Construction and evaluation of a practical model for measuring health-adjusted life expectancy (HALE) in China.

BACKGROUND: HALE is now a regular strategic planning indicator for all levels of the Chinese government. However, HALE measurements necessitate comprehensive data collection and intricate technology. Therefore, effectively converting numerous diseases into the years lived with disability (YLD) rate is a significant challenge for HALE measurements. Our study aimed to construct a simple YLD rate measurement model with high applicability based on the current situation of actual data resources within China to address challenges in measuring HALE target values during planning. METHODS: First, based on the Chinese YLD rate in the Global Burden of Disease (GBD) 2019, Pearson correlation analysis, the global optimum method, etc., was utilized to screen the best predictor variables from the current Chinese data resources. Missing data for predictor variables were filled in via spline interpolation. Then, multiple linear regression models were fitted to construct the YLD rate measurement model. The Sullivan method was used to measure HALE. The Monte Carlo method was employed to generate 95% uncertainty intervals. Finally, model performances were assessed using the mean absolute error (MAE) and mean absolute percentage error (MAPE). RESULTS: A three-input-parameter model was constructed to measure the age-specific YLD rates by sex in China, directly using the incidence of infectious diseases, the incidence of chronic diseases among persons aged 15 and older, and the addition of an under-five mortality rate covariate. The total MAE and MAPE for the combined YLD rate were 0.0007 and 0.5949%, respectively. The MAE and MAPE of the combined HALE in the 0-year-old group were 0.0341 and 0.0526%, respectively. There were slightly fewer males (0.0197, 0.0311%) than females (0.0501, 0.0755%). CONCLUSION: We constructed a high-accuracy model to measure the YLD rate in China by using three monitoring indicators from the Chinese national routine as predictor variables. The model provides a realistic and feasible solution for measuring HALE at the national and especially regional levels, considering limited data.

Influence of room temperature on magnesium isotope measurements by multi-collector inductively coupled plasma mass spectrometry.

RATIONALE: We observed that the accuracy and precision of magnesium (Mg) isotope analyses could be affected if the room temperature oscillated during measurements. To achieve high-quality Mg isotopic data, it is critical to evaluate how the unstable room temperature affects Mg isotope measurements by multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). METHODS: We measured the Mg isotopes for the reference material DSM-3 using MC-ICP-MS under oscillating room temperatures in spring. For a comparison, we also measured the Mg isotopes under stable room temperatures, which were achieved by the installation of an improved temperature control system in the laboratory. RESULTS: The δ26 Mg values measured under oscillating room temperatures have a larger deviation (δ26 Mg from -0.09 to 0.08‰, with average δ26 Mg = 0.00 ± 0.08‰) than those measured under a stable room temperature (δ26 Mg from -0.03 to 0.03‰, with average δ26 Mg = 0.00 ± 0.02‰) using the same MC-ICP-MS system. CONCLUSIONS: The room temperature variation can influence the stability of MC-ICP-MS. Therefore, it is critical to keep the room temperature stable to acquire high-precision and accurate isotopic data when using MC-ICP-MS, especially when using the sample-standard bracketing (SSB) correction method.