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This study explored the roles of epidemic-spread-related behaviors, vaccination status and weather factors during the COVID-19 epidemic in 50 U.S. states since March 2020. Data from March 1, 2020 to February 5, 2022 were incorporated into panel model. The states were clustered by the k-means method. In addition to discussing the whole time period, we also took multiple events nodes into account and analyzed the data in different time periods respectively by panel linear regression method. In addition, influence of cluster grouping and different incubation periods were been discussed. Non-segmented analysis showed the rate of people staying at home and the vaccination dose per capita were significantly negatively correlated with the daily incidence rate, while the number of long-distance trips was positively correlated. Weather indicators also had a negative effect to a certain extent. Most segmental results support the above view. The vaccination dose per capita was unsurprisingly proved to be the most significant factor especially for epidemic dominated by Omicron strains. 7-day was a more robust incubation period with the best model fit while weather had different effects on the epidemic spread in different time period. The implementation of prevention behaviors and the promotion of vaccination may have a successful control effect on COVID-19, including variants' epidemic such as Omicron. The spread of COVID-19 also might be associated with weather, albeit to a lesser extent. [ABSTRACT FROM AUTHOR]

Cardiovascular health (CVH) is closely associated with various noncommunicable diseases (NCDs) and comorbidity; however, the influence of CVH on NCD multimorbidity was not fully elucidated. We aimed to examine the association between CVH using Life's Essential 8 (LE8) and NCD multimorbidity among adults, males, and females in the United States, conducting a cross-sectional analysis using data involving 24,445 participants from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018. LE8 was categorized into low, moderate, and high CVH groups. Multivariate logistic regressions and restricted cubic spline regressions were used to estimate the association between LE8 and NCD multimorbidity. Overall, 6162 participants had NCD multimorbidity, of which 1168 (43.5%), 4343 (25.9%), and 651 (13.4%) had low, moderate, and high CVH, separately. After multivariable adjustment, LE8 was negatively associated with NCD multimorbidity among adults (odds ratio (OR) for per 1 standard deviation (SD) increase in LE8 and 95% confidence interval (CI), 0.67 (0.64, 0.69)), and the top 3 NCDs associated with CVH were emphysema, congestive heart failure, stroke, and the dose-response relationships between LE8 and NCD multimorbidity were observed among adults (overall P < 0.001). Similar patterns were also identified among males and females. Higher CVH measured by the LE8 score was associated with lower odds of NCD multimorbidity among adults, males, and females. [ABSTRACT FROM AUTHOR]

Objectives: To describe the prevalence and trends of mild, moderate and severe depression among adults and all age groups in the US from 2005 to 2016, and analysis the risk factors for depression.Methods: This study analyzed the prevalence and association with risk factors of depression using weighted univariate logistic regression model. Data of NHANES 2005-2016 were used.Results: This study analyzed 29,303 participants. From 2005 through 2016, the trends of severe depression increased among ≥20 years (p for trend = 0.026, difference, 0.109[0.012,0.207]); severe depression increased among ≥65 years (p for trend <0.001, difference, 0.302[0.170,0.435]); and moderate depression increased among 20-39 years (p for trend = 0.028, difference, 0.137[0.045,0.229]). In adults, the odds ratios (OR)(95% confidence intervals (CI)) of mild depression for < 25000$ was 2.24 (1.96, 2.55), moderate depression was 4.94(3.91,6.24), and severe depression was 6.45(4.78,8.71); the OR(95%CI) of mild depression for smoking was 1.69(1.55,1.84), moderate depression was 2.94(2.57,3.35), and severe depression was 3.36(2.87,3.93); the OR(95%CI) of mild depression for hypertension was1.27(1.18,1.38), moderate depression was1.50(1.31,1.73), and severe depression was 1.94(1.61,2.34); the OR(95%CI) of mild depression for diabetes mellitus was1.45(1.30,1.61), moderate depression was1.83(1.51,2.22), and severe depression was 2.05(1.70,2.48).Conclusions: There was an increasing trend of severe depression in American adults, which was mainly manifested in the increasing trend of severe depression in the population ≥65 years. And the trend of moderate depression increased in 20-39 years. In addition, lower income, smoking, hypertension and diabetes mellitus increased the risk of depression, and the risk increased with the degree of depression. [ABSTRACT FROM AUTHOR]

