reduced risk of all-cause mortality and incidence of 19 specific health conditions. Unfavourable changes were correspondingly associated with increased risk of mortality and 27 specific health conditions. Among participants who did not move residence during the observation period, relative to individuals who continually lived in disadvantaged neighbourhoods, those who experienced favourable modifications in neighbourhood characteristics had a lower risk of future diabetes (HR 0·84, 95% CI 0·75-0·93), stroke (0·49, 0·29-0·83), skin disease (0·72, 0·53-0·97), and osteoarthritis (0·87, 0·77-0·99). Living in a neighbourhood with improving characteristics was also associated with improvements in individual-level health-related lifestyle factors. Among participants who lived in advantaged residential environments at baseline, unfavourable changes in neighbourhood characteristics were associated with an increased risk of diabetes, stroke, skin disease, and osteoarthritis compared with individuals who lived in advantaged neighbourhoods throughout the study period., Interpretation: Favourable modifications to residential neighbourhoods showed robust, longitudinal associations with a range of improvements in health outcomes, including improved health behaviours and reduced risk of cardiometabolic, infectious, and orthopaedic conditions., Funding: UK Medical Research Council, US National Institute on Aging, NordForsk, and Academy of Finland., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Conventional risk factors targeted by prevention (e.g., low education, smoking, and obesity) are associated with a 1.2- to 2-fold increased risk of dementia. It is unclear whether having a physical disease is an equally important risk factor for dementia., Methods: In this exploratory multicohort study of 283,414 community-dwelling participants, we examined 22 common hospital-treated physical diseases as risk factors for dementia., Results: During a median follow-up of 19 years, a total of 3416 participants developed dementia. Those who had erysipelas (hazard ratio = 1.82; 95% confidence interval = 1.53 to 2.17), hypothyroidism (1.94; 1.59 to 2.38), myocardial infarction (1.41; 1.20 to 1.64), ischemic heart disease (1.32; 1.18 to 1.49), cerebral infarction (2.44; 2.14 to 2.77), duodenal ulcers (1.88; 1.42 to 2.49), gastritis and duodenitis (1.82; 1.46 to 2.27), or osteoporosis (2.38; 1.75 to 3.23) were at a significantly increased risk of dementia. These associations were not explained by conventional risk factors or reverse causation., Discussion: In addition to conventional risk factors, several physical diseases may increase the long-term risk of dementia., (© 2020 The Authors. Alzheimer's & Dementia published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association.)

Background: Research on the prevalence of smokers in patients with brain arteriovenous malformation (AVM) remains nonexistent, even though smoking is a well-known risk factor for intracranial aneurysms., Objective: To examine the prevalence and smoking habits of AVM patients., Methods: Data on smoking habits were collected with a quality-of-life questionnaire mailed in 2016 to all patients in our large AVM database. These smoking data were supplemented with registry data derived from medical records. The prevalence of smokers was compared to that of the general population, derived from statistics of National Institute for Health and Welfare. Logit transformation of proportions and Students t distribution were used to calculate the 95% CIs for prevalence estimates., Results: Of the 384 patients aged over 18 yr on admission, 277 (72.1%) returned the questionnaires in 2016. When compared to age, sex, and admission year matched general population, the proportion of smokers in AVM patients was 48% (CI = 41%-55%) and 19% (CI = 16%-21%) in the general population. The difference increased in older age groups; in those aged 65 to 77 yr, the percentage of smokers reached 73% (CI = 46%-90%), while the corresponding percentage in the general population was 7% (CI = 5%-9%)., Conclusion: We observed considerably higher rates of smoking among AVM patients when compared to age, sex, and admission year matched general population. Our results suggest that in the development of AVMs, the role played by nicotine and other substances in tobacco smoke should be examined. Cigarette smoking could potentially be a common cerebrovascular risk factor., (Copyright © 2020 by the Congress of Neurological Surgeons.)

