Associations of sedentary time and physical activity with adverse health conditions: Outcome-wide analyses using isotemporal substitution model

Cao, Zhi; Xu, Chenjie; Zhang, Pengjie; Wang, Yaogang

doi:10.1016/j.eclinm.2022.101424

Cited by 63 publications

(45 citation statements)

References 49 publications

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“…Television and computer time are characteristic indicators of sedentary behavior. A comprehensive analysis of a large UK-based prospective study showed a linear dose–response relationship between sedentary time and 14 noncommunicable diseases, including cardiometabolic diseases, diabetes, and depression (Cao et al 2022 ). Some studies have shown that sedentariness reduces voluntary energy expenditure, inhibits skeletal muscle activation, and leads to reduced venous and arterial blood flow, all of which may contribute to impaired glucose metabolism (Bellettiere et al 2019 ).…”

Section: Discussionmentioning

confidence: 99%

“…The frequency (Patterson et al 2018 ), posture, accompanying behaviors (Cameron et al 2016 ), and content interactivity (Andrade-Gomez et al 2017 ) with respect to the use of different types of electronics have been shown to be associated with different health risks, but few studies have considered the impact of multiple types of electronic devices on health status. In addition, many studies have used only one type of indicator to measure health, such as physical activity, which may be problematic, as studies using various indicators of physical and mental health and functioning have shown different associations with electronics use (Cao et al 2022 ). Therefore, this study incorporated a more comprehensive set of electronic device use, including TV watching, computer use, computer gaming, and mobile phone use, and selected the following three health status indicators that are closely related to the quality of life of older adults.…”

Section: Introductionmentioning

confidence: 99%

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Association between electronic device use and health status among a middle-aged and elderly population: a cross-sectional analysis in the UK Biobank

Wei

Liu

Cheng

et al. 2023

J Public Health (Berl.)

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Aim Few previous studies have investigated the impact of multiple types of electronic devices on health status, and the moderating effects of gender, age, and BMI. Our aim is to examine the relationships between the use of four types of electronics and three health status indicators in a middle-aged and elderly population, and how these relationships varied by gender, age, and BMI. Subject and methods Using data from 376,806 participants aged 40–69 years in the UK Biobank, we conducted a multivariate linear regression to estimate the association between electronic device use and health status. Electronics use was categorized as TV watching, computer use, computer gaming, and mobile phone use, and health status included self-rated health (SRH), multisite chronic pain (MCP), and total physical activity (TPA). Interaction terms were utilized to assess whether the above associations were modified by BMI, gender, and age. Further stratified analysis was performed to explore the role of gender, age, and BMI. Results Higher levels of TV watching (B SRH = 0.056, B MCP = 0.044, B TPA = −1.795), computer use (B SRH = 0.007, B TPA = −3.469), and computer gaming (B SRH = 0.055, B MCP = 0.058, B TPA = −6.076) were consistently associated with poorer health status (all P < 0.05). Contrastingly, earlier exposure to mobile phones (B SRH = −0.048, B TPA = 0.933, B MCP = 0.056) was inconsistent with health (all P < 0.05). Additionally, BMI (B computer use-SRH = 0.0026, B phone-SRH = 0.0049, B TV-MCP = 0.0031, and B TV-TPA = −0.0584) exacerbated the negative effects of electronics use, and male (B phone-SRH = −0.0414, B phone-MCP = −0.0537, B phone-TPA = 2.8873) were healthier with earlier exposure to mobile phones (all P < 0.05). Conclusion Our findings suggest that the adverse health effects associated with watching TV, computer use, and computer gaming were consistent and were moderated by BMI, gender, and age, which advances a comprehensive understanding of the association between multiple types of electronic devices and health status, and provides new perspectives for future research. Supplementary Information The online version contains supplementary material available at 10.1007/s10389-023-01886-5.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Association between electronic device use and health status among a middle-aged and elderly population: a cross-sectional analysis in the UK Biobank

Wei

Liu

Cheng

et al. 2023

J Public Health (Berl.)

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“…In this analysis, education was categorized by using survey questions as educational level: illiteracy, primary school, junior high school, and more than high school. Physical activity was based on Chinese adults divided into three levels [22]: light, moderate and heavy. Marital status was classi ed as single, married and others, including divorced and widowed, by self-report of respondents.…”

Section: Assessments Of Covariatesmentioning

confidence: 99%

Association between macronutrient intake and liver dysfunction among tuberculosis patients in rural China

Liangjie

et al. 2023

Preprint

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Background Macronutrients play a vital role in liver dysfunction and affect the treatment and prognosis of tuberculosis. This study aimed to clarify the associations between macronutrients intakes or to energy percentages and liver dysfunction in tuberculosis patients. Methods In this cross-sectional study, 2695 active tuberculosis patients aged ≥ 18 years were included based on the data from local tuberculosis clinics in Linyi rural areas, China. Macronutrients intakes and to energy percentages were assessed by the 24-hour dietary recalls. The concentration of alanine transferase (ALT) or aspartate transaminase (AST) greater than 40 U/L was defined liver dysfunction. In addition, restricted cubic spline (RCS) was applied to determine the dose-response relationships. Results Among those who were male, or normal BMI, or consumed energy less than 1646.80 kcal/d, it was suggested both inverse associations between protein (47.30–78.80 g/d) or fat (> 20.30 g/d) intake and the risks of liver dysfunction in all models (all P-trend < 0.05). Moreover, the RCS model showed J-shaped associations between protein, fat intake, the fat or carbohydrate to energy percentages and the odds of liver dysfunction (the cut-off values = 70.69 g/d, 47.50 g/d, 22% and 69%, respectively, and all P-nonlinearity < 0.05). Conclusions An appropriate increase in dietary intakes of protein or fat might reduce liver dysfunction risk. However, intakes of more than 70.69 g/d for protein or 47.50 g/d for fat could increase the risk of liver dysfunction. Our study may provide a novel idea of alleviating liver dysfunction with nutritional improvement.

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“…In this study, we focused on a prede ned list of 76 common ICD-10 disease chapters and diagnostic groups constructed for outcome-wide studies based on a large number of literature searches and common chronic diseases [14,15](Supplemental Table 1). The primary study exposure was prediabetes vs. normoglycemia, and 76 types of common clinical conditions and prediabetes-related multimorbidity as outcomes.…”

Section: De Nitions and Outcomesmentioning

confidence: 99%

Association of Prediabetes with the Risks of Adverse Health Outcomes and Complex Multimorbidity: An Observational Study

Fan

Zhang

et al. 2022

SSRN Journal

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Associations of sedentary time and physical activity with adverse health conditions: Outcome-wide analyses using isotemporal substitution model

Cited by 63 publications

References 49 publications

Association between electronic device use and health status among a middle-aged and elderly population: a cross-sectional analysis in the UK Biobank

Association between electronic device use and health status among a middle-aged and elderly population: a cross-sectional analysis in the UK Biobank

Association between macronutrient intake and liver dysfunction among tuberculosis patients in rural China

Association of Prediabetes with the Risks of Adverse Health Outcomes and Complex Multimorbidity: An Observational Study

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