38 research outputs found

    Estimating and characterizing the burden of multimorbidity in the community: A comprehensive multistep analysis of two large nationwide representative surveys in France

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    This is the final version. Available on open access from Public Library of Science via the DOI in this recordData Availability: All relevant data are within the manuscript and its Supporting Information files.Background Given the increasing burden of chronic conditions, multimorbidity is now a priority for healthcare and public health systems worldwide. Appropriate methodological approaches for assessing the phenomenon have not yet been established, resulting in inconsistent and incomplete descriptions. We aimed to estimate and characterize the burden of multimorbidity in the adult population in France in terms of number and type of conditions, type of underlying mechanisms, and analysis of the joint effects for identifying combinations with the most deleterious interaction effects on health status. Methods and findings We used a multistep approach to analyze cross-sectional and longitudinal data from 2 large nationwide representative surveys: 2010/2014 waves of the Health, Health Care, and Insurance Survey (ESPS 2010–2014) and Disability Healthcare Household Survey 2008 (HSM 2008), that collected similar data on 61 chronic or recurrent conditions. Adults aged ≥25 years in either ESPS 2010 (14,875) or HSM 2008 (23,348) were considered (participation rates were 65% and 62%, respectively). Longitudinal analyses included 7,438 participants of ESPS 2010 with follow-up for mortality (97%) of whom 3,798 were reinterviewed in 2014 (52%). Mortality, activity limitation, self-reported health, difficulties in activities/instrumental activities of daily living, and Medical Outcomes Study Short-Form 12-Item Health Survey were the health status measures. Multiple regression models were used to estimate the impact of chronic or recurrent conditions and multimorbid associations (dyads, triads, and tetrads) on health status. Etiological pathways explaining associations were investigated, and joint effects and interactions between conditions on health status measures were evaluated using both additive and multiplicative scales. Forty-eight chronic or recurrent conditions had an independent impact on mortality, activity limitations, or perceived heath. Multimorbidity prevalence varied between 30% (1-year time frame) and 39% (lifetime frame), and more markedly according to sex (higher in women), age (with greatest increases in middle-aged), and socioeconomic status (higher in less educated and low-income individuals and manual workers). We identified various multimorbid combinations, mostly involving vasculometabolic and musculoskeletal conditions and mental disorders, which could be explained by direct causation, shared or associated risk factors, or less frequently, confounding or chance. Combinations with the highest health impacts included diseases with complications but also associations of conditions affecting systems involved in locomotion and sensorial functions (impact on activity limitations), and associations including mental disorders (impact on perceived health). The interaction effects of the associated conditions varied on a continuum from subadditive and additive (associations involving cardiometabolic conditions, low back pain, osteoporosis, injury sequelae, depression, and anxiety) to multiplicative and supermultiplicative (associations involving obesity, chronic obstructive pulmonary disease, migraine, and certain osteoarticular pathologies). Study limitations included self-reported information on chronic conditions and the insufficient power of some analyses. Conclusions Multimorbidity assessments should move beyond simply counting conditions and take into account the variable impacts on health status, etiological pathways, and joint effects of associated conditions. In particular, the multimorbid combinations with substantial health impacts or shared risk factors deserve closer attention. Our findings also suggest that multimorbidity assessment and management may be beneficial already in midlife and probably earlier in disadvantaged groups.Public Health Franc

    Multiple imputation for estimating hazard ratios and predictive abilities in case-cohort surveys

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    <p>Abstract</p> <p>Background</p> <p>The weighted estimators generally used for analyzing case-cohort studies are not fully efficient and naive estimates of the predictive ability of a model from case-cohort data depend on the subcohort size. However, case-cohort studies represent a special type of incomplete data, and methods for analyzing incomplete data should be appropriate, in particular multiple imputation (MI).</p> <p>Methods</p> <p>We performed simulations to validate the MI approach for estimating hazard ratios and the predictive ability of a model or of an additional variable in case-cohort surveys. As an illustration, we analyzed a case-cohort survey from the Three-City study to estimate the predictive ability of D-dimer plasma concentration on coronary heart disease (CHD) and on vascular dementia (VaD) risks.</p> <p>Results</p> <p>When the imputation model of the phase-2 variable was correctly specified, MI estimates of hazard ratios and predictive abilities were similar to those obtained with full data. When the imputation model was misspecified, MI could provide biased estimates of hazard ratios and predictive abilities. In the Three-City case-cohort study, elevated D-dimer levels increased the risk of VaD (hazard ratio for two consecutive tertiles = 1.69, 95%CI: 1.63-1.74). However, D-dimer levels did not improve the predictive ability of the model.</p> <p>Conclusions</p> <p>MI is a simple approach for analyzing case-cohort data and provides an easy evaluation of the predictive ability of a model or of an additional variable.</p

