To examine whether social isolation and loneliness (1) predict acute myocardial infarction (AMI) and stroke among those with no history of AMI or stroke, (2) are related to mortality risk among those ...with a history of AMI or stroke, and (3) the extent to which these associations are explained by known risk factors or pre-existing chronic conditions.
Participants were 479 054 individuals from the UK Biobank. The exposures were self-reported social isolation and loneliness. AMI, stroke and mortality were the outcomes.
Over 7.1 years, 5731 had first AMI, and 3471 had first stroke. In model adjusted for demographics, social isolation was associated with higher risk of AMI (HR 1.43, 95% CI 1.3 to -1.55) and stroke (HR 1.39, 95% CI 1.25 to 1.54). When adjusted for all the other risk factors, the HR for AMI was attenuated by 84% to 1.07 (95% CI 0.99 to 1.16) and the HR for stroke was attenuated by 83% to 1.06 (95% CI 0.96 to 1.19). Loneliness was associated with higher risk of AMI before (HR 1.49, 95% CI 1.36 to 1.64) but attenuated considerably with adjustments (HR 1.06, 95% CI 0.96 to 1.17). This was also the case for stroke (HR 1.36, 95% CI 1.20 to 1.55 before and HR 1.04, 95% CI 0.91 to 1.19 after adjustments). Social isolation, but not loneliness, was associated with increased mortality in participants with a history of AMI (HR 1.25, 95% CI 1.03 to 1.51) or stroke (HR 1.32, 95% CI 1.08 to 1.61) in the fully adjusted model.
Isolated and lonely persons are at increased risk of AMI and stroke, and, among those with a history of AMI or stroke, increased risk of death. Most of this risk was explained by conventional risk factors.
Background
Personality is suggested to be a major risk factor for depression but large‐scale individual participant meta‐analyses on this topic are lacking.
Method
Data from 10 prospective community ...cohort studies with 117,899 participants (mean age 49.0 years; 54.7% women) were pooled for individual participant meta‐analysis to determine the association between personality traits of the five‐factor model and risk of depressive symptoms.
Results
In cross‐sectional analysis, low extraversion (pooled standardized regression coefficient (B) = –.08; 95% confidence interval = –0.11, –0.04), high neuroticism (B = .39; 0.32, 0.45), and low conscientiousness (B = –.09; –0.10, –0.06) were associated with depressive symptoms. Similar associations were observed in longitudinal analyses adjusted for baseline depressive symptoms (n = 56,735; mean follow‐up of 5.0 years): low extraversion (B = –.03; –0.05, –0.01), high neuroticism (B = .12; 0.10, 0.13), and low conscientiousness (B = –.04; –0.06, –0.02) were associated with an increased risk of depressive symptoms at follow‐up. In turn, depressive symptoms were associated with personality change in extraversion (B = –.07; 95% CI = –0.12, –0.02), neuroticism (B = .23; 0.09, 0.36), agreeableness (B = –.09; –0.15, –0.04), conscientiousness (B = –.14; –0.21, –0.07), and openness to experience (B = –.04; –0.08, 0.00).
Conclusions
Personality traits are prospectively associated with the development of depressive symptoms. Depressive symptoms, in turn, are associated with changes in personality that may be temporary or persistent.
The associations of social isolation and loneliness with premature mortality are well known, but the risk factors linking them remain unclear. We sought to identify risk factors that might explain ...the increased mortality in socially isolated and lonely individuals.
We used prospective follow-up data from the UK Biobank cohort study to assess self-reported isolation (a three-item scale) and loneliness (two questions). The main outcomes were all-cause and cause-specific mortality. We calculated the percentage of excess risk mediated by risk factors to assess the extent to which the associations of social isolation and loneliness with mortality were attributable to differences between isolated and lonely individuals and others in biological (body-mass index, systolic and diastolic blood pressure, and handgrip strength), behavioural (smoking, alcohol consumption, and physical activity), socioeconomic (education, neighbourhood deprivation, and household income), and psychological (depressive symptoms and cognitive capacity) risk factors.
466 901 men and women (mean age at baseline 56·5 years SD 8·1) were included in the analyses, with a mean follow-up of 6·5 years (SD 0·8). The hazard ratio for all-cause mortality for social isolation compared with no social isolation was 1·73 (95% CI 1·65–1·82) after adjustment for age, sex, ethnic origin, and chronic disease (ie, minimally adjusted), and was 1·26 (95% CI 1·20–1·33) after further adjustment for socioeconomic factors, health-related behaviours, depressive symptoms, biological factors, cognitive performance, and self-rated health (ie, fully adjusted). The minimally adjusted hazard ratio for mortality risk related to loneliness was 1·38 (95% CI 1·30–1·47), which reduced to 0·99 (95% CI 0·93–1·06) after full adjustment for baseline risks.