Importance: Evidence on alcohol consumption as a risk factor for dementia usually relates to overall consumption. The role of alcohol-induced loss of consciousness is uncertain., Objective: To examine the risk of future dementia associated with overall alcohol consumption and alcohol-induced loss of consciousness in a population of current drinkers., Design, Setting, and Participants: Seven cohort studies from the UK, France, Sweden, and Finland (IPD-Work consortium) including 131 415 participants were examined. At baseline (1986-2012), participants were aged 18 to 77 years, reported alcohol consumption, and were free of diagnosed dementia. Dementia was examined during a mean follow-up of 14.4 years (range, 12.3-30.1). Data analysis was conducted from November 17, 2019, to May 23, 2020., Exposures: Self-reported overall consumption and loss of consciousness due to alcohol consumption were assessed at baseline. Two thresholds were used to define heavy overall consumption: greater than 14 units (U) (UK definition) and greater than 21 U (US definition) per week., Main Outcomes and Measures: Dementia and alcohol-related disorders to 2016 were ascertained from linked electronic health records., Results: Of the 131 415 participants (mean [SD] age, 43.0 [10.4] years; 80 344 [61.1%] women), 1081 individuals (0.8%) developed dementia. After adjustment for potential confounders, the hazard ratio (HR) was 1.16 (95% CI, 0.98-1.37) for consuming greater than 14 vs 1 to 14 U of alcohol per week and 1.22 (95% CI, 1.01-1.48) for greater than 21 vs 1 to 21 U/wk. Of the 96 591 participants with data on loss of consciousness, 10 004 individuals (10.4%) reported having lost consciousness due to alcohol consumption in the past 12 months. The association between loss of consciousness and dementia was observed in men (HR, 2.86; 95% CI, 1.77-4.63) and women (HR, 2.09; 95% CI, 1.34-3.25) during the first 10 years of follow-up (HR, 2.72; 95% CI, 1.78-4.15), after excluding the first 10 years of follow-up (HR, 1.86; 95% CI, 1.16-2.99), and for early-onset (<65 y: HR, 2.21; 95% CI, 1.46-3.34) and late-onset (≥65 y: HR, 2.25; 95% CI, 1.38-3.66) dementia, Alzheimer disease (HR, 1.98; 95% CI, 1.28-3.07), and dementia with features of atherosclerotic cardiovascular disease (HR, 4.18; 95% CI, 1.86-9.37). The association with dementia was not explained by 14 other alcohol-related conditions. With moderate drinkers (1-14 U/wk) who had not lost consciousness as the reference group, the HR for dementia was twice as high in participants who reported having lost consciousness, whether their mean weekly consumption was moderate (HR, 2.19; 95% CI, 1.42-3.37) or heavy (HR, 2.36; 95% CI, 1.57-3.54)., Conclusions and Relevance: The findings of this study suggest that alcohol-induced loss of consciousness, irrespective of overall alcohol consumption, is associated with a subsequent increase in the risk of dementia.

Importance: It is well established that selected lifestyle factors are individually associated with lower risk of chronic diseases, but how combinations of these factors are associated with disease-free life-years is unknown., Objective: To estimate the association between healthy lifestyle and the number of disease-free life-years., Design, Setting, and Participants: A prospective multicohort study, including 12 European studies as part of the Individual-Participant-Data Meta-analysis in Working Populations Consortium, was performed. Participants included 116 043 people free of major noncommunicable disease at baseline from August 7, 1991, to May 31, 2006. Data analysis was conducted from May 22, 2018, to January 21, 2020., Exposures: Four baseline lifestyle factors (smoking, body mass index, physical activity, and alcohol consumption) were each allocated a score based on risk status: optimal (2 points), intermediate (1 point), or poor (0 points) resulting in an aggregated lifestyle score ranging from 0 (worst) to 8 (best). Sixteen lifestyle profiles were constructed from combinations of these risk factors., Main Outcomes and Measures: The number of years between ages 40 and 75 years without chronic disease, including type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease., Results: Of the 116 043 people included in the analysis, the mean (SD) age was 43.7 (10.1) years and 70 911 were women (61.1%). During 1.45 million person-years at risk (mean follow-up, 12.5 years; range, 4.9-18.6 years), 17 383 participants developed at least 1 chronic disease. There was a linear association between overall healthy lifestyle score and the number of disease-free years, such that a 1-point improvement in the score was associated with an increase of 0.96 (95% CI, 0.83-1.08) disease-free years in men and 0.89 (95% CI, 0.75-1.02) years in women. Comparing the best lifestyle score with the worst lifestyle score was associated with 9.9 (95% CI 6.7-13.1) additional years without chronic diseases in men and 9.4 (95% CI 5.4-13.3) additional years in women (P < .001 for dose-response). All of the 4 lifestyle profiles that were associated with the highest number of disease-free years included a body-mass index less than 25 (calculated as weight in kilograms divided by height in meters squared) and at least 2 of the following factors: never smoking, physical activity, and moderate alcohol consumption. Participants with 1 of these lifestyle profiles reached age 70.3 (95% CI, 69.9-70.8) to 71.4 (95% CI, 70.9-72.0) years disease free depending on the profile and sex., Conclusions and Relevance: In this multicohort analysis, various healthy lifestyle profiles appeared to be associated with gains in life-years without major chronic diseases.

