Prevalent migraine as a predictor of incident hypertension.

BACKGROUND: Migraine has been associated with several diseases. This population-based prospective Finnish postal survey Health and Social Support Study explored whether self-reported migraine predicted incident hypertension independently in a working-age population by utilizing two data sources: the baseline survey from the year 1998 in combination with the follow-up survey data from the years 2003 and 2012 with linkage to the national Social Insurance Institution registry data of the special reimbursement medication for hypertension from 1999 to 2013. The survey follow-up reached until the second follow-up in the year 2012. The register follow-up also included the year 2013. METHODS: The present population-based prospective cohort study, utilizing two different data sources, included 8593 respondents (22.7% response rate) who participated in 1998, 2003, and 2012 but who did not report hypertension at the baseline in 1998, and whose responses could be linked with the Social Insurance Institution registry data from the beginning of 1999 to the end of 2013. The multivariable logistic regression analysis was based on the combined two data sets. RESULTS: A significant association of self-reported migraine and incident hypertension (odds ratio 1.37; 95% confidence interval 1.20-1.57) prevailed in the multiple logistic regression analysis adjusted for central socio-demographic and health behaviour variables. CONCLUSION: Extra attention should be paid to prevention and control of hypertension in working-age migraine patients.

Physical inactivity, cardiometabolic disease, and risk of dementia: an individual-participant meta-analysis.

OBJECTIVE: To 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. DESIGN: Meta-analysis of 19 prospective observational cohort studies. DATA SOURCES: The 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 METHOD: The 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. RESULTS: Study 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). CONCLUSIONS: In 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.

Author Correction: Development and validation of a risk prediction model for work disability: multicohort study.

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Lifestyle factors and risk of sickness absence from work: a multicohort study.

BACKGROUND: Lifestyle factors influence the risk of morbidity and mortality, but the extent to which they are associated with employees' absence from work due to illness is unclear. We examined the relative contributions of smoking, alcohol consumption, high body-mass index, and low physical activity to diagnosis-specific sickness absence. METHODS: We did a multicohort study with individual-level data of participants of four cohorts from the UK, France, and Finland. Participants' responses to a lifestyle survey were linked to records of sickness absence episodes, typically lasting longer than 9 days; for each diagnostic category, the outcome was the total number of sickness absence days per year. We estimated the associations between lifestyle factors and sickness absence by calculating rate ratios for the number of sickness absence days per year and combining cohort-specific estimates with meta-analysis. The criteria for assessing the evidence included the strength of association, consistency across cohorts, robustness to adjustments and multiple testing, and impact assessment by use of population attributable fractions (PAF), with both internal lifestyle factor prevalence estimates and those obtained from European populations (PAFexternal). FINDINGS: For 74 296 participants, during 446 478 person-years at risk, the most common diagnoses for sickness absence were musculoskeletal diseases (70·9 days per 10 person-years), depressive disorders (26·5 days per 10 person-years), and external causes (such as injuries and poisonings; 12·8 days per 10 person-years). Being overweight (rate ratio [adjusted for age, sex, socioeconomic status, and chronic disease at baseline] 1·30, 95% CI 1·21-1·40; PAFexternal 8·9%) and low physical activity (1·23, 1·14-1·34; 7·8%) were associated with absences due to musculoskeletal diseases; heavy episodic drinking (1·90, 1·41-2·56; 15·2%), smoking (1·70, 1·42-2·03; 11·8%), low physical activity (1·67, 1·42-1·96; 19·8%), and obesity (1·38, 1·11-1·71; 5·6%) were associated with absences due to depressive disorders; heavy episodic drinking (1·64, 1·33-2·03; 11·3%), obesity (1·48, 1·27-1·72; 6·6%), smoking (1·35, 1·20-1·53; 6·3%), and being overweight (1·20, 1·08-1·33; 6·2%) were associated with absences due to external causes; obesity (1·82, 1·40-2·36; 11·0%) and smoking (1·60, 1·30-1·98; 10·3%) were associated with absences due to circulatory diseases; low physical activity (1·37, 1·25-1·49; 12·0%) and smoking (1·27, 1·16-1·40; 4·9%) were associated with absences due to respiratory diseases; and obesity (1·67, 1·34-2·07; 9·7%) was associated with absences due to digestive diseases. INTERPRETATION: Lifestyle factors are associated with sickness absence due to several diseases, but observational data cannot determine the nature of these associations. Future studies should investigate the cost-effectiveness of lifestyle interventions aimed at reducing sickness absence and the use of information on lifestyle for identifying groups at risk. FUNDING: NordForsk, British Medical Research Council, Academy of Finland, Helsinki Institute of Life Sciences, and Economic and Social Research Council.

