Evidence map›Paper›PMID 37924067›Full record

ArticleThe international journal of behavioral nutrition and physical activity2023

Different types of screen time, physical activity, and incident dementia, Parkinson's disease, depression and multimorbidity status.

Hanzhang Wu, Yeqing Gu, Wenxiu Du, Ge Meng, Hongmei Wu, Shunming Zhang, Xuena Wang, Juanjuan Zhang, Yaogang Wang, Tao Huang and 1 more

Open access · goldAbstract read
In one paragraph

Article in The international journal of behavioral nutrition and physical activity, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 4 pooled it
4.7field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 4 syntheses or guidelines pooled it, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 2 countries.

Hanzhang WuSchool of Public Health of Tianjin, University of Traditional Chinese Medicine, 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin, 301617, China.
Yeqing GuInstitute of Radiation Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Baidi Road 238, Tianjin, 300192, China. gyq900916@163.com.
Wenxiu DuSchool of Public Health of Tianjin, University of Traditional Chinese Medicine, 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin, 301617, China.
Ge MengSchool of Public Health of Tianjin, University of Traditional Chinese Medicine, 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin, 301617, China.
Hongmei WuSchool of Public Health of Tianjin, University of Traditional Chinese Medicine, 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin, 301617, China.
Shunming ZhangSchool of Public Health of Tianjin, University of Traditional Chinese Medicine, 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin, 301617, China.
Xuena WangSchool of Public Health of Tianjin, University of Traditional Chinese Medicine, 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin, 301617, China.
Juanjuan ZhangSchool of Public Health of Tianjin, University of Traditional Chinese Medicine, 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin, 301617, China.
Yaogang WangSchool of Integrative Medicine, Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China. YaogangWANG@tmu.edu.cn.
Tao HuangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China. huangtao@bjmu.edu.cn.
Kaijun NiuSchool of Public Health of Tianjin, University of Traditional Chinese Medicine, 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin, 301617, China. nkj0809@gmail.com.ORCID 0000-0002-8772-2481
Tianjin University of Traditional Chinese Medicine · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral previous studies have shown that excessive screen time is associated with an increased prevalence of dementia, Parkinson's disease (PD), and depression. However, the results have been inconsistent. This study aimed to prospectively investigate the association between different types of screen time and brain structure, as well as the incidence of dementia, Parkinson's disease, depression, and their multimorbidity status.

methodsWe included 473,184 participants initially free of dementia, PD, and depression from UK Biobank, as well as 39,652 participants who had magnetic resonance imaging (MRI) data. Screen time exposure variables including TV viewing and computer using were self-reported by participants. Cox proportional hazards regression models were used to estimate the association between different types of screen time and the incidence of dementia, Parkinson's disease, depression, and their multimorbidity status. Multiple linear regression models were used to assess the linear relationship between different types of screen time and MRI biomarkers in a subgroup of participants.

resultsDuring the follow up, 6,096, 3,061, and 23,700 participants first incident cases of dementia, PD, and depression respectively. For moderate versus the lowest computer uses, the adjusted HRs (95% CIs) were 0.68 (0.64, 0.72) for dementia, 0.86 (0.79, 0.93) for PD, 0.85 (0.83, 0.88) for depression, 0.64 (0.55, 0.74) for dementia and depression multimorbidity, and 0.59 (0.47, 0.74) for PD and depression multimorbidity. The multivariable HRs (95% CIs) for the highest versus the lowest group of TV viewing time were 1.28 (1.17, 1.39) for dementia, 1.16 (1.03, 1.29) for PD, 1.35 (1.29, 1.40) for depression, 1.49 (1.21, 1.84) for dementia and depression multimorbidity, and 1.44 (1.05, 1.97) for PD and depression multimorbidity. Moderate computer using time was negatively associated with white matter hyperintensity volume (β = -0.042; 95% CI -0.067, -0.017), and positively associated with hippocampal volume (β = 0.059; 95% CI 0.034, 0.084). Participants with the highest TV viewing time were negatively associated with hippocampal volume (β = -0.067; 95% CI -0.094, -0.041). In isotemporal substitution analyses, substitution of TV viewing or computer using by equal time of different types of PA was associated with a lower risk of all three diseases, with strenuous sports showing the strongest benefit.

conclusionWe found that moderate computer use was associated with a reduced risk of dementia, PD, depression and their multimorbidity status, while increased TV watching was associated with a higher risk of these disease. Notably, different screen time may affect the risk of developing diseases by influencing brain structures. Replacing different types of screen time with daily-life PA or structured exercise is associated with lower dementia, PD, and depression risk.

Indexed as

DementiaParkinson DiseaseDepressionExerciseHumansMultimorbidityScreen TimeDementiaDepressionMagnetic resonance imagingParkinson’s diseaseScreen time

Identifiers

PMID37924067
PMCPMC10625186
OpenAlexW4388290349

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.