Objectives: One of the underlying mechanisms of aging is chronic inflammation, which has been closely associated with daily diet. Phenotypic age (PhenoAge) has been used as an index to track the aging process before diseases show clinical symptoms. The present study aimed to explore the association between the dietary inflammatory index (DII) and PhenoAge., Methods: In total, 9,275 adults aged 20 years old and over in the National Health and Nutrition Examination Survey were involved in this study. Dietary patterns were classified as pro-inflammatory or anti-inflammatory according to the DII. PhenoAge was regarded as a continuous variable, and linear regression was used to explore its association with dietary inflammation. Stratified analyses by sex, age, race, physical exercise, smoking status, drinking status, and body mass index were used to test the sensitivity of these associations., Results: The median value of PhenoAge was 38.60 years and 39.76 years for the participants with anti-inflammatory and pro-inflammatory diets, respectively. A pro-inflammatory diet was positively associated with PhenoAge (β=0.73; 95% confidence interval, 0.31 to 1.14), compared with participants who had an anti-inflammatory diet. There was an interaction between dietary inflammation and age for PhenoAge (pinteraction<0.001). The strength of the association between a pro-inflammatory diet and PhenoAge was stronger as age increased., Conclusions: A pro-inflammatory diet was associated with a higher PhenoAge, and the association was strongest in the elderly. We recommended reducing dietary inflammation to delay phenotypic aging, especially for the elderly.

Objectives: Multimorbidity of non-communicable diseases (NCDs) has brought enormous challenges to public health, becoming a major medical burden. However, the patterns, temporal trends, and all-cause mortality associated with NCD multimorbidity over time have not been well described in the United States., Methods: All adult participants were sourced from nationally representative data from the National Health and Nutrition Examination Survey. In total, 55,081 participants were included in trend analysis, and 38,977 participants were included in Cox regression., Results: The 5 NCDs with the largest increases over the study period were diabetes, osteoporosis, obesity, liver conditions, and cancer. The estimated prevalence of multimorbidity increased with age, especially for middle-aged participants with 5 or more NCDs; in general, the prevalence of NCD multimorbidity was higher among females than males. Participants with 5 or more NCDs were at 4.49 times the risk of all-cause mortality of participants without any diseases. Significant interactions were found between multimorbidity and age group (p for interaction <0.001), race/ethnicity (p for interaction<0.001), and educational attainment (p for interaction=0.010)., Conclusions: The prevalence of multiple NCDs significantly increased from 1999 to 2018. Those with 5 or more NCDs had the highest risk of all-cause mortality, especially among the young population. The data reported by this study could serve as a reference for additional NCD research.

Objective: Traditionally, the absence of insulin resistance risk factors (IRRFs) was considered a low risk for insulin resistance (IR). However, IR also existed in certain individuals without IRRFs; thus this study aims to explore predictors of IR targeted at the population without IRRFs., Design: Cross-sectional survey., Setting: National Health and Nutrition Examination Survey., Participants: Participants without regular IRRFs (IRRF-Free, n=2478) and a subgroup without optimal IRRFs (IRRF-Optimal, n=1414) were involved in this study., Primary and Secondary Outcome Measure: IRRFs and the optimal cut-off value of triglyceride (TG) to predict IR., Results: Overall, the prevalence of IR was 6.9% and 5.7% in the IRRF-Free group and the IRRF-Optimal group, respectively. TG and waist circumference were independently associated with the prevalence of IR in both the groups (OR=1.010 to 10.20; p<0.05 for all), where TG was positively associated with IR. The area under the receiver operating characteristic curve of TG was 0.7016 (95% CI: 0.7013 to 0.7018) and 0.7219 (95% CI: 0.7215 to 0.7222), and the optimal cut-off value of TG to predict IR was 79.5 mg/dL and 81.5 mg/dL in the IRRF-Free group and the IRRF-Optimal group, respectively., Conclusion: There is an association between TG and IR even in the normal range of TG concentration. Therefore, normal TG could be used as an important indicator to predict the prevalence of IR in the absence of IRRFs., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)