Obesity and loss of disease-free years owing to major non-communicable diseases: a multicohort study.

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/m2), overweight (≥25 kg/m2 to <30 kg/m2), and obesity (class I [mild] ≥30 kg/m2 to <35 kg/m2; class II-III [severe] ≥35 kg/m2) compared with normal weight (≥18·5 kg/m2 to <25 kg/m2) 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.

Work stress and risk of death in men and women with and without cardiometabolic disease: a multicohort study.

BACKGROUND: Although some cardiovascular disease prevention guidelines suggest a need to manage work stress in patients with established cardiometabolic disease, the evidence base for this recommendation is weak. We sought to clarify the status of stress as a risk factor in cardiometabolic disease by investigating the associations between work stress and mortality in men and women with and without pre-existing cardiometabolic disease. METHODS: In this multicohort study, we used data from seven cohort studies in the IPD-Work consortium, initiated between 1985 and 2002 in Finland, France, Sweden, and the UK, to examine the association between work stress and mortality. Work stress was denoted as job strain or effort-reward imbalance at work. We extracted individual-level data on prevalent cardiometabolic diseases (coronary heart disease, stroke, or diabetes [without differentiation by diabetes type]) at baseline. Work stressors, socioeconomic status, and conventional and lifestyle risk factors (systolic and diastolic blood pressure, total cholesterol, smoking status, BMI, physical activity, and alcohol consumption) were also assessed at baseline. Mortality data, including date and cause of death, were obtained from national death registries. We used Cox proportional hazards regression to study the associations of work stressors with mortality in men and women with and without cardiometabolic disease. RESULTS: We identified 102 633 individuals with 1 423 753 person-years at risk (mean follow-up 13·9 years [SD 3·9]), of whom 3441 had prevalent cardiometabolic disease at baseline and 3841 died during follow-up. In men with cardiometabolic disease, age-standardised mortality rates were substantially higher in people with job strain (149·8 per 10 000 person-years) than in those without (97·7 per 10 000 person-years; mortality difference 52·1 per 10 000 person-years; multivariable-adjusted hazard ratio [HR] 1·68, 95% CI 1·19-2·35). This mortality difference for job strain was almost as great as that for current smoking versus former smoking (78·1 per 10 000 person-years) and greater than those due to hypertension, high total cholesterol concentration, obesity, physical inactivity, and high alcohol consumption relative to the corresponding lower risk groups (mortality difference 5·9-44·0 per 10 000 person-years). Excess mortality associated with job strain was also noted in men with cardiometabolic disease who had achieved treatment targets, including groups with a healthy lifestyle (HR 2·01, 95% CI 1·18-3·43) and those with normal blood pressure and no dyslipidaemia (6·17, 1·74-21·9). In all women and in men without cardiometabolic disease, relative risk estimates for the work stress-mortality association were not significant, apart from effort-reward imbalance in men without cardiometabolic disease (mortality difference 6·6 per 10 000 person-years; multivariable-adjusted HR 1·22, 1·06-1·41). INTERPRETATION: In men with cardiometabolic disease, the contribution of job strain to risk of death was clinically significant and independent of conventional risk factors and their treatment, and measured lifestyle factors. Standard care targeting conventional risk factors is therefore unlikely to mitigate the mortality risk associated with job strain in this population. FUNDING: NordForsk, UK Medical Research Council, and Academy of Finland.

Long working hours and depressive symptoms: systematic review and meta-analysis of published studies and unpublished individual participant data.

