Work ability trends 2000-2020 and birth-cohort projections until 2040 in Finland.

Aims: To examine age-group and birth-cohort trends in perceived work ability in Finland in 2000-2020 and make projections of perceived work ability up to 2040 based on the observed birth-cohort development. Methods: Ten population-representative cross-sectional surveys conducted in Finland between 2000 and 2020 were used (overall N = 61,087, range 817-18,956). Self-reported estimates of current work ability in relation to the person's lifetime best on a scale from zero to ten (0-10) were classified into three groups: limited (0-5), intermediate (6-7), and good (8-10). Multiple imputation was used in projecting work ability. Results: Examining past trends by 5-year birth-cohorts born between 1961 and 1995 showed that work ability has declined steadily over time among older birth-cohorts, while in the two younger cohorts a stable development before 2017 and a steep decline between 2017 and 2020 was seen. Trends by 5-year age groups showed a declining trend of good work ability among 20-44-year-olds, a stable trend among 45-54-year-olds, and an improving trend among 55-year-olds and older was observed for the period 2000-2020. Among the under 55-year-olds the prevalence of good work ability ended up around 75% and at 68% among the 55-59-year-olds, 58% among the 60-69-year-olds and 49% among the 70-74-year-olds in 2020. Birth-cohort projections suggested a declining work ability in the future among all age groups included (30-74 years). By 2040, the prevalence of good work ability is projected to decline by 10 to 15 percentage points among 45-74-year-olds. Conclusions: The projections suggest declining work ability in the future. Efforts to counteract the decline in work ability are needed.

Regional and temporal differences in the associations between cardiovascular disease and its classic risk factors: an analysis of 49 cohorts from 11 European countries.

AIMS: The regional and temporal differences in the associations between cardiovascular disease (CVD) and its classic risk factors are unknown. The current study examined these associations in different European regions over a 30-year period. METHODS AND RESULTS: The study sample comprised 553 818 individuals from 49 cohorts in 11 European countries (baseline: 1982-2012) who were followed up for a maximum of 10 years. Risk factors [sex, smoking, diabetes, non-HDL cholesterol, systolic blood pressure (BP), and body mass index (BMI)] and CVD events (coronary heart disease or stroke) were harmonized across cohorts. Risk factor-outcome associations were analysed using multivariable-adjusted Cox regression models, and differences in associations were assessed using meta-regression. The differences in the risk factor-CVD associations between central Europe, northern Europe, southern Europe, and the UK were generally small. Men had a slightly higher hazard ratio (HR) in southern Europe (P = 0.043 for overall difference), and those with diabetes had a slightly lower HR in central Europe (P = 0.022 for overall difference) compared with the other regions. Of the six CVD risk factors, minor HR decreases per decade were observed for non-HDL cholesterol [7% per mmol/L; 95% confidence interval (CI), 3-10%] and systolic BP (4% per 20 mmHg; 95% CI, 1-8%), while a minor HR increase per decade was observed for BMI (7% per 10 kg/m2; 95% CI, 1-13%). CONCLUSION: The results demonstrate that all classic CVD risk factors are still relevant in Europe, irrespective of regional area. Preventive strategies should focus on risk factors with the greatest population attributable risk.

All classic cardiovascular disease (CVD) risk factors are still relevant in Europe, irrespective of regional area. The differences in the associations of CVD risk factors with overt CVD between regions of Europe are generally small. Minor temporal hazard decreases were observed for non-HDL cholesterol and systolic blood pressure, while a minor hazard increase was observed for body mass index.

Diabetes and heart failure associations in women and men: Results from the MORGAM consortium.

Background: Diabetes and its cardiovascular complications are a growing concern worldwide. Recently, some studies have demonstrated that relative risk of heart failure (HF) is higher in women with type 1 diabetes (T1DM) than in men. This study aims to validate these findings in cohorts representing five countries across Europe. Methods: This study includes 88,559 (51.8% women) participants, 3,281 (46.3% women) of whom had diabetes at baseline. Survival analysis was performed with the outcomes of interest being death and HF with a follow-up time of 12 years. Sub-group analysis according to sex and type of diabetes was also performed for the HF outcome. Results: 6,460 deaths were recorded, of which 567 were amongst those with diabetes. Additionally, HF was diagnosed in 2,772 individuals (446 with diabetes). A multivariable Cox proportional hazard analysis showed that there was an increased risk of death and HF (hazard ratio (HR) of 1.73 [1.58-1.89] and 2.12 [1.91-2.36], respectively) when comparing those with diabetes and those without. The HR for HF was 6.72 [2.75-16.41] for women with T1DM vs. 5.80 [2.72-12.37] for men with T1DM, but the interaction term for sex differences was insignificant (p for interaction 0.45). There was no significant difference in the relative risk of HF between men and women when both types of diabetes were combined (HR 2.22 [1.93-2.54] vs. 1.99 [1.67-2.38] respectively, p for interaction 0.80). Conclusion: Diabetes is associated with increased risks of death and heart failure, and there was no difference in relative risk according to sex.

