Effect of Social Media on Child Obesity: Application of Structural Equation Modeling with the Taguchi Method

Khajeheian, Datis; Colabi, Amir Mohammad; Shah, Nordiana Binti Ahmad Kharman; Radzi, Che Wan Jasimah Wan Mohamed; Jenatabadi, Hashem Salarzadeh

doi:10.3390/ijerph15071343

Cited by 31 publications

(39 citation statements)

References 71 publications

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“…Besides, daily screen time (e.g., TV, smartphone, tablet, etc.) was added to measure the lifestyle of the respondents in terms of social media, which corresponded to Khajeheian et al’s research [ 45 ]. Regarding the average working hours per day, the responses consisted of five categories denoted by “none”, “less than 7 hours”, “7 to 8 hours”, “8 to 9 hours” and “more than 9 hours”.…”

Section: Methodsmentioning

confidence: 99%

Postpartum depression symptoms in survey-based research: a structural equation analysis

2021

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Background Since the last decade, postpartum depression (PPD) has been recognized as a significant public health problem, and several factors have been linked to PPD. Mothers at risk are rarely undetected and underdiagnosed. Our study aims to determine the factors leading to symptoms of depression using Structural Equation Modeling (SEM) analysis. In this research, we introduced a new framework for postpartum depression modeling for women. Methods We structured the model of this research to take into consideration the Malaysian culture in particular. A total of 387 postpartum women have completed the questionnaire. The symptoms of postpartum depression were examined using the Edinburgh Postnatal Depression Scale (EPDS), and they act as a dependent variable in this research model. Results Four hundred fifty mothers were invited to participate in this research. 86% of the total distributed questionnaire received feedback. The majority of 79.6% of respondents were having depression symptoms. The highest coefficients of factor loading analysis obtained in every latent variable indicator were income (β = 0.77), screen time (β = 0.83), chips (β = 0.85), and anxiety (β = 0.88). Lifestyle, unhealthy food, and BMI variables were directly affected by the dependent variable. Based on the output, respondents with a high level of depression symptoms tended to consume more unhealthy food and had a high level of body mass indexes (BMI). The highest significant impact on depression level among postpartum women was unhealthy food consumption. Based on our model, the findings indicated that 76% of the variances stemmed from a variety of factors: socio-demographics, lifestyle, healthy food, unhealthy food, and BMI. The strength of the exogenous and endogenous variables in this research framework is strong. Conclusion The prevalence of postpartum women with depression symptoms in this study is considerably high. It is, therefore, imperative that postpartum women seek medical help to prevent postpartum depressive symptoms from worsening.

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Section: Methodsmentioning

confidence: 99%

Postpartum depression symptoms in survey-based research: a structural equation analysis

2021

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“…Datis Khajeheian et al 10 study illustrates that increased daily use of social media is independently associated with greater BMI levels for high school students. Griffiths and Page 11 mentioned that obesity has been related to victimization and social isolation.…”

Section: Association Of Physical Parameters (Body Mass Index and Waismentioning

confidence: 97%

Use of Social Media and its Effects in School Going Adolescents

Sahithi

Mane

Agarkhedkar

2020

IJoYAH

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To determine the use of social media and its effects on physical health in school going adolescents. Methods: We enrolled 412 students and questionnaire on social media usage was given to the students and physical parameters like BMI (Body Mass Index) and WHR (Waist Hip Ratio) was taken. Result: It was observed that 60.9%, 19.7% and 0.7% were having mild, moderate and severe addiction, respectively, while 18.7% students were having no addiction of social media. It was seen that there were 0.9% subjects are severe underweight in boys and 0.5% in girls. 0.4% boys and 2.1% girls were underweight. 61.3% subjects were normal in boys and 70.1% in girls. 24.4% subjects were overweight in boys and 20.9% in girls. 12.9% subjects were obese in boys and 6.4% in girls. The waist-hip ratio was observed to be increasing from 0.82±0.07 among students having no addiction to 0.83±0.08 in mild addiction students and 0.88±0.07 in moderate addiction students which is statistically significant. Conclusion: Majority of the students (60.9%) were having mild social media addiction. There was significant association observed in severity of addiction and waist-hip ratio, which might lead to obesity and other non-communicable diseases in later life.

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“…In the current study, one more element was added to the postpartum women's lifestyle, namely the average hours of screen time (e.g., TV, smartphone, tablet, etc.) to measure the respondents' social media use [67][68][69]. For measuring average screen time, we asked three questions.…”

Section: Lifestyle (First Mediator)mentioning

confidence: 99%

Associations of Body Mass Index with Demographics, Lifestyle, Food Intake, and Mental Health among Postpartum Women: A Structural Equation Approach

Jenatabadi

Radzi

Samsudin

2020

IJERPH

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As postpartum obesity is becoming a global public health challenge, there is a need to apply postpartum obesity modeling to determine the indicators of postpartum obesity using an appropriate statistical technique. This research comprised two phases, namely: i) development of a previously created postpartum obesity modeling; ii) construction of a statistical comparison model and introduction of a better estimator for the research framework. The research model displayed the associations and interactions between the variables that were analyzed using the Structural Equation Modeling (SEM) method to determine the body mass index (BMI) levels related to postpartum obesity. The most significant correlations obtained were between BMI and other substantial variables in the SEM analysis. The research framework included two categories of data related to postpartum women: living in urban and rural areas in Iran. The SEM output with the Bayesian estimator was 81.1%, with variations in the postpartum women’s BMI, which is related to their demographics, lifestyle, food intake, and mental health. Meanwhile, the variation based on SEM with partial least squares estimator was equal to 70.2%, and SEM with a maximum likelihood estimator was equal to 76.8%. On the other hand, the output of the root mean square error (RMSE), mean absolute error (MSE) and mean absolute percentage error (MPE) for the Bayesian estimator is lower than the maximum likelihood and partial least square estimators. Thus, the predicted values of the SEM with Bayesian estimator are closer to the observed value compared to maximum likelihood and partial least square. In conclusion, the higher values of R-square and lower values of MPE, RMSE, and MSE will produce better goodness of fit for SEM with Bayesian estimators.

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Effect of Social Media on Child Obesity: Application of Structural Equation Modeling with the Taguchi Method

Cited by 31 publications

References 71 publications

Postpartum depression symptoms in survey-based research: a structural equation analysis

Postpartum depression symptoms in survey-based research: a structural equation analysis

Use of Social Media and its Effects in School Going Adolescents

Associations of Body Mass Index with Demographics, Lifestyle, Food Intake, and Mental Health among Postpartum Women: A Structural Equation Approach

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