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Xu X, Liu D, Rao Y, Zeng H, Zhang F, Wang L, Xie Y, Sharma M, Zhao Y. Prolonged Screen Viewing Times and Sociodemographic Factors among Pregnant Women: A Cross-Sectional Survey in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15030403. [PMID: 29495439 PMCID: PMC5876948 DOI: 10.3390/ijerph15030403] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Revised: 02/10/2018] [Accepted: 02/19/2018] [Indexed: 11/28/2022]
Abstract
Objectives: This study aimed to assess the prevalence of prolonged television, computer, and mobile phone viewing times and examined related sociodemographic factors among Chinese pregnant women. Methods: In this study, a cross-sectional survey was implemented among 2400 Chinese pregnant women in 16 hospitals of 5 provinces from June to August in 2015, and the response rate of 97.76%. We excluded women with serious complications and cognitive disorders. The women were asked about their television, computer, and mobile phone viewing during pregnancy. Prolonged television watching or computer viewing was defined as spending more than two hours on television or computer viewing per day. Prolonged mobile phone viewing was watching more than one hour on mobile phone per day. Results: Among 2345 pregnant women, about 25.1% reported prolonged television viewing, 20.6% reported prolonged computer viewing, and 62.6% reported prolonged mobile phone viewing. Pregnant women with long mobile phone viewing times were likely have long TV (Estimate = 0.080, Standard Error (SE) = 0.016, p < 0.001) and computer viewing times (Estimate = 0.053, SE = 0.022, p = 0.015). Pregnant women with long TV (Estimate = 0.134, SE = 0.027, p < 0.001) and long computer viewing times (Estimate = 0.049, SE = 0.020, p = 0.015) were likely have long mobile phone viewing times. Pregnant women with long TV viewing times were less likely to have long computer viewing times (Estimate = -0.032, SE = 0.015, p = 0.035), and pregnant women with long computer viewing times were less likely have long TV viewing times (Estimate = -0.059, SE = 0.028, p = 0.035). Pregnant women in their second pregnancy had lower prolonged computer viewing times than those in their first pregnancy (Odds Ratio (OR) 0.56, 95% Confidence Interval (CI) 0.42-0.74). Pregnant women in their second pregnancy were more likely have longer prolonged mobile phone viewing times than those in their first pregnancy (OR 1.25, 95% CI 1.01-1.55). Conclusions: The high prevalence rate of prolonged TV, computer, and mobile phone viewing times was common for pregnant women in their first and second pregnancy. This study preliminarily explored the relationship between sociodemographic factors and prolonged screen time to provide some indication for future interventions related to decreasing screen-viewing times during pregnancy in China.
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Affiliation(s)
- Xianglong Xu
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China.
- Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China.
- Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing 400016, China.
| | - Dengyuan Liu
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China.
- Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China.
- Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing 400016, China.
| | - Yunshuang Rao
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China.
- Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China.
- Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing 400016, China.
| | - Huan Zeng
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China.
- Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China.
- Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing 400016, China.
| | - Fan Zhang
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China.
- Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China.
- Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing 400016, China.
| | - Lu Wang
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China.
- Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China.
- Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing 400016, China.
| | - Yaojie Xie
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong 999077, China.
| | - Manoj Sharma
- Department of Behavioral and Environmental Health, Jackson State University, Jackson, MS 39213, USA.
| | - Yong Zhao
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China.
- Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China.
- Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing 400016, China.
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