Isolated and lonely people are at increased risk of death. Health policies addressing risk factors such as adverse socioeconomic conditions, unhealthy lifestyle, and lower mental wellbeing might reduce excess mortality among the isolated and the lonely.
Academy of Finland, NordForsk, and the UK Medical Research Council.
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.
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.
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.
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.
UK Medical Research Council, US National Institute on Aging, NordForsk, British Heart Foundation, Academy of Finland, and Helsinki Institute of Life Science.
This study aimed to compare the utility of risk estimation derived from questionnaires and administrative records in predicting long-term sickness absence among shift workers.
This prospective cohort ...study comprised 3197 shift-working hospital employees (mean age 44.5 years, 88.0% women) who responded to a brief 8-item questionnaire on work disability risk factors and were linked to 28 variables on their working hour and workplace characteristics obtained from administrative registries at study baseline. The primary outcome was the first sickness absence lasting ≥90 days during a 4-year follow-up.
The C-index of 0.73 95% confidence interval (CI) 0.70-0.77 for a questionnaire-only based prediction model, 0.71 (95% CI 0.67-0.75) for an administrative records-only model, and 0.79 (95% CI 0.76-0.82) for a model combining variables from both data sources indicated good discriminatory ability. For a 5%-estimated risk as a threshold for positive test results, the detection rates were 76%, 74%, and 75% and the false positive rates were 40%, 45% and 34% for the three models. For a 20%-risk threshold, the corresponding detection rates were 14%, 8%, and 27% and the false positive rates were 2%, 2%, and 4%. To detect one true positive case with these models, the number of false positive cases accompanied varied between 7 and 10 using the 5%-estimated risk, and between 2 and 3 using the 20%-estimated risk cut-off. The pattern of results was similar using 30-day sickness absence as the outcome.
The best predictive performance was reached with a model including both questionnaire responses and administrative records. Prediction was almost as accurate with models using only variables from one of these data sources. Further research is needed to examine the generalizability of these findings.
Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed ...to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight.
We pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0–24·9 kg/m2), overweight (25·0–29·9 kg/m2), class I (mild) obesity (30·0–34·9 kg/m2), and class II and III (severe) obesity (≥35·0 kg/m2). We used an inclusive definition of underweight (<20 kg/m2) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis.
Participants were 120 813 adults (mean age 51·4 years, range 35–103; 71 445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973–2012). During a mean follow-up of 10·7 years (1995–2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio OR 2·0, 95% CI 1·7–2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5–5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1–21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9–2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1–17·9) for vascular disease followed by diabetes, 18·6 (16·6–20·9) for diabetes only, and 29·8 (21·7–40·8) for diabetes followed by vascular disease.
The risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes.
NordForsk, Medical Research Council, Cancer Research UK, Finnish Work Environment Fund, and Academy of Finland.
Justice at the Workplace: A Review VIRTANEN, MARIANNA; ELOVAINIO, MARKO
Cambridge quarterly of healthcare ethics,
04/2018, Letnik:
27, Številka:
2
Journal Article
Recenzirano
Odprti dostop
Modern work life is characterized by constant change, reorganizations, and requirements of efficiency, which make the distribution of resources and obligations, as well as justice in decisionmaking, ...highly important. In the work life context, it is a question not only of distributing resources and obligations, but also of the procedures and rules that guide the decisionmaking in the organization. Studies of these rules and procedures have provided the basis for a new line of research that evaluates leadership and social relationships in working communities; that is, distributive, procedural, and relational justice. This review follows the development of research on organizational justice from its origins in early social and motivational psychological theories to its establishment as a major line of research in modern work and organizational psychology. The adverse consequences of injustice include poor team climate, reduced productivity and well-being, and work-related illnesses.