Development of non-communicable disease risk factors in Finland: projections up to 2040.

BACKGROUND: Non-communicable diseases are a major cause of mortality and morbidity worldwide. They share the same behavioural risk factors (smoking, sedentary behaviour, alcohol consumption and an unhealthy diet), all of which are modifiable risk factors, and biological consequences (hypertension, elevated total cholesterol, obesity and diabetes). METHODS: Using data from a series of cross-sectional health examination surveys conducted among the adult population in Finland from 1997 to 2017, a projection of risk factor development (smoking, leisure time sedentary behaviour, hypertension, elevated total cholesterol, overweight and obesity, and diabetes) up to the year 2040 was made. The projections were estimated using a multiple imputation method. RESULTS: Smoking prevalence is estimated to continue to decline up to 2040, similar to hypertension and elevated total cholesterol. By contrast, obesity and diabetes will develop unfavourably, with an increase in prevalence. The increase in obesity is mainly due to polarisation - that is, normal-weight people remain of a normal weight, but overweight people tend to gain more weight and become obese. The observed and estimated changes for leisure time sedentary lifestyle were not statistically significant. CONCLUSIONS: Projections of risk factors for non-communicable diseases are needed to guide public health policies and programmes, decision-making and the allocation of health care resources for prevention and care. In Finland, favourable developments have been seen in many of the risk factors, but obesity and diabetes show unfavourable development. There is a need to continue regular, systematic monitoring of the development of risk factors through health examination surveys and to set national goals and programmes to tackle the existing problems.

Projections for obesity, smoking and hypertension based on multiple imputation.

AIMS: Information on the future development of prevalences of risk factors and health indicators is needed to prepare for the forthcoming burden of disease in the population and to allocate resources properly for prevention. We aim to present how multiple imputation can be used flexibly to project future prevalences. METHODS: The proposed approach uses data on repeated cross-sectional surveys from different years. We create future samples with age and sex distributions corresponding to the official national population forecasts. Then, the risk factors are simulated using multiple imputation by chained equations. Finally, the imputations are pooled to obtain the prevalences of interest. Covariates, such as sociodemographic variables as well as their possible interactions and non-linear terms, can be included in the modelling. The future development of these covariates is also projected simultaneously. We apply the procedure to data from five Finnish health examination surveys conducted between 1997 and 2017, and project the prevalences of obesity, smoking and hypertension to 2020 and 2025. RESULTS: The prevalence of obesity is projected to increase to 24% for both men and women in 2025. The prevalences of hypertension and smoking are expected to continue decreasing, and the differences between men and women are projected to remain so that men will have higher prevalences. CONCLUSIONS: Simulation of future observations by multiple imputation can be used as a flexible yet relatively easy-to-use projection method.

Associations of the vasoactive peptides CT-proET-1 and MR-proADM with incident type 2 diabetes: results from the BiomarCaRE Consortium.