Polygenic risk scores (PRSs) have shown promise in predicting susceptibility to common diseases 1-3 . We estimated their added value in clinical risk prediction of five common diseases, using large-scale biobank data (FinnGen; n = 135,300) and the FINRISK study with clinical risk factors to test genome-wide PRSs for coronary heart disease, type 2 diabetes, atrial fibrillation, breast cancer and prostate cancer. We evaluated the lifetime risk at different PRS levels, and the impact on disease onset and on prediction together with clinical risk scores. Compared to having an average PRS, having a high PRS contributed 21% to 38% higher lifetime risk, and 4 to 9 years earlier disease onset. PRSs improved model discrimination over age and sex in type 2 diabetes, atrial fibrillation, breast cancer and prostate cancer, and over clinical risk in type 2 diabetes, breast cancer and prostate cancer. In all diseases, PRSs improved reclassification over clinical thresholds, with the largest net reclassification improvements for early-onset coronary heart disease, atrial fibrillation and prostate cancer. This study provides evidence for the additional value of PRSs in clinical disease prediction. The practical applications of polygenic risk information for stratified screening or for guiding lifestyle and medical interventions in the clinical setting remain to be defined in further studies.

Background: Socioeconomic disadvantage is a risk factor for many diseases. We characterised cascades of these conditions by using a data-driven approach to examine the association between socioeconomic status and temporal sequences in the development of 56 common diseases and health conditions., Methods: In this multi-cohort study, we used data from two Finnish prospective cohort studies: the Health and Social Support study and the Finnish Public Sector study. Our pooled prospective primary analysis data comprised 109 246 Finnish adults aged 17-77 years at study entry. We captured socioeconomic status using area deprivation and education at baseline (1998-2013). Participants were followed up for health conditions diagnosed according to the WHO International Classification of Diseases until 2016 using linkage to national health records. We tested the generalisability of our findings with an independent UK cohort study-the Whitehall II study (9838 people, baseline in 1997, follow-up to 2017)-using a further socioeconomic status indicator, occupational position., Findings: During 1 110 831 person-years at risk, we recorded 245 573 hospitalisations in the Finnish cohorts; the corresponding numbers in the UK study were 60 946 hospitalisations in 186 572 person-years. Across the three socioeconomic position indicators and after adjustment for lifestyle factors, compared with more advantaged groups, low socioeconomic status was associated with increased risk for 18 (32·1%) of the 56 conditions. 16 diseases formed a cascade of inter-related health conditions with a hazard ratio greater than 5. This sequence began with psychiatric disorders, substance abuse, and self-harm, which were associated with later liver and renal diseases, ischaemic heart disease, cerebral infarction, chronic obstructive bronchitis, lung cancer, and dementia., Interpretation: Our findings highlight the importance of mental health and behavioural problems in setting in motion the development of a range of socioeconomically patterned physical illnesses. Policy and health-care practice addressing psychological health issues in social context and early in the life course could be effective strategies for reducing health inequalities., Funding: UK Medical Research Council, US National Institute on Aging, NordForsk, British Heart Foundation, Academy of Finland, and Helsinki Institute of Life Science., (Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objective: Two recent hospital-based studies have reported that both smoking and hypertension-the 2 most important risk factors for aneurysmal subarachnoid hemorrhage (aSAH)-may improve survival after aSAH. We tested the hypothesis that a higher case fatality among smokers and hypertensive individuals after aSAH contributes to these paradoxical findings., Methods: We followed 65,521 population-based FINRISK participants during 1.52 million person-years and identified 445 first-ever hospitalized aSAHs and 98 sudden-death aSAHs occurring between 1974 and 2014. We measured risk factors prior to disease onset in the cohort surveys, and confirmed, among all sudden-death aSAHs, 80% by extensive (including the brain) forensic autopsy; the remaining 20% were based