Non-housing assets and all-cause mortality in middle-aged and older Chinese adults: a National cohort study

Abstract Background Financial resources beyond housing may influence survival in later life. Given China’s rapid population aging and high home ownership, focusing on non-housing assets can clarify wealth–health links. We therefore examined the association between total non-housing assets and all-cause mortality among Chinese middle-aged and older adults. Methods A nationwide cohort of 12,670 adults (aged 45–85) was established using the harmonized CHARLS dataset (2011–2018). All-cause mortality was ascertained through 2020 by supplementing harmonized data with vital status information from the raw CHARLS 2020 wave. The main exposure was total non-housing assets. In addition, non-housing assets were combined with household consumption (median split) to create four joint groups: Group 1 (low assets/low consumption), Group 2 (low assets/high consumption), Group 3 (high assets/low consumption), and Group 4 (high assets/high consumption). All-cause mortality was tracked. Baseline characteristics and mortality were presented by asset quartile and asset consumption group. Survival curves, Cox models (adjusted for confounders), and restricted cubic splines assessed associations. Subgroup and interaction analyses, especially for marital status, were visualized using forest and stratified plots. Results During a 9-year follow-up, 2,418 deaths occurred. Higher total non-housing assets were associated with lower mortality: Q4 (highest) vs. Q1 (lowest), adjusted HR = 0.79 (95% CI 0.68–0.91). In fully adjusted models, we also observed a graded inverse association across asset–consumption groups (P for trend < 0.001); high-consumption categories remained protective (Group 2: HR = 0.85, 95% CI 0.74–0.97; Group 4: HR = 0.75, 95% CI 0.65–0.85). Marital status showed a significant interaction with asset level (P‑interaction < 0.001). Conclusions Greater non-housing assets was associated with lower mortality. Marital status has a significant interacting effect on this association. Focus should be on vulnerable elderly groups with middle-low assets, low consumption, or those who are non-married.