We aimed to investigate the determinants of attendance to a preventive health check program and to explore the homogeneity of the attenders.4853 eligible persons living in the municipality of Randers, Denmark, from 2012 to 2013, aged 30–49 years, received an invitation to attend the ‘Check Your Health Preventive Program’. Data was obtained from the Danish National Registers. Socio-demographic factors, use of preventive services, morbidity were examined as determinants of attendance by Poisson regression analyses. A chi-squared automatic interaction detection decision tree analysis was used to identify mutually exclusive groups.In total, 55% of the invited population attended (49% men). Attenders were more likely to be: of higher age; immigrants; cohabiting; have: higher socio-economic status; higher use of preventive services and lower morbidity. Decision tree analysis revealed six groups, with the most important variable being income: 1) low income, low education (A = attendance rate: 38%; P = population size: 11%); 2) low income, education higher than 10 years, living alone (A: 41%; P: 5%); 3) low income, education higher than 10 years, cohabiting (A: 56%; P: 16%); 4) middle income (A: 60%; P: 34%); 5) high income, living alone (A: 56%; P: 4%); 6) high income, cohabiting (A: 69%; P: 30%).More than half of a general population voluntarily attended a general health check, despite a resource intensive offer. People with low resources had lower attendance rates. This study adds a detailed description of mutually exclusive groups of attenders, for use in future planning and implementation of preventive actions.
In this population with low physical activity levels, cross-sectional findings indicate that increasing overall physical activity and decreasing time spent sedentary is important to avoid the accumulation of metabolically deleterious VAT.
BackgroundPoor uptake among socio-economically disadvantaged and susceptible populations is a well-known challenge of general health check interventions, and is widely cited as one of the reasons for the lack of population level effects seen in many studies. We report on patient characteristics among attendees and non-attendees of health checks made available to residents in the social housing sector of the municipality of Aarhus. We focus on this general population, as well as a particular sub-group living in an exceptionally deprived social housing area, and discuss the properties of intervention uptake that we need to be aware of to qualify and compare the effects of general versus targeted health checks in socially deprived areas.MethodsCross-sectionally in a sample of 6650 residents of the Aarhus social housing sector who were invited for a health check in the first year of the ‘Your Life – Your Health’ program. The analyses consisted of 1) descriptive analysis of the characteristics of attenders/non-attenders, 2) unadjusted and adjusted Poisson regression to examine associations of patient characteristics and uptake of health checks, and 3) decision tree analyses (CHAID) to examine interaction and homogeneity in patient characteristics among attenders.ResultsOf the overall population 30% attended. In a nested cohort of people residing in a particularly deprived social housing settlement, 25% attended. Further, in the overall population, we found an association between the likelihood of taking up a health check and age, sex, country of origin, educational attainment, cohabitation, occupational status, and past medical treatment. In the nested cohort the association between uptake and medical treatment was non-significant, while the association between uptake and occupation was limited to people who were employed. These results resonate with past evidence on health check attendance.ConclusionsAttendance in the ‘Your Life – Your Health’ program is higher among people of a higher socio-economic status. This should be taken into consideration when analysing and interpreting the overall study effects. Moreover, the results suggest that a targeted approach in the social housing sector could be more effective than a mass screening approach. However, more information is required to make such assertion definitive.Electronic supplementary materialThe online version of this article (10.1186/s12889-018-5506-6) contains supplementary material, which is available to authorized users.
ObjectivesIt has long been discussed whether fitness or fatness is a more important determinant of health status. If the same genetic factors that promote body fat percentage (body fat%) are related to cardiorespiratory fitness (CRF), part of the concurrent associations with health outcomes could reflect a common genetic origin. In this study we aimed to 1) examine genetic correlations between body fat% and CRF; 2) determine whether CRF can be attributed to a genetic risk score (GRS) based on known body fat% increasing loci; and 3) examine whether the fat mass and obesity associated (FTO) locus associates with CRF.MethodsGenetic correlations based on pedigree information were examined in a family based cohort (n = 230 from 55 families). For the genetic association analyses, we examined two Danish population-based cohorts (ntotal = 3206). The body fat% GRS was created by summing the alleles of twelve independent risk variants known to associate with body fat%. We assessed CRF as maximal oxygen uptake expressed in millilitres of oxygen uptake per kg of body mass (VO2max), per kg fat-free mass (VO2maxFFM), or per kg fat mass (VO2maxFM). All analyses were adjusted for age and sex, and when relevant, for body composition.ResultsWe found a significant negative genetic correlation between VO2max and body fat% (ρG = -0.72 (SE ±0.13)). The body fat% GRS associated with decreased VO2max (β = -0.15 mL/kg/min per allele, p = 0.0034, age and sex adjusted). The body fat%-increasing FTO allele was associated with a 0.42 mL/kg/min unit decrease in VO2max per allele (p = 0.0092, age and sex adjusted). Both associations were abolished after additional adjustment for body fat%. The fat% increasing GRS and FTO risk allele were associated with decreased VO2maxFM but not with VO2maxFFM.ConclusionsOur findings suggest a shared genetic etiology between whole body fat% and CRF.
Rationale The hormone glucagon-like peptide-1 (GLP-1) decreases blood glucose and appetite. Greater physical activity (PA) is associated with lower incidence of type 2 diabetes. While acute exercise may increase glucose-induced response of GLP-1, it is unknown how habitual PA affects GLP-1 secretion. We hypothesised that habitual PA associates with greater glucose-induced GLP-1 responses in overweight individuals. Methods Cross-sectional analysis of habitual PA levels and GLP-1 concentrations in 1326 individuals (mean (s.d.) age 66 (7) years, BMI 27.1 (4.5) kg/m2) from the ADDITION-PRO cohort. Fasting and oral glucose-stimulated GLP-1 responses were measured using validated radioimmunoassay. PA was measured using 7-day combined accelerometry and heart rate monitoring. From this, energy expenditure (PAEE; kJ/kg/day) and fractions of time spent in activity intensities (h/day) were calculated. Cardiorespiratory fitness (CRF; mL O2/kg/min) was calculated using step tests. Age-, BMI- and insulin sensitivity-adjusted associations between PA and GLP-1, stratified by sex, were evaluated by linear regression analysis. Results In 703 men, fasting GLP-1 concentrations were 20% lower (95% CI: −33; −3%, P = 0.02) for every hour of moderate-intensity PA performed. Higher CRF and PAEE were associated with 1–2% lower fasting GLP-1 (P = 0.01). For every hour of moderate-intensity PA, the glucose-stimulated GLP-1 response was 16% greater at peak 30 min (1; 33%, P rAUC0-30 = 0.04) and 20% greater at full response (3; 40%, P rAUC0-120 = 0.02). No associations were found in women who performed PA 22 min/day vs 32 min/day for men. Conclusion Moderate-intensity PA is associated with lower fasting and greater glucose-induced GLP-1 responses in overweight men, possibly contributing to improved glucose and appetite regulation with increased habitual PA.
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