RESUMEN
This study aimed to investigate the association between residential greenness and tinnitus and the potential interaction between greenness and genetic predisposition to tinnitus. The normalized difference vegetation index (NDVI) is used to measure residential greenness. The tinnitus is defined based on self-reported. In the cross-sectional analyses, logistic regression models are used for the baseline sample of the United Kingdom Biobank cohort. In the secondary analysis, a Cox proportional hazard model is used for a subsample of participants who completed the tinnitus questionnaire at follow-up. In the cross-sectional analysis including 106471 participants, higher residential greenness is associated with lower odds of tinnitus for each interquartile range increase in continuous NDVI, with an adjusted odds ratio of 0.97 (95% confidence interval: 0.95 to 0.99) for tinnitus. A similar association is observed in the longitudinal analysis, with an adjusted hazard ratio of 0.92 (95% confidence interval: 0.86 to 0.98) for the association of NDVI increased per interquartile range with incident tinnitus. Moreover, there is a significant interaction between greenness and genetic predisposition to tinnitus (P < 0.05). This study suggested that residential greenness is negatively associated with tinnitus. Greenness and genetic predisposition to tinnitus are found to have a significant interaction.
Asunto(s)
Predisposición Genética a la Enfermedad , Acúfeno , Acúfeno/genética , Acúfeno/epidemiología , Humanos , Masculino , Femenino , Predisposición Genética a la Enfermedad/genética , Persona de Mediana Edad , Estudios Transversales , Reino Unido/epidemiología , Anciano , Encuestas y Cuestionarios , Adulto , Estudios de Cohortes , Modelos de Riesgos Proporcionales , Factores de RiesgoRESUMEN
BACKGROUND: Imported malaria has been an important challenge for China. Fatality rates from malaria increased in China, particularly in Henan Province, primarily due to malpractice and misdiagnoses in healthcare institutions, and the level of imported malaria. This study aims to investigate the relationship between the state of diagnosis and subsequent complications among imported malaria cases at healthcare institutions, based on malaria surveillance data in Henan Province from 2012 to 2017. METHODS: A retrospective descriptive analysis was performed using data from the Centre for Disease Control and Prevention, Zhengzhou City, the capital of Henan Province. A decision tree method was exploited to provide valuable insight into the correlation between imported malaria cases and healthcare institutions. RESULTS: From 2012 to 2017, there were 371 imported malaria cases, mostly in males aged between 20 and 50 years, including 319 Plasmodium falciparum cases. First visits of 32.3%, 19.9% and 15.9% malaria cases for treatment were to provincial, municipal and county healthcare institutions, respectively. The time interval between onset and initial diagnosis of 284 cases (76.5%) and the time interval between initial diagnosis and final diagnosis of 197 cases (53.1%) was no more than 72 h. An apparent trend was found that there were notably fewer patients misdiagnosed at first visit to healthcare institutions of a higher administrative level; 12.5% of cases were misdiagnosed in provincial healthcare institutions compared to 98.2% in private clinics, leading to fewer complications at healthcare institutions of higher administrative level due to correct initial diagnosis. In the tree model, the rank of healthcare facilities for initial diagnosis, and number of days between onset and initial diagnosis, made a major contribution to the classification of initial diagnosis, which subsequently became the most significant factor influencing complications developed in the second tree model. The classification accuracy were 82.2 and 74.1%, respectively for the tree models of initial diagnosis and complications developed. CONCLUSION: Inadequate seeking medical care by imported malaria patients, and insufficient capacity to diagnose malaria by healthcare institutions of lower administrative level were identified as major factors influencing complications of imported malaria cases in Henan Province. The lack of connection between uncommon imported malaria cases and superior medical resources was found to be the crucial challenge. A web-based system combined with WeChat to target imported malaria cases was proposed to cope with the challenge.