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Background: To enhance the usability of existing large population-based studies in epidemiologicresearch on office workers, we developed a procedure for a proxy variable on office worker in datawith open-ended responses on occupation.

Methods: Self-reported open answers on occupation (n=3738) from the LifeGene pilot study werelinked to a modified version of the Swedish Standard Classification of Occupation 2012 (SSYK12). TheSSYK12 includes 8946 job titles with 4-digit codes which were categorized to managers, white-collarand blue-collar workers. Managers and white-collar workers were used as a proxy for office workers.We then used fuzzy string matching in R to calculate the Jaro-Winkler distance between the LifeGenepilot data answers on occupation and the modified SSYK12 job titles. Zero distance indicated aperfect match, whereas distances above zero were checked manually to assess various job titles asoffice worker or non-office worker. Thereafter, the resulting procedure was applied to the wholeLifeGene study with data on occupation (n=23 525).

Results: We got perfect match against the modified SSYK12 job titles for 16 275 responses (69%) inthe large LifeGene data. Another 1721 responses (7%) matched occupations that we had manuallydefined as office worker or non-office worker in the pilot data set, and the remaining 5529 (24%)were unmatched. Among the matched occupations, 15 159 (84%) were office-workers, 2493 (14%)non-office workers, and 344 (2%) nondistinctive.

Conclusion: The procedure for a proxy variable on office worker allowed us to classify three quartersof the open-ended responses on occupation.

Background: To enhance the usability of existing large population-based studies in epidemiologicresearch on office workers, we developed a procedure for a proxy variable on office worker in datawith open-ended responses on occupation.

Methods: Self-reported open answers on occupation (n=3738) from the LifeGene pilot study werelinked to a modified version of the Swedish Standard Classification of Occupation 2012 (SSYK12). TheSSYK12 includes 8946 job titles with 4-digit codes which were categorized to managers, white-collarand blue-collar workers. Managers and white-collar workers were used as a proxy for office workers.We then used fuzzy string matching in R to calculate the Jaro-Winkler distance between the LifeGenepilot data answers on occupation and the modified SSYK12 job titles. Zero distance indicated aperfect match, whereas distances above zero were checked manually to assess various job titles asoffice worker or non-office worker. Thereafter, the resulting procedure was applied to the wholeLifeGene study with data on occupation (n=23 525).

Results: We got perfect match against the modified SSYK12 job titles for 16 275 responses (69%) inthe large LifeGene data. Another 1721 responses (7%) matched occupations that we had manuallydefined as office worker or non-office worker in the pilot data set, and the remaining 5529 (24%)were unmatched. Among the matched occupations, 15 159 (84%) were office-workers, 2493 (14%)non-office workers, and 344 (2%) nondistinctive.

Conclusion: The procedure for a proxy variable on office worker allowed us to classify three quartersof the open-ended responses on occupation.

AbstractBackground Adolescent mental health problems are on the rise globally, including in Sweden. One indicator of this trend is increased psychosomatic symptoms (PSS) over time. Lifestyle factors such as physical activity (PA), diet, smoking, and alcohol consumption may influence the time trends in PSS; however, the evidence base is scarce. The aim of this study was to investigate associations between time trends in PSS and lifestyle factors. Methods The study was based on data collected from a nationally representative sample of 9,196 fifteen-year-old boys and girls in Sweden using the Health Behavior in School-aged Children (HBSC) symptom checklist. The sample comprised nearly equal proportions of girls (50.5%) and boys. The lifestyle factors examined in this study included PA, regular breakfast intake, consumption of fruits, vegetables, sweets, or soft drinks, smoking, and alcohol drunkenness. We used data from 2002 to 2018 and stratified by family affluence scale (FAS) to demonstrate how the associations varied among the FAS groups. We fitted separate regression models for the high- and low-FAS groups, where interaction terms between the year of the survey and each lifestyle factor were used to estimate the level and direction of associations between the factors and trends in PSS. Results There was a generally increasing trend in PSS mean scores from 2.26 in 2002 to 2.49 in 2018 (p<.001). The changes in each survey year compared to the average mean scores during the preceding years were significant in all years except 2010. Regular breakfast intake, daily fruit and vegetable consumption, and higher PA were associated with lower PSS mean scores, while smoking and drunkenness had opposite associations with PSS. The only significant interaction between the survey year and the lifestyle factors was observed regarding drunkenness in the high FAS group, suggesting that the association between trends in PSS and the experience of getting drunk at least twice got stronger over time (B=0.057; CI:0.016, 0.097; p<.01).Conclusions The results indicate increasing trends in PSS among young people in Sweden from 2002 to 2018, with a significant increase observed among adolescents in the high FAS group who reported getting drunk on at least two occasions. 

Objectives: To examine associations between parents’ socioeconomic position (SEP) and child overweight and obesity, using registry data. Methods: Data (final n = 194,423) on children’s height, weight and parents’ SEP were drawn from the national Register of Primary Health Care Visits (Avohilmo) and Statistics Finland. Risk ratios for bernoulli-distributed overweight (RROW) and obesity (RROB) according to SEP were estimated using generalized linear models and using a log -link. Results: The risk for obesity was lower in boys from high-income families (RROB 0.76), for overweight and obesity was lower in boys (RROW 0.72, RROB 0.58) and girls (RROW 0.72, RROB 0.54) with highly educated fathers, in boys (RROW 0.79, RROB 0.58) and girls (RROW 0.78, RROB 0.56) with high-educated mothers and in boys (RROW 0.85, RROB 0.77) and girls (RROW 0.80, RROB 0.69) living in urban areas, as compared to low-income families, low-educated parents, and rural residence, respectively. Conclusion: The risk of overweight and obesity was increased in children with low SEP or rural residence. Administrative registers are a valid approach to monitor childhood obesity by parents’ SEP.

Background:

Adolescent mental health problems are on the rise globally, including in Sweden. One indicator is an increase in psychosomatic symptoms (PSS) over time. Lifestyle factors such as physical activity (PA), diet, smoking, and alcohol consumption may influence the trends in PSS. However, we found limited research on such associations.

Methods:

This study is based on data collected every four years from nationally representative samples of 15-year-old boys and girls in Sweden (N = 9,196, 50.5% girls), as part of the Health Behavior in School-aged Children (HBSC) study. PSS was measured using a scale developed from the HBSC symptom checklist. We analyzed the trends in PSS from 2002 to 2018 and fitted models to investigate the associations between the trends and lifestyle factors. We included interaction terms between time and each lifestyle factor and fitted separate models for the high and low socioeconomic status (SES) groups.

Results

In general, the mean scores for PSS increased from 2.26 in 2002 to 2.49 in 2018 (p<.001). Compared to the average mean scores during preceding years, the changes in PSS mean scores at each survey year were also significant in all years except 2010. More frequent breakfast intake, daily consumption of fruits and vegetables, and higher PA were associated with lower PSS mean scores while smoking and alcohol consumption had the opposite association. The only significant interaction (B = .050; CI: .015, ¬ .085; p<.01) was observed in the high SES group, indicating that the increasing trend in PSS was stronger among those who had been drunk once or more in a lifetime, compared to those who had never been drunk.

Conclusions

The results indicate increasing trends in mental health problems among young people in Sweden. Furthermore, the study revealed that alcohol drunkenness was associated with a more substantial rise in PSS over time among those in the high SES group. Further research is needed to understand the reasons behind these findings.

Evidence on the associations between built environment and overweight in children outside developed countries is scarce. We examined associations between access to local food and physical activity environments and overweight in 5- to 17-year-old Malaysians in two states with differing overweight levels. Information on children was measured in the National Health and Morbidity Survey 2015 and combined with Geographic Information System–derived data on local food and physical activity environments. Access to the built environment was measured by presence and distance from child’s residence. Complete data were available for 880 children. Access to local food outlets and parks was higher and associated with higher occurrence of overweight in children living in the state with higher overweight prevalence. When adjusted for sociodemographic factors, higher presence of and shorter distance to convenience stores and parks were associated with overweight. Both built environment and children’s sociodemographic backgrounds should be considered when planning interventions to curb the overweight epidemic in Malaysia.

 Background:  Obesity is associated with low-grade systemic inflammation, and it has been suggested that increased inflammation markers could predict future weight gain. Our aim was to investigate the associations of high-sensitivity C-reactive protein (hs-CRP) concentration with changes in weight and waist circumference in adults during 11 years of follow-up.

 Methods:  We used data from the Health 2000 and Health 2011 surveys consisting of a population-based sample of Finnish adults. We included those 3143 participants, aged 30-75 years at baseline, whose baseline hs-CRP was measured, and who had information on measured weight and height at both time points. Associations between baseline hs-CRP and changes in weight and waist circumference were analyzed using multinomial logistic regression, adjusted for sociodemographic factors (age, sex, marital status, and educational status), lifestyle factors (smoking, alcohol consumption, leisure-time physical activity, sitting time, sleeping time, and psychological distress), and baseline values of BMI and waist circumference.

 Results:  Hs-CRP was not associated with weight gain (≥5%) when adjusted for potential confounders (OR 0.99, 95% CI 0.96-1.01), compared to stable weight (change <±5%). Higher baseline hs-CRP was associated with decrease in weight (≤-5%) in the unadjusted (OR 1.03, 1.01-1.05), but not in the adjusted (OR 1.01, 0.99-1.03) model. No association was observed between hs-CRP and waist circumference.