Spatial accessibility to medical resources is an integral component of universal health coverage. However, research evaluating the spatial accessibility of healthcare services at the community level in China remains limited. We assessed the community-level spatial access to beds, doctors, and nurses at general hospitals and identified the shortage areas in Shenzhen, one of the fastest growing cities in China. Based on hospital and population data from 2016, spatial accessibility was analyzed using several methods: shortest path analysis, Gini coefficient, and enhanced 2-step floating catchment area (E2SFCA). The study found that 99.9% of the residents in Shenzhen could get to the nearest general hospital within 30 min. Healthcare supply was much more equitable between populations than across communities in the city. E2SFCA scores showed that the communities with the best and worst hospital accessibility were found in the southwest and southeast of the city, respectively. State-owned public hospitals still dominated the medical resources supply market and there was a clear spatial accessibility disparity between private and public healthcare resources. The E2SFCA scores supplement more details about resource disparity over space than do crude provider-to-population ratios (PPR) and can help improve the efficiency of the distribution of medical resources.

BACKGROUNDThe current understanding of the magnitude and consequences of multimorbidity in Chinese older adults with coronary heart disease (CHD) is insufficient. We aimed to assess the association and population-attributable fractions (PAFs) between multimorbidity and mortality among hospitalized older patients who were diagnosed with CHD in Shenzhen, China. METHODSWe conducted a retrospective cohort study of older Chinese patients (aged ≥ 65 years) who were diagnosed with CHD. Cox proportional hazards models were used to estimate the associations between multimorbidity and all-cause and cardiovascular disease (CVD) mortality. We also calculated the PAFs. RESULTSThe study comprised 76,455 older hospitalized patients who were diagnosed with CHD between January 1, 2016, and August 31, 2022. Among them, 70,217 (91.9%) had multimorbidity, defined as the presence of at least one of the predefined 14 chronic conditions. Those with cancer, hemorrhagic stroke and chronic liver disease had the worst overall death risk, with adjusted HRs (95% CIs) of 4.05 (3.77, 4.38), 2.22 (1.94, 2.53), and 1.85 (1.63, 2.11), respectively. For CVD mortality, the highest risk was observed for hemorrhagic stroke, ischemic stroke, and chronic kidney disease; the corresponding adjusted HRs (95% CIs) were 3.24 (2.77, 3.79), 1.91 (1.79, 2.04), and 1.81 (1.64, 1.99), respectively. All-cause mortality was mostly attributable to cancer, heart failure and ischemic stroke, with PAFs of 11.8, 10.2, and 9.1, respectively. As for CVD mortality, the leading PAFs were heart failure, ischemic stroke and diabetes; the corresponding PAFs were 18.0, 15.7, and 6.1, respectively. CONCLUSIONSMultimorbidity was common and had a significant impact on mortality among older patients with CHD in Shenzhen, China. Cancer, heart failure, ischemic stroke and diabetes are the primary contributors to PAFs. Therefore, prioritizing improved treatment and management of these comorbidities is essential for the survival prognosis of CHD patients from a holistic public health perspective.

Background: Benzodiazepines (BZDs) are commonly prescribed as adjunctive drugs for patients with cardiovascular diseases (CVDs), particularly those who experience anxiety or insomnia. However, the relationship between the use of BZDs and incident risk of sudden cardiac arrest (SCA) has not been well investigated. In this study, we aimed to examine the association between the use of BZDs and the incident risk of SCA among patients with CVD. Method: In this retrospective cohort study, a total of 74,715 eligible patients with new-onset CVD as a primary cause of hospitalization between July 2016 and August 2022 were included from the health information platform in Shenzhen, China. Among them, 61,761 BZD non-initiators were identified and matched to 12,954 BZD initiators by propensity score at a maximum ratio of 5:1. Propensity score-matched Cox proportional hazard models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). Results: Over a 12-month follow-up period, 29 (2.24 per 1000 person-years) and 137 (2.22 per 1000 person-years) SCA cases occurred among propensity score-matched BZD initiators and non-initiators, respectively. Patients who initiated BZD treatment were associated with a 101% increased risk of SCA incidence compared with patients without BZD treatment (adjusted HR: 2.01, 95% CI: 1.42, 2.83). Furthermore, compared with the non-use (0 defined daily dose, DDD), the adjusted HR was 1.43 (95% CI: 1.32, 1.56) for the BZD consumption of ≤1 DDD and 2.58 (95% CI: 2.37, 2.81) for the BZD consumption of >1 DDD ( P for trend < 0.001) within a 12-month follow-up period. Conclusion: This study provides evidence that BZD initiation may be associated with an increased incident risk of SCA in patients with CVD. Our finding highlights the importance of cautious prescribing BZDs in the health management of patients with CVD.

The coronavirus disease 2019 (COVID-19) pandemic has posed a profound psychological impact on healthcare workers. However, the role of positive affect in moderating the effect of perceived stress on the psychological states of healthcare workers remains unknown. This study aimed to analyze the moderating effect of positive affect on the association between stress and the mental health of healthcare workers during the COVID-19 pandemic. This cross-sectional study evaluated the relationships between perceived stress (the Perceived Stress Scale), positive affect (the Positive and Negative Affect Schedule), depression (the Patient Health Questionnaire-9), and anxiety (the Generalized Anxiety Disorder 7-item Scale) during the COVID-19 pandemic in 644 Chinese healthcare workers who completed online self-reports. The results revealed a significant negative association between positive affect and psychological problems, including stress, depression, and anxiety. At the total group level, multiple regression analysis showed that positive affect alleviated the influence of perceived stress on depression, but no significant moderating effect was found for anxiety. In the subgroups divided by perceived stress, the moderating effect of positive affect on depression was only significant in healthcare workers with a high level of perceived stress. These results suggested that positive affect played a moderative role in alleviating the effect of stress on depression among healthcare workers, particularly those with a high level of stress, thus emphasizing the importance of positive affect as an intervention strategy for promoting the mental health of healthcare workers in the context of the ongoing COVID-19 pandemic.

Nowadays, air pollution is a severe environmental problem in China. To investigate the effects of ambient air pollution on health, a time series analysis of daily outpatient and inpatient visits in 2015 were conducted in Shenzhen (China). Generalized additive model was employed to analyze associations between six air pollutants (namely SO₂, CO, NO₂, O₃, PM₁₀, and PM_2.5) and daily outpatient and inpatient visits after adjusting confounding meteorological factors, time and day of the week effects. Significant associations between air pollutants and two types of hospital visits were observed. The estimated increase in overall outpatient visits associated with each 10 µg/m³ increase in air pollutant concentration ranged from 0.48% (O₃ at lag 2) to 11.48% (SO₂ with 2-day moving average); for overall inpatient visits ranged from 0.73% (O₃ at lag 7) to 17.13% (SO₂ with 8-day moving average). Our results also suggested a heterogeneity of the health effects across different outcomes and in different populations. The findings in present study indicate that even in Shenzhen, a less polluted area in China, significant associations exist between air pollution and daily number of overall outpatient and inpatient visits.