|
 |
| BRIEF RESEARCH ARTICLE |
|
| Year : 2022 | Volume
: 66
| Issue : 3 | Page : 327-330 |
|
|
Excess Screen Time and its Associated Factors among Young Men in a Rural Community of North India
Sumit Malhotra1, Shashi Kant2, Ramashankar Rath3, Farhad Ahamed4, Ramadass Sathiyamoorthy5, Sanjeev Kumar Gupta6
1 Additional Professor, All India Institute of Medical Sciences, New Delhi, India
2 Professor and Head, All India Institute of Medical Sciences, New Delhi, India
3 Assistant Professor, Department of Community and Family Medicine, All India Institute of Medical Sciences, Gorakhpur, Uttar Pradesh, India
4 Assistant Professor, Department of Community and Family Medicine, All India Institute of Medical Sciences, Kalyani, West Bengal, India
5 Senior Resident, All India Institute of Medical Sciences, New Delhi, India
6 Professor, Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
| Date of Submission | 08-Nov-2021 |
| Date of Decision | 03-Jan-2022 |
| Date of Acceptance | 19-Feb-2022 |
| Date of Web Publication | 22-Sep-2022 |
Correspondence Address:
Sumit Malhotra
Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijph.ijph_2027_21
 Abstract | | |
Screen-based media usage among young people is blooming rapidly due to technological and digital revolution. We conducted community-based cross-sectional study to determine the prevalence of excess screen time and its association with sociodemographic and behavioral patterns in a rural block of Haryana, India. A semi-structured interview schedule was administered by trained physicians to ascertain screen time in a typical day and various socioeconomic and behavioral factors among a random sample of 860 young men aged 18–24 years. The prevalence of excess screen time was 61.8% (95% confidence interval [CI] 58.4–65.1). It was significantly associated with education (adjusted odds ratio [AOR] 1.7, 95% CI 1.1–2.6) and occupation (AOR 2.2, 95% CI 1.2–3.9) of the father and their sleep duration of ≤8 h (AOR 1.6, 95% CI 1.2–2.3). Limiting the screen time as per international standards and behavioral interventions are needed for this young population.
Keywords: Excess screen time, rural, young men
How to cite this article:
Malhotra S, Kant S, Rath R, Ahamed F, Sathiyamoorthy R, Gupta SK. Excess Screen Time and its Associated Factors among Young Men in a Rural Community of North India. Indian J Public Health 2022;66:327-30 |
How to cite this URL:
Malhotra S, Kant S, Rath R, Ahamed F, Sathiyamoorthy R, Gupta SK. Excess Screen Time and its Associated Factors among Young Men in a Rural Community of North India. Indian J Public Health [serial online] 2022 [cited 2023 Mar 26];66:327-30. Available from: https://www.ijph.in/text.asp?2022/66/3/327/356597 |
Screen-based electronic media usage is ubiquitous among every individual in this 21st century of the technological and digital revolution. Screen time is the time spent in sedentary behavior involving screen-based media such as watching television, working or gaming/surfing in laptops or computers, etc.[1] Excess screen time leads to increase in sedentary behavior and risk of various health-related morbidity and mortality.[2] Screen-based electronic media forms an important part of the young population in both developed and developing countries. Their time spent in using these screen-based media has increased substantially due to the advent of Internet revolution and social media platforms.
The American Academy of Pediatrics recommends a screen time of not more than 2 h per day for all groups above 2 years.[3] There are no specific guidelines to limit screen time among the youth population in India. Screen-based media usage is increasing in both urban and rural areas of India. In rural districts of India, almost 95% of households have television viewing sets which are their major part of leisure activities. Usage of these screen-based media can differ by various sociodemographic age, sex, marital status, occupation, and education of the parents. They also differ by the behavioral patterns such as consumption of carbonated drinks, fast food, and sleep patterns. We aimed to study the prevalence of excess screen time and its association with sociodemographic and behavioral patterns among young men aged 18–24 years in the rural population of India.
This community-based cross-sectional study was conducted in the rural area of Ballabgarh block, Faridabad district, Haryana, India. The study area is an Intensive Field Practice Area with the Health and Demographic Surveillance System recording the vital events and health status of every individual using a computerized Health Management Information System.[4] The sampling frame consisted of young men in the age group of 18–24 years residing in the study area, and data were collected from November 2017, to January 2018.
