Circulating sex hormone levels have been linked to a wide range of cardiovascular risk factors in men, but studies on incident CVD have been inconclusive [1]. Recent data from meta-analyses show an increase in CVD risk with low testosterone in elderly men and no association with estradiol levels [2,3]. To clarify the role of sex hormones in male CVD risk, we examined the cross-sectional and longitudinal associations between endogenous sex hormones and subclinical atherosclerosis in a population-based cohort of middle-aged and older men.
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PURPOSE: Several studies have reported seasonal variation in intake of food groups and certain nutrients. However, whether this could lead to a seasonal pattern of diet quality has not been addressed. We aimed to describe the seasonality of diet quality, and to examine the contribution of the food groups included in the dietary guidelines to this seasonality.METHODS: Among 9701 middle-aged and elderly participants of the Rotterdam Study, a prospective population-based cohort, diet was assessed using food-frequency questionnaires (FFQ). Diet quality was measured as adherence to the Dutch dietary guidelines, and expressed in a diet quality score ranging from 0 to 14 points. The seasonality of diet quality and of the food group intake was examined using cosinor linear mixed models. Models were adjusted for sex, age, cohort, energy intake, physical activity, body mass index, comorbidities, and education.RESULTS: Diet quality had a seasonal pattern with a winter-peak (seasonal variation = 0.10 points, December-peak) especially among participants who were men, obese and of high socio-economic level. This pattern was mostly explained by the seasonal variation in the intake of legumes (seasonal variation = 3.52 g/day, December-peak), nuts (seasonal variation = 0.78 g/day, January-peak), sugar-containing beverages (seasonal variation = 12.96 milliliters/day, June-peak), and dairy (seasonal variation = 17.52 g/day, June-peak).CONCLUSIONS: Diet quality varies seasonally with heterogeneous seasonality of food groups counteractively contributing to the seasonal pattern in diet quality. This seasonality should be considered in future research on dietary behavior. Also, season-specific recommendations and policies are required to improve diet quality throughout the year.
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Objectives: Decline in the performance of instrumental activities of daily living (IADL) and mobility may be preceded by symptoms the patient experiences, such as fatigue. The aim of this study is to investigate whether self-reported non-task-specific fatigue is a long-term risk factor for IADL-limitations and/or mobility performance in older adults after 10 years. Methods: A prospective study from two previously conducted cross-sectional studies with 10-year follow-up was conducted among 285 males and 249 females aged 40–79 years at baseline. Fatigue was measured by asking “Did you feel tired within the past 4 weeks?” (males) and “Do you feel tired?” (females). Self-reported IADLs were assessed at baseline and follow-up. Mobility was assessed by the 6-minute walk test. Gender-specific associations between fatigue and IADL-limitations and mobility were estimated by multivariable logistic and linear regression models. Results: A total of 18.6% of males and 28.1% of females were fatigued. After adjustment, the odds ratio for fatigued versus non-fatigued males affected by IADL-limitations was 3.3 (P=0.023). In females, the association was weaker and not statistically significant, with odds ratio being 1.7 (P=0.154). Fatigued males walked 39.1 m shorter distance than those non-fatigued (P=0.048). For fatigued females, the distance was 17.5 m shorter compared to those non-fatigued (P=0.479). Conclusion: Our data suggest that self-reported fatigue may be a long-term risk factor for IADL-limitations and mobility performance in middle-aged and elderly males but possibly not in females.
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Background. Quality of life is an important health outcome for older persons. It predicts the adverse outcomes of institutionalization and premature death. The aim of this cross-sectional study was to determine the influence of both disability in activities of daily living (ADL) and instrumental activities of daily living (IADL) on physical and mental dimensions of quality of life. Methods. A total of 377 Dutch people aged 75 years and older completed a web-based questionnaire. This questionnaire contained the Groningen Activity Restriction Scale (GARS) for measuring ADL and IADL and the Short-Form Health Survey (SF-12) for measuring quality of life. The SF-12 distinguishes two dimensions of quality of life, a physical and mental dimension.