Objectives This systematic review and meta-analysis combined published study-level data and unpublished individual-participant data with the aim of quantifying the relation between long working hours and the onset of depressive symptoms. Methods We searched PubMed and Embase for published prospective cohort studies and included available cohorts with unpublished individual-participant data. We used a random-effects meta-analysis to calculate summary estimates across studies. Results We identified ten published cohort studies and included unpublished individual-participant data from 18 studies. In the majority of cohorts, long working hours was defined as working ≥55 hours per week. In multivariable-adjusted meta-analyses of 189 729 participants from 35 countries [96 275 men, 93 454 women, follow-up ranging from 1-5 years, 21 747 new-onset cases), there was an overall association of 1.14 (95% confidence interval (CI) 1.03-1.25] between long working hours and the onset of depressive symptoms, with significant evidence of heterogeneity (I 2=45.1%, P=0.004). A moderate association between working hours and depressive symptoms was found in Asian countries (1.50, 95% CI 1.13-2.01), a weaker association in Europe (1.11, 95% CI 1.00-1.22), and no association in North America (0.97, 95% CI 0.70-1.34) or Australia (0.95, 95% CI 0.70-1.29). Differences by other characteristics were small. Conclusions This observational evidence suggests a moderate association between long working hours and onset of depressive symptoms in Asia and a small association in Europe.

Prediction of long-term absence due to sickness in employees: development and validation of a multifactorial risk score in two cohort studies.

Objectives This study aimed to develop and validate a risk prediction model for long-term sickness absence. Methods Survey responses on work- and lifestyle-related questions from 65 775 public-sector employees were linked to sickness absence records to develop a prediction score for medically-certified sickness absence lasting >9 days and ≥90 days. The score was externally validated using data from an independent population-based cohort of 13 527 employees. For both sickness absence outcomes, a full model including 46 candidate predictors was reduced to a parsimonious model using least-absolute-shrinkage-and-selection-operator (LASSO) regression. Predictive performance of the model was evaluated using C-index and calibration plots. Results Variance explained in ≥90-day sickness absence by the full model was 12.5%. In the parsimonious model, the predictors included self-rated health (linear and quadratic term), depression, sex, age (linear and quadratic), socioeconomic position, previous sickness absences, number of chronic diseases, smoking, shift work, working night shift, and quadratic terms for body mass index and Jenkins sleep scale. The discriminative ability of the score was good (C-index 0.74 in internal and 0.73 in external validation). Calibration plots confirmed high correspondence between the predicted and observed risk. In >9-day sickness absence, the full model explained 15.2% of the variance explained, but the C-index of the parsimonious model was poor (<0.65). Conclusions Individuals' risk of a long-term sickness absence that lasts ≥90 days can be estimated using a brief risk score. The predictive performance of this score is comparable to those for established multifactorial risk algorithms for cardiovascular disease, such as the Framingham risk score.

Body mass index and risk of dementia: Analysis of individual-level data from 1.3 million individuals.

INTRODUCTION: Higher midlife body mass index (BMI) is suggested to increase the risk of dementia, but weight loss during the preclinical dementia phase may mask such effects. METHODS: We examined this hypothesis in 1,349,857 dementia-free participants from 39 cohort studies. BMI was assessed at baseline. Dementia was ascertained at follow-up using linkage to electronic health records (N = 6894). We assumed BMI is little affected by preclinical dementia when assessed decades before dementia onset and much affected when assessed nearer diagnosis. RESULTS: Hazard ratios per 5-kg/m2 increase in BMI for dementia were 0.71 (95% confidence interval = 0.66-0.77), 0.94 (0.89-0.99), and 1.16 (1.05-1.27) when BMI was assessed 10 years, 10-20 years, and >20 years before dementia diagnosis. CONCLUSIONS: The association between BMI and dementia is likely to be attributable to two different processes: a harmful effect of higher BMI, which is observable in long follow-up, and a reverse-causation effect that makes a higher BMI to appear protective when the follow-up is short.

Characteristics of Social Networks and Mortality Risk: Evidence From 2 Prospective Cohort Studies.