    Proinflammatory genotype is associated with the frailty phenotype in the English Longitudinal Study of Ageing

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    Background: Frailty is a state of increased vulnerability to poor resolution of homeostasis after a stressor event, which increases the risk of adverse outcomes including falls, disability and death. The underlying pathophysiological pathways of frailty are not known but the hypothalamic–pituitary–adrenal axis and heightened chronic systemic inflammation appear to be major contributors. Methods: We used the English Longitudinal Study of Ageing dataset of 3160 individuals over the age of 50 and assessed their frailty status according to the Fried-criteria. We selected single nucleotide polymorphisms in genes involved in the steroid hormone or inflammatory pathways and performed linear association analysis using age and sex as covariates. To support the biological plausibility of any genetic associations, we selected biomarker levels for further analyses to act as potential endophenotypes of our chosen genetic loci. Results: The strongest association with frailty was observed in the Tumor Necrosis Factor (TNF) (rs1800629, P = 0.001198, β = 0.0894) and the Protein Tyrosine Phosphatase, Receptor type, J (PTPRJ) (rs1566729, P = 0.001372, β = 0.09397) genes. Rs1800629 was significantly associated with decreased levels of high-density lipoprotein (HDL) (P = 0.00949) and cholesterol levels (P = 0.00315), whereas rs1566729 was associated with increased levels of HDL (P = 0.01943). After correcting for multiple testing none of the associations remained significant. Conclusions: We provide potential evidence for the involvement of a multifunctional proinflammatory cytokine gene (TNF) in the frailty phenotype. The implication of this gene is further supported by association with the endophenotype biomarker results

    Statins but Not Aspirin Reduce Thrombotic Risk Assessed by Thrombin Generation in Diabetic Patients without Cardiovascular Events: The RATIONAL Trial

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    The systematic use of aspirin and statins in patients with diabetes and no previous cardiovascular events is controversial. We sought to assess the effects of aspirin and statins on the thrombotic risk assessed by thrombin generation (TG) among patients with type II diabetes mellitus and no previous cardiovascular events.Prospective, randomized, open, blinded to events evaluation, controlled, 2×2 factorial clinical trial including 30 patients randomly allocated to aspirin 100 mg/d, atorvastatin 40 mg/d, both or none. Outcome measurements included changes in TG levels after treatment (8 to 10 weeks), assessed by a calibrated automated thrombogram. At baseline all groups had similar clinical and biochemical profiles, including TG levels. There was no interaction between aspirin and atorvastatin. Atorvastatin significantly reduced TG measured as peak TG with saline (85.09±55.34 nmol vs 153.26±75.55 nmol for atorvastatin and control groups, respectively; p = 0.018). On the other hand, aspirin had no effect on TG (121.51±81.83 nmol vs 116.85±67.66 nmol, for aspirin and control groups, respectively; p = 0.716). The effects of treatments on measurements of TG using other agonists were consistent.While waiting for data from ongoing large clinical randomized trials to definitively outline the role of aspirin in primary prevention, our study shows that among diabetic patients without previous vascular events, statins but not aspirin reduce thrombotic risk assessed by TG.ClinicalTrials.gov NCT00793754

    Trajectories of dementia-related cognitive decline in a large mental health records derived patient cohort

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    Background: Modeling trajectories of decline can help describe the variability in progression of cognitive impairment in dementia. Better characterisation of these trajectories has significant implications for understanding disease progression, trial design and care planning. Methods: Patients with at least three Mini-mental State Examination (MMSE) scores recorded in the South London and Maudsley NHS Foundation Trust Electronic Health Records, UK were selected (N = 3441) to form a retrospective cohort. Trajectories of cognitive decline were identified through latent class growth analysis of longitudinal MMSE scores. Demographics, Health of Nation Outcome Scales and medications were compared across trajectories identified. Results: Four of the six trajectories showed increased rate of decline with lower baseline MMSE. Two trajectories had similar initial MMSE scores but different rates of decline. In the faster declining trajectory of the two, a higher incidence of both behavioral problems and sertraline prescription were present. Conclusions: We find suggestive evidence for association of behavioral problems and sertraline prescription with rate of decline. Further work is needed to determine whether trajectories replicate in other datasets

