Association between famine exposure during infancy and childhood and the risk of chronic kidney disease in adulthood.

BACKGROUND: Famine exposure in childhood is proven to be associated with multiple chornic disease in adult but has not been studied with chronic kidney disease (CKD). AIMS: This study was conducted to identify the relationship between famine exposure during infancy and childhood - specifically, the Chinese famine of 1959-1961 - and the risk of adult-onset chronic kidney disease (CKD) among Chinese individuals. METHODS: This study included 2937 individuals from the Qingdao Diabetes Prevention Program. They were stratified by birth year into infancy-exposed (1956-1958), childhood-exposed (1950-1955) and unexposed (1963-1971) groups. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation. CKD was defined as an eGFR of <90 mL/min/1.73 m2 . RESULTS: The mean eGFR values for the infancy-exposed and childhood-exposed groups were 107.23 ± 12.53 and 103.23 ± 12.44 mL/min/1.73 m2 , respectively, both of which were lower than that of the unexposed group (114.82 ± 13.39 mL/min/1.73 m2 ; P < 0.05). In the crude model, the odds ratio (OR) for CKD was 2.00 (95% confidence interval (CI): 1.39-2.88) in the infancy-exposed group and 2.92 (95% CI: 2.17-3.93) in the childhood-exposed group. Further adjustments for urban/rural residence, body mass index, age, current smoking, type 2 diabetes, systolic blood pressure, diastolic blood pressure and total cholesterol did not significantly alter the association between famine exposure and CKD. The corresponding ORs were 1.71 (95% CI: 1.17-2.50) and 2.48 (95% CI: 1.81-3.40) for the infancy-exposed and childhood-exposed groups respectively. CONCLUSIONS: Famine exposure during infancy and childhood is associated with a long-term decline in eGFR and an increased adult-onset CKD risk. Early intervention for high-risk individuals may mitigate the risk of adult-onset CKD.

Association of seafood consumption with cardiovascular disease among adults in Qingdao, China.

BACKGROUND AND AIMS: The relationship between seafood consumption and cardiovascular disease (CVD) is controversial, and studies have not considered competing risk events. Our study examined the association between a full range of seafood consumption and CVD incidence and mortality based on the Qingdao Diabetes Prevention Program. METHODS AND RESULTS: We followed up 5285 participants without CVD at baseline until December 31, 2021. CVD cases and deaths were identified through record linkage with the Qingdao CVD Surveillance System and the Qingdao Death Surveillance System, respectively. Information on seafood consumption was obtained using a food frequency questionnaire. We used the Cox proportional hazard model and the competing risk model to evaluate the association between all types of seafood consumption and CVD incidence and mortality. During a median follow-up of 11.4 years, 122 CVD cases and 75 deaths occurred. After adjustment for potential confounders, compared with nonconsumers, seafood consumption of 300-500 and > 500 g/week was associated with a lower risk of CVD incidence [hazards ratio and 95 % confidence interval (CI): 0.54 (0.29-0.99) and 0.49 (0.26-0.91), respectively]. However, seafood consumption of >500 g/week had a significantly lower risk of CVD mortality [subdistribution hazard ratio and 95 % CI: 0.40 (0.17-0.95)], but it was insignificant in other groups. CONCLUSION: Seafood consumption of 300-500 g/week and >500 g/week was associated with a lower CVD incidence and mortality. Our findings provide evidence of the recommendations of the 2022 Dietary Guidelines for Chinese residents and may guide the promotion of strategies for CVD prevention.

Clinical characteristics and predictive model of pulmonary tuberculosis patients with pulmonary fungal coinfection.

BACKGROUND: In clinical settings, pulmonary tuberculosis (PTB) patients were often found to have pulmonary fungal coinfection. This study aimed to assess the clinical characteristics of patients suffering from coinfection with TB and pulmonary fungal and construct a predictive model for evaluating the probability of pulmonary fungal coinfection in patients with pulmonary tuberculosis. METHODS: The present case-control study retrospectively collected information from 286 patients affected by PTB who received treatment from December 6,2016- December 6,2021 at Beijing Chest Hospital, Capital Medical University. As control subjects, patients with sex and address corresponding to those of the case subjects were included in the study in a ratio of 1:1. These 286 patients were randomly divided into the training and internal validation sets in a ratio of 3:1. Chi-square test and logistic regression analysis were performed for the training set, and a predictive model was developed using the selected predictors. Bootstrapping was performed for internal validation. RESULTS: Seven variables [illness course, pulmonary cavitation, broad-spectrum antibiotics use for at least 1 week, chemotherapy or immunosuppressants, surgery, bacterial pneumonia, and hypoproteinemia] were validated and used to develop a predictive model which showed good discrimination capability for both training set [area under the curve (AUC) = 0.860, 95% confidence interval (CI) = 0.811-0.909] and internal validation set (AUC = 0.884, 95% CI = 0.799-0.970). The calibration curves also showed that the probabilities predicted using the predictive model had satisfactory consistency with the actual probability for both training and internal validation sets. CONCLUSIONS: We developed a predictive model that can predict the probability of pulmonary fungal coinfection in pulmonary tuberculosis patients. It showed potential clinical utility.

Infection rate models for COVID-19: Model risk and public health news sentiment exposure adjustments.

During the COVID-19 pandemic, governments globally had to impose severe contact restriction measures and social mobility limitations in order to limit the exposure of the population to COVID-19. These public health policy decisions were informed by statistical models for infection rates in national populations. In this work, we are interested in modelling the temporal evolution of national-level infection counts for the United Kingdom (UK-Wales, England, Scotland), Germany (GM), Italy (IT), Spain (SP), Japan (JP), Australia (AU) and the United States (US). We model the national-level infection counts for the period January 2020 to January 2021, thus covering both the pre- and post-vaccine roll-out periods, in order to better understand the most reliable model structure for the COVID-19 epidemic growth curve. We achieve this by exploring a variety of stochastic population growth models and comparing their calibration, with respect to in-sample fitting and out-of-sample forecasting, both with and without exposure adjustment, to the most widely used and reported growth model, the Gompertz population model, often referred to in the public health policy discourse during the COVID-19 pandemic. Model risk as we explore it in this work manifests in the inability to adequately capture the behaviour of the disease progression growth rate curve. Therefore, our concept of model risk is formed relative to the standard reference Gompertz model used by decision-makers, and then we can characterise model risk mathematically as having two components: the dispersion of the observation distribution, and the structure of the intensity function over time for cumulative counts of new infections daily (i.e. the force of infection) attributed directly to the COVID-19 pandemic. We also explore how to incorporate in these population models the effect that governmental interventions have had on the number of infected cases. This is achieved through the development of an exposure adjustment to the force of infection comprised of a purpose-built sentiment index, which we construct from various authoritative public health news reporting. The news reporting media we employed were the New York Times, the Guardian, the Telegraph, Reuters global blog, as well as national and international health authorities: the European Centre for Disease Prevention and Control, the United Nations Economic Commission for Europe, the United States Centres for Disease Control and Prevention, and the World Health Organisation. We find that exposure adjustments that incorporate sentiment are better able to calibrate to early stages of infection spread in all countries under study.