BACKGROUND: Endothelin-1 (ET-1) and adrenomedullin (ADM) are commonly known as vasoactive peptides that regulate vascular homeostasis. Less recognised is the fact that both peptides could affect glucose metabolism. Here, we investigated whether ET-1 and ADM, measured as C-terminal-proET-1 (CT-proET-1) and mid-regional-proADM (MR-proADM), respectively, were associated with incident type 2 diabetes. METHODS: Based on the population-based Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) Consortium data, we performed a prospective cohort study to examine associations of CT-proET-1 and MR-proADM with incident type 2 diabetes in 12,006 participants. During a median follow-up time of 13.8 years, 862 participants developed type 2 diabetes. The associations were examined in Cox proportional hazard models. Additionally, we performed two-sample Mendelian randomisation analyses using published data. RESULTS: CT-proET-1 and MR-proADM were positively associated with incident type 2 diabetes. The multivariable hazard ratios (HRs) [95% confidence intervals (CI)] were 1.10 [1.03; 1.18], P = 0.008 per 1-SD increase of CT-proET-1 and 1.11 [1.02; 1.21], P = 0.016 per 1-SD increase of log MR-proADM, respectively. We observed a stronger association of MR-proADM with incident type 2 diabetes in obese than in non-obese individuals (P-interaction with BMI < 0.001). The HRs [95%CIs] were 1.19 [1.05; 1.34], P = 0.005 and 1.02 [0.90; 1.15], P = 0.741 in obese and non-obese individuals, respectively. Our Mendelian randomisation analyses yielded a significant association of CT-proET-1, but not of MR-proADM with type 2 diabetes risk. CONCLUSIONS: Higher concentrations of CT-proET-1 and MR-proADM are associated with incident type 2 diabetes, but our Mendelian randomisation analysis suggests a probable causal link for CT-proET-1 only. The association of MR-proADM seems to be modified by body composition.

Influence of geographical latitude on vitamin D status: cross-sectional results from the BiomarCaRE consortium.

Even though sunlight is viewed as the most important determinant of 25-hydroxyvitamin D (25(OH)D) status, several European studies have observed higher 25(OH)D concentrations among north-Europeans than south-Europeans. We studied the association between geographical latitude (derived from ecological data) and 25(OH)D status in six European countries using harmonised immunoassay data from 81 084 participants in the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) project (male sex 48·9 %; median age 50·8 years; examination period 1984-2014). Quantile regression models, adjusted for age, sex, decade and calendar week of sampling and time from sampling to analysis, were used for between-country comparisons. Up until the median percentile, the ordering of countries by 25(OH)D status (from highest to lowest) was as follows: Sweden (at 65·6-63·8°N), Germany (at 48·4°N), Finland (at 65·0-60·2°N), Italy (at 45·6-41·5°N), Scotland (at 58·2-55·1°N) and Spain (at 41·5°N). From the 75th percentile and upwards, Finland had higher values than Germany. As an example, using the Swedish cohort as a comparator, the median 25(OH)D concentration was 3·03, 3·28, 5·41, 6·54 and 9·28 ng/ml lower in the German, Finnish, Italian, Scottish and Spanish cohort, respectively (P-value < 0·001 for all comparisons). The ordering of countries was highly consistent in subgroup analyses by sex, age, and decade and season of sampling. In conclusion, we confirmed the previous observation of a north-to-south gradient of 25(OH)D status in Europe, with higher percentile values among north-Europeans than south-Europeans.

Cross-national comparisons of health indicators require standardized definitions and common data sources.

BACKGROUND: Health indicators are used to monitor the health status and determinants of health of the population and population sub-groups, identify existing or emerging health problems which would require prevention and health promotion activities, help to target health care resources in the most adequate way as well as for evaluation of the success of public health actions both at the national and international level. The quality and validity of the health indicator depends both on available data and used indicator definition. In this study we will evaluate existing knowledge about comparability of different data sources for definition of health indicators, compare how selected health indicators presented in different international databases possibly differ, and finally, present the results from a case study from Finland on comparability of health indicators derived from different data sources at national level. METHODS: For comparisons, four health indicators were selected that were commonly available in international databases and available for the Finnish case study. These were prevalence of obesity, hypertension, diabetes, and asthma in the adult populations. Our evaluation has three parts: 1) a scoping review of the latest literature, 2) comparison of the prevalences presented in different international databases, and 3) a case study using data from Finland. RESULTS: Literature shows that comparability of estimated outcomes for health indicators using different data sources such as self-reported questionnaire data from surveys, measured data from surveys or data from administrative health registers, varies between indicators. Also, the case study from Finland showed that diseases which require regular health care visits such as diabetes, comparability is high while for health outcomes which can remain asymptomatic for a long time such as hypertension, comparability is lower. In different international health related databases, country specific results differ due to variations in the used data sources but also due to differences in indicator definitions. CONCLUSIONS: Reliable comparison of the health indicators over time and between regions within a country or across the countries requires common indicator definitions, similar data sources and standardized data collection methods.

Diabetes status-related differences in risk factors and mediators of heart failure in the general population: results from the MORGAM/BiomarCaRE consortium.

