Multimorbidity as an important issue among women: results of gender difference investigation in a large population-based cross-sectional study in West Asia

Objectives: To investigate the impact of gender on multimorbidity in northern Iran. Design: A cross-sectional analysis of the Golestan cohort data. Setting: Golestan Province, Iran. Study population: 49 946 residents (age 40–75 years) of Golestan Province, Iran. Main outcome measures: Researchers collected data related to multimorbidity, defined as co-existence of two or more chronic diseases in an individual, at the beginning of a representative cohort study which recruited its participants from 2004 to 2008. The researchers utilised simple and multiple Poisson regression models with robust variances to examine the simultaneous effects of multiple factors. Results: Women had a 25.0% prevalence of multimorbidity, whereas men had a 13.4% prevalence (p<0.001). Women of all age-groups had a higher prevalence of multimorbidity. Of note, multimorbidity began at a lower age (40–49 years) in women (17.3%) compared with men (8.6%) of the same age (p<0.001). This study identified significant interactions between gender as well as socioeconomic status, ethnicity, physical activity, marital status, education level and smoking (p<0.01). Conclusion: Prevention and control of multimorbidity requires health promotion programmes to increase public awareness about the modifiable risk factors, particularly among women

Correlational Analysis of Sarcopenia and Multimorbidity Among Older Inpatients

BACKGROUND: Sarcopenia and multimorbidity are common in older adults, and most of the available clinical studies have focused on the relationship between specialist disorders and sarcopenia, whereas fewer studies have been conducted on the relationship between sarcopenia and multimorbidity. We therefore wished to explore the relationship between the two. METHODS: The study subjects were older patients (aged ≥ 65 years) who were hospitalized at the Department of Geriatrics of the First Affiliated Hospital of Chongqing Medical University between March 2016 and September 2021. Their medical records were collected. Based on the diagnostic criteria of the Asian Sarcopenia Working Group in 2019, the relationship between sarcopenia and multimorbidity was elucidated. RESULTS: 1.A total of 651 older patients aged 65 years and above with 2 or more chronic diseases were investigated in this study, 46.4% were suffering from sarcopenia. 2. Analysis of the relationship between the number of chronic diseases and sarcopenia yielded that the risk of sarcopenia with 4-5 chronic diseases was 1.80 times higher than the risk of 2-3 chronic diseases (OR 1.80, 95%CI 0.29-2.50), and the risk of sarcopenia with ≥ 6 chronic diseases was 5.11 times higher than the risk of 2-3 chronic diseases (OR 5.11, 95% CI 2.97-9.08), which remained statistically significant, after adjusting for relevant factors. 3. The Charlson comorbidity index was associated with skeletal muscle mass index, handgrip strength, and 6-meter walking speed, with scores reaching 5 and above suggesting the possibility of sarcopenia. 4. After adjusting for some covariates among 14 common chronic diseases in older adults, diabetes (OR 3.20, 95% CI 2.01-5.09), cerebrovascular diseases (OR 2.07, 95% CI 1.33-3.22), bone and joint diseases (OR 2.04, 95% CI 1.32-3.14), and malignant tumors (OR 2.65, 95% CI 1.17-6.55) were among those that still a risk factor for the development of sarcopenia. CONCLUSION: In the hospitalized older adults, the more chronic diseases they have, the higher the prevalence of sarcopenia. When the CCI is 5, attention needs to be paid to the occurrence of sarcopenia in hospitalized older adults

What determines health-related quality of life among people living with HIV : an updated review of the literature

Background: As infection with the Human Immunodeficiency Virus (HIV) has evolved to a chronic disease, perceived health-related quality of life (HRQoL) is becoming a prominent and important patient-reported outcome measure in HIV care. Literature discusses different factors influencing HRQoL in this population, however, currently no consensus exists about the main determinants. In this review a clear, up-to-date overview of the determinants influencing HRQOL among people living with HIV is provided. Methods: All studies published before July 2013 that identified determinants of HRQoL among people living with HIV in high-income countries, were considered in this narrative review. PubMed, Web of Science and The Cochrane Library were consulted using the keywords ‘determinants’, ‘quality of life’, ‘HIV’ and ‘AIDS’. To be included, studies should have reported overall health and/or physical/mental health scores on a validated instrument and performed multivariable regression analyses to identify determinants that independently influence perceived HRQoL. Results: In total, 49 studies were included for further analysis and they used a variety of HRQoL instruments: Medical Outcomes Study Short Form-36 or variants, Medical Outcomes Study-HIV, HIV Cost and Services Utilization Study measure, Multidimensional Quality of Life Questionnaire, HIV targeted quality of life instrument, Functional Assessment of Human Immunodeficiency Virus Infection, HIV Overview of Problems Evaluation System, EuroQol, Fanning Quality of Life scale, Health Index and PROQOL-HIV. In this review, the discussed determinants were thematically divided into socio-demographic, clinical, psychological and behavioural factors. Employment, immunological status, presence of symptoms, depression, social support and adherence to antiretroviral therapy were most frequently and consistently reported to be associated with HRQoL among people living with HIV. Conclusions: HRQoL among people living with HIV is influenced by several determinants. These determinants independently, but simultaneously impact perceived HRQoL. Most HRQoL instruments do not capture all key determinants. We recommend that the choice for an instrument should depend on the purpose of the HRQoL assessment

