[Disease burden for gynecological disease in China, 2016]

"Premature" Girls with "Illegitimate" Diseases: A Qualitative Exploration of the Stigma of Gynecological Diseases for Unmarried Young Women in China

Stigma has been a prominent barrier in women's pursuit of better sexual and reproductive health (SRH). Specifically, evidence supports the stigmatization of gynecological diseases (GDs) for unmarried young women. Drawing upon the model of social identity threats, this study explored the GD stigma and social identity threats faced by unmarried young women in China with 26 in-depth interview data. The interpersonal, socio-cultural, and intrapersonal layers of GD stigma were identified. First, participants' disclosure and concealment of GDs concerning different significant others were contrasted as an interpersonal layer and voluntary response to social identity threats. In participants' GD experiences, peers stood out for providing emotional, tangible, and informational support, while parents were most often avoided for anticipated stigma. Second, collective representations of GDs and the cultural rationale in the socio-cultural layer were probed. The traditional and modernized sexual norms centering on the legitimacy of premarital sex and SRH knowledge were unveiled. At last, the interpersonal layer was identified. Unmarried young patients suffered social identity threats regarding their independence, sexual agency, and bodily awareness. This is one of the first studies that investigated the underappreciated GD stigma in China. Theoretical and practical implications are discussed.

Fast and accurate automated recognition of the dominant cells from fecal images based on Faster R-CNN

Fecal samples can easily be collected and are representative of a person’s current health state; therefore, the demand for routine fecal examination has increased sharply. However, manual operation may pollute the samples, and low efficiency limits the general examination speed; therefore, automatic analysis is needed. Nevertheless, recognition exhaustion time and accuracy remain major challenges in automatic testing. Here, we introduce a fast and efficient cell-detection algorithm based on the Faster-R-CNN technique: the Resnet-152 convolutional neural network architecture. Additionally, a region proposal network and a network combined with principal component analysis are proposed for cell location and recognition in microscopic images. Our algorithm achieved a mean average precision of 84% and a 723 ms detection time per sample for 40,560 fecal images. Thus, this approach may provide a solid theoretical basis for real-time detection in routine clinical examinations while accelerating the process to satisfy increasing demand.

Secular trends in HIV/AIDS mortality in China from 1990 to 2016: Gender disparities

OBJECTIVES

HIV/AIDS has become the leading cause of death by infectious disease in China since 2009. However, the trend of gender disparities in HIV/AIDS has not been reported in China since 1990. Our study aimed to explore the secular trend of HIV/AIDS mortality in China from 1990 to 2016 and to identify its gender disparities over the past 27 years.

METHOD

The mortality data of HIV/AIDS were obtained from the Global Burden of Disease Study 2016 (GBD 2016). Logistic regression was used to estimate the prevalence odds ratio (POR) of gender for HIV/AIDS mortality in different surveys.

RESULTS

The standardized mortality of HIV/AIDS in China rose dramatically from 0.33 per 100,000 people in 1990 to 2.50 per 100,000 people in 2016. The rate of HIV/AIDS mortality increased more quickly in men than in women, and the sex gap of mortality of HIV/AIDS widened. By 2016, the HIV/AIDS mortality in men was 3 times that in women and was 5.74 times that in women within the 75- to 79-year-old age group.

CONCLUSIONS

The mortality of HIV/AIDS in China is increasing, with a widening gender disparity. It is critical for policymakers to develop policies to eliminate these disparities and to ensure that everyone can live a long life in full health.