Population health metrics · 2025
The assimilation affects research from three days' social facilitation of eating by using whole network autocorrelation analysis plus multilevel linear modeling: a normative analysis based on prospective cohort study data in the UK.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Wu Qiaohui, Wu Linjian, Liang Xueqing, Zhang Yihan, Chen Yingmeng, Ma Zhen
Аннотация
OBJECTIVE: This study aimed to evaluate the influence of social facilitation of eating on dietary assimilation effects using a multi-method approach integrating whole-network autocorrelation analysis (WNA) and multilevel linear modeling (MLM).
METHODS: We analyzed data from 26 participants (13 friend pairs) comprising 468 observations across multiple social and solitary eating contexts. The study combined WNA of 70 dietary similarity matrices with multilevel modeling to examine both systemic behavioral patterns and individual-level effects. MLM specifically assessed hierarchical data structure and fixed effects of social context and meal type.
RESULTS: Our analyses revealed that 31.1% of variance in eating behaviors originated from individual and dyad levels (ICC = 0.311), confirming the necessity of multilevel approaches. Network analysis identified"Friendship_close," "Friendship_howWell," and"Menu_VigEx" as primary factors influencing dietary assimilation during social eating, with effects varying significantly across consecutive days and mealtimes. MLM results showed strong meal-type effects (P < 0.001) but non-significant main effects of social context alone (P = 0.266), suggesting that social influence operates through behavioral coordination mechanisms rather than mean-level consumption changes. Notably, dietary similarity networks exhibited instability in assimilation effects during solitary eating, while social contexts promoted consistent behavioral patterning.
CONCLUSIONS: Social facilitation of eating enhances dietary assimilation through behavioral coordination patterns that vary under specific temporal and contextual conditions. The complementary findings from network analysis and MLM indicate that social influence manifests primarily in synchronized eating patterns rather than overall consumption increases. Leveraging these coordinated behavioral patterns offers promising avenues for promoting healthy dietary norms through social contexts, potentially mitigating excess energy intake while fostering lifestyle norms conducive to physical and mental health. Future research should employ integrated methodological approaches to further elucidate these complex social dynamics.
METHODS: We analyzed data from 26 participants (13 friend pairs) comprising 468 observations across multiple social and solitary eating contexts. The study combined WNA of 70 dietary similarity matrices with multilevel modeling to examine both systemic behavioral patterns and individual-level effects. MLM specifically assessed hierarchical data structure and fixed effects of social context and meal type.
RESULTS: Our analyses revealed that 31.1% of variance in eating behaviors originated from individual and dyad levels (ICC = 0.311), confirming the necessity of multilevel approaches. Network analysis identified"Friendship_close," "Friendship_howWell," and"Menu_VigEx" as primary factors influencing dietary assimilation during social eating, with effects varying significantly across consecutive days and mealtimes. MLM results showed strong meal-type effects (P < 0.001) but non-significant main effects of social context alone (P = 0.266), suggesting that social influence operates through behavioral coordination mechanisms rather than mean-level consumption changes. Notably, dietary similarity networks exhibited instability in assimilation effects during solitary eating, while social contexts promoted consistent behavioral patterning.
CONCLUSIONS: Social facilitation of eating enhances dietary assimilation through behavioral coordination patterns that vary under specific temporal and contextual conditions. The complementary findings from network analysis and MLM indicate that social influence manifests primarily in synchronized eating patterns rather than overall consumption increases. Leveraging these coordinated behavioral patterns offers promising avenues for promoting healthy dietary norms through social contexts, potentially mitigating excess energy intake while fostering lifestyle norms conducive to physical and mental health. Future research should employ integrated methodological approaches to further elucidate these complex social dynamics.