    Hormone Treatment, Estrogen Receptor Polymorphisms and Mortality: A Prospective Cohort Study

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    International audienceBACKGROUND: The association between hormone treatment (HT) and mortality remains controversial. This study aimed to determine whether the risk of mortality associated with HT use varies depending on the specific characteristics of treatment and genetic variability in terms of the estrogen receptor. METHODOLOGY/PRINCIPAL FINDINGS: A prospective, population-based study of 5135 women aged 65 years and older who were recruited from three cities in France and followed over six years. Detailed information related to HT use was obtained and five estrogen receptor polymorphisms were genotyped. The total follow-up was 25,436 person-years and during this time 352 women died. Cancer (36.4%) and cardiovascular disease (19.3%) were the major causes of death. Cox proportional hazards models adjusted for age, education, centre, living situation, comorbidity, depression, physical and mental incapacities, indicated no significant association between HT and mortality, regardless of the type or duration of treatment, or the age at initiation. However, the association between HT and all-cause or cancer-related mortality varied across women, with significant interactions identified with three estrogen receptor polymorphisms (p-values = 0.004 to 0.03) in adjusted analyses. Women carrying the C allele of ESR1 rs2234693 had a decreased risk of all-cause mortality with HT (HR: 0.42, 95% CI: 0.18-0.97), while in stark contrast, those homozygous for the T allele had a significantly increased risk of cancer-related mortality (HR: 3.18, 95% CI: 1.23-8.20). The findings were similar for ESR1 rs9340799 and ESR2 rs1271572. CONCLUSIONS/SIGNIFICANCE: The risk of mortality was not associated with HT duration, type or age at initiation. It was however not equal across all women, with some women appearing genetically more vulnerable to the effects of HT in terms of their estrogen receptor genotype. These findings, if confirmed in another independent study, may help explain the differential susceptibility of women to the beneficial or adverse effects of HT

    The epidemiology of multimorbidity in France: Variations by gender, age and socioeconomic factors, and implications for surveillance and prevention

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    10.1371/journal.pone.0265842PLoS ONE174e0265842

    Identification des maladies neurodégénératives dans les bases de données médicoadministratives en France : revue systématique de la littérature

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    National audienceBackground - Given the health, social and economic burden of neurodegenerative diseases (ND), the development of epidemiologic studies is required. Administrative databases, such as the French national health insurance database (SNIIRAM) could represent an opportunity for researchers. ND could be presumed from drug reimbursement data, hospital stays or registration of a chronic condition. The aim of this study was to describe, in French administrative databases, algorithms used to identify Alzheimer's disease and associated disorders (ADAD), Parkinson's disease and associated disorders (PDAD), multiple sclerosis (MS), and amyotrophic lateral sclerosis (ALS). Methods - A systematic literature review was performed in Medline and gray literature through December 31th, 2015. French studies focusing on ADAD, PDAD, MS or ALS as a primary health outcome, conducted among one of the SNIIRAM data sources (outpatient reimbursements, chronic condition registration, hospital discharge) were included. Results - Thirty-four studies were included (ADAD, n=18, PDAD, n=9, MS, n=4, ALS, n=3), leading to 36 algorithms. For each studied ND, there was an important variability in the algorithms, concerning (i) the type of criteria used (administrative database versus multi-source systems); (ii) the number of criteria used; (iii) the definition used for each criteria. The extent and level of drug exposure highly varied. Identification through hospitalizations showed variations in terms of type of stay (short stay, long-term stay, psychiatric ward…), extent of diagnosis codes used, diagnosis type (principal, related, associated diagnosis) and period used. A validation study was conducted for 2 out of 36 algorithms (PDAD), and criteria completeness was estimated for 3 algorithms (MS, ALS). Conclusion - Despite the increase in ND identification among French administrative databases, few algorithms have been validated. Validation studies should be encouraged
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