Criterion validity of the Saltin-Grimby Physical Activity Level Scale in adolescents. The Fit Futures Study

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PCM4EU and PRIME-ROSE:Collaboration for implementation of precision cancer medicine in Europe

Background: In the two European Union (EU)-funded projects, PCM4EU (Personalized Cancer Medicine for all EU citizens) and PRIME-ROSE (Precision Cancer Medicine Repurposing System Using Pragmatic Clinical Trials), we aim to facilitate implementation of precision cancer medicine (PCM) in Europe by leveraging the experience from ongoing national initiatives that have already been particularly successful. Patients and methods: PCM4EU and PRIME-ROSE gather 17 and 24 partners, respectively, from 19 European countries. The projects are based on a network of Drug Rediscovery Protocol (DRUP)-like clinical trials that are currently ongoing or soon to start in 11 different countries, and with more trials expected to be established soon. The main aims of both the projects are to improve implementation pathways from molecular diagnostics to treatment, and reimbursement of diagnostics and tumour-tailored therapies to provide examples of best practices for PCM in Europe. Results: PCM4EU and PRIME-ROSE were launched in January and July 2023, respectively. Educational materials, including a podcast series, are already available from the PCM4EU website (http://www.pcm4eu. eu). The first reports, including an overview of requirements for the reimbursement systems in participating countries and a guide on patient involvement, are expected to be published in 2024. Conclusion: European collaboration can facilitate the implementation of PCM and thereby provide affordable and equitable access to precision diagnostics and matched therapies for more patients.</p

PCM4EU and PRIME-ROSE:Collaboration for implementation of precision cancer medicine in Europe

Background: In the two European Union (EU)-funded projects, PCM4EU (Personalized Cancer Medicine for all EU citizens) and PRIME-ROSE (Precision Cancer Medicine Repurposing System Using Pragmatic Clinical Trials), we aim to facilitate implementation of precision cancer medicine (PCM) in Europe by leveraging the experience from ongoing national initiatives that have already been particularly successful. Patients and methods: PCM4EU and PRIME-ROSE gather 17 and 24 partners, respectively, from 19 European countries. The projects are based on a network of Drug Rediscovery Protocol (DRUP)-like clinical trials that are currently ongoing or soon to start in 11 different countries, and with more trials expected to be established soon. The main aims of both the projects are to improve implementation pathways from molecular diagnostics to treatment, and reimbursement of diagnostics and tumour-tailored therapies to provide examples of best practices for PCM in Europe. Results: PCM4EU and PRIME-ROSE were launched in January and July 2023, respectively. Educational materials, including a podcast series, are already available from the PCM4EU website (http://www.pcm4eu. eu). The first reports, including an overview of requirements for the reimbursement systems in participating countries and a guide on patient involvement, are expected to be published in 2024. Conclusion: European collaboration can facilitate the implementation of PCM and thereby provide affordable and equitable access to precision diagnostics and matched therapies for more patients.</p

Do declines in occupational physical activity contribute to population gains in body mass index? Tromsø Study 1974–2016

Objective To examine whether occupational physical activity changes predict future body mass index (BMI) changes. Methods This longitudinal cohort study included adult participants attending ≥3 consecutive Tromsø Study surveys (examinations 1, 2 and 3) from 1974 to 2016 (N=11 308). If a participant attended >3 surveys, the three most recent surveys were included. Occupational physical activity change (assessed by the Saltin-Grimby Physical Activity Level Scale) was computed from the first to the second examination, categorised into persistently inactive (n=3692), persistently active (n=5560), active to inactive (n=741) and inactive to active (n=1315). BMI change was calculated from the second to the third examination (height being fixed at the second examination) and regressed on preceding occupational physical activity changes using analysis of covariance adjusted for sex, birth year, smoking, education and BMI at examination 2. Results Overall, BMI increased by 0.84 kg/m2 (95% CI 0.82 to 0.89). Following adjustments as described previously, we observed no differences in BMI increase between the occupational physical activity change groups (Persistently Inactive: 0.81 kg/m2, 95% CI 0.75 to 0.87; Persistently Active: 0.87 kg/m2, 95% CI 0.82 to 0.92; Active to Inactive: 0.81 kg/m2, 95% CI 0.67 to 0.94; Inactive to Active: 0.91 kg/m2, 95% CI 0.81 to 1.01; p=0.25). Conclusion We observed no prospective association between occupational physical activity changes and subsequent BMI changes. Our findings do not support the hypothesis that occupational physical activity declines contributed to population BMI gains over the past decades. Public health initiatives aimed at weight gain prevention may have greater success if focusing on other aspects than occupational physical activity