The size of a person's social network is linked to health and longevity, but it is unclear whether the number of strong social ties or the number of weak social ties is most influential for health. We examined social network characteristics as predictors of mortality in the Finnish Public Sector Study (n = 7,617) and the Health and Social Support Study (n = 20,816). Social network characteristics were surveyed at baseline in 1998. Information about mortality was obtained from the Finnish National Death Registry. During a mean follow-up period of 16 years, participants with a small social network (≤10 members) were more likely to die than those with a large social network (≥21 members) (adjusted hazard ratio (HR) = 1.23, 95% confidence interval (CI): 1.04, 1.46). Mortality risk was increased among participants with both a small number of strong ties (≤2 members) and a small number of weak ties (≤5 members) (HR = 1.55, 95% CI: 1.26, 1.79) and among participants with both a large number of strong ties and a small number of weak ties (HR = 1.28, 95% CI: 1.08, 1.52), but not among those with a small number of strong ties and a large number of weak ties (HR = 1.04, 95% CI: 0.87, 1.25). These findings suggest that in terms of mortality risk, the number of weak ties may be an important component of social networks.

Changes in sleep quality with age-a 36-year follow-up study of Finnish working-aged adults.

Long-term follow-up data on changes in sleep quality among middle-aged adults is scarce. We assessed sleep quality in a population-based cohort (n = 4847) of twins born between 1945 and 1957 during a follow-up of 36 years, with four measurement points in 1975, 1981, 1990 and 2011. Sleep quality was categorized as sleeping well, fairly well, fairly poorly or poorly. The mean age at the beginning of follow-up was 24.0, and at the end was 60.3 years. Of all the adults, 71.1% slept well or fairly well at each time-point throughout the follow-up and 0.5% poorly or fairly poorly. The proportion of those sleeping poorly or fairly poorly increased linearly over time; 3.5% among both sexes at the start, and 15.5% among men and 20.9% among women at the end of the follow-up. The last survey indicated a strong association between self-rated health and sleep quality: sleeping poorly or fairly poorly was reported 15 times more frequently by those rating their health as fairly poor than by those rating their health as very good. There was a strong association between indicators of depression and poor sleep. Although many studies have reported increasing frequencies in sleep problems, our results, based on a long-term cohort study, indicate that the majority of people sleep well or fairly well. Sleep quality declines with age, but only a very small fraction of the adults in this long follow-up consistently slept poorly.

Education in Twins and Their Parents Across Birth Cohorts Over 100 years: An Individual-Level Pooled Analysis of 42-Twin Cohorts.

Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990-1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.

Development and validation of a risk prediction model for work disability: multicohort study.

Work disability affects quality of life, earnings, and opportunities to contribute to society. Work characteristics, lifestyle and sociodemographic factors have been associated with the risk of work disability, but few multifactorial algorithms exist to identify individuals at risk of future work disability. We developed and validated a parsimonious multifactorial score for the prediction of work disability using individual-level data from 65,775 public-sector employees (development cohort) and 13,527 employed adults from a general population sample (validation cohort), both linked to records of work disability. Candidate predictors for work disability included sociodemographic (3 items), health status and lifestyle (38 items), and work-related (43 items) variables. A parsimonious model, explaining > 99% of the variance of the full model, comprised 8 predictors: age, self-rated health, number of sickness absences in previous year, socioeconomic position, chronic illnesses, sleep problems, body mass index, and smoking. Discriminative ability of a score including these predictors was high: C-index 0.84 in the development and 0.83 in the validation cohort. The corresponding C-indices for a score constructed from work-related predictors (age, sex, socioeconomic position, job strain) were 0.79 and 0.78, respectively. It is possible to identify reliably individuals at high risk of work disability by using a rapidly-administered prediction score.

Long working hours as a risk factor for atrial fibrillation: a multi-cohort study.

AIMS: Studies suggest that people who work long hours are at increased risk of stroke, but the association of long working hours with atrial fibrillation, the most common cardiac arrhythmia and a risk factor for stroke, is unknown. We examined the risk of atrial fibrillation in individuals working long hours (≥55 per week) and those working standard 35-40 h/week. METHODS AND RESULTS: In this prospective multi-cohort study from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium, the study population was 85 494 working men and women (mean age 43.4 years) with no recorded atrial fibrillation. Working hours were assessed at study baseline (1991-2004). Mean follow-up for incident atrial fibrillation was 10 years and cases were defined using data on electrocardiograms, hospital records, drug reimbursement registers, and death certificates. We identified 1061 new cases of atrial fibrillation (10-year cumulative incidence 12.4 per 1000). After adjustment for age, sex and socioeconomic status, individuals working long hours had a 1.4-fold increased risk of atrial fibrillation compared with those working standard hours (hazard ratio = 1.42, 95% CI = 1.13-1.80, P = 0.003). There was no significant heterogeneity between the cohort-specific effect estimates (I2 = 0%, P = 0.66) and the finding remained after excluding participants with coronary heart disease or stroke at baseline or during the follow-up (N = 2006, hazard ratio = 1.36, 95% CI = 1.05-1.76, P = 0.0180). Adjustment for potential confounding factors, such as obesity, risky alcohol use and high blood pressure, had little impact on this association. CONCLUSION: Individuals who worked long hours were more likely to develop atrial fibrillation than those working standard hours.

