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Frequency of watching television, owning a mobile phone and risk of being overweight/obese among reproductive-aged women in low- and lower-middle-income countries: A pooled analysis from Demographic and Health Survey data

Published online by Cambridge University Press:  16 May 2022

Benojir Ahammed*
Affiliation:
Statistics Discipline, Khulna University, Khulna-9208, Bangladesh
Rezwanul Haque
Affiliation:
School of Business, University of Southern Queensland, Toowoomba, QLD 4350, Australia
Syed Mahbubur Rahman
Affiliation:
BRAC Business School, BRAC University, Dhaka 1212, Bangladesh
Syed Afroz Keramat
Affiliation:
Economics Discipline, Khulna University, Khulna-9208, Bangladesh
Afrin Mahbub
Affiliation:
Department of Economics, American International University-Bangladesh
Farzana Ferdausi
Affiliation:
Ministry of Health and Family Welfare (MOHFW), Bangladesh
Khorshed Alam
Affiliation:
School of Business, University of Southern Queensland, Toowoomba, QLD 4350, Australia Centre for Health Research, University of Southern Queensland, Toowoomba, QLD 4350, Australia
*
*Corresponding author. Email: benojirstat@ku.ac.bd

Abstract

People who are overweight and obese suffer from significant health impacts that have increased globally. Concurrently, usage of information and communication devices such as television and mobile phones have also been growing, affecting people’s weight. This study examined the association between watching television and owning a mobile phone with overweight and obesity among reproductive-aged women in low- and lower-middle-income countries (LLMICs). Data of 21 LLMICs reported between 2015 and 2020 were collected from the Demographic and Health Surveys. Multivariate logistic regression was performed to determine the association into three pooled segments: a group of 21 countries, the World Bank income classification and the regional categorisation of the countries. The all-inclusive prevalence of overweight or obesity was found at 27.1% among 175,370 reproductive-aged women, and this prevalence varied among countries. Overall, the odds of being overweight or obese were 1.20 (adjusted odds ratio [AOR]=1.20, 95% confidence interval [CI]: 1.15–1.24), 1.40 (AOR=1.40, 95% CI: 1.35–1.44) and 1.18 (AOR=1.18, 95% CI: 1.03–1.35) times higher among those who watched television less than once a week, at least once a week and almost every day, respectively, compared with those who did not watch television. Besides, women’s mobile phone ownership is more likely to experience overweight or obesity (AOR=1.72, 95% CI: 1.67–1.77). Consistent results were found for the countries categorised according to the World Bank income and regional classification. Focus on sedentary behaviour, such as television watching and mobile phone use, of women and regional or country-specific innovative strategies and programs are of great immediate importance to decrease the prevalence of overweight and obesity.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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References