BACKGROUND: The risk of heart failure among diabetic individuals is high, even under tight glycemic control. The correlates and mediators of heart failure risk in individuals with diabetes need more elucidation in large population-based cohorts with long follow-up times and a wide panel of biologically relevant biomarkers. METHODS: In a population-based sample of 3834 diabetic and 90,177 non-diabetic individuals, proportional hazards models and mediation analysis were used to assess the relation of conventional heart failure risk factors and biomarkers with incident heart failure. RESULTS: Over a median follow-up of 13.8 years, a total of 652 (17.0%) and 5524 (6.1%) cases of incident heart failure were observed in participants with and without diabetes, respectively. 51.4% were women and the mean age at baseline was 48.7 (standard deviation [SD] 12.5) years. The multivariable-adjusted hazard ratio (HR) for heart failure among diabetic individuals was 2.70 (95% confidence interval, 2.49-2.93) compared to non-diabetic participants. In the multivariable-adjusted Cox models, conventional cardiovascular disease risk factors, such as smoking (diabetes: HR 2.07 [1.59-2.69]; non-diabetes: HR 1.85 [1.68-2.02]), BMI (diabetes: HR 1.30 [1.18-1.42]; non-diabetes: HR 1.40 [1.35-1.47]), baseline myocardial infarction (diabetes: HR 2.06 [1.55-2.75]; non-diabetes: HR 2.86 [2.50-3.28]), and baseline atrial fibrillation (diabetes: HR 1.51 [0.82-2.80]; non-diabetes: HR 2.97 [2.21-4.00]) had the strongest associations with incident heart failure. In addition, biomarkers for cardiac strain (represented by nT-proBNP, diabetes: HR 1.26 [1.19-1.34]; non-diabetes: HR 1.43 [1.39-1.47]), myocardial injury (hs-TnI, diabetes: HR 1.10 [1.04-1.16]; non-diabetes: HR 1.13 [1.10-1.16]), and inflammation (hs-CRP, diabetes: HR 1.13 [1.03-1.24]; non-diabetes: HR 1.29 [1.25-1.34]) were also associated with incident heart failure. In general, all these associations were equally strong in non-diabetic and diabetic individuals. However, the strongest mediators of heart failure in diabetes were the direct effect of diabetes status itself (relative effect share 43.1% [33.9-52.3] and indirect effects (effect share 56.9% [47.7-66.1]) mediated by obesity (BMI, 13.2% [10.3-16.2]), cardiac strain/volume overload (nT-proBNP, 8.4% [-0.7-17.4]), and hyperglycemia (glucose, 12.0% [4.2-19.9]). CONCLUSIONS: The findings suggest that the main mediators of heart failure in diabetes are obesity, hyperglycemia, and cardiac strain/volume overload. Conventional cardiovascular risk factors are strongly related to incident heart failure, but these associations are not stronger in diabetic than in non-diabetic individuals. Active measurement of relevant biomarkers could potentially be used to improve prevention and prediction of heart failure in high-risk diabetic patients.

Natriuretic Peptides and Risk of Type 2 Diabetes: Results From the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) Consortium.

OBJECTIVE: Natriuretic peptide (NP) concentrations are increased in cardiovascular diseases (CVDs) but are associated with a lower diabetes risk. We investigated associations of N-terminal pro-B-type NP (NT-proBNP) and midregional proatrial NP (MR-proANP) with incident type 2 diabetes stratified by the presence of CVD. RESEARCH DESIGN AND METHODS: Based on the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) Consortium, we included 45,477 participants with NT-proBNP measurements (1,707 developed type 2 diabetes over 6.5 years of median follow-up; among these, 209 had CVD at baseline) and 11,537 participants with MR-proANP measurements (857 developed type 2 diabetes over 13.8 years of median follow-up; among these, 106 had CVD at baseline). The associations were estimated using multivariable Cox regression models. RESULTS: Both NPs were inversely associated with incident type 2 diabetes (hazard ratios [95% CI] per 1-SD increase of log NP: 0.84 [0.79; 0.89] for NT-proBNP and 0.77 [0.71; 0.83] for MR-proANP). The inverse association between NT-proBNP and type 2 diabetes was significant in individuals without CVD but not in individuals with CVD (0.81 [0.76; 0.86] vs. 1.04 [0.90; 1.19]; P multiplicative interaction = 0.001). There was no significant difference in the association of MR-proANP with type 2 diabetes between individuals without and with CVD (0.75 [0.69; 0.82] vs. 0.81 [0.66; 0.99]; P multiplicative interaction = 0.236). CONCLUSIONS: NT-proBNP and MR-proANP are inversely associated with incident type 2 diabetes. However, the inverse association of NT-proBNP seems to be modified by the presence of CVD. Further investigations are warranted to confirm our findings and to investigate the underlying mechanisms.

