BackgroundSelf-rated health (SRH) is not only used to measure health status and health inequalities, but also as a strong predictor of morbidity and mortality. The purpose of this study was to: 1) evaluate the factors that account for variations in self-rated health among Chinese citizens; and to 2) explore the process through which socio-economic status may impact self-rated health.MethodsData were derived from the Chinese General Social Survey (CGSS) (2013). Determinants of self-rated health were analyzed along four main dimensions: demographic characteristics, socio-economic status, lifestyle, and psychosocial factors. Multivariate odds ratios for good self-rated health were calculated for different variables in order to analyze the determinants. Binary logistic regression analysis was performed to assess the extent to which lifestyle and psychosocial factors explained the association between socio-economic status and self-rated health.ResultsAbout 65% of the survey respondents reported good self-rated health. Women, the elderly, married or single respondents and residents of Western China were less likely to report good self-rated health. Respondents who were engaged in work, had higher household income, reported high social class and higher socio-economic status compared with peers were more likely to report good self-rated health. Normal weight and physically active respondents along with those reporting a happy life, no depression, and good relationships with families and friends were related to good self-rated health. We also found the effect of socio-economic status on self-rated health was partly explained by lifestyle and psychosocial factors.ConclusionThe present findings support the notion that both socio-economic status and lifestyle as well as psychosocial factors were related with good self-rated health. The interventions targeting these factors could improve the health status of the population. The depression was the most influential predictor of self-rated health, especially for the women and the elderly. Although lifestyle and psychosocial factors explained partly the the association between socio-economic status and health, the reason why socio-economic difference exists in health must be further explored. What’s more, it needs to be further studied why the same determinant has different influence strengths on the health of different groups of people.

BackgroundIn recent decades, China has experienced tremendous economic growth and also witnessed growing socioeconomic-related health inequality. The study aims to explore the potential causes of socioeconomic-related health inequality in urban and rural areas of China over the past two decades.MethodsThis study used six waves of the China Health and Nutrition Survey (CHNS) from 1991 to 2006. The recentered influence function (RIF) regression decomposition method was employed to decompose socioeconomic-related health inequality in China. Health status was derived from self-rated health (SRH) scores. The analyses were conducted on urban and rural samples separately.ResultsWe found that the average level of health status declined from 1989 to 2006 for both urban and rural populations. Average health scores were greater for the rural population compared with those for the urban population. We also found that there exists pro-rich health inequality in China. While income and secondary education were the main factors to reduce health inequality, older people, unhealthy lifestyles and a poor home environment increased inequality. Health insurance had the opposite effects on health inequality for urban and rural populations, resulting in lower inequality for urban populations and higher inequality for their rural counterparts.ConclusionThese findings suggest that an effective way to reduce socioeconomic-related health inequality is not only to increase income and improve access to health care services, but also to focus on improvements in the lifestyles and the home environment. Specifically, for rural populations, it is particularly important to improve the design of health insurance and implement a more comprehensive insurance package that can effectively target the rural poor. Moreover, it is necessary to comprehensively promote the flush toilets and tap water in rural areas. For urban populations, in addition to promoting universal secondary education, healthy lifestyles should be promoted, including measures such as alcohol control.Electronic supplementary materialThe online version of this article (doi:10.1186/s12939-017-0624-9) contains supplementary material, which is available to authorized users.

Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting-terrestrial (DVB-T)-based passive radars. However, television broadcast-transmitted signals offer poor range resolution for imaging purposes, because they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, signals composed of multiple DVB-T channels are required. Problems arise, however, because DVB-T channels are typically widely separated in the frequency domain. The gaps between channels produce high grating Manuscript lobes in the image domain when Fourier-based algorithms are used to form the ISAR image. In this paper, compressive sensing theory is investigated to address this problem because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization problem under the constraint of signal sparsity, passive ISAR images can be obtained with strongly reduced grating lobes. Both simulation and experimental results are shown to demonstrate the validity of the proposed approach.

China is facing a dramatic aging of its population. Little is known about the factors that influence the place of death and the trends in the place of death for elderly people in China. The purposes of this study were: (1) to examine the impact of the socioeconomic status (SES) on place of death for elderly Chinese residents; and (2) to assess temporal trends in the place of death over the last 15 years. Data were derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) (1998–2012). Place-of-death as an outcome was dichotomized into either death at home or death outside the home. Logistic regression analyses were used to examine the impact of SES on place of death. The results showed that, of the 23,098 deaths during the study period, 87.78% occurred at home. The overall trend in home death has increased since 2005. SES was shown to be an important factor affecting place of death. The elderly with higher SES were more likely to die where health resources were concentrated, i.e., in a hospital or other type of institution. Our finding suggests that the trend towards a greater emphasis on death at home may call for the development of more supportive home care programs in China. Our finding also suggests that the socioeconomic differences in the place of death may be related to the availability of or access to health care services.

Inverse synthetic aperture radar (ISAR) can form two-dimensional (2D) electromagnetic images of a target, but it cannot provide the third dimensional information about the target. Conventional 3D turntable ISAR imaging requires data collection over densely azimuth-elevation samples, which needs a large amount of data storage. In this study, an effective 3D ISAR imaging algorithm for turntable model based on compressive sensing is proposed, which exploits the sparsity in the image domain to achieve 3D reconstruction by using a limited number of measurements. Firstly, the 3D data tensor is converted into a 2D matrix by stacking slices of data along one specific dimension; then a 2D optimisation reconstruction approach is applied to solve a sparsity-driven optimisation problem to obtain the 2D distribution of the scatterers. Lastly, 3D ISAR images are generated by rearranging the scatterer distribution in the 2D map into a 3D volume. This imaging scheme only needs a small number of measurements, and reduces the required memory and computational burden significantly. Simulation results are finally shown to validate the proposed algorithm