Banaji, S, Livingstone, S, Nandi, A, & Stoilova, M (2018). Instrumentalising the digital: adolescents’ engagement with ICTs in low-and middle-income countries. Development in Practice, 28(3), 432443.CrossRefGoogle Scholar
Bhurosy, T, & Jeewon, R (2014). Overweight and obesity epidemic in developing countries: a problem with diet, physical activity, or socioeconomic status? The Scientific World Journal, 2014.Google Scholar
Carter, B, Rees, P, Hale, L, Bhattacharjee, D & Paradkar, MS (2016). Association between portable screen-based media device access or use and sleep outcomes: a systematic review and meta-analysis. JAMA pediatrics, 170(12), 12021208.CrossRefGoogle ScholarPubMed
Chowdhury, MAB, Adnan, MM, & Hassan, MZ (2018). Trends, prevalence and risk factors of overweight and obesity among women of reproductive age in Bangladesh: a pooled analysis of five national cross-sectional surveys. BMJ open, 8(7), e018468.CrossRefGoogle ScholarPubMed
Chrisman, M, Chow, WH, Daniel, CR, Wu, X, & Zhao, H (2016). mobile Phone Use and its Association with Sitting Time and Meeting Physical Activity Recommendations in a Mexican American Cohort. JMIR mHealth and uHealth, 4(2), e4926.Google Scholar
Corsi, DJ, Neuman, M, Finlay, JE, & Subramanian, SV (2012). Demographic and health surveys: a profile. International journal of epidemiology, 41(6), 16021613.CrossRefGoogle ScholarPubMed
Das Gupta, R, Haider, SS, Sutradhar, I, Hashan, MR, Sajal, IH, Hasan, M, Haider, MR, & Sarker, M (2019). Association of frequency of television watching with overweight and obesity among women of reproductive age in India: Evidence from a nationally representative study. PloS one, 14(8), e0221758.CrossRefGoogle ScholarPubMed
Dube, N, Khan, K, Loehr, S, Chu, Y, & Veugelers, P (2017). The use of entertainment and communication technologies before sleep could affect sleep and weight status: a population-based study among children. International Journal of Behavioral Nutrition and Physical Activity, 14(1), 115.CrossRefGoogle ScholarPubMed
Felső, R, Lohner, S, Hollódy, K, Erhardt, É, & Molnár, D (2017). Relationship between sleep duration and childhood obesity: systematic review including the potential underlying mechanisms. Nutrition, Metabolism and Cardiovascular Diseases, 27(9), 751761.CrossRefGoogle ScholarPubMed
Ferdausi, F, Al-Zubayer, MA, Keramat, SA & Ahammed, B (2022). Prevalence and associated factors of underweight and overweight/obesity among reproductive-aged women: A pooled analysis of data from South Asian countries (Bangladesh, Maldives, Nepal and Pakistan). Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 16(3), p.102428.CrossRefGoogle ScholarPubMed
Fernandes, B, Uzun, B, Aydin, C, Tan-Mansukhani, R, Vallejo, A, Saldaña-Gutierrez, A, Biswas, UN, & Essau, CA (2021). Internet use during COVID-19 lockdown among young people in low-and middle-income countries: Role of psychological wellbeing. Addictive Behaviors Reports, 14, 100379.CrossRefGoogle ScholarPubMed
Fruh, SM (2017). Obesity: Risk factors, complications, and strategies for sustainable long-term weight management. Journal of the American Association of Nurse Practitioners, 29(S1), S3S14.CrossRefGoogle ScholarPubMed
Global Burden of Disease (GBD) 2015 Obesity Collaborators. (2017). Health effects of overweight and obesity in 195 countries over 25 years. New England Journal of Medicine, 377(1), 1327.CrossRefGoogle Scholar
Gortmaker, SL, Peterson, K, Wiecha, J, Sobol, AM, Dixit, S, Fox, MK, & Laird, N (1999). Reducing obesity via a school-based interdisciplinary intervention among youth: Planet Health. Archives of pediatrics & adolescent medicine, 153(4), 409418.CrossRefGoogle Scholar
Grøntved, A, & Hu, FB (2011). Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: a meta-analysis. Jama, 305(23), 24482455.CrossRefGoogle ScholarPubMed
Gupta, RD, Sajal, IH, Hasan, M, Sutradhar, I, Haider, MR, & Sarker, M (2019). Frequency of television viewing and association with overweight and obesity among women of the reproductive age group in Myanmar: results from a nationwide cross-sectional survey. BMJ open, 9(3), e024680.CrossRefGoogle ScholarPubMed
Hale, L & Guan, S (2015). Screen time and sleep among school-aged children and adolescents: a systematic literature review. Sleep medicine reviews, 21, 5058.CrossRefGoogle ScholarPubMed
Haque, R, Keramat, SA, Rahman, SM, Mustafa, MUR, & Alam, K (2021). Association of maternal obesity with fetal and neonatal death: Evidence from South and South-East Asian countries. PloS one, 16(9), e0256725. http://www.searo.who.int/nepal/mediacentre/non_communicable_diseases_risk_factors_steps_survey_nepal_2013.pdf (accessed 20th April 2018).CrossRefGoogle ScholarPubMed
Kanguru, L, McCaw-Binns, A, Bell, J, Yonger-Coleman, N, Wilks, R & Hussein, J (2017). The burden of obesity in women of reproductive age and in pregnancy in a middle-income setting: A population-based study from Jamaica. PLoS One, 12(12), e0188677.CrossRefGoogle Scholar
Kassie, AM, Abate, BB, & Kassaw, MW (2020). Education and prevalence of overweight and obesity among reproductive age group women in Ethiopia: analysis of the 2016 Ethiopian demographic and health survey data. BMC Public Health, 20(1), 111.Google Scholar
