Publications by authors named "Jaakko Airaksinen"

18 Publications

  • Page 1 of 1

Socioeconomic inequalities in impairment associated with depressive symptoms: Evidence from the National Survey on Drug Use and Health.

J Psychiatr Res 2021 Jun 21;141:74-80. Epub 2021 Jun 21.

Department of Psychology and Logopedics, University of Helsinki, Finland.

Objective: Individuals with low socioeconomic status have higher rates of depression, but it is unknown whether the socioeconomically disadvantaged also have more disabling depressive symptoms. We examined (1) the associations of three indicators of socioeconomic status with depression-related severe role impairment, and (2) whether socioeconomic factors moderate the association between individual depression symptoms and depression-related severe role impairment.

Methods: We used data from the National Survey on Drug Use and Health (NSDUH). Depressive symptoms, role impairment and socioeconomic indicators (poverty, participation in workforce, educational attainment) were self-reported by participants. The analytic sample consisted of participants who screened positive for a depressive episode during past 12 months (n = 32 661). We used survey-weighted logistic models to examine the associations of depressive symptoms with severe role impairment and the modifying effects of socioeconomic indicators.

Results: The association between depression symptom count and severe role impairment was stronger among those not in workforce (OR = 1.12[1.02-1.23]). The association between specific depression symptoms and severe role impairment was stronger for conditions of poverty (fatigue, OR = 2.97 [1.54-5.73]; and anhedonia, OR = 1.93[1.13-3.30]), workforce non-participation (inability to concentrate/indecisiveness, OR = 1.54[1.12-2.12]), and lower educational attainment (anhedonia, OR = 0.77 [0.59-0.99]). Feelings of worthlessness was the only symptom with independent associations for all socioeconomic groups (adjusted OR = 1.91[1.35-2.70]).

Conclusion: Depression was more frequent and also more disabling for socioeconomically disadvantaged groups, especially when assessed with workforce participation. Additionally, some specific symptoms showed socioeconomic differences. Our findings highlight the need to prioritize population groups with more severe impairment associated with depressive symptoms.
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http://dx.doi.org/10.1016/j.jpsychires.2021.06.029DOI Listing
June 2021

Subclinical hypothyroidism and symptoms of depression: Evidence from the National Health and Nutrition Examination Surveys (NHANES).

Compr Psychiatry 2021 Jun 12;109:152253. Epub 2021 Jun 12.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

Background: Subclinical hypothyroidism has been associated with increased risk for depression, yet the findings remain controversial. It is possible that subclinical hypothyroidism is associated with some, but not all symptoms of depression. We examined symptom-specific associations between depression and subclinical hypothyroidism.

Methods: Participants (N = 7683 adults) were from the National Health and Nutrition Examination Surveys of 2007-2008, 2009-2010, and 2011-2012 We included participants who had data on their thyroid profile and depressive symptoms (measured using Patient Health Questionnaire), and excluded those with overt hypothyroidism or hyperthyroidism, and those on thyroid hormone replacement therapy. Logistic regression with sampling weights was used to examine the association between subclinical hypothyroidism and depression symptoms. We also ran sensitivity analysis using different cut-off points for defining subclinical hypothyroidism.

Results: Of all the participants, 208 (2.7%) had subclinical hypothyroidism and of them only six had depression. Subclinical hypothyroidism was not associated with depression (OR = 0.61, 95% CI 0.20-1.87) nor with the specific depression symptoms. Using lower criteria for subclinical hypothyroidism diagnosis resulted in similar findings.

Conclusions: In a nationally representative sample of US adults, we observed no association between subclinical hypothyroidism and overall depression risk or any of the individual symptoms of depression.
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http://dx.doi.org/10.1016/j.comppsych.2021.152253DOI Listing
June 2021

Specific symptoms of the General Health Questionnaire (GHQ) in predicting persistence of psychological distress: Data from two prospective cohort studies.

J Psychiatr Res 2020 Nov 12. Epub 2020 Nov 12.

Department of Psychology and Logopedics, University of Helsinki, Finland; Finnish Institute for Health and Welfare, Helsinki, Finland.