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Reducing social inequalities in physical activity (PA) has become a priority for public health. However, evidence concerning the impact of interventions on inequalities in PA is scarce. This study aims to develop and test the application of a strategy for re-analyzing equity-specific effects of existing PA intervention studies in middle-aged and older adults, as part of an international interdisciplinary collaboration. This article aims to describe (1) the establishment and characteristics of the collaboration; and (2) the jointly developed equity-specific re-analysis strategy as a first result of the collaboration. To develop the strategy, a collaboration based on a convenience sample of eight published studies of individual-level PA interventions among the general population of adults aged ≥45 years was initiated (UK, n = 3; The Netherlands, n = 3; Belgium, n = 1; Germany, n = 1). Researchers from these studies participated in a workshop and subsequent e-mail correspondence. The developed strategy will be used to investigate social inequalities in intervention adherence, dropout, and efficacy. This will allow for a comprehensive assessment of social inequalities within intervention benefits. The application of the strategy within and beyond the collaboration will help to extend the limited evidence regarding the effects of interventions on social inequalities in PA among middle-aged and older adults.
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Objective:This study investigated whether visual function is associated with cognitive activity engagement and mild cognitive impairment in middle-aged and elderly individuals. Method:This cross-sectional study was conducted on 120 individuals aged 50–89. The Florida Cognitive Activity Scale (FCAS) was used to assess cognitive activity engagement. Visual function was assessed by near visual acuity(nVA) and contrast sensitivity (CS), and both combined to obtain a visual function (VF) compound score. Multi-variable linear regression models, adjusted for confounders, were used to assess the association between the determinants and FCAS. Results:After confounder adjustment, nVA was not associated with overall cognitive activity engagement. CS was significantly associated with the FCAS“Higher Cognitive Abilities”subscale score (BHC= 5.5 [95% CI 1.3; 9.7]).Adjustment for nVA attenuated the association between CS and engagement in tasks of Higher Cognitive Abilities(BHC= 4.7 [95% CI 0.1; 9.3]).In retired individuals(N= 87), theVF compound score was associated with a lower Cognitive Activity Scale score(BCA=−1.2 [95% CI−2.3;−0.1]), lower Higher Cognitive Abilities score(BHC=−0.7 [95% CI−1.3;−0.1])and lower Frequent Cognitive Abilities score (BFA=−0.5 [95% CI−0.9;−0.1]). Conclusion:CS, but not nVA, plays a role in engagement in tasks associated with Higher Cognitive Abilities in middle-aged and elderly individuals. In retired individuals, the VF compound score is associated with lower Cognitive Activity score, lower Higher Cognitive Abilities score and lower Frequent Cognitive Abilities score.
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In this chapter, I look back at the implementation of W12-16, a major reform of mathematics education in the lower grades of general secondary education and pre-vocational secondary education in the Netherlands including all students aged 12–16. The nationwide implementation of W12-16 started in 1990 and envisioned a major change in what and how mathematics was taught and learned. The content was broadened from algebra and geometry to algebra, geometry and measurement, numeracy, and data processing and statistics. The learning trajectories and the instruction theory were based on the ideas of Realistic Mathematics Education (RME): the primary processes used in the classroom were to be guided re-invention and problem solving. ‘Ensuring usability’ in the title of this chapter refers to the aim of the content being useful and understandable for all students, but also to the involvement of all relevant stakeholders in the implementation project, including teachers, students, parents, editors, curriculum and assessment developers, teacher educators, publishers, media and policy makers. Finally, I reflect on the current state of affairs more than 20 years after the nationwide introduction. The main questions to be asked are: Have the goals been reached? Was the implementation successful?
