Health behaviour
Web program increased older adults’ measured activity in a trial
Open access · cc by · source: Europe PMC
A Dutch RCT found a web-based intervention raised daily activity ~46% and improved weight and HbA1c markers in inactive 60–70-year-olds.
Study at a glance
- Design
- RCT — Web-based PA program vs control; accelerometer outcomes ~3 months
- N
- N=235 · Adults aged 60–70 near Leiden
- Population
- Adults aged 60–70 near Leiden randomized to a web-based physical-activity program
- Outcome
- Daily activity (ankle accelerometer), weight, and HbA1c
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
Ankle-measured daily activity rose 46% vs 12% in controls; intervention lost more weight (−1.49 vs −0.82 kg) and had greater HbA1c decline.
Methodology
235 adults aged 60–70 near Leiden were randomized to a web-based physical-activity program or control; ankle/wrist accelerometers and metabolic measures were assessed over ~3 months.
Limitations
Long-term maintenance beyond 3 months or effects in adults with established diabetes (excluded).
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
A web programme can raise daily activity and short-term weight and HbA1c markers in older adults.
In older adults, a web-based activity programme increased ankle-measured daily activity (~46% vs ~12% in controls) and was associated with greater short-term weight and HbA1c improvements than control.
Evidence for the claim as stated.
Team walking can add minutes during the programme — advantages often fade months later.
A Facebook team-walking programme increased walking by about 155 min/week during the intervention, but between-group advantages were not maintained 3 months after the stimulus ended.
Scope note — different age group and measures — older adults with ankle sensors
Limits the claim's scope: a different population, assay, or outcome.
A child-care nutrition and activity trial shifted zBMI slightly, with design caveats.
In a child-care nutrition/activity RCT, intervention versus control differed in mean zBMI change (coeff about −0.14), with center-level randomisation and socioeconomic imbalances noted as caution flags.
Scope note — different population — older adults, not child-care settings
Limits the claim's scope: a different population, assay, or outcome.
Healthier lifestyle scores associate with lower CVD and diabetes incidence in cohorts.
In a multinational prospective cohort, a higher healthy lifestyle index was inversely associated with incident CVD (HR about 0.77 per 3 units) and type 2 diabetes (HR about 0.67), and more weakly with cancer (HR about 0.89).
Scope note — different design — short-term activity RCT, not long-horizon observational index
Limits the claim's scope: a different population, assay, or outcome.
Digital tools show mixed proximal effects — logging more is not the same as preventing disease.
Digital tools show mixed proximal endpoints: a step-log app was associated with higher odds of continued daily logging versus matched controls, while a small uncontrolled smoking EMI reported 20% biochemically confirmed abstinence at 12 weeks.
Scope note — stronger activity design — randomised measured activity, not logging-only
Limits the claim's scope: a different population, assay, or outcome.
Randomised activity/diet programmes, observational lifestyle indices, and digital pilots measure different endpoints (minutes walked, zBMI, incident disease, logging, abstinence). Treating them as one efficacy number manufactures agreement that the designs do not support.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Randomised activity/diet programmes, observational lifestyle indices, and digital pilots measure different endpoints (minutes walked, zBMI, incident disease, logging, abstinence). Treating them as one efficacy number manufactures agreement that the designs do not support.
- Supports · Healthy lifestyle and multimorbidity risk
- Supports · Child-care diet/activity RCT and zBMI
- Supports · Does a step-log app keep people tracking activity?
- Supports · Smart-T smoking EMI app
- Supports · Facebook team walking RCT
History
When this study was placed
Dated entries from the concept change log — when this paper was added or removed as support, challenge, or qualifier on a claim.
Placed as a scope qualifier on Health Behaviour
A Facebook team-walking programme increased walking by about 155 min/week during the intervention, but between-group advantages were not maintained 3 months after the stimulus ended.
Placed as a scope qualifier on Health Behaviour
In a child-care nutrition/activity RCT, intervention versus control differed in mean zBMI change (coeff about −0.14), with center-level randomisation and socioeconomic imbalances noted as caution flags.
Placed as a scope qualifier on Health Behaviour
In a multinational prospective cohort, a higher healthy lifestyle index was inversely associated with incident CVD (HR about 0.77 per 3 units) and type 2 diabetes (HR about 0.67), and more weakly with cancer (HR about 0.89).
Placed as a scope qualifier on Health Behaviour
Digital tools show mixed proximal endpoints: a step-log app was associated with higher odds of continued daily logging versus matched controls, while a small uncontrolled smoking EMI reported 20% biochemically confirmed abstinence at 12 weeks.
Related papers in this topic
Same topic cluster — not a recommendation engine.