Роль корпоративной культуры в системе мотивации труда

OBJECTIVES: Multimorbidity is common in the older population, but the impact of combinations of chronic conditions on disability and quality of life (QoL) is not well known. This analysis explores the effect of specific combinations of chronic diseases on disability, QoL and self-rated health (SRH). DESIGN: We used data from two population representative cross-sectional studies, the Northern Ireland Health and Social Wellbeing Survey (NIHSWS) 2005 and the Survey of Lifestyle, Attitudes and Nutrition (SLAN) 2007 (conducted in the Republic of Ireland). SETTING: Randomly selected community-living participants were interviewed at home. PARTICIPANTS: A total of 6159 participants aged 50 years and older were included in the analysis. OUTCOME MEASURES: Chronic conditions were classified as cardiovascular disease, chronic pain, diabetes or respiratory disease. Interaction terms estimated by logistic regression were used to examine the effects of multiple chronic conditions on disability, SRH and QoL. RESULTS: Each chronic condition group was correlated with each of the others after adjusting for sociodemographic factors. Those from Northern Ireland were more likely to report a limitation in daily activities (45%) compared to those from the Republic of Ireland (21%). Each condition had an independent effect on disability, SRH and QoL, and those with multiple chronic conditions reported the worst outcomes. However, there were no statistically significant positive interactions between chronic condition groups with respect to any outcome. CONCLUSIONS: Chronic conditions affect individuals largely independent of each other with respect to their effect on disability, SRH and QoL. However, a significant proportion of the population aged 50 years and over across the island of Ireland lives with multimorbidity, and this group is at the highest risk of disability, poor SRH and poor QoL

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

The chronic ills of multimorbidity : a cross-sectional examination of the prevalence, patterns and factors associated with multimorbidity in the Irish population aged 50 years and over and its corresponding impact on health and social care utilisation

THESIS 10390Multimorbidity predicts many adverse health outcomes, placing a heavy burden on the individual as well as population health. It has clear implications for current healthcare provision and with the projected ageing of the Irish population presents substantial challenges for future healthcare policy and planning. Population level evidence on multimorbidity is, however, limited. The factors driving multimorbidity prevalence are poorly understood and appropriate responses have yet to be integrated into population health planning and service delivery. The overall aim of this thesis was to gain a greater understanding of the prevalence, patterns and factors associated with multimorbidity at a population level in Ireland, as well as the corresponding impact of multimorbidity on health and social care utilisation. Three separate but related empirical studies were conducted based on the following central objectives: -- 1. To estimate the prevalence and non-random patterning of multimorbidity in the community-dwelling population aged 50 years and over in Ireland. -- 2. To examine the factors associated with multimorbidity in mid to late life in an Irish context. -- 3. To determine the impact of multimorbidity on health and social care utilisation and quality of care in Ireland. Conceptual issues of multimorbidity definition and measurement were considered in this thesis to contextualise multimorbidity within population health and inform a framework for evaluating multimorbidity in community-dwelling populations

Multimorbidity in the older population

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A tobacco free future. An all-Ireland report on tobacco, inequalities and childhood.

Children growing up in disadvantaged circumstances face a number of threats to their health and development. Protecting children from the burden of tobacco related harm from both active and passive smoking is a priority action in enhancing population health and reducing health inequalities. Population health strategies on the island of Ireland are increasingly focussing on addressing the root causes of health inequality through social determinants of health approaches and through focussing on early childhood as a key period for intervention. At the same time, governments in both jurisdictions are working to enhance their approaches to effective tobacco control. The World Health Organization considers that there are three key ‘windows of exposure’ in terms of tobacco-related harm in childhood – in the womb (associated with active or passive smoking by the mother), directly through children taking up smoking and through exposure to second hand smoke (SHS) in indoor and outdoor environments. This report presents findings on these three windows of exposure based on a range of data sources in the Republic of Ireland and Northern Ireland. The central aim of the report is to contribute to knowledge on the exposure of children to the harmful effects of tobacco smoke at various stages of their development. The findings of the report can support policy makers and service providers in their efforts to make tobacco-free childhoods a reality on the island of Ireland

The Effect of Multiple Chronic Conditions on Self-Rated Health, Disability and Quality of Life Among the Older Populations of Northern Ireland and the Republic of Ireland

Article in Irish Journal of Medical Science 181:S273-S273 · September 201

The effect of multiple chronic conditions on self-rated health, disability and quality of life among the older populations of Northern Ireland and the Republic of Ireland: A comparison of two nationally representative cross-sectional surveys

Multimorbidity is common in the older population, but the impact of combinations of chronic conditions on disability and quality of life (QoL) is not well known. This analysis explores the effect of specific combinations of chronic diseases on disability, QoL and self-rated health (SRH).We used data from two population representative cross-sectional studies, the Northern Ireland Health and Social Wellbeing Survey (NIHSWS) 2005 and the Survey of Lifestyle, Attitudes and Nutrition (SLAN) 2007 (conducted in the Republic of Ireland).Randomly selected community-living participants were interviewed at home.A total of 6159 participants aged 50 years and older were included in the analysis.Chronic conditions were classified as cardiovascular disease, chronic pain, diabetes or respiratory disease. Interaction terms estimated by logistic regression were used to examine the effects of multiple chronic conditions on disability, SRH and QoL.Each chronic condition group was correlated with each of the others after adjusting for sociodemographic factors. Those from Northern Ireland were more likely to report a limitation in daily activities (45%) compared to those from the Republic of Ireland (21%). Each condition had an independent effect on disability, SRH and QoL, and those with multiple chronic conditions reported the worst outcomes. However, there were no statistically significant positive interactions between chronic condition groups with respect to any outcome.Chronic conditions affect individuals largely independent of each other with respect to their effect on disability, SRH and QoL. However, a significant proportion of the population aged 50 years and over across the island of Ireland lives with multimorbidity, and this group is at the highest risk of disability, poor SRH and poor Qo