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AbstractObjective: Many older individuals receive rehabilitation in an out-of-hospital setting (OOHS) after acute hospitalization; however, its effect onmobility and unplanned hospital readmission is unclear. Therefore, a systematic review and meta-analysis were conducted on this topic.Data Sources: Medline OVID, Embase OVID, and CINAHL were searched from their inception until February 22, 2018.Study Selection: OOHS (ie, skilled nursing facilities, outpatient clinics, or community-based at home) randomized trials studying the effect ofmultidisciplinary rehabilitation were selected, including those assessing exercise in older patients (mean age 65y) after discharge from hospitalafter an acute illness.Data Extraction: Two reviewers independently selected the studies, performed independent data extraction, and assessed the risk of bias.Outcomes were pooled using fixed- or random-effect models as appropriate. The main outcomes were mobility at and unplanned hospitalreadmission within 3 months of discharge.Data Synthesis: A total of 15 studies (1255 patients) were included in the systematic review and 12 were included in the meta-analysis (7assessing mobility using the 6-minute walk distance [6MWD] test and 7 assessing unplanned hospital readmission). Based on the 6MWD, patientsreceiving rehabilitation walked an average of 23 m more than controls (95% confidence interval [CI]Z: 1.34 to 48.32; I2: 51%). Rehabilitationdid not lower the 3-month risk of unplanned hospital readmission (risk ratio: 0.93; 95% CI: 0.73-1.19; I2: 34%). The risk of bias was present,mainly due to the nonblinded outcome assessment in 3 studies, and 7 studies scored this unclearly.Conclusion: OOHS-based multidisciplinary rehabilitation leads to improved mobility in older patients 3 months after they are discharged fromhospital following an acute illness and is not associated with a lower risk of unplanned hospital readmission within 3 months of discharge.However, the wide 95% CIs indicate that the evidence is not robust.
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Objective: The effects of sociodemographic factors on quality of life in older people differ strongly, possibly due to the fact that different measurement instruments have been used. The main aim of this cross-sectional study is to compare the associations of sex, age, marital status, education, and income with quality of life assessed with the Short-Form Health Survey (SF-12), the World Health Organization Quality of Life Questionnaire-BREF (WHOQOL-BREF), and the World Health Organization Quality of Life Questionnaire-Older Adults Module (WHOQOL-OLD). Methods: The associations between sociodemographic factors and eleven quality of life domains were examined using a sample of 1,492 Dutch people aged $50 years. Participants completed the “Senioren Barometer”, a web-based questionnaire including sociodemographic factors, the SF-12, the WHOQOL-BREF, and the WHOQOL-OLD. Results: All the sociodemographic factors together explained a significant part of the variance of all the quality of life domains’ scores, ranging from 5% to 17% for the WHOQOL-BREF, 5.8% to 6.7% for the SF-12, and 1.4% to 26% for the WHOQOL-OLD. Being a woman and being older were negatively associated with two and four quality of life domains, respectively. Being a woman, being married or cohabiting, and having higher education and a higher income were positively associated with six, six, one, and eleven quality of life domains, respectively. Conclusion: Our study showed that the associations of sociodemographic factors and quality of life in middle-aged and older people depend on the instruments used to assess quality of life. We recommend that health care and welfare professionals focus particularly on people with a low income and carry out interventions aimed at improving their quality of life.
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Intra-ocular straylight can cause decreased visual functioning, and it may cause diminished vision-related quality of life (VRQOL). This cross-sectional population-based study investigates the association between straylight and VRQOL in middle-aged and elderly individuals. Multivariable linear regression analyses were used to assess the association between straylight modeled continuously and cutoff at the recommended fitness-to-drive value, straylight ≥ 1.4 log(s), and VRQOL. The study showed that participants with normal straylight values, straylight ≤ 1.4 log(s), rated their VRQOL slightly better than those with high straylight values (straylight ≥ 1.4 log(s)). Furthermore, multivariable regression analysis revealed a borderline statistical significant association (p = .06) between intra-ocular straylight and self-reported VRQOL in middle-aged and elderly individuals. The association between straylight and self-reported VRQOL was not influenced by the status of the intra-ocular lens (natural vs. artificial intra-ocular lens after cataract extraction) or the number of (instrumental) activities of daily living that were reported as difficult for the elderly individuals.
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