AbstractObjectiveTo examine whether physical inactivity is a risk factor for dementia, with attention to the role of cardiometabolic disease in this association and reverse causation bias that arises ...from changes in physical activity in the preclinical (prodromal) phase of dementia.DesignMeta-analysis of 19 prospective observational cohort studies.Data sourcesThe Individual-Participant-Data Meta-analysis in Working Populations Consortium, the Inter-University Consortium for Political and Social Research, and the UK Data Service, including a total of 19 of a potential 9741 studies.Review methodThe search strategy was designed to retrieve individual-participant data from prospective cohort studies. Exposure was physical inactivity; primary outcomes were incident all-cause dementia and Alzheimer’s disease; and the secondary outcome was incident cardiometabolic disease (that is, diabetes, coronary heart disease, and stroke). Summary estimates were obtained using random effects meta-analysis.ResultsStudy population included 404 840 people (mean age 45.5 years, 57.7% women) who were initially free of dementia, had a measurement of physical inactivity at study entry, and were linked to electronic health records. In 6.0 million person-years at risk, we recorded 2044 incident cases of all-cause dementia. In studies with data on dementia subtype, the number of incident cases of Alzheimer’s disease was 1602 in 5.2 million person-years. When measured <10 years before dementia diagnosis (that is, the preclinical stage of dementia), physical inactivity was associated with increased incidence of all-cause dementia (hazard ratio 1.40, 95% confidence interval 1.23 to 1.71) and Alzheimer’s disease (1.36, 1.12 to 1.65). When reverse causation was minimised by assessing physical activity ≥10 years before dementia onset, no difference in dementia risk between physically active and inactive participants was observed (hazard ratios 1.01 (0.89 to 1.14) and 0.96 (0.85 to 1.08) for the two outcomes). Physical inactivity was consistently associated with increased risk of incident diabetes (hazard ratio 1.42, 1.25 to 1.61), coronary heart disease (1.24, 1.13 to 1.36), and stroke (1.16, 1.05 to 1.27). Among people in whom cardiometabolic disease preceded dementia, physical inactivity was non-significantly associated with dementia (hazard ratio for physical activity assessed >10 before dementia onset 1.30, 0.79 to 2.14).ConclusionsIn analyses that addressed bias due to reverse causation, physical inactivity was not associated with all-cause dementia or Alzheimer’s disease, although an indication of excess dementia risk was observed in a subgroup of physically inactive individuals who developed cardiometabolic disease.
Research strategies for precarious employment Ervasti, Jenni; Virtanen, Marianna
Scandinavian journal of work, environment & health,
09/2019, Letnik:
45, Številka:
5
Journal Article
Recenzirano
Odprti dostop
...as the response rates to questionnaire data are decreasing internationally, and there are widely known biases in self-reported data such as 'common method bias' (9, 10), we may need additional ...data sources. ...as Rönnblad et al note, precarious employees are almost by definition, difficult to follow longitudinally. ...Van Aerden and her colleagues (11) have used latent class cluster analysis of survey data and found that it is empirically possible to identify separate clusters of employment quality based on information on employment contract, income level, uncompensated work, long working hours, schedule unpredictability, involuntary parttime employment, training opportunities, information on occupational health and safety issues, and employee involvement. ...the dynamic nature of the labor market sets requirements to future research so that we need to consider changes of employment relationships over time, across the individual's working life course.
Summary Background Long working hours might increase the risk of cardiovascular disease, but prospective evidence is scarce, imprecise, and mostly limited to coronary heart disease. We aimed to ...assess long working hours as a risk factor for incident coronary heart disease and stroke. Methods We identified published studies through a systematic review of PubMed and Embase from inception to Aug 20, 2014. We obtained unpublished data for 20 cohort studies from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium and open-access data archives. We used cumulative random-effects meta-analysis to combine effect estimates from published and unpublished data. Findings We included 25 studies from 24 cohorts in Europe, the USA, and Australia. The meta-analysis of coronary heart disease comprised data for 603 838 men and women who were free from coronary heart disease at baseline; the meta-analysis of stroke comprised data for 528 908 men and women who were free from stroke at baseline. Follow-up for coronary heart disease was 5·1 million person-years (mean 8·5 years), in which 4768 events were recorded, and for stroke was 3·8 million person-years (mean 7·2 years), in which 1722 events were recorded. In cumulative meta-analysis adjusted for age, sex, and socioeconomic status, compared with standard hours (35–40 h per week), working long hours (≥55 h per week) was associated with an increase in risk of incident coronary heart disease (relative risk RR 1·13, 95% CI 1·02–1·26; p=0·02) and incident stroke (1·33, 1·11–1·61; p=0·002). The excess risk of stroke remained unchanged in analyses that addressed reverse causation, multivariable adjustments for other risk factors, and different methods of stroke ascertainment (range of RR estimates 1·30–1·42). We recorded a dose–response association for stroke, with RR estimates of 1·10 (95% CI 0·94–1·28; p=0·24) for 41–48 working hours, 1·27 (1·03–1·56; p=0·03) for 49–54 working hours, and 1·33 (1·11–1·61; p=0·002) for 55 working hours or more per week compared with standard working hours (ptrend <0·0001). Interpretation Employees who work long hours have a higher risk of stroke than those working standard hours; the association with coronary heart disease is weaker. These findings suggest that more attention should be paid to the management of vascular risk factors in individuals who work long hours. Funding Medical Research Council, Economic and Social Research Council, European Union New and Emerging Risks in Occupational Safety and Health research programme, Finnish Work Environment Fund, Swedish Research Council for Working Life and Social Research, German Social Accident Insurance, Danish National Research Centre for the Working Environment, Academy of Finland, Ministry of Social Affairs and Employment (Netherlands), US National Institutes of Health, British Heart Foundation.
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