Prevalence and Determinants of Undiagnosed Liver Steatosis and Fibrosis in a Nationally Representative Sample of US Adults.

Background Chronic liver diseases account for approximately 1.9 million deaths globally every year and negatively affect health-related quality of life. Early detection of liver disease may enable timely treatment, potentially improving patient outcomes. This study aimed to determine the prevalence and determinants of liver steatosis and fibrosis in US adults with no previously diagnosed liver condition. Methods We conducted an observational, nationally representative, cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) conducted from January 2017 to March 2020. Study participants were 7,391 adults aged 21 and older with no history of diagnosed liver disorders who underwent vibration-controlled transient elastography (VCTE) to determine liver steatosis and fibrosis. Controlled attenuation parameter (CAP) values between 248 and 267 dB/m were classified as mild steatosis, and those over 267 dB/m as advanced steatosis. Liver stiffness measurement (LSM) values between 7.65 and 13 kPa were classified as moderate/severe fibrosis, and those over 13 kPa as cirrhosis. Covariates included age, sex, race, body mass index (BMI), diabetes mellitus, kidney disease, smoking history, alcohol intake, alanine aminotransferase (ALT), aspartate aminotransferase (AST), physical activity, sedentary time, and sleep time. The associations of subject characteristics with liver CAP and LSM were evaluated using survey multivariable linear regression. Shapley Additive Explanations values determined the relative importance of each attribute in the model. The discriminative performance of classification models was assessed using the area under the receiver operating characteristic (AUROC) curve. Results The population prevalence of liver steatosis was 57.2% (10.2% mild; 47.0% advanced). The relative importance of covariates in predicting liver CAP was 63.1% for BMI, 10.7% for ALT, and less than 10% for the other covariates. The prevalence of significant fibrosis was 11.4% (8.3% moderate/severe fibrosis; 3.1% cirrhosis). The relative importance of covariates in predicting LSM was 67.3% for BMI and less than 10% for the other covariates. BMI alone demonstrated acceptable discriminative performance in classifying varying severities of steatosis and fibrosis (AUROC range 72%-78%) at cutoffs between 28 and 33 kg/m2. Conclusions Undiagnosed chronic liver disease based on VCTE findings is highly prevalent among US adults, particularly in obese individuals. Efforts to increase awareness about liver disease and to reconsider existing BMI thresholds for liver disease screening may be warranted.

Determinants of life dissatisfaction among adults in the United States: A cross-sectional analysis of the National Health Interview Survey.

The number of Americans who report dissatisfaction with their quality of life has increased over the past several decades. This study investigated social- and health-related determinants of life dissatisfaction among adults in the United States (US). We conducted a cross-sectional observational study using data from the 2021 National Health Interview Survey, a nationally representative sample of adults in the US. We analyzed the association between self-reported life dissatisfaction and independent variables including demographics, family-level information, health status and conditions, functioning and disability, health insurance coverage, chronic pain, occupational variables, socioeconomic indicators, health-related behaviors, and psychological distress indicators. Survey multivariable logistic regression was used to determine the association among social- and health-related determinants and life dissatisfaction. The relative importance of each variable in the final model was determined using Shapley Additive Explanations values (0-100% scale). Among the 253.2 million civilian noninstitutionalized adults, 12.2 million (4.8%) reported life dissatisfaction. Recent psychological distress, unmarried status, poor general health, lack of social/emotional support, and lower food security were independently associated with life dissatisfaction (all P < .001). The relative importance of these variables in predicting life dissatisfaction was 39.3% for recent psychological distress, 22.2% for unmarried status, 18.3% for poor general health, 13.4% for lack of social/emotional support, and 6.9% for lower food security. Additionally, racial inequities were identified in the prevalence of these factors. Life dissatisfaction among adults in the US is associated with social- and health-related factors that are more prevalent in racial minority groups. The study findings suggest that resource prioritization should be targeted towards individuals with these factors, with particular emphasis on racial minority groups. This study aligns with US health policy initiatives and the results may help policymakers address the underlying factors contributing to life dissatisfaction among the US population.

Diabetes mellitus increases the risk of hospital mortality in patients with Covid-19: Systematic review with meta-analysis.

BACKGROUND: The mortality rate associated with Covid-19 varies considerably among studies and determinants of this variability are not well characterized. METHODS: A systematic review of peer-reviewed literature published through March 31, 2020 was performed to estimate the mortality rate among hospitalized patients in China with a confirmed diagnosis of Covid-19. Hospital mortality rates were estimated using an inverse variance-weighted random-effects meta-analysis model. Funnel plot symmetry was evaluated for small-study effects, a one-study removed sensitivity analysis assessed the influence of individual studies on the pooled mortality rate, and metaregression assessed the association of potential confounding variables with mortality rates. RESULTS: The review included 16 observational studies involving 1832 hospitalized patients with a diagnosis of Covid-19. The surveillance period among studies ranged from December 16, 2019 to February 23, 2020. The median patient age was 53 years and 53% were males. A total of 38.5% of patients presented with at least 1 comorbidity, most commonly hypertension (24.0%), cardiac disease (15.1%), and diabetes mellitus (14.4%). Fever and cough, reported in 84.8% and 61.7% of patients respectively, were the most common patient symptoms. The pooled mortality rate was 9.9% (95% confidence interval 6.1% to 14.5%). Funnel plot asymmetry was not observed and the meta-analysis results were not substantially influenced by any single study since the pooled mortality rate ranged from 8.9% to 11.1% following iterative removal of one study at a time. Substantial heterogeneity in the mortality rate was identified among studies (I = 87%; P < .001). In a metaregression that included demographics, patient risk factors, and presenting symptoms, only a higher prevalence of diabetes mellitus was associated with a higher mortality rate (P = .03). CONCLUSIONS: In a meta-analysis of hospitalized patients in China with a diagnosis of Covid-19, the mortality rate was 9.9% and a higher diabetes mellitus prevalence was independently associated with a worse prognosis. The independent influence of diabetes mellitus with Covid-19 mortality should be viewed as hypothesis-generating and warrants further study.

Data regarding country-specific variability in Covid-19 prevalence, incidence, and case fatality rate.

This article contains data on country-specific variability in Covid-19 prevalence, incidence, and case fatality rate among the 238 countries globally. We used the World Health Organization worldwide Covid-19 tracking site to determine the number of confirmed Covid-19 cases, the number of fatalities attributed to Covid-19, and the case fatality rate for each of 238 countries. Using data from the United Nations Department of Economic and Social Affairs, we extracted key country-specific metrics with potential associations with Covid-19 including total population, land area, population density, percentage of residents living in urban areas, and median age. We extracted country-specific economic indicators from The World Bank Group Open Data database. All data were extracted on August 15, 2020. We developed consolidated data sets and calculated the country-specific point prevalence and incