Tracking of fruit and vegetable consumption from adolescence into adulthood and its longitudinal association with overweight.

The objective of the present study was to assess to what extent fruit and vegetable intakes track over a 24-year time period and to assess longitudinal associations between fruit and vegetable intakes and (change in) BMI and sum of skinfolds. Dietary intake and anthropometrics were repeatedly assessed for 168 men and women between the ages of 12 and 36 years. Linear general estimating equations analyses were applied (1) to estimate tracking coefficients, (2) to estimate predictability for meeting the national recommendation for fruit and vegetable intake and for being in the highest quartile for fruit and vegetable intake, and (3) to estimate the association between fruit and vegetable intake and BMI and sum of skinfolds. We found that tracking coefficients were 0.33 (P<0.001) for fruit intake and 0.27 (P<0.001) for vegetable intake. Mean fruit intake decreased over a 24-year period. For fruit intake, predictability was higher in men than in women (OR 6.02 (P<0.001) and 2.33 (P=0.001) for meeting the recommendation for men and women respectively). After adjustment, fruit intake was not associated with BMI, but being in the lowest quartile of fruit intake was significantly associated with a lower sum of skinfolds. Women in the lowest quartiles of vegetable intake had significantly higher BMI and sum of skinfolds and also greater positive changes in these parameters. In conclusion, tracking and predictability for fruit and vegetable intake appear to be low to moderate, which might indicate that fruit and vegetable promotion should be started at an early age and continued into adulthood. Despite the fact that we only observed beneficial weight- maintaining effects of vegetable intake in women, promoting vegetables is important for both sexes because of other positive properties of vegetables. No evidence was found for promoting fruit intake as a means of weight maintenance. © The Authors 2007

Risk reclassification analysis investigating the added value of fatigue to sickness absence predictions

Prognostic models including age, self-rated health and prior sickness absence (SA) have been found to predict high (a parts per thousand yen30) SA days and high (a parts per thousand yen3) SA episodes during 1-year follow-up. More predictors of high SA are needed to improve these SA prognostic models. The purpose of this study was to investigate fatigue as new predictor in SA prognostic models by using risk reclassification methods and measures. This was a prospective cohort study with 1-year follow-up of 1,137 office workers. Fatigue was measured at baseline with the 20-item checklist individual strength and added to the existing SA prognostic models. SA days and episodes during 1-year follow-up were retrieved from an occupational health service register. The added value of fatigue was investigated with Net Reclassification Index (NRI) and integrated discrimination improvement (IDI) measures. In total, 579 (51 %) office workers had complete data for analysis. Fatigue was prospectively associated with both high SA days and episodes. The NRI revealed that adding fatigue to the SA days model correctly reclassified workers with high SA days, but incorrectly reclassified workers without high SA days. The IDI indicated no improvement in risk discrimination by the SA days model. Both NRI and IDI showed that the prognostic model predicting high SA episodes did not improve when fatigue was added as predictor variable. In the present study, fatigue increased false-positive rates which may reduce the cost-effectiveness of interventions for preventing SA

Development of Prediction Models for Sickness Absence Due to Mental Disorders in the General Working Population

PurposeThis study investigated if and how occupational health survey variables can be used to identify workers at risk of long-term sickness absence (LTSA) due to mental disorders.MethodsCohort study including 53,833 non-sicklisted participants in occupational health surveys between 2010 and 2013. Twenty-seven survey variables were included in a backward stepwise logistic regression analysis with mental LTSA at 1-year follow-up as outcome variable. The same variables were also used for decision tree analysis. Discrimination between participants with and without mental LTSA during follow-up was investigated by using the area under the receiver operating characteristic curve (AUC); the AUC was internally validated in 100 bootstrap samples.Results30,857 (57%) participants had complete data for analysis; 450 (1.5%) participants had mental LTSA during follow-up. Discrimination by an 11-predictor logistic regression model (gender, marital status, economic sector, years employed at the company, role clarity, cognitive demands, learning opportunities, co-worker support, social support from family/friends, work satisfaction, and distress) was AUC = 0.713 (95% CI 0.692-0.732). A 3-node decision tree (distress, gender, work satisfaction, and work pace) also discriminated between participants with and without mental LTSA at follow-up (AUC = 0.709; 95% CI 0.615-0.804).ConclusionsAn 11-predictor regression model and a 3-node decision tree equally well identified workers at risk of mental LTSA. The decision tree provides better insight into the mental LTSA risk groups and is easier to use in occupational health care practice

External validation of a prediction model and decision tree for sickness absence due to mental disorders

Purpose: A previously developed prediction model and decision tree were externally validated for their ability to identify occupational health survey participants at increased risk of long-term sickness absence (LTSA) due to mental disorders. Methods: The study population consisted of N = 3415 employees in mobility services who were invited in 2016 for an occupational health survey, consisting of an online questionnaire measuring the health status and working conditions, followed by a preventive consultation with an occupational health provider (OHP). The survey variables of the previously developed prediction model and decision tree were used for predicting mental LTSA (no = 0, yes = 1) at 1-year follow-up. Discrimination between survey participants with and without mental LTSA was investigated with the area under the receiver operating characteristic curve (AUC). Results: A total of n = 1736 (51%) non-sick-listed employees participated in the survey and 51 (3%) of them had mental LTSA during follow-up. The prediction model discriminated (AUC = 0.700; 95% CI 0.628–0.773) between participants with and without mental LTSA during follow-up. Discrimination by the decision tree (AUC = 0.671; 95% CI 0.589–0.753) did not differ significantly (p = 0.62) from discrimination by the prediction model. Conclusion: At external validation, the prediction model and the decision tree both poorly identified occupational health survey participants at increased risk of mental LTSA. OHPs could use the decision tree to determine if mental LTSA risk factors should be explored in the preventive consultation which follows after completing the survey questionnaire

Selection for health professions education leads to increased inequality of opportunity and decreased student diversity in The Netherlands, but lottery is no solution:A retrospective multi-cohort study

Background Concerns exist about the role of selection in the lack of diversity in health professions education (HPE). In The Netherlands, the gradual transition from weighted lottery to selection allowed for investigating the variables associated with HPE admission, and whether the representativeness of HPE students has changed. Method We designed a retrospective multi-cohort study using Statistics Netherlands microdata of all 16-year-olds on 1 October 2008, 2012, and 2015 (age cohorts, N > 600,000) and investigated whether they were eligible students for HPE programs (n > 62,000), had applied (n > 14,000), and were HPE students at age 19 (n > 7500). We used multivariable logistic regression to investigate which background variables were associated with becoming an HPE student. Results HPE students with >= 1 healthcare professional (HP) parent, >= 1 top-10% income/wealth parent, and women are overrepresented compared to all age cohorts. During hybrid lottery/selection (cohort-2008), applicants with >= 1 top-10% wealth parent and women had higher odds of admission. During 100% selection (cohort-2015) this remained the case. Additionally, applicants with >= 1 HP parent had higher odds, those with a migration background had lower odds. Conclusions Odds of admission are increasingly influenced by applicants' backgrounds. Targeted recruitment and equitable admissions procedures are required to increase matriculation of underrepresented students

Association between workarounds and medication administration errors in bar-code-assisted medication administration in hospitals

Objective: To study the association of workarounds with medication administration errors using barcode-assisted medication administration (BCMA), and to determine the frequency and types of workarounds and medication administration errors. Materials and Methods: A prospective observational study in Dutch hospitals using BCMA to administer medication. Direct observation was used to collect data. Primary outcome measure was the proportion of medication administrations with one or more medication administration errors. Secondary outcome was the frequency and types of workarounds and medication administration errors. Univariate and multivariate multilevel logistic regression analysis were used to assess the association between workarounds and medication administration errors. Descriptive statistics were used for the secondary outcomes. Results: We included 5793 medication administrations for 1230 inpatients. Workarounds were associated with medication administration errors (adjusted odds ratio 3.06 [95% CI: 2.49-3.78]). Most commonly, procedural workarounds were observed, such as not scanning at all (36%), not scanning patients because they did not wear a wristband (28%), incorrect medication scanning, multiple medication scanning, and ignoring alert signals (11%). Common types of medication administration errors were omissions (78%), administration of non-ordered drugs (8.0%), and wrong doses given (6.0%). Discussion: Workarounds are associated with medication administration errors in hospitals using BCMA. These data suggest that BCMA needs more post-implementation evaluation if it is to achieve the intended benefits for medication safety. Conclusion: In hospitals using barcode-assisted medication administration, workarounds occurred in 66% of medication administrations and were associated with large numbers of medication administration errors

Neighbourhood drivability: environmental and individual characteristics associated with car use across Europe

Background: Car driving is a form of passive transportation associated with higher sedentary behaviour, which is associated with morbidity. The decision to drive a car is likely to be influenced by the ‘drivability’ of the built environment, but there is lack of scientific evidence regarding the relative contribution of environmental characteristics of car driving in Europe, compared to individual characteristics. This study aimed to determine which neighbourhood- and individual-level characteristics were associated with car driving in adults of five urban areas across Europe. Second, the study aimed to determine the percentage of variance in car driving explained by individual- and neighbourhood-level characteristics. Methods: Neighbourhood environment characteristics potentially related to car use were identified from the literature. These characteristics were subsequently assessed using a Google Street View audit and available GIS databases, in 59 administrative residential neighbourhoods in five European urban areas. Car driving (min/week) and individual level characteristics were self-reported by study participants (analytic sample n = 4258). We used linear multilevel regression analyses to assess cross-sectional associations of individual and neighbourhood-level characteristics with weekly minutes of car driving, and assessed explained variance at each level and for the total model. Results: Higher residential density (β:-2.61, 95%CI: − 4.99; -0.22) and higher land-use mix (β:-3.73, 95%CI: − 5.61; -1.86) were significantly associated with fewer weekly minutes of car driving. At the individual level, higher age (β: 1.47, 95%CI: 0.60; 2.33), male sex (β: 43.2, 95%CI:24.7; 61.7), being employed (β:80.1, 95%CI: 53.6; 106.5) and ≥ 3 person household composition (β: 47.4, 95%CI: 20.6; 74.2) were associated with higher weekly minutes of car driving. Individual and neighbourhood characteristics contributed about equally to explained variance in minutes of weekly car driving, with 2 and 3% respectively, but total explained variance remained low. Conclusions: Residential density and land-use mix were neighbourhood characteristics consistently associated with minutes of weekly car driving, besides age, sex, employment and household composition. Although total explained variance was low, both individual- and neighbourhood-level characteristics were similarly important in their associations with car use in five European urban areas. This study suggests that more, higher quality, and longitudinal data are needed to increase our understanding of car use and its effects on determinants of health

Psychosocial work characteristics and long-term sickness absence due to mental disorders

Background: Psychosocial work characteristics are associated with all-cause long-term sickness absence (LTSA). Aims: This study investigated whether psychosocial work characteristics such as higher workload, faster pace of work, less variety in work, lack of performance feedback, and lack of supervisor support are prospectively associated with higher LTSA due to mental disorders. Methods: Cohort study including 4877 workers employed in the distribution and transport sector in The Netherlands. Psychosocial work characteristics were included in a logistic regression model estimating the odds ratios (OR) and 95% confidence intervals (CI) of mental LTSA during 2-year follow-up. The ability of the regression model to discriminate between workers with and without mental LTSA was investigated with the area under the receiver operating characteristic curve (AUC). Results: Tow thousand seven hundred and eighty-two (57%) workers were included in the analysis; 73 (3%) had mental LTSA. Feedback about one’s performance (OR = 0.82; 95% CI 0.70–0.96) was associated with mental LTSA. A prediction model including psychosocial work characteristics poorly discriminated (AUC = 0.65; 95% CI 0.56–0.74) between workers with and without mental LTSA. Conclusions: Feedback about one’s performance is associated with lower rates of mental LTSA, but it is not useful to measure psychosocial work characteristics to identify workers at risk of mental LTSA

Analysing outcome variables with floor effects due to censoring: a simulation study with longitudinal trial data

ackground: Randomised controlled trials (RCTs) are the gold standard to estimate treatment effects. When patients receive effective treatment over time they may reach the limit of a certain measurement scale. This phenomenon is known as censoring and lead to skewed distributions of the outcome variable with an excess of either low (floor effect) or high values (ceiling effect). Applying traditional methods such as linear mixed models to analyse this kind of longitudinal RCT data may result in bias of the regression parameters. To deal with floor effects due to censoring,&nbsp; a tobit mixed model can be used. The objective of this study was to compare the results of longitudinal linear mixed model analyses with longitudinal tobit mixed model analyses.Methods: First, a simulation study was performed in which several situations of RCTs with floor effects were simulated. Second, data from an empirical RCT was analysed with both methods.Results: Although all analyses underestimated the intervention effects, the tobit mixed model performed much better than the linear mixed model in handling floor effects. However, with an increasing number of follow-up measurements in combination with a strong floor effect estimates from the tobit mixed model were also not accurate.Conclusion: tobit mixed model analysis should be used to estimate treatments effects in longitudinal RCTs with floor effects due to censoring.&nbsp

Peer-provided psychological intervention for Syrian refugees: results of a randomised controlled trial on the effectiveness of Problem Management Plus

Background The mental health burden among refugees in high-income countries (HICs) is high, whereas access to mental healthcare can be limited. Objective To examine the effectiveness of a peer-provided psychological intervention (Problem Management Plus; PM+) in reducing symptoms of common mental disorders (CMDs) among Syrian refugees in the Netherlands. Methods We conducted a single-blind, randomised controlled trial among adult Syrian refugees recruited in March 2019–December 2021 (No. NTR7552). Individuals with psychological distress (Kessler Psychological Distress Scale (K10) >15) and functional impairment (WHO Disability Assessment Schedule (WHODAS 2.0) >16) were allocated to PM+ in addition to care as usual (PM+/CAU) or CAU only. Participants were reassessed at 1-week and 3-month follow-up. Primary outcome was depression/anxiety combined (Hopkins Symptom Checklist; HSCL-25) at 3-month follow-up. Secondary outcomes included depression (HSCL-25), anxiety (HSCL-25), post-traumatic stress disorder (PTSD) symptoms (PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; PCL-5), impairment (WHODAS 2.0) and self-identified problems (PSYCHLOPS; Psychological Outcomes Profiles). Primary analysis was intention-to-treat. Findings Participants (n=206; mean age=37 years, 62% men) were randomised into PM+/CAU (n=103) or CAU (n=103). At 3-month follow-up, PM+/CAU had greater reductions on depression/anxiety relative to CAU (mean difference −0.25; 95% CI −0.385 to −0.122; p=0.0001, Cohen’s d=0.41). PM+/CAU also showed greater reductions on depression (p=0.0002, Cohen’s d=0.42), anxiety (p=0.001, Cohen’s d=0.27), PTSD symptoms (p=0.0005, Cohen’s d=0.39) and self-identified problems (p=0.03, Cohen’s d=0.26), but not on impairment (p=0.084, Cohen’s d=0.21). Conclusions PM+ effectively reduces symptoms of CMDs among Syrian refugees. A strength was high retention at follow-up. Generalisability is limited by predominantly including refugees with a resident permit. Clinical implications Peer-provided psychological interventions should be considered for scale-up in HICs