Persistent psychological distress is more harmful than transient psychological distress, but little is known about the development of persistent distress. We examined whether some specific symptoms of the 12-item General Health Questionnaire (GHQ-12) were more important than others in predicting the persistence of psychological distress over a 3-year follow-up period among individuals who had at least moderate psychological distress at baseline (GHQ≥3). Participants were from the UK Household Longitudinal Study (UKHLS; n = 6430) and British Household Panel Survey (BHPS; n = 5954). Sense of worthlessness, loss of self-confidence, loss of sleep over worry, and feelings of strain were associated with increasingly persistent distress. General happiness, feelings of unhappiness or depressed mood, and enjoyment of activities showed no such increasing associations. Symptoms of social functioning (capability of making decisions, concentration problems, feelings of usefulness, ability to face problems) showed some but not consistent associations. These results suggest that feelings of worthlessness, loss of self-confidence, loss of sleep over worry, and strain may be particularly important markers for persistent psychological distress.
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http://dx.doi.org/10.1016/j.jpsychires.2020.11.026DOI Listing
November 2020

Association of depressive symptoms with health care utilization in older adults: Longitudinal evidence from the Survey of Health, Aging, and Retirement in Europe.

Int J Geriatr Psychiatry 2021 04 26;36(4):521-529. Epub 2020 Oct 26.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

Objectives: Many older adults with depression do not receive adequate treatment. Differences in treatment utilization may reflect the heterogeneous nature of depression, encompassing multiple distinct symptoms. We assessed whether depressive symptoms are differentially associated with subsequent health care utilization with respect to three outcomes as follows: (1) contact with a medical doctor (MD), (2) depression-specific treatment, and (3) inpatient psychiatric admission.

Methods/design: Longitudinal analyses were based on data from three follow-up cycles conducted between 2004 and 2013 among 53,139 participants from the Survey of Health, Aging, and Retirement in Europe. Depressive symptoms were self-reported at baseline of each follow-up cycle using the 12-item EURO-D scale. Health care utilization was self-reported at the end of each follow-up cycle.

Results: After adjustment for sex, age, country of interview, follow-up time, educational attainment, presence of a partner in household, body-mass index, the number of chronic diseases, disability, average/prior frequency of contact with an MD, and all other depressive symptoms, people with more frequent contact with an MD had most often reported sleep problems (IRR = 1.10) and fatigue (IRR = 1.10), followed by sad/depressed mood, tearfulness, concentration problems, guilt, irritability, and changes in appetite. Those treated for depression had most often reported sad/depressed mood (OR = 2.18) and suicidal ideation (OR = 1.72), but also sleep problems, changes in appetite, fatigue, concentration problems, hopelessness, and irritability. Sad/depressed mood (OR = 2.87) was also associated with psychiatric inpatient admission. Similarly to other outcomes, appetite change, fatigue, and sleep problems were associated with inpatient admission.

Conclusions: Specific symptoms of depression may determine utilization of different types of health care among elderly.
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http://dx.doi.org/10.1002/gps.5447DOI Listing
April 2021

Network dynamics of depressive symptoms in antidepressant medication treatment: secondary analysis of eight clinical trials.

Mol Psychiatry 2020 Sep 16. Epub 2020 Sep 16.

Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland.

Depression can be viewed as a network of depressive symptoms that tend to reinforce each other via feedback loops. Specific symptoms of depression may be differently responsive to antidepressant treatment, and some symptoms may be more important than others in the overall improvement of depression associated with treatment. We pooled prospective data from eight industry-sponsored placebo-controlled trials for paroxetine, fluoxetine and imipramine (total n = 3559) to examine whether improvements in specific depressive symptoms were more strongly related to improvements in other depressive symptoms among patients on active antidepressant treatment as compared to placebo. Depressive symptoms were assessed with the 17-item Hamilton Depression Rating Scale. Data on treatment was dichotomized into active treatment (receiving any antidepressant agent) vs. placebo. Time-lagged longitudinal analyses suggested that improvement in three symptoms-depressed mood, insomnia, and suicidality-had a broader overall impact on subsequent improvement in other depressive symptoms in the antidepressant condition compared to placebo (i.e., greater out-strength). Moreover, improvements in depressed mood and insomnia were more likely to follow the improvements in other symptoms in the antidepressant condition compared to placebo (i.e., greater in-strength). These results from clinical trial data suggest that depressed mood, insomnia, and suicidality may be particularly important in accounting for the remission and recovery in response to antidepressant treatment.
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http://dx.doi.org/10.1038/s41380-020-00884-3DOI Listing
September 2020

Connectivity of depression symptoms before and after diagnosis of a chronic disease: A network analysis in the U.S. Health and Retirement Study.

J Affect Disord 2020 04 29;266:230-234. Epub 2020 Jan 29.

Medicum, University of Helsinki, Helsinki, Finland.

Background: Many chronic diseases increase the risk of depressive symptoms, but few studies have examined whether these diseases also affect the composition of symptoms a person is likely to experience. As the risk and progression of depression may vary between chronic diseases, we used network analysis to examine how depression symptoms are connected before and after the diagnosis of diabetes, heart disease, stroke, and cancer.

Methods: Participants (N = 7779) were from the longitudinal survey of the Health and Retirement Study. Participants were eligible if they had information on depression symptoms two and/or four years before and after the diagnosis of either diabetes, heart disease, cancer or stroke. We formed a control group with no chronic disease that was matched on age, sex and ethnic background to those with a disease. We constructed depression symptom networks and compared the overall connectivity of those networks, and depression symptom sum scores, for before and after the diagnosis of each disease.

Results: Depression symptom sum scores increased with the diagnosis of each disease. The connectivity of depression symptoms remained unchanged for all the diseases, except for stroke, for which the connectivity decreased with the diagnosis.

Limitations: Comorbidity with other chronic diseases was not controlled for as we focused on the onset of specific diseases.

Conclusions: Our results suggest that although the mean level of depression symptoms increases after the diagnosis of chronic disease, with most chronic diseases, these changes are not reflected in the network structure of depression symptoms.
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http://dx.doi.org/10.1016/j.jad.2020.01.170DOI Listing
April 2020

An Example of How Immortal Time Bias Can Reverse the Results of an Observational Study.

Epidemiology 2020 03;31(2):e19-e20

Clinicum, University of Helsinki, Helsinki, Finland and Department of Epidemiology and Public Health, University College, London, UK.

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http://dx.doi.org/10.1097/EDE.0000000000001103DOI Listing
March 2020

Personality, disability-free life years, and life expectancy: Individual participant meta-analysis of 131,195 individuals from 10 cohort studies.

J Pers 2020 06 12;88(3):596-605. Epub 2019 Sep 12.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

Objective: We examined how personality traits of the Five Factor Model were related to years of healthy life years lost (mortality and disability) for individuals and the population.

Method: Participants were 131,195 individuals from 10 cohort studies from Australia, Germany, the United Kingdom, and the United States (n = 43,935 from seven cohort studies for the longitudinal analysis of disability, assessed using scales of Activities of Daily Living).

Results: Lower Conscientiousness was associated with higher mortality and disability risk, but only when Conscientiousness was below its median level. If the excess risk associated with low Conscientiousness had been absent, population life expectancy would have been 1.3 years longer and disability-free life 1.0 years longer. Lower emotional stability was related to shorter life expectancy, but only among those in the lowest 15% of the distribution, and disability throughout the distribution: if the excess risk associated with low emotional stability had been absent, population life expectancy would have been 0.4 years longer and disability-free life 2.4 years longer.

Conclusions: Personality traits of low Conscientiousness and low emotional stability are associated with reduced healthy life expectancy of individuals and population.
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http://dx.doi.org/10.1111/jopy.12513DOI Listing
June 2020

Health behaviors and psychological distress: changing associations between 1997 and 2016 in the United States.

Soc Psychiatry Psychiatr Epidemiol 2020 Mar 26;55(3):385-391. Epub 2019 Jul 26.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, PO Box 63, 00014, Helsinki, Finland.

Objectives: Smoking rates have declined with a slower pace among those with psychological distress compared to those without. We examined whether other health behaviors (heavy alcohol consumption, physical inactivity, short sleep duration) showed similar trends associated with psychological distress. We also examined differences by age and birth cohort.

