Nonlinear association of alkaline phosphatase-to-albumin ratio with all-cause and cancer mortality: Evidence from NHANES 2005 to 2016

The relationship between the alkaline phosphatase-to-albumin ratio (APAR) and mortality remains unclear. This research looked into the association between APAR levels and cause-specific mortality in US adults. A cohort of 7561 participants from National Health and Nutrition Examination Survey (2005–2016) was analyzed, with mortality outcomes collected from National Death Index records. Cox proportional hazards models and restricted cubic spline (RCS) analysis were utilized to determine hazard ratio (HR) and reveal the nonlinear relationship between APAR levels and mortality. Inflection points were calculated using a recursive algorithm. Followed for an average 99.41 months, a total of 1048 deaths occurred, including 200 cancer deaths and 348 cardiovascular disease-related deaths. Following multivariate adjustment, significant associations were observed between APAR levels and increased all-cause (HR 1.50, 95% CI 1.28–1.75, P < .001) and cardiovascular disease (HR 1.39, 95% CI 1.06–1.82, P = .018) mortality. Furthermore, nonlinear correlations between APAR levels and all-cause and cancer mortality were revealed, characterized by an L-shaped pattern, with mortality rates stabilizing at 1.289 and 2.167, respectively. Participants with APAR levels above the inflection point exhibited a 29.2% increase in all-cause mortality risk per unit increase in APAR levels (HR 1.292, 95% CI 1.217–1.372, P < .001), and a 38.3% increase in cancer mortality risk (HR 1.383, 95% CI 1.199–1.596, P < .001). This study demonstrated nonlinear associations between APAR levels and all-cause and cancer mortality. Thresholds of 1.289 and 2.167 might serve as potential targets for APAR to reduce all-cause and cancer mortality, respectively. Our findings suggest that APAR can be a valuable prognostic tool for clinical mortality risk assessments, helping to identify individuals at higher risk. Nevertheless, these findings necessitate validation through large-scale clinical trials for further substantiation.