The impact of pension on the health behavior of elderly rural residents: evidence from China.

BACKGROUND: Unhealthy behavior is an important factor threatening the health of older rural residents in China. We examine the effects of receiving pension on elderly rural residents' health behavior (namely conscious control of sugar, salt, and edible oil intake, as well as learning health or wellness knowledge), also including effect heterogeneity by income level and gender. METHODS: Using China Rural Revitalization Survey (CRRS) in 2020, we used the policy rule of the China's New Rural Pension Scheme that only those people who are over 60 years old can have access to pension as the natural experiment, and explore the causal effect of receiving pensions on the health behaviors by using regression discontinuity design method. RESULTS: Having access to pension can improve the health behavior of rural elderly residents, including increasing the probability of rural residents' conscious control of sugar (p < 0.1) and conscious control of salt intake (p < 0.1), which is still valid after a series of robustness tests. Heterogeneity analysis finds that access to pensions is more likely to improve the health behavior of low-income families and male rural elderly residents. CONCLUSIONS: The research has expanded the discussion on the correlation between the pension and the health of rural elderly residents, and the conclusion provides important policy implications for optimizing the rural elderly insurance system and leveraging pension to improve the health behavior of rural elderly residents.

An Aided Navigation Method Based on Strapdown Gravity Gradiometer.

The gravity gradient is the second derivative of gravity potential. A gravity gradiometer can measure the small change of gravity at two points, which contains more abundant navigation and positioning information than gravity. In order to solve the problem of passive autonomous, long-voyage, and high-precision navigation and positioning of submarines, an aided navigation method based on strapdown gravity gradiometer is proposed. The unscented Kalman filter framework is used to realize the fusion of inertial navigation and gravity gradient information. The performance of aided navigation is analyzed and evaluated from six aspects: long voyage, measurement update period, measurement noise, database noise, initial error, and inertial navigation system device level. When the parameters are set according to the benchmark parameters and after about 10 h of simulation, the results show that the attitude error, velocity error, and position error of the gravity gradiometer aided navigation system are less than 1 arcmin, 0.1 m/s, and 33 m, respectively.