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Objective To explore the association between dietary quality and perceived stress among adult Chinese. Methods The China Health and Nutrition Survey (CHNS) was used to investigate the association between dietary quality and perceived stress in Chinese adults. The Chinese Perceived Stress Scale (CPSS) was used to assess the perceived stress in Chinese adults. Binary logistic regression models were utilized to explore the relationship between diet quality and perceived stress. Restricted cubic splines (RCS) were utilized to clarify the dose response relationship between diet quality and perceived stress. Results Binary logistic regression models revealed that adults with CHEI score ranged from P25 to P50 and higher than P75 had 15.1% (OR=0.849，95%CI：0.738-0.977) and 23.0% (OR=0.770，95%CI：0.666-0.891) reduced risk of high perceived stress after multivariable adjustment when compared with adults with CHEI score less than P25. RCS results showed that the OR value of high perceived stress risk decreased gradually with increasing CHEI score in the overall population, but this association was not statistically significant in adults with lower CHEI score. Conclusion High dietary quality is associated with a reduced risk of high perceived stress. This study provides a theoretical reference for the health effects of high dietary quality on high perceived stress risk reduction.
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Objective The study aims to find a suitable obesity index for predicting hyperuricemia (HUA)in Chinese adults. Methods The obesity indexes of 8133 subjects in China Health and Nutrition Survey in 2009 were calculated, and the basic situation of them was analyzed descriptively. χ2 test and t test were used to test the differences of categorical variables and continuous variables between the HUA group and the non-HUA group. The area under the curve (AUC) and receiver operating characteristic (ROC) curves were used to analyze the predictive value of these indices for HUA. Binary logistic regression was used to analyze the relationship between obesity and HUA. Results Demographic covariates, prevalence and Body Mass Index (BMI) all have impacts on the prevalence of HUA. Obesity indexes have a good predictive effect on HUA, and the Lipid Accumulation Product (LAP) is the best (AUC=0.77 (95% CI [0.75, 0.78]). Obesity indexes all have a significant correlation with HUA. When covariates were not adjusted, LAP had the highest OR value (OR=5.87, 95% CI [5.08, 6.77]). Conclusion LAP index is significantly related to HUA, and it can be used as an emerging index to assess the prevalence of HUA in Chinese adults.
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BackgroundCOVID-19 has rapidly evolved to become a global pandemic due largely to the transmission of its causative virus through asymptomatic carriers. Detection of SARS-CoV-2 in asymptomatic people is an urgent priority for the prevention and containment of disease outbreaks in communities. However, few data are available in asymptomatic persons regarding the accuracy of PCR testing. Additionally, although self-collected saliva has significant logistical advantages in mass screening, its utility as an alternative specimen in asymptomatic persons is yet to be determined. MethodsWe conducted a mass-screening study to compare the utility of nucleic acid amplification, such as reverse transcriptase polymerase chain reaction (RT-PCR) testing, using NPS and saliva samples from each individual in two cohorts of asymptomatic persons: the contact tracing cohort and the airport quarantine cohort. ResultsIn this mass-screening study including 1,924 individuals, the sensitivity of nucleic acid amplification testing with nasopharyngeal and saliva specimens were 86% (90%CI:77-93%) and 92% (90%CI:83-97%), respectively, with specificities greater than 99.9%. The true concordance probability between the nasopharyngeal and saliva tests was estimated at 0.998 (90%CI:0.996-0.999) on the estimated airport prevalence, 0.3%. In positive individuals, viral load was highly correlated between NPS and saliva. ConclusionBoth nasopharyngeal and saliva specimens had high sensitivity and specificity. Self-collected saliva is a valuable specimen to detect SARS-CoV-2 in mass screening of asymptomatic persons.
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The impact of the drastic reduction in travel volume within mainland China in January and February 2020 was quantified with respect to reports of novel coronavirus (COVID-19) infections outside China. Data on confirmed cases diagnosed outside China were analyzed using statistical models to estimate the impact of travel reduction on three epidemiological outcome measures: (i) the number of exported cases, (ii) the probability of a major epidemic, and (iii) the time delay to a major epidemic. From 28 January to 7 February 2020, we estimated that 226 exported cases (95% confidence interval: 86, 449) were prevented, corresponding to a 70.4% reduction in incidence compared to the counterfactual scenario. The reduced probability of a major epidemic ranged from 7% to 20% in Japan, which resulted in a median time delay to a major epidemic of two days. Depending on the scenario, the estimated delay may be less than one day. As the delay is small, the decision to control travel volume through restrictions on freedom of movement should be balanced between the resulting estimated epidemiological impact and predicted economic fallout.
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A total of 565 Japanese citizens were evacuated from Wuhan, China to Japan. All passengers were screened for symptoms and also undertook reverse transcription polymerase chain reaction testing, identifying 5 asymptomatic and 7 symptomatic passengers testing positive for 2019-nCoV. We show that the screening result is suggestive of the asymptomatic ratio at 41.6%.
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The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside of China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number--the average number of secondary cases generated by a single primary case in a naive population. We modeled epidemic growth either from a single index case with illness onset on 8 December, 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January, 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% CI: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.
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The geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2-14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. The mean time from illness onset to hospital admission (for treatment and/or isolation) was estimated at 3-4 days without truncation and at 5-9 days when right truncated. Based on the 95th percentile estimate of the incubation period, we recommend that the length of quarantine should be at least 14 days. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk.
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ObjectiveVirological tests indicate that a novel coronavirus is the most likely explanation for the 2019-20 pneumonia outbreak in Wuhan, China. We demonstrate that non-virological descriptive characteristics could have determined that the outbreak is caused by a novel pathogen in advance of virological testing. MethodsCharacteristics of the ongoing outbreak were collected in real time from two medical social media sites. These were compared against characteristics of ten existing pathogens that can induce atypical pneumonia. The probability that the current outbreak is due to "Disease X" (i.e., previously unknown etiology) as opposed to one of the known pathogens was inferred, and this estimate was updated as the outbreak continued. ResultsThe probability that Disease X is driving the outbreak was assessed as over 32% on 31 December 2019, one week before virus identification. After some specific pathogens were ruled out by laboratory tests on 5 Jan 2020, the inferred probability of Disease X was over 59%. ConclusionsWe showed quantitatively that the emerging outbreak of atypical pneumonia cases is consistent with causation by a novel pathogen. The proposed approach, that uses only routinely-observed non-virological data, can aid ongoing risk assessments even before virological test results become available.