Cardiac Troponin I and Incident Stroke in European Cohorts: Insights From the BiomarCaRE Project.

BACKGROUND AND PURPOSE: Stroke is a common cause of death and a leading cause of disability and morbidity. Stroke risk assessment remains a challenge, but circulating biomarkers may improve risk prediction. Controversial evidence is available on the predictive ability of troponin concentrations and the risk of stroke in the community. Furthermore, reports on the predictive value of troponin concentrations for different stroke subtypes are scarce. METHODS: High-sensitivity cardiac troponin I (hsTnI) concentrations were assessed in 82 881 individuals (median age, 50.7 years; 49.7% men) free of stroke or myocardial infarction at baseline from 9 prospective European community cohorts. We used Cox proportional hazards regression to determine relative risks, followed by measures of discrimination and reclassification using 10-fold cross-validation to control for overoptimism. Follow-up was based upon linkage with national hospitalization registries and causes of death registries. RESULTS: Over a median follow-up of 12.7 years, 3033 individuals were diagnosed with incident nonfatal or fatal stroke (n=1654 ischemic strokes, n=612 hemorrhagic strokes, and n=767 indeterminate strokes). In multivariable regression models, hsTnI concentrations were associated with overall stroke (hazard ratio per 1-SD increase, 1.15 [95% CI, 1.10-1.21]), ischemic stroke (hazard ratio, 1.14 [95% CI, 1.09-1.21]), and hemorrhagic stroke (hazard ratio, 1.10 [95% CI, 1.01-1.20]). Adding hsTnI concentrations to classical cardiovascular risk factors (C indices, 0.809, 0.840, and 0.736 for overall, ischemic, and hemorrhagic stroke, respectively) increased the C index significantly but modestly. In individuals with an intermediate 10-year risk (5%-20%), the net reclassification improvement for overall stroke was 0.038 (P=0.021). CONCLUSIONS: Elevated hsTnI concentrations are associated with an increased risk of incident stroke in the community, irrespective of stroke subtype. Adding hsTnI concentrations to classical risk factors only modestly improved estimation of 10-year risk of stroke in the overall cohort but might be of some value in individuals at an intermediate risk.

Comparing data sources in estimating disability-adjusted life years (DALYs) for ischemic heart disease and chronic obstructive pulmonary disease in a cross-sectional setting in Finland.

BACKGROUND: The disability-adjusted life years (DALYs) summarize the burden of years of life lost (YLL) due to premature mortality and years lost due to disability (YLD). Our aim was to estimate the burden of ischemic heart disease (IHD) and chronic obstructive pulmonary disease (COPD) in Finland in 2012, and to examine, how much the YLD are affected by the use of different data sources. METHODS: The YLL were calculated using mortality data for the Finnish 25-74-year-old population in 2012. The YLD were calculated using data from the FINRISK 2012 survey (3041 males, 3383 females aged 25-74 years) and then directly adjusted to the corresponding population. Different administrative registers on 1) hospital inpatient episodes and specialist outpatient visits, 2) entitlement to specially reimbursed medicines, and 3) purchases of prescribed medicines were used for estimation of the YLD in addition to self-reported data. The DALYs were calculated without age-weighting. RESULTS: The YLL for IHD were 37.5 for males and 9.1 for females per 1000 population among 25-74-year-old people in Finland in 2012. The YLD for IHD varied markedly depending on which data sources were used. All data sources combined, the YLD per 1000 were 5.3 for males and 2.5 for females resulting in estimated 42.8 and 11.6 DALYs per 1000 due to IHD among males and females, respectively. For COPD, the YLL were 4.7 for males and 2.0 for females per 1000. Also for COPD, the YLD varied markedly depending on data sources used. The YLD per 1000 based on all data sources combined were 2.0 for males and 1.6 for females. As a result, estimated 6.7 and 3.6 DALYs per 1000 were due to COPD among males and females, respectively. CONCLUSIONS: Especially for COPD, all mild disease cases could probably not be identified from the included registers. Thereby, including survey data improved the coverage of the data. The YLD of IHD and COPD varied markedly between the data sources used in the calculations. However, as YLL constituted a major part of DALYs for these diseases, the variation in YLD did not lead to substantial variation in DALYs.