on clinical examination (CT of the head, spinal tap, or both). The Cox proportional hazards model estimated survival curves., Results: Analyses repeating the protocol of the 2 recent hospital-based studies again showed improved survival among smokers and those with hypertension. Conversely, in analyses including more accurate risk factor measurements and including patients with sudden-death aSAH who never reached a hospital, these paradoxical results were reversed. Smokers had reduced survival compared to that of never-smokers ( p = 0.04), and those with high systolic blood pressure (SBP) (≥160 mm Hg) had reduced survival when compared to survival of those with SBP <160 mm Hg ( p = 0.05)., Conclusions: After aSAH, smoking and hypertension were associated with worse survival. The earlier and opposite findings are likely explained by inadequate risk factor measurement and by survival bias inherent to hospital-based risk factor studies lacking information on out-of-hospital deaths confirmed by autopsy., (© 2019 American Academy of Neurology.)

Benefit of physical activity in prevention of aneurysmal subarachnoid hemorrhage (SAH) is unclear. We aimed to clarify this by studying how different types of physical activity associate with SAH risk. By following 65 521 population-based FINRISK participants prospectively from medical and autopsy registries since 1972 until 2014, we detected 543 incident SAHs. At baseline, we measured leisure-time physical activity (LTPA), occupational physical activity (OPA), and commuting physical activity (CPA) levels. The Cox model adjusted for all well-known SAH risk factors and for socioeconomic status, provided hazard ratios (HRs) for physical activity variables. Every 30-minute increase in weekly LTPA decreased SAH risk linearly in men and women HR = 0.95 (95% CI = 0.90-1.00). CPA reduced SAH risk as well, but the association diminished as participants retired. In contrast, individuals with moderate (1.41, 1.04-1.92) and high OPA (1.34, 0.99-1.81) had elevated SAH risk. Protective association of LTPA persisted in all age and hypertension groups, and was even greater in current smokers 0.88 (0.81-0.96) than non-smokers (p = 0.04 for difference). Commuting and leisure time physical activity seem to reduce SAH risk in men and women and is most beneficial for smokers. Future intervention studies should investigate whether physical activity can reduce the rupture risk of intracranial aneurysms.

Background: Frailty is an important geriatric syndrome, but little is known about its development in the years preceding onset of the syndrome. The aim of this study was to examine the progression of frailty and compare the trajectories of each frailty component prior to frailty onset., Methods: Repeat data were from two cohort studies: the Longitudinal Aging Study Amsterdam (n = 1440) with a 15-year follow-up and the InCHIANTI Study (n = 998) with a 9-year follow-up. Participants were classified as frail if they had >3 frailty components (exhaustion, slowness, physical inactivity, weakness, and weight loss). Transitions between frailty components were examined with multistate modeling. Trajectories of frailty components were compared among persons who subsequently developed frailty to matched nonfrail persons by using mixed effects models., Results: The probabilities were 0.43, 0.40, and 0.36 for transitioning from 0 to 1 frailty component, from 1 component to 2 components, and from 2 components to 3-5 components (the frail state). The transition probability from frail to death was 0.13. Exhaustion separated frail and nonfrail groups already 9 years prior to onset of frailty (pooled risk ratio [RR] = 1.53, 95% confidence interval [CI] 1.04-2.24). Slowness (RR = 1.94, 95% CI 1.44-2.61), low activity (RR = 1.59, 95% CI 1.19-2.13), and weakness (RR = 1.39, 95% CI 1.10-1.76) separated frail and nonfrail groups 6 years prior to onset of frailty. The fifth frailty component, weight loss, separated frail and nonfrail groups only at the onset of frailty (RR = 3.36, 95% CI 2.76-4.08)., Conclusions: Evidence from two cohort studies suggests that feelings of exhaustion tend to emerge early and weight loss near the onset of frailty syndrome., (© The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Clinical guidelines suggest preventive interventions such as statin therapy for individuals with a high estimated 10-year risk of major cardiovascular events. For those with a low or intermediate estimated risk, risk-factor screenings are recommended at 5-year intervals; this interval is based on expert opinion rather than on direct