Methods: Data were from the annually repeated cross-sectional U.S. National Health Interview Surveys (NHIS) of 1997-2016 (total n = 603,518). Psychological distress was assessed with the 6-item Kessler Psychological Distress Scale (K6).

Results: Psychological distress became more strongly associated with smoking (OR 1.09 per 10 years; 95% CI 1.07, 1.12), physical inactivity (OR 1.08; 1.05, 1.11), and short sleep (OR 1.12; 1.06, 1.18), but less strongly associated with heavy alcohol consumption (OR 0.93; 0.89, 0.98). The associations of smoking and alcohol consumption attenuated with age, whereas the association with physical inactivity strengthened with age. Compared to older birth cohorts, smoking became more strongly associated with psychological distress among younger birth cohorts up to those born in the 1980s.

Conclusions: The strength of associations between psychological distress and health behaviors may vary by time period, age, and birth cohort.
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http://dx.doi.org/10.1007/s00127-019-01741-7DOI Listing
March 2020

Chronic diseases and social risk factors in relation to specific symptoms of depression: Evidence from the U.S. national health and nutrition examination surveys.

J Affect Disord 2019 05 22;251:242-247. Epub 2019 Mar 22.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland; Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway.

Background: Depression is a heterogeneous mental disorder with multiple symptoms, but only few studies have examined whether associations of risk factors with depression are symptom-specific. We examined whether chronic diseases and social risk factors (poverty, divorce, and perceived lack of emotional support) are differently associated with somatic and cognitive/affective symptoms of depression.

Methods: Cross-sectional analyses were based on individual-level data from the 31,191 participants of six cross-sectional U.S. National Health and Nutrition Examination Surveys (NHANES) carried out between 2005 and 2016. Depressive symptoms were assessed using the 9-item Patient Health Questionnaire. Information on chronic diseases and social risk factors was self-reported by participants.

Results: After adjustment for sex, age, race/ethnicity, and all the of other symptoms besides the outcome symptom, higher number of chronic diseases was independently related to fatigue, psychomotor retardation/agitation, and sleep problems in a dose-response pattern (range of odds ratios: 1.21 to 2.59). Except for concentration problems, social risk factors were associated with almost all of the cognitive/affective symptoms (range of odds ratios: 1.02 to 2.09) but only sporadically with somatic symptoms.

Limitations: All measures were self-reported by the participants, which may have introduced bias to the associations. Cross-sectional data did not allow us to study temporal dynamics.

Conclusions: Specific symptoms of depression may be useful in characterizing the heterogeneous etiology of depression with respect to somatic versus social risk factors.
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http://dx.doi.org/10.1016/j.jad.2019.03.074DOI Listing
May 2019

The effect of smoking cessation on work disability risk: a longitudinal study analysing observational data as non-randomized nested pseudo-trials.

Int J Epidemiol 2019 04;48(2):415-422

Department of Occupational Health, Finnish Institute of Occupational Health, Helsinki, Finland.

Background: Smoking increases disability risk, but the extent to which smoking cessation reduces the risk of work disability is unclear. We used non-randomized nested pseudo-trials to estimate the benefits of smoking cessation for preventing work disability.

Methods: We analysed longitudinal data on smoking status and work disability [long-term sickness absence (≥90 days) or disability pension] from two independent prospective cohort studies-the Finnish Public Sector study (FPS) (n = 7393) and the Health and Social Support study (HeSSup) (n = 2701)-as 'nested pseudo-trials'. All the 10 094 participants were smokers at Time 1 and free of long-term work disability at Time 2. We compared the work disability risk after Time 2 of the participants who smoked at Time 1 and Time 2 with that of those who quit smoking between these times.

Results: Of the participants in pseudo-trials, 2964 quit smoking between Times 1 and 2. During the mean follow-up of 4.8 to 8.6 years after Time 2, there were 2197 incident cases of work disability across the trials. Quitting smoking was associated with a reduced risk of any work disability [summary hazard ratio = 0.89, 95% confidence interval (CI) 0.81-0.98]. The hazard ratio for the association between quitting smoking and permanent disability pension (928 cases) was of similar magnitude, but less precisely estimated (0.91, 95% CI 0.81-1.02). Among the participants with high scores on the work disability risk score (top third), smoking cessation reduced the risk of disability pension by three percentage points. Among those with a low risk score (bottom third), smoking cessation reduced the risk by half a percentage point.