Kim, SY, England, L, Wilson, HG, Bish, C, Satten, GA, & Dietz, P (2010). Percentage of gestational diabetes mellitus attributable to overweight and obesity. American journal of public health, 100(6), 10471052.CrossRefGoogle ScholarPubMed
Lajunen, HR, Keski-Rahkonen, A, Pulkkinen, L, Rose, RJ, Rissanen, A, & Kaprio, J (2007). Are computer and cell phone use associated with body mass index and overweight? A population study among twin adolescents. BMC public health, 7(1), 18.CrossRefGoogle ScholarPubMed
LeBourgeois, MK, Hale, L, Chang, AM, Akacem, LD, Montgomery-Downs, HE, & Buxton, OM (2017). Digital media and sleep in childhood and adolescence. Pediatrics, 140(Supplement 2), S92S96.CrossRefGoogle ScholarPubMed
Lepp, A, Barkley, JE, & Karpinski, AC (2015). The relationship between cell phone use and academic performance in a sample of US college students. Sage Open, 5(1), 2158244015573169.CrossRefGoogle Scholar
Lepp, A, Barkley, JE, Sanders, GJ, Rebold, M, & Gates, P. (2013). The relationship between cell phone use, physical and sedentary activity, and cardiorespiratory fitness in a sample of US college students. International Journal of Behavioral Nutrition and physical activity, 10(1), 19.CrossRefGoogle Scholar
Li, L, Zhang, S, Huang, Y & Chen, K (2017). Sleep duration and obesity in children: a systematic review and meta-analysis of prospective cohort studies. Journal of paediatrics and child health, 53(4), 378385.CrossRefGoogle ScholarPubMed
Maher, C, Olds, TS, Eisenmann, JC, & Dollman, J (2012). Screen time is more strongly associated than physical activity with overweight and obesity in 9-to 16-year-old Australians. Acta Paediatrica, 101(11), 11701174.CrossRefGoogle ScholarPubMed
Ministry of Health and Population (MOHP), Nepal Health Research Council (NHRC) and World Health Organization (WHO) (2014) Non-Communicable Diseases Risk Factors: STEPS Survey. Nepal Health Research Council, Kathmandu Nepal.Google Scholar
Morgen, CS & Sørensen, TI (2014). Global trends in the prevalence of overweight and obesity. Nature Reviews Endocrinology, 10(9), 513514.CrossRefGoogle ScholarPubMed
National Heart, Lung, Blood Institute, National Institute of Diabetes, Digestive, & Kidney Diseases (US). (1998). Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report (No. 98). National Heart, Lung, and Blood Institute.Google Scholar
Ng, M, Fleming, T, Robinson, M, Thomson, B, Graetz, N, Margono, C, Mullany, EC, Biryukov, S, Abbafati, C, Abera, SF, & Gakidou, E (2014). Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. The lancet, 384(9945), 766781.CrossRefGoogle ScholarPubMed
Sharma, R, Biedenharn, KR, Fedor, JM, & Agarwal, A (2013). Lifestyle factors and reproductive health: taking control of your fertility. Reproductive biology and endocrinology, 11(1), 115.CrossRefGoogle ScholarPubMed
Strasburger, VC (2011). Children, adolescents, obesity, and the media. Pediatrics, 128(1), 201208.CrossRefGoogle ScholarPubMed
Subedi, YP, Marais, D and Newlands, D (2015) Where is Nepal in the nutrition transition? Asia Pacific Journal of Clinical Nutrition 26, 358367.Google Scholar
Sutradhar, I, Akter, T, Hasan, M, Gupta, RD, Joshi, H, Haider, MR, & Sarker, M (2021). Nationally representative surveys show gradual shifting of overweight and obesity towards poor and less-educated women of reproductive age in Nepal. Journal of biosocial science, 53(2), 214232.Google ScholarPubMed
Tennant, PWG, Rankin, J, & Bell, R (2011). Maternal body mass index and the risk of fetal and infant death: a cohort study from the North of England. Human reproduction, 26(6), 15011511.CrossRefGoogle ScholarPubMed
Tianyi, FL, Agbor, VN, & Njamnshi, AK (2018). Prevalence, awareness, treatment, and control of hypertension in Cameroonians aged 50 years and older: A community-based study. Health science reports, 1(5), e44.CrossRefGoogle Scholar
Trübswasser, U, Verstraeten, R, Salm, L, Holdsworth, M, Baye, K, Booth, A, Feskens, EJ, Gillespie, S, & Talsma, EF (2021). Factors influencing obesogenic behaviours of adolescent girls and women in low-and middle-income countries: A qualitative evidence synthesis. Obesity Reviews, 22(4), e13163.CrossRefGoogle ScholarPubMed
Tuoyire, DA (2018). Television exposure and overweight/obesity among women in Ghana. BMC obesity, 5(1), 110.CrossRefGoogle ScholarPubMed
Wada, K, Yamakawa, M, Konishi, K, Goto, Y, Mizuta, F, Koda, S, Uji, T, Tamura, T, Nakamura, K, Tsuji, M, & Nagai, H (2019). Associations of Cell Phone Use and Screen Viewing with Overweight in Children. Childhood Obesity, 15(7), 417425.CrossRefGoogle ScholarPubMed
Yang-Huang, J, van Grieken, A, Moll, HA, Jaddoe, VW, Wijtzes, AI, & Raat, H (2017). Socioeconomic differences in children’s television viewing trajectory: A population-based prospective cohort study. PLoS One, 12(12), e0188363.CrossRefGoogle ScholarPubMed
Yatsuya, H, Li, Y, Hilawe, EH, Ota, A, Wang, C, Chiang, C, Zhang, Y, Uemura, M, Osako, A, Ozaki, Y, & Aoyama, A (2014). Global trend in overweight and obesity and its association with cardiovascular disease incidence. Circulation Journal, CJ14.Google ScholarPubMed