Determinants of minimum dietary diversity attainment among infants aged 6–11 months in rural China: a COM-B model-based Bayesian network analysis

Abstract

Achieving minimum dietary diversity (MDD), a crucial indicator of infant and young child diet quality, remains a challenge in rural China, especially for infants aged 6–11 months. This study examined the rate of MDD attainment in rural China, identified its determinants using the Capability, Opportunity, Motivation, and Behavior (COM-B) model and Bayesian network analysis, and estimated the potential impact of improving each modifiable determinant. A multi-stage sampling design selected 1328 caregivers of infants aged 6–11 months across 77 rural townships in China. Data were collected through a cross-sectional survey via in-person household interviews. Bayesian network analysis identified key factors influencing MDD attainment and their interrelationships, while Bayesian inference estimated MDD attainment probabilities. Results showed that only 22.2 % of the sample infants attained MDD. Bayesian network analysis revealed that caregiver knowledge (a proxy of capability), self-efficacy and habits (proxies of motivation), and infant age directly influenced MDD attainment. Social support (a proxy of opportunity) indirectly promoted MDD attainment by boosting self-efficacy and habit. Notably, simultaneous improvements in knowledge, self-efficacy, and habit could increase MDD attainment by 17.6 %, underscoring the potential effectiveness of interventions focused on enhancing caregiver capability and motivation. The critically low MDD attainment rate among rural Chinese infants highlights the urgent need for targeted interventions. Strategies should prioritize enhancing caregiver feeding knowledge, self-efficacy, and habit formation to improve infant dietary diversity. Addressing these key factors could substantially boost MDD attainment in rural China.