research evidence. Using longitudinal data on the progression of cardiovascular disease risk over time, we compared different screening intervals in terms of timely detection of high-risk individuals, cardiovascular events prevented, and health-care costs., Methods: We used data from participants in the British Whitehall II study (aged 40-64 years at baseline) who had repeated biomedical screenings at 5-year intervals and linked these data to electronic health records between baseline (Aug 7, 1991, to May 10, 1993) and June 30, 2015. We estimated participants' 10-year risk of a major cardiovascular event (myocardial infarction, cardiac death, and fatal or non-fatal stroke) using the revised Atherosclerotic Cardiovascular Disease (ASCVD) calculator. We used multistate Markov modelling to estimate optimum screening intervals on the basis of progression rates from low-risk and intermediate-risk categories to the high-risk category (ie, ≥7·5% 10-year risk of a major cardiovascular event). Our assessment criteria included person-years spent in a high-risk category before detection, the number of major cardiovascular events prevented and quality-adjusted life-years (QALYs) gained, and screening costs., Findings: Of 6964 participants (mean age 50·0 years [SD 6·0] at baseline) with 152 700 person-years of follow-up (mean follow-up 22·0 years [SD 5·0]), 1686 participants progressed to the high-risk category and 617 had a major cardiovascular event. With the 5-year screening intervals, participants spent 7866 (95% CI 7130-8658) person-years unrecognised in the high-risk group. For individuals in the low, intermediate-low, and intermediate-high risk categories, 21 alternative risk category-based screening intervals outperformed the 5-yearly screening protocol. Screening intervals at 7 years, 4 years, and 1 year for those in the low, intermediate-low, and intermediate-high-risk category would reduce the number of person-years spent unrecognised in the high-risk group by 62% (95% CI 57-66; 4894 person-years), reduce the number of major cardiovascular events by 8% (7-9; 49 events), and raise 44 QALYs (40-49) for the study population., Interpretation: In terms of timely preventive interventions, the 5-year screening intervals were unnecessarily frequent for low-risk individuals and insufficiently frequent for intermediate-risk individuals. Screening intervals based on risk-category-specific progression rates would perform better in terms of preventing major cardiovascular disease events and improving cost-effectiveness., Funding: Medical Research Council, British Heart Association, National Institutes on Aging, NordForsk, Academy of Finland., (Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Acute kidney injury (AKI) is a common complication in severe burns and can lead to significantly poorer outcomes. Although the prognosis has improved in recent decades, the mortality of AKI remains considerable. We investigated the factors that increase the risk of AKI and death after severe burn injury., Methods: Intensive care patients with ≥20% burned total body surface area (TBSA%) between January 2006 and December 2015 treated in Helsinki Burn Centre were enrolled retrospectively. Patients who arrived > 36 h after burn injury or died < 48 h from arrival were excluded. A total of 187 patients were included in the final analysis. Serum creatinine ≥120 μmol/l (1.4 mg/dl) was the criterion for AKI., Results: Fifty-one patients (27.3%) developed AKI during hospital stay and 21 (11.2%) required renal replacement therapy (RRT); 37 patients (19.8%) died during hospital stay. Mortality was significantly higher in the AKI group (52.9%) than in the AKI-negative group (7.4%). The Abbreviated Burn Severity Index (ABSI), Baux, and the modified Baux score were nearly equivalent in predicting mortality during ICU stay (AUC: 0.83-0.84). The risk of death and AKI were minimal with Baux scores < 80. LD 50 was 112 for Baux score in all patients. In flame burns, the risk of death increased rapidly after Baux score > 80. Multivariate logistic regression model detected age, TBSA%, sepsis, and rhabdomyolysis as independent risk factors for AKI. Age (per 10 yrs. OR 1.99), TBSA% (per 10% OR 1.64), and AKI predicted mortality during hospital stay; AKI had an odds ratio of (OR) of 5.97 (95% confidence interval [CI] 2.2-16.2)., Conclusions: Age, TBSA%, and AKI were the strongest independent factors in predicting outcome in severe burns. Even a major burn (> 50% TBSA) has a relatively good prognosis without simultaneous AKI. Prognosis is poorer even in minor burns for patients with AKI.