Living alone and positive mental health: a systematic review.

BACKGROUND: Living alone has become more common in today's societies. Despite the high number of the population living alone, research directed towards the mental wellbeing issues related to living alone has been limited. This systematic literature review aimed to assess the association between living alone and positive mental health. METHODS: We conducted searches in Medline, Web of Science, Cochrane Library, CINAHL, PsycINFO, and other complementary databases from January 1998 to May 2019. Randomised trials and observational studies investigating adults over 18 years of age and living alone (defined as living in a single household or a household size of one person) were eligible. The primary outcome was positive mental health, defined as comprising both hedonic and eudaimonic elements of mental wellbeing, and it was measured with the Warwick-Edinburgh Mental Well-being Scale and/or theWHO-5 Index. Two reviewers independently screened and selected data; one reviewer extracted data, and the second checked the extracted data. A narrative synthesis described the quality and content of the evidence. Included studies were appraised using relevant Joanna Briggs Institute checklist. RESULTS: A total of 4 cross-sectional studies (22,591 adult participants) were included after screening of 341 titles and abstracts and 46 full-text articles. These studies were conducted in Europe and were published between 2014 and 2017. The studies differed in their measurements of positive mental health (WHO-5 Well-Being Index, 3 studies; WEMWBS, 1 study), sources of data (1 regional, 1 national, and 2 European-level studies), and study populations (regional study, adults over 65 years of age; national-level study, mental health nurses over 21 years of age; European-level studies, employees between 15 and 65 years of age and adults over 18 years of age). A potential association between living alone and low positive mental health was found in three out of the four studies. Our findings were limited as the number of included studies was low and the quality of evidence varied across studies. CONCLUSIONS: This review allows a limited look at the association between living alone and positive mental health. Because the number of included studies was low and the quality of evidence varied across studies, further research is warranted.

Adjusting for non-response in the Finnish Drinking Habits Survey.

AIM: We aim to compare four different weighting methods to adjust for non-response in a survey on drinking habits and to examine whether the problem of under-coverage of survey estimates of alcohol use could be remedied by these methods in comparison to sales statistics. METHOD: The data from a general population survey of Finns aged 15-79 years in 2016 ( n=2285, response rate 60%) were used. Outcome measures were the annual volume of drinking and prevalence of hazardous drinking. A wide range of sociodemographic and regional variables from registers were available to model the non-response. Response propensities were modelled using logistic regression and random forest models to derive two sets of refined weights in addition to design weights and basic post-stratification weights. RESULTS: Estimated annual consumption changed from 2.43 litres of 100% alcohol using design weights to 2.36-2.44 when using the other three weights and the estimated prevalence of hazardous drinkers changed from 11.4% to 11.4-11.8%, correspondingly. The use of weights derived by the random forest method generally provided smaller estimates than use of the logistic regression-based weights. CONCLUSIONS: The use of complex non-response weights derived from the logistic regression model or random forest are not likely to provide much added value over more simple weights in surveys on alcohol use. Surveys may not catch heavy drinkers and therefore are prone for under-reporting of alcohol use at the population level. Also, factors other than sociodemographic characteristics are likely to influence participation decisions.

Recommendations for design and analysis of health examination surveys under selective non-participation.

Background: The decreasing participation rates and selective non-participation peril the representativeness of health examination surveys (HESs). Methods: Finnish HESs conducted in 1972-2012 are used to demonstrate that survey participation rates can be enhanced with well-planned recruitment procedures and auxiliary information about survey non-participants can be used to reduce selection bias. Results: Experiments incorporated to pilot surveys and experience from previously conducted surveys lead to practical improvements. For example, SMS reminders were taken as a routine procedure to the Finnish HESs after testing their effect on a pilot study and finding them as a cost-effective way to increase participation rate especially among younger age groups. Auxiliary information about survey non-participants can be obtained from many sources: sampling frames, previous measurements in longitudinal setting, re-contacts and non-response questionnaires, and record linkage to administrative data sources. These data can be used in statistical modelling to adjust the population level estimates for the selection bias. Information on the characteristics of non-participants also helps to improve targeting the recruitment in the future. Conclusion: All methods discussed and recommended are relatively easy to incorporate to any national HES in Europe except the record linkage of survey data from administrative data sources. This is not feasible in all European countries because of non-existence of registries, lack of an identifier needed for record linkage, or national data protection legislation which restricts the data use.