Change in ß2-agonist use after severe life events in adults with asthma: A population-based cohort study: Life events and bronchodilator usage among adults with asthma.

OBJECTIVE: This prospective, population-based cohort study of 1102 Finnish adults with asthma, examined whether exposure to stressful life events is associated with the intensity of usage of inhaled short-acting ß2-agonists. METHODS: Survey data was collected by two postal questionnaires. Baseline characteristics were obtained in 1998 and data on 19 specific stressful events (e.g. death of a child or spouse or divorce) within the six preceding months in 2003. Exposure to life events was indicated by a sum score weighted by mean severity of the events. Participants were linked to records of filled prescriptions for inhaled short-acting ß2-agonists from national registers from 2000 through 2006. The rates of purchases of short-acting ß2-agonists before (2000-2001), during (2002-2003) and after (2004-2006) the event exposure were estimated using repeated-measures Poisson regression analyses with the generalized estimating equation. RESULTS: Of the 1102 participants, 162 (15%) were exposed to highly stressful events, 205 (19%) to less stressful events. During the 7-year observation period, 5955 purchases of filled prescription for inhaled short-acting ß2-agonists were recorded. After exposure to highly stressful events, the rate of purchases of ß2-agonists was 1.50 times higher (95% confidence interval (CI): 1.05, 2.13) than before the stressful event occurred. Among those with low or no exposure to life events, the corresponding rate ratios were not elevated (rate ratio 0.81, 95% CI: 0.66, 0.99 and 0.95, 95% CI: 0.83, 1.09 respectively). CONCLUSION: An increase in ß2-agonist usage after severe life events suggests that stressful experiences may worsen asthma symptoms.

Social support and breast cancer: A comparatory study of breast cancer survivors, women with mental depression, women with hypertension and healthy female controls.

OBJECTIVES: Among breast cancer (BC) survivors, inadequate social support (SS) is associated with a significant increase in cancer-related mortality and reduction in quality of life (QoL). The aim of the study was to explore perceived SS during BC trajectory by comparing BC survivors, women with depression, women with arterial hypertension, and healthy female controls to each other, and to compare perceived balance of receiving and providing SS. MATERIAL AND METHODS: The data of ongoing prospective postal survey was linked with national health registries. Respondents with BC (n = 64), depression (n = 471), arterial hypertension (n = 841) and healthy controls (n = 6274) formed the study population. SS was measured by a Sarason's 6-item shortened version of the Social Support Questionnaire (SSQ). The modified Antonucci's (1986) social support convoy model of the network of individuals was used to measure the dominating direction of SS. RESULTS: The main provider of SS for all participants combined was the spouse or partner (94.3%), close relative (12.0%) and friends (5.4%). In all groups, particularly in the BC and arterial hypertension group, spouse or partner was seen as the most important supporter. The group suffering from depression reported significantly less SS in each domain of appraisal (p < 0.001). In total, 24.6% of all respondents reported receipt dominance of SS. CONCLUSION: SS is a well-known determinant of wellbeing. Our study lends support to the spouse's or the partner's central role during the recovery phase of BC. Identification of factors improving the overall QoL of BC survivors is an important public health challenge.

Social networks and patterns of health risk behaviours over two decades: A multi-cohort study.