Background: Obesity increases the risk of several chronic diseases, but the extent to which the obesity-related loss of disease-free years varies by lifestyle category and across socioeconomic groups is unclear. We estimated the number of years free from major non-communicable diseases in adults who are overweight and obese, compared with those who are normal weight., Methods: We pooled individual-level data on body-mass index (BMI) and non-communicable diseases from men and women with no initial evidence of these diseases in European cohort studies from the Individual-Participant-Data Meta-Analysis in Working Populations consortium. BMI was assessed at baseline (1991-2008) and non-communicable diseases (incident type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease) were ascertained via linkage to records from national health registries, repeated medical examinations, or self-report. Disease-free years from age 40 years to 75 years associated with underweight (BMI <18·5 kg/m 2 ), overweight (≥25 kg/m 2 to <30 kg/m 2 ), and obesity (class I [mild] ≥30 kg/m 2 to <35 kg/m 2 ; class II-III [severe] ≥35 kg/m 2 ) compared with normal weight (≥18·5 kg/m 2 to <25 kg/m 2 ) were estimated., Findings: Of 137 503 participants from ten studies, we excluded 6973 owing to missing data and 10 349 with prevalent disease at baseline, resulting in an analytic sample of 120 181 participants. Of 47 127 men, 211 (0·4%) were underweight, 21 468 (45·6%) normal weight, 20 738 (44·0%) overweight, 3982 (8·4%) class I obese, and 728 (1·5%) class II-III obese. The corresponding numbers among the 73 054 women were 1493 (2·0%), 44 760 (61·3%), 19 553 (26·8%), 5670 (7·8%), and 1578 (2·2%), respectively. During 1 328 873 person-years at risk (mean follow-up 11·5 years [range 6·3-18·6]), 8159 men and 8100 women developed at least one non-communicable disease. Between 40 years and 75 years, the estimated number of disease-free years was 29·3 (95% CI 28·8-29·8) in normal-weight men and 29·4 (28·7-30·0) in normal-weight women. Compared with normal weight, the loss of disease-free years in men was 1·8 (95% CI -1·3 to 4·9) for underweight, 1·1 (0·7 to 1·5) for overweight, 3·9 (2·9 to 4·9) for class I obese, and 8·5 (7·1 to 9·8) for class II-III obese. The corresponding estimates for women were 0·0 (-1·4 to 1·4) for underweight, 1·1 (0·6 to 1·5) for overweight, 2·7 (1·5 to 3·9) for class I obese, and 7·3 (6·1 to 8·6) for class II-III obese. The loss of disease-free years associated with class II-III obesity varied between 7·1 and 10·0 years in subgroups of participants of different socioeconomic level, physical activity level, and smoking habit., Interpretation: Mild obesity was associated with the loss of one in ten, and severe obesity the loss of one in four potential disease-free years during middle and later adulthood. This increasing loss of disease-free years as obesity becomes more severe occurred in both sexes, among smokers and non-smokers, the physically active and inactive, and across the socioeconomic hierarchy., Funding: NordForsk, UK Medical Research Council, US National Institute on Aging, Academy of Finland, Helsinki Institute of Life Science, and Cancer Research UK., (Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background and Purpose: One in every 4 subarachnoid hemorrhage (SAH) patients dies suddenly outside hospital, but most SAH risk factor studies focus on hospitalized patients. We studied the differences in risk factors between hospitalized SAH and sudden-death SAH patients., Methods: The population-based FINRISK study cohort of 65 521 individuals was followed up for 1.52 million person-years. The Cox proportional hazards model calculated hazard ratios (HRs), with all analyses adjusted for known SAH risk factors, marital status, and socioeconomic status. A competing risks model analyzed differences in risk factors between hospitalized SAHs and sudden-death SAHs., Results: We identified 98 sudden-death SAHs and 445 hospitalized SAHs confirmed by autopsy or by standard SAH diagnostics. Increase by 5 cigarettes smoked per day elevated sudden-death SAH risk (HR, 1.28; 95% confidence interval [CI], 1.17-1.39) more than hospitalized SAH risk (HR, 1.19; 95% CI, 1.13-1.24; P =0.05 for difference). Per SD (21.4 mm Hg) increase, systolic blood pressure elevated risk of sudden-death SAH (HR, 1.34; 95% CI, 1.09-1.65) more than risk for hospitalized SAH (HR, 1.25; (95% CI, 1.12-1.38; P =0.05 for difference). Participants living without a partner were at elevated risk of sudden-death SAH (HR, 2.09; 95% CI, 1.33-3.28) but not of hospitalized SAH. No sudden-death SAHs occurred in normotensive never smokers aged <50 years., Conclusions: Sudden-death SAH risk seems to be highest among those individuals with the most adverse risk factor profiles and among those who live without a partner, whereas it is rare among normotensive never smokers aged <50 years., (© 2017 American Heart Association, Inc.)