Health care resouce use and stroke outcome

Background and Purpose: Outcome in patients hospitalized for acute stroke varies considerably between populations. Within the framework of the GAIN International trial, a large multicenter trial of a neuroprotective agent (gavestinel, glycine antagonist), stroke outcome in relation to health care resource use has been compared in a large number of countries, allowing for differences in case mix. Methods: This substudy includes 1,422 patients in 19 countries grouped into 10 regions. Data on prognostic variables on admission to hospital, resource use, and outcome were analyzed by regression models. Results: All results were adjusted for differences in prognostic factors on admission (NIH Stroke Scale, age, comorbidity). There were threefold variations in the average number of days in hospital/institutional care (from 20 to 60 days). The proportion of patients who met with professional rehabilitation staff also varied greatly. Three-month case fatality ranged from 11% to 28%, and mean Barthel ADL score at three months varied between 64 and 73. There was no relationship between health care resource use and outcome in terms of survival and ADL function at three months. The proportion of patients living at home at three months did not show any relationship to ADL function across countries. Conclusions: There are wide variations in health care resource use between countries, unexplained by differences in case mix. Across countries, there is no obvious relationship between resource use and clinical outcome after stroke. Differences in health care traditions (treatment pathways) and social We thank the coinvestigators and research staff at the participating centers for their support. Glaxo Wellcome sponsored the GAIN International trial, supported the present analyses and reviewed the final draft of the article

Towards large-cohort comparative studies to define the factors influencing the gut microbial community structure of ASD patients.

Differences in the gut microbiota have been reported between individuals with autism spectrum disorders (ASD) and neurotypical controls, although direct evidence that changes in the microbiome contribute to causing ASD has been scarce to date. Here we summarize some considerations of experimental design that can help untangle causality in this complex system. In particular, large cross-sectional studies that can factor out important variables such as diet, prospective longitudinal studies that remove some of the influence of interpersonal variation in the microbiome (which is generally high, especially in children), and studies transferring microbial communities into germ-free mice may be especially useful. Controlling for the effects of technical variables, which have complicated efforts to combine existing studies, is critical when biological effect sizes are small. Large citizen-science studies with thousands of participants such as the American Gut Project have been effective at uncovering subtle microbiome effects in self-collected samples and with self-reported diet and behavior data, and may provide a useful complement to other types of traditionally funded and conducted studies in the case of ASD, especially in the hypothesis generation phase

A Mixture of Regressions Model of COVID-19 Death Rates and Population Comorbidities

As the COVID-19 pandemic spread worldwide, it has become clearer that prevalence of certain comorbidities in a given population could make it more vulnerable to serious outcomes of that disease, including fatality. Indeed, it might be insightful from a health policy perspective to identify clusters of populations in terms of the associations between their prevalent comorbidities and the observed COVID-19 specific death rates. In this study, we described a mixture of polynomial time series (MoPTS) model to simultaneously identify (a) three clusters of 86 U.S. cities in terms of their dynamic death rates, and (b) the different associations of those rates with 5 key comorbidities among the populations in the clusters. We also described an EM algorithm for efficient maximum likelihood estimation of the model parameters

Variation in the estimated prevalence of multimorbidity: systematic review and meta-analysis of 193 international studies

Objective: (1) To estimate the pooled prevalence of multimorbidity in all age groups, globally. (2) To examine how measurement of multimorbidity impacted the estimated prevalence. Methods: In this systematic review and meta-analysis, we conducted searches in nine bibliographic databases (PsycINFO, Embase, Global Health, Medline, Scopus, Web of Science, Cochrane Library, CINAHL and ProQuest Dissertations and Theses Global) for prevalence studies published between database inception and 21 January 2020. Studies reporting the prevalence of multimorbidity (in all age groups and in community, primary care, care home and hospital settings) were included. Studies with an index condition or those that did not include people with no long-term conditions in the denominator were excluded. Retrieved studies were independently reviewed by two reviewers, and relevant data were extracted using predesigned pro forma. We used meta-analysis to pool the estimated prevalence of multimorbidity across studies, and used random-effects meta-regression and subgroup analysis to examine the association of heterogeneous prevalence estimates with study and measure characteristics. Results: 13 807 titles were screened, of which 193 met inclusion criteria for meta-analysis. The pooled prevalence of multimorbidity was 42.4% (95% CI 38.9% to 46.0%) with high heterogeneity (I2 >99%). In adjusted meta-regression models, participant mean age and the number of conditions included in a measure accounted for 47.8% of heterogeneity in effect sizes. The estimated prevalence of multimorbidity was significantly higher in studies with older adults and those that included larger numbers of conditions. There was no significant difference in estimated prevalence between low-income or middle-income countries (36.8%) and high-income countries (44.3%), or between self-report (40.0%) and administrative/clinical databases (52.7%). Conclusions: The pooled prevalence of multimorbidity was significantly higher in older populations and when studies included a larger number of baseline conditions. The findings suggest that, to improve study comparability and quality of reporting, future studies should use a common core conditions set for multimorbidity measurement and report multimorbidity prevalence stratified by sociodemographics