OBJECTIVE: To determine the associations between social network size and subsequent long-term health behaviour patterns, as indicated by alcohol use, smoking, and physical activity. METHODS: Repeat data from up to six surveys over a 15- or 20-year follow-up were drawn from the Finnish Public Sector study (Raisio-Turku cohort, n=986; Hospital cohort, n=7307), and the Health and Social Support study (n=20,115). Social network size was determined at baseline, and health risk behaviours were assessed using repeated data from baseline and follow-up. We pooled cohort-specific results from repeated-measures log-binomial regression with the generalized estimating equations (GEE) method using fixed-effects meta-analysis. RESULTS: Participants with up to 10 members in their social network at baseline had an unhealthy risk factor profile throughout the follow-up. The pooled relative risks adjusted for age, gender, survey year, chronic conditions and education were 1.15 for heavy alcohol use (95% CI: 1.06-1.24), 1.19 for smoking (95% CI: 1.12-1.27), and 1.25 for low physical activity (95% CI: 1.21-1.29), as compared with those with >20 members in their social network. These associations appeared to be similar in subgroups stratified according to gender, age and education. CONCLUSIONS: Social network size predicted persistent behaviour-related health risk patterns up to at least two decades.

Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe.

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. INTERPRETATION: 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. FUNDING: NordForsk, Medical Research Council, Cancer Research UK, Finnish Work Environment Fund, and Academy of Finland.

Impact of major life events on breast-cancer-specific mortality: A case fatality study on 8000 breast cancer patients.

BACKGROUND: It has been suggested that long-term activation of the body's stress-response system and subsequent overexposure to stress hormones may be associated with increased morbidity. However, evidence on the impact of major life events on mortality from breast cancer (BC) remains inconclusive. The main aim of this study is to investigate whether major negatively or positively experienced life events before or after diagnosis have an effect on BC-specific mortality in women who have survived with BC for at least 2 years. METHODS: We conducted a case fatality study with data on life events from a self-administered survey and data on BC from the Finnish Cancer Registry. Cox models were fitted to estimate BC mortality hazard ratios (MRs) between those who have undergone major life events and those who haven't. RESULTS: None of the pre-diagnostic negative life events had any effect on BC-specific mortality. Regarding post-diagnostic events, the effect was greatest in women with moderate scores of events. As for event-specific scores, increased BC mortality was observed with spouse unemployment, relationship problems, and death of a close friend. By contrast, falling in love and positive developments in hobbies were shown to be associated with lower BC mortality (MRs 0.67, 95%CI: 0.49-0.92 and 0.74, 95%CI: 0.57-0.96, respectively). In an analysis restricted to recently diagnosed cases (2007), also death of a child and of a mother was associated with increased BC mortality. CONCLUSIONS: Some major life events regarding close personal relationships may play a role in BC-specific mortality, with certain negative life events increasing BC mortality and positive events decreasing it. The observed favorable associations between positive developments in romantic relationships and hobbies and BC mortality are likely to reflect the importance of social interaction and support.

Leisure-time physical inactivity and association with body mass index: a Finnish Twin Study with a 35-year follow-up.

Background: We investigated the stability and change of leisure-time physical inactivity in adult men and women during a 35-year follow-up. We also analysed the impact of long-term physical inactivity on the development of body mass index (BMI). Methods: : In this population-based cohort study, 5254 Finnish twin individuals (59% women) participated in four surveys in 1975, 1981, 1990 and 2011. Mean age at baseline was 23.9 years. Individual long-term leisure-time physical activity (LTPA) was categorized into seven classes varying from 'persistently inactive' to 'persistently active'. We used the multivariate multilevel mixed-effects linear regression model and paired-sample t-test in the analyses. Co-twin control design was used for examining within-pair associations. Results: : Of men 11%, and of women 8%, were persistently inactive. Among both sexes, the mean BMI slope trajectories were steeper among the persistently inactive and those who became inactive than among those who were persistently active. Overall, the inactive participants gained 1.4 kg/m 2 [95% confidence interval (CI) 1.2 to 1.7] more in weight than did the active participants from 1975 to 2011. Among twin pairs discordant for LTPA, the corresponding difference was 1.4 kg/m 2 (95% CI 0.83 to 2.0) in dizygotic pairs and 0.68 kg/m 2 (95% CI 0.05 to1.3) in monozygotic pairs. Conclusions: Over a 35-year time span from young adulthood, persistently inactive participants and those who had become inactive had greater weight increases than those who were persistently active. This association was also found in twin-pair analyses, although attenuated in monozygotic pairs. This may support the importance of LTPA in weight management, although further causal inference is required.