Background and Purpose: Women are at higher risk for subarachnoid hemorrhage (SAH) than men for unknown reasons. Also cumulative effects of smoking have been neglected among prospective studies. We studied associations between smoking habits and SAH and interactions between known SAH risk factors in a prospective population-based study., Methods: The population-based FINRISK study cohort of 65 521 individuals was followed up for 1.38 million person-years. We used the Cox proportional hazards model to calculate hazard ratios and evaluated additive and multiplicative interactions between study variables, with all analyses adjusted for known SAH risk factors., Results: During follow-up, we identified 492 SAHs (266 women). Smoking had a linear dose-dependent and cumulative association with risk for SAH in both sexes. Women smoking >20 cigarettes per day had a hazard ratio of 8.35 (95% confidence interval, 3.86-18.06) compared with a hazard ratio of 2.76 (95% confidence interval, 1.68-4.52) in men in the same cigarettes per day group. Hazard ratios differed by sex in all cigarettes per day and pack-year categories; this association was stronger in women in all categories (P=0.01). When an adjusted model included interaction terms between sex and cigarettes per day or pack-years, female sex was no longer an independent SAH risk factor. Former smokers had a markedly decreased risk for SAH in both sexes when compared with current smokers., Conclusions: Smoking has a dose-dependent and cumulative association with SAH risk, and this risk is highest in female heavy smokers. Vulnerability to smoking seems to explain in part the increased SAH risk in women., (© 2016 American Heart Association, Inc.)

Background: The role played by total cholesterol (TC) in risk for subarachnoid hemorrhage (SAH) is unclear because studies report both high and low TC each as a risk factor. We performed a systematic review to clarify associations between lipid profile and SAH., Methods: Our literature search comprised Pubmed, Scopus, and Cochrane Library databases with no language, publication year, or study type limitations. The Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) checklist guided our reporting. Data forms adapted from the Critical Appraisal Skills Program (CASP), and Cochrane Collaboration guidelines provided a platform for risk-of-bias evaluation. We used a random effects model to calculate pooled estimates and assessed heterogeneity with I2-statistics., Results: Of the final 21 studies reviewed, 12 were prospective and 9 retrospective. All studies assessed TC, four assessed HDL, and none LDL in risk for SAH. Heterogeneity among all, retrospective, and Asian studies was high (I2 = 79.5%, I2 = 89.0%, and I2 = 84.3%) and considerable in prospective (I2 = 46.0%). We therefore focused on qualitative analysis and found that only two studies had a low risk of bias. According to these studies high TC increases risk for SAH in men, whereas the role of HDL remained unclear., Conclusion: The low-risk-of-bias studies suggest that elevated TC levels elevate risk for SAH in men. Due to the high prevalence of hypercholesterolemia, population attributable risk (PAR) of hypercholesterolemia may exceed the PARs of smoking and hypertension in men. Apart from diabetes and obesity, the risk-factor profile of SAH seems to resemble that of other cerebrovascular diseases, at least in men.