Sample size was calculated considering the prevalence of screen time more than 120 min in young men aged 18 years and above as 57.9%.[5] Considering a relative precision of 6%, level of significance of 5%, power of 80%, and a nonresponse of 10%, the final sample size was 860 young men aged 18–24 years.
A simple random sample of 860 young men aged 18–24 years was generated from the sampling frame. Household visits were made to contact all the selected individuals. If the participant was not available in the first visit, their mobile phone numbers were collected. After contacting them over phone for their availability, a second house visit was conducted. A maximum of two household visits were made before declaring the participant as noncontactable.
A pretested semi-structured interview schedule was administered by trained physicians to collect information regarding sociodemographic details (age, years of schooling, marital status, education, and occupation of parents) and behavioral patterns (physical activity, consumption of carbonated drink and fast food, sleep duration, and screen time). Illiteracy was defined as an individual who was unable to read and write any single language. Physical activity was captured in minutes of moderate-intensity activity during daily routine and work-related activities. Screen time was captured in minutes spent during a typical day in watching television, using the computer, smartphones, or any other screen-based electronic devices. Ethical clearance was obtained from the Institute Ethics Committee of the All India Institute of Medical Sciences, New Delhi (IEC/91/2017). Written informed consent was obtained from the study participants.
Data were entered in Microsoft Excel 2013 and analyzed using STATA software version 12.0 (StataCorp LP, College Station, Texas, USA). Categorical variables and continuous variables were expressed as number (percentage) and mean ± standard deviation (SD), respectively. The prevalence (95% confidence intervals [CIs]) estimates for the screen time more than 120 min were reported. The independent variables considered were age, years of education, marital status, education and occupation of the mother and father, consumption of carbonated drinks and fast food, sleep duration per day, and the dependent variable was screen time. The association between independent and dependent variables was modeled using bivariable and step-wise multivariable logistic regression. Variables with P < 0.25 were entered in the final multivariable logistic regression. P < 0.05 was considered statistically significant. Crude and adjusted odds ratios are reported along with 95% CI.
Of the 860 randomly selected young men aged 18–24 years, 834 participated in the study. The response rate was 97% and 26 individuals were noncontactable. The young men included in the study had a mean (SD) age of 20.6 (1.9) years and their mean (SD) years of education was 11.8 (2.8). 720 (86.4%) young men were unmarried. Mother and father were literate for 431 (51.7%) and 699 (86.0%) young men, respectively [Table 1]. Mothers of the 745 (89.3%) participants were homemakers and 756 (93.0%) participants' fathers were currently employed. Physical activity of 150 min and above per week was performed by 630 (75.6%) young men. Consumption of carbonated drinks and fast food at least once in a typical week was carried out by 495 (59.3%) and 576 (69.1%) young men, respectively. For 24 (2.9%) young men, either one of their parents was not alive at the time of the study. | Table 1: Sociodemographic profile and behavioral pattern of young men aged 18-24 years (n=834)*
Click here to view |
The prevalence of screen time of 120 min and above among young men 18–24 years was 61.8% (95% CI 58.4–65.1). The median (interquartile range [IQR]) screen time of watching television was 90 (60–120) minutes per day. The median (IQR) screen time of using smartphones was 120 (60–210) minutes per day and median (IQR) screen time of using laptops or computers for various activities such as work, gaming, leisure, etc., was 120 (60–180) minutes per day. Other electronic devices with screens were used for a median (IQR) screen time of 120 (90–300) minutes per day.
In the bivariable model, logistic regression of screen time with the independent variables was found significantly associated with education of the mother, education and occupation of the father, consumption of carbonated drinks, and sleep duration ≤8 h/day [Table 2]. In the multivariable model, education (AOR 1.7, 95% CI 1.1–2.6) and occupation (AOR 2.2, 95% CI 1.2–3.9) of the father were significantly associated with screen time of 120 min and above per day. Participants not consuming carbonated drinks at least once in a typical week had 1.5 times increased risk of having an unhealthy screen time (AOR 1.5, 95% CI 1.1–20). Participants sleeping ≤8 h had 1.6 times increased risk of screen time of 120 min and above (AOR 1.6, 95% CI 1.2–2.3). | Table 2: Crude and multivariable logistic regression models of factors associated with screen time
Click here to view |
The study observed that 61.8% of young men aged 18–24 years had a screen time of 2 h and above. Montagni et al. on studying the association of screen time and headaches in young adults found that the prevalence of excess screen time was 58% among young men aged 18 years and above.[5] Sousa and Silva, in their study to estimate the prevalence of excess screen time found that 91% of young men aged 17–19 years exceeded the screen time recommendations of 2 h/day.[6] Youth Risk Behavior Surveillance in the United States, in 2017, found that 21% of young men in 12th grade exceeded the screen time of 3 h/day. Excess screen time prevalence in our study was higher than the Youth Risk Behavior Surveillance because of the cutoff used.[7]
Screen time was higher among young men if their father was literate and currently employed. A systemic review of adult sedentary behavior and its association with various socioeconomic and behavioral factors by Rhodes et al. found that the majority of the studies did not find any association with educational status.[8] Furthermore, some studies in this review found a positive association with employment status and most found a negative association with excess screen time. Young men sleeping <8 h had higher screen time in our study. Similar findings were observed in a study by Hale et al.[9] Eating habits such as consumption of carbonated drinks and fast food were associated with excess screen time and increased risk of cardiovascular events.[10]
Our study had several strengths. First, this was a community-based study conducted in a rural population of India. Second, our study had a high response rate, and lastly, various screen-based electronic device usages were captured in the study. Limitations included elicitation of screen time through self-reports. Thus, the probability of recall bias could not be ruled out. To limit this bias, a typical day in the past week was chosen for the interview. Due to the cross-sectional nature of the study, temporality of the association could not be ascertained.
Screen time was higher among young men aged 18–24 years in a rural community of north India. Excess screen time was significantly associated with occupation and education of the father and sleep duration <8 h. Appropriate behavioral interventions may reduce the screen time duration and its associated risk of health-related morbidity and mortality.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | |  |
| 1. | Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, et al. Sedentary Behavior Research Network (SBRN) – Terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act 2017;14:75.  |
| 2. | Thorp AA, Owen N, Neuhaus M, Dunstan DW. Sedentary behaviors and subsequent health outcomes in adults a systematic review of longitudinal studies, 1996-2011. Am J Prev Med 2011;41:207-15. |
| 3. | American Academy of Pediatrics Committee on Public Education. American academy of pediatrics: Children, adolescents, and television. Pediatrics 2001;107:423-6. |
| 4. | Kant S, Misra P, Gupta S, Goswami K, Krishnan A, Nongkynrih B, et al. The Ballabgarh Health and Demographic Surveillance System (CRHSP-AIIMS). Int J Epidemiol 2013;42:758-68. |
| 5. | Montagni I, Guichard E, Carpenet C, Tzourio C, Kurth T. Screen time exposure and reporting of headaches in young adults: A cross-sectional study. Cephalalgia 2016;36:1020-7. |
| 6. | Sousa GR, Silva DA. Sedentary behavior based on screen time: Prevalence and associated sociodemographic factors in adolescents. Cien Saude Colet 2017;22:4061-72. |
| 7. | Kann L, McManus T, Harris WA, Shanklin SL, Flint KH, Queen B, et al. Youth risk behavior surveillance – United States, 2017. MMWR Surveill Summ 2018;67:1-114. |
| 8. | Rhodes RE, Mark RS, Temmel CP. Adult sedentary behavior: A systematic review. Am J Prev Med 2012;42:e3-28. |
| 9. | Hale L, Kirschen GW, LeBourgeois MK, Gradisar M, Garrison MM, Montgomery-Downs H, et al. Youth screen media habits and sleep: Sleep-friendly screen behavior recommendations for clinicians, educators, and parents. Child Adolesc Psychiatr Clin N Am 2018;27:229-45. |
| 10. | Hobbs M, Pearson N, Foster PJ, Biddle SJ. Sedentary behaviour and diet across the lifespan: An updated systematic review. Br J Sports Med 2015;49:1179-88. |
[Table 1], [Table 2]
|
