Mobile Phone Call Duration and Cardiovascular Outcomes: Prospective and Genetic Evidence on a Potential Depression-Related Pathway
Abstract
Background: Mobile phone use has been associated with cardiovascular disease (CVD), but the role of major depressive disorder (MDD) in this relationship remains uncertain. Methods: We examined self-reported weekly mobile phone call duration and incident heart failure (HF), coronary artery disease (CAD), stroke, and myocardial infarction (MI) in four UK Biobank at-risk cohorts (N = 320,343–328,170) using Cox regression. Baseline MDD was evaluated as a stratification and effect-modification variable. We also conducted two-sample MR and an exploratory two-step MR analysis of the pathway from call duration through MDD to CVD. Genome-wide significant instruments (p < 5 × 10−8) defined the primary MR analysis; p < 10−6 was examined as a sensitivity threshold. Results: In fully adjusted Cox models, call duration greater than 6 h/week was associated with CAD (HR 1.18, 95% CI 1.10–1.27) and stroke (HR 1.17, 95% CI 1.05–1.29) but not HF or MI. MDD-by-call-duration interactions were not significant (all interaction p ≥ 0.115). Primary IVW MR estimates supported associations of genetically predicted call duration with MDD (OR 1.56, 95% CI 1.04–2.33) and CAD (OR 1.69, 95% CI 1.13–2.55), whereas estimates for HF, stroke, and MI were imprecise. None of the four primary two-step indirect effects excluded the null, and none remained significant after false-discovery-rate correction at the sensitivity threshold. Conclusions: Longer weekly mobile phone call duration was prospectively associated with CAD and stroke in UK Biobank. The MR findings provide exploratory, but not conclusive, support for an MDD-related pathway.
AI evidence extraction
Main findings
Call duration greater than 6 hours/week was associated with coronary artery disease and stroke, but not heart failure or myocardial infarction, in adjusted prospective analyses. Genetic analyses provided exploratory support for associations with major depressive disorder and coronary artery disease, but did not establish a depression-related pathway.
Outcomes measured
- Heart failure
- Coronary artery disease
- Stroke
- Myocardial infarction
- Major depressive disorder
Limitations
- Call duration was self-reported and does not quantify electromagnetic-field exposure.
- Primary two-step indirect effects did not exclude the null.
- Genetic estimates for heart failure, stroke, and myocardial infarction were imprecise.
Suggested hubs
-
mobile-phones
(0.9) The study examines mobile phone call duration.
View raw extracted JSON
{
"study_type": "cohort",
"exposure": {
"band": null,
"source": "mobile phone",
"frequency_mhz": null,
"sar_wkg": null,
"duration": "Self-reported weekly call duration; results reported for >6 hours/week"
},
"population": "UK Biobank participants in four at-risk cohorts",
"sample_size": null,
"outcomes": [
"Heart failure",
"Coronary artery disease",
"Stroke",
"Myocardial infarction",
"Major depressive disorder"
],
"main_findings": "Call duration greater than 6 hours/week was associated with coronary artery disease and stroke, but not heart failure or myocardial infarction, in adjusted prospective analyses. Genetic analyses provided exploratory support for associations with major depressive disorder and coronary artery disease, but did not establish a depression-related pathway.",
"effect_direction": "mixed",
"limitations": [
"Call duration was self-reported and does not quantify electromagnetic-field exposure.",
"Primary two-step indirect effects did not exclude the null.",
"Genetic estimates for heart failure, stroke, and myocardial infarction were imprecise."
],
"evidence_strength": "low",
"confidence": 0.9499999999999999555910790149937383830547332763671875,
"peer_reviewed_likely": "yes",
"keywords": [
"mobile phone calls",
"call duration",
"cardiovascular disease",
"coronary artery disease",
"stroke",
"major depressive disorder",
"UK Biobank",
"Mendelian randomization"
],
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{
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"reason": "The study examines mobile phone call duration."
}
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}
AI can be wrong. Always verify against the paper.
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