Do declines in occupational physical activity contribute to population gains in body mass index? Tromsø Study 1974–2016

Objective - To examine whether occupational physical activity changes predict future body mass index (BMI) changes. Methods - This longitudinal cohort study included adult participants attending ≥3 consecutive Tromsø Study surveys (examinations 1, 2 and 3) from 1974 to 2016 (N=11 308). If a participant attended >3 surveys, the three most recent surveys were included. Occupational physical activity change (assessed by the Saltin-Grimby Physical Activity Level Scale) was computed from the first to the second examination, categorised into persistently inactive (n=3692), persistently active (n=5560), active to inactive (n=741) and inactive to active (n=1315). BMI change was calculated from the second to the third examination (height being fixed at the second examination) and regressed on preceding occupational physical activity changes using analysis of covariance adjusted for sex, birth year, smoking, education and BMI at examination 2. Results - Overall, BMI increased by 0.84 kg/m2 (95% CI 0.82 to 0.89). Following adjustments as described previously, we observed no differences in BMI increase between the occupational physical activity change groups (Persistently Inactive: 0.81 kg/m2, 95% CI 0.75 to 0.87; Persistently Active: 0.87 kg/m2, 95% CI 0.82 to 0.92; Active to Inactive: 0.81 kg/m2, 95% CI 0.67 to 0.94; Inactive to Active: 0.91 kg/m2, 95% CI 0.81 to 1.01; p=0.25). Conclusion - We observed no prospective association between occupational physical activity changes and subsequent BMI changes. Our findings do not support the hypothesis that occupational physical activity declines contributed to population BMI gains over the past decades. Public health initiatives aimed at weight gain prevention may have greater success if focusing on other aspects than occupational physical activity

Do declines in occupational physical activity contribute to population gains in body mass index? Tromsø Study 1974–2016

Objective: To examine whether occupational physical activity changes predict future body mass index (BMI) changes. Methods: This longitudinal cohort study included adult participants attending ≥3 consecutive Tromsø Study surveys (examinations 1, 2 and 3) from 1974 to 2016 (N=11 308). If a participant attended >3 surveys, the three most recent surveys were included. Occupational physical activity change (assessed by the Saltin-Grimby Physical Activity Level Scale) was computed from the first to the second examination, categorised into persistently inactive (n=3692), persistently active (n=5560), active to inactive (n=741) and inactive to active (n=1315). BMI change was calculated from the second to the third examination (height being fixed at the second examination) and regressed on preceding occupational physical activity changes using analysis of covariance adjusted for sex, birth year, smoking, education and BMI at examination 2. Results: Overall, BMI increased by 0.84 kg/m2 (95% CI 0.82 to 0.89). Following adjustments as described previously, we observed no differences in BMI increase between the occupational physical activity change groups (Persistently Inactive: 0.81 kg/m2, 95% CI 0.75 to 0.87; Persistently Active: 0.87 kg/m2, 95% CI 0.82 to 0.92; Active to Inactive: 0.81 kg/m2, 95% CI 0.67 to 0.94; Inactive to Active: 0.91 kg/m2, 95% CI 0.81 to 1.01; p=0.25). Conclusion: We observed no prospective association between occupational physical activity changes and subsequent BMI changes. Our findings do not support the hypothesis that occupational physical activity declines contributed to population BMI gains over the past decades. Public health initiatives aimed at weight gain prevention may have greater success if focusing on other aspects than occupational physical activity