Low-grade inflammation in first-episode psychosis is determined by increased waist circumference.

Psychosis is associated with low-grade inflammation as measured by high-sensitivity C-reactive protein (hs-CRP), a risk factor for cardiovascular events and mortality in the general population. We investigated the relationship between hs-CRP and anthropometric and metabolic changes in first-episode psychosis (FEP) during the first treatment year. We recruited 95 FEP patients and 62 controls, and measured longitudinal changes in hs-CRP, weight, waist circumference, insulin resistance, and lipids. We used linear mixed models to analyze the longitudinal relationship between hs-CRP and clinical, anthropometric and metabolic measures. At baseline, patients with FEP had higher levels of insulin resistance, total and low-density lipoprotein cholesterol, apolipoprotein B, and triglycerides. Baseline weight, waist circumference, hs-CRP, fasting glucose, and high-density lipoprotein cholesterol were similar between patients and controls. Marked increases in anthropometric measures and hs-CRP were observed in FEP during the 12-month follow-up. However, glucose and lipid parameters did not change significantly. In the mixed models, waist circumference and female sex were significant predictors of hs-CRP levels in FEP. Prevention of the early development of abdominal obesity in FEP is crucial, as abdominal obesity is accompanied by chronic low-grade inflammation, which increases further the cardiovascular risk in this vulnerable population.

Time-varying covariates and coefficients in Cox regression models.

Time-varying covariance occurs when a covariate changes over time during the follow-up period. Such variable can be analyzed with the Cox regression model to estimate its effect on survival time. For this it is essential to organize the data in a counting process style. In situations when the proportional hazards assumption of the Cox regression model does not hold, we say that the effect of the covariate is time-varying. The proportional hazards assumption can be tested by examining the residuals of the model. The rejection of the null hypothesis induces the use of time varying coefficient to describe the data. The time varying coefficient can be described with a step function or a parametric time function. This article aims to illustrate how to carry out statistical analyses in the presence of time-varying covariates or coefficients with R.

Adjusting for selective non-participation with re-contact data in the FINRISK 2012 survey.

AIMS: A common objective of epidemiological surveys is to provide population-level estimates of health indicators. Survey results tend to be biased under selective non-participation. One approach to bias reduction is to collect information about non-participants by contacting them again and asking them to fill in a questionnaire. This information is called re-contact data, and it allows to adjust the estimates for non-participation. METHODS: We analyse data from the FINRISK 2012 survey, where re-contact data were collected. We assume that the respondents of the re-contact survey are similar to the remaining non-participants with respect to the health given their available background information. Validity of this assumption is evaluated based on the hospitalisation data obtained through record linkage of survey data to the administrative registers. Using this assumption and multiple imputation, we estimate the prevalences of daily smoking and heavy alcohol consumption and compare them to estimates obtained with a commonly used assumption that the participants represent the entire target group. RESULTS: When adjusting for non-participation using re-contact data, higher prevalence estimates were observed compared to prevalence estimates based on participants only. Among men, the smoking prevalence estimate was 28.5% (23.2% for participants) and heavy alcohol consumption prevalence was 9.4% (6.8% for participants). Among women, smoking prevalence was 19% (16.5% for participants) and heavy alcohol consumption was 4.8% (3% for participants). CONCLUSIONS: The utilisation of re-contact data is a useful method to adjust for non-participation bias on population estimates in epidemiological surveys.

Participation rates by educational levels have diverged during 25 years in Finnish health examination surveys.

Background: Declining participation rates in health examination surveys may impair the representativeness of surveys and introduce bias into the comparison of results between population groups if participation rates differ between them. Changes in the characteristics of non-participants over time may also limit comparability with earlier surveys. Methods: We studied the association of socio-economic position with participation, and its changes over the past 25 years. Occupational class and educational level are used as indicators of socio-economic position. Data from six cross-sectional FINRISK surveys conducted between 1987 and 2012 in Finland were linked to national administrative registers, which allowed investigation of the differences between survey participants and non-participants. Results: Our results show that individuals with low occupational class or low level of education were less likely to participate than individuals with high occupational class or high level of education. Participation rates decreased in all subgroups of the population but the decline was fastest among those with low level of education. Conclusions: The differences in participation rates must be taken into account to avoid biased estimates because socio-economic position has also been shown to be strongly related to health, health behaviour and biological risk factors. Particular attention should be paid to the recruitment of the less-educated population groups.