A cross-sectional descriptive analysis of technology addiction in adolescents: associations with food addiction, emotional eating, and body weight status

Table 2 Multivariable logistic regression analysis assessing the risk factors of digital games and social media addiction

Risk estimates (Addicted/Non-addicted)	β	Wald	p^*	Odds Ratio	95% Confidence Interval
Risk estimates (Addicted/Non-addicted)	β	Wald	p^*	Odds Ratio	Lower	Upper
Game Addiction Scale^a
Age (years)	0.194	7.723	0.005	1.214	1.059	1.392
Sex (boy)	1.428	75.045	< 0.001	4.171	3.019	5.761
Body mass index Z-score	0.173	8.485	0.004	1.189	1.058	1.335
Mother’s age (years)	−0.033	2.214	0.137	0.968	0.926	1.011
Father’s age (years)	0.035	2.816	0.093	1.036	0.994	1.079
Mother's job (housewife)	−0.201	1.452	0.228	0.818	0.589	1.134
Father's job		4.458	0.108
Self-employment	−0.631	3.255	0.071	0.532	0.268	1.056
Officer/worker	−0.399	1.176	0.278	0.671	0.327	1.380
Income status		1.418	0.492
Low	0.308	0.774	0.379	1.360	0.685	2.701
High	0.180	0.768	0.381	1.197	0.801	1.788
Social Media Disorder Scale^a
Age (years)	0.383	7.889	0.005	1.467	1.123	1.917
Body mass index Z-score	0.271	7.430	0.006	1.312	1.079	1.594
Father’s age (years)	−0.039	2.617	0.106	0.962	0.917	1.008
Father's job		4.114	0.128
Self-employment	−0.848	2.598	0.107	0.428	0.153	1.201
Officer/worker	−0.432	0.609	0.435	0.649	0.220	1.921
Income status		1.584	0.453
Low	−1.237	1.316	0.251	0.290	0.035	2.404
High	0.148	0.210	0.646	1.159	0.617	2.179

^*p-trend < 0.001; Nagelkerke R² = 14.4% (n = 1318) and 6.9% (n = 457) for Game Addiction Scale and Social Media Disorder Scale, respectively
^aReference categories are “girl” for sex, “employed” for mother's job, “retired” for father's job, and “moderate” for income status

ISSN: 2072-1315