Conclusions: Our results suggest an approximately 10% hazard reduction of work disability as a result of quitting smoking.
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http://dx.doi.org/10.1093/ije/dyz020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469311PMC
April 2019

Does increasing physical activity reduce the excess risk of work disability among overweight individuals?

Scand J Work Environ Health 2019 07 14;45(4):376-385. Epub 2019 Jan 14.

Finnish Institute of Occupational Health, PO Box 18, FI-00032 TYÖTERVEYSLAITOS, Finland.

Objectives We examined the extent to which an increase in physical activity would reduce the excess risk of work disability among overweight and obese people (body mass index ≥ 25kg/m ). Methods We used counterfactual modelling approaches to analyze longitudinal data from two Finnish prospective cohort studies (total N=38 744). Weight, height and physical activity were obtained from surveys and assessed twice and linked to electronic records of two indicators of long-term work disability (≥90-day sickness absence and disability pension) for a 7-year follow-up after the latter survey. The models were adjusted for age, sex, socioeconomic status, smoking, and alcohol consumption. Results The confounder-adjusted hazard ratio (HR) of long-term sickness absence for overweight compared to normal-weight participants was 1.43 [95% confidence interval (CI) 1.35-1.53]. An increase in physical activity among overweight compared to normal-weight individuals was estimated to reduce this HR to 1.40 (95% CI 1.31-1.48). In pseudo-trial analysis including only the persistently overweight, initially physically inactive participants, the HR for long-term sickness absence was 0.82 (95% CI 0.70-0.94) for individuals with increased physical activity compared to those who remained physically inactive. The results for disability pension as an outcome were similar. Conclusions These findings suggest that the excess risk of work disability among overweight individuals would drop by 3-4% if they increased their average physical activity to the average level of normal-weight people. However, overweight individuals who are physically inactive would reduce their risk of work disability by about 20% by becoming physically active.
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http://dx.doi.org/10.5271/sjweh.3799DOI Listing
July 2019

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

Sci Rep 2018 Nov 16;8(1):17224. Epub 2018 Nov 16.

Finnish Institute of Occupational Health, Helsinki, Finland.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.
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http://dx.doi.org/10.1038/s41598-018-35363-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237879PMC
November 2018

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

Scand J Work Environ Health 2018 05 24;44(3):274-282. Epub 2018 Jan 24.

Finnish Institute of Occupational Health, P.O. Box 40, FIN-00251 Helsinki, Finland.

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.
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http://dx.doi.org/10.5271/sjweh.3713DOI Listing
May 2018

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

Sci Rep 2017 10 19;7(1):13578. Epub 2017 Oct 19.

Finnish Institute of Occupational Health, Helsinki, Finland.

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.
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http://dx.doi.org/10.1038/s41598-017-13892-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648892PMC
October 2017

Moving on: How depressive symptoms, social support, and health behaviors predict residential mobility.

Scand J Public Health 2016 Jun 18;44(4):394-401. Epub 2015 Dec 18.

Institute of Behavioral Sciences, University of Helsinki, Finland.

Background: There are major health inequalities between residential areas. However, it remains unclear whether these inequalities are due to social causation or selective residential mobility, because little is known about the associations between health-related factors and selective residential mobility. This study examined how depressive symptoms, social support, and health behaviors are associated with subsequent residential mobility, as measured by frequency, distance, and direction of moves.

Methods: Participants were selected from the Young Finns prospective cohort study (N = 3017) with four study waves in 1992, 1997, 2001, and 2007. Complete residential mobility history was gathered for each participant from registry data. Residential mobility was assessed over three-year periods following each study wave. The direction of mobility was measured as changes in residential location's population density, health index, mortality index, and unemployment. Area characteristics were used as covariates together with the participants' age, sex, and education.

Results: Individuals reporting higher social support from friends were more likely to move (b = 0.20; 95% confidence interval (CI): 0.08, 0.37) and move more frequently (b = 0.08; 95% CI: 0.01, 0.14), whereas individuals reporting higher social support from their family members were less likely to move (b = -0.08; 95% CI: -0.14, -0.02). Better health behaviors were associated with longer moving distances (b = 0.14; 95% CI: 0.06, -0.23). None of the individual characteristics were associated with the direction of moves as measured by changes in municipality characteristics. CONCLUSIONS SOME OF THE HEALTH-RELATED CHARACTERISTICS ARE ASSOCIATED WITH RESIDENTIAL MOBILITY IN FINLAND HOWEVER, THESE INDIVIDUAL CHARACTERISTICS DO NOT SEEM TO PREDICT SYSTEMATIC SELECTIVE RESIDENTIAL MOBILITY ACROSS MUNICIPALITIES WITH DIFFERENT REGIONAL HEALTH PROFILES.
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http://dx.doi.org/10.1177/1403494815622850DOI Listing
June 2016

Neighbourhood effects in health behaviours: a test of social causation with repeat-measurement longitudinal data.

Eur J Public Health 2016 06 14;26(3):417-21. Epub 2015 Nov 14.

Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland.

Background: Neighbourhood characteristics have been associated with health behaviours of residents. We used longitudinal data to examine whether neighbourhood characteristics (level of urbanization and socioeconomic status) are related to within-individual variations in health behaviours (alcohol consumption, smoking, exercise and self-interest in health) as people live in different neighbourhoods over time.

Methods: Participants were from the Young Finns prospective cohort study (N = 3145) with four repeated measurement times (1992, 2001, 2007 and 2011/2012). Neighbourhood socioeconomic status and level of urbanization were measured on the level of municipality and zip code area. Within-individual (i.e. fixed-effect) regression was used to examine whether these associations were observed within individuals who lived in different neighbourhood in different measurement times.

Results: People living in more urban zip code areas were more likely to smoke (b = 0.06; CI = 0.03-0.09) and drink alcohol (b = 0.11; CI = 0.08-0.14), and these associations were replicated in within-individual analysis-supporting social causation. Neighbourhood socioeconomic status and urbanization were associated with higher interest in maintaining personal health (b = 0.05; CI = 0.03-0.08 and b = 0.05; CI = 0.02-0.07, respectively), and these associations were also similar in within-individual analysis. Physical exercise was not associated with neighbourhood characteristics.

Conclusions: These data lend partial support for the hypothesis that neighbourhood differences influence people's health behaviours.
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http://dx.doi.org/10.1093/eurpub/ckv210DOI Listing
June 2016

Neighborhood effects in depressive symptoms, social support, and mistrust: Longitudinal analysis with repeated measurements.

Soc Sci Med 2015 Jul 1;136-137:10-6. Epub 2015 May 1.

Institute of Behavioral Sciences, University of Helsinki, Finland.

While many associations between neighborhood characteristics and individual well-being have been reported, there is a lack of longitudinal studies that could provide evidence for or against causal interpretations of neighborhood effects. This study examined whether neighborhood urbanicity and socioeconomic status were associated with within-individual variation in depression, mistrust and social support when individuals were living in different neighborhoods with different levels of urbanicity and socioeconomic status. Participants were from the Young Finns prospective cohort study (N = 3074) with five repeated measurement times in 1992, 1997, 2001, 2007, and 2011. Neighborhood urbanicity and socioeconomic status were measured at the level of municipalities and zip-code areas. Within-individual variation over time was examined with multilevel regression, which adjusted the models for all stable individual differences that might confound associations between neighborhood characteristics and individual well-being. Social support from friends was higher in urban areas and in areas with higher socioeconomic status, whereas social support from the family was higher in rural areas. These associations were observed also in the within-individual analyses, and they were partly accounted for by employment and socioeconomic status of the participants. There were no associations between neighborhood characteristics and depression or mistrust. These findings suggest that people receive less support from their families and more support from their friends when living in urban compared to rural regions of Finland. These differences are partly explained by people's changing socioeconomic and employment statuses.
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http://dx.doi.org/10.1016/j.socscimed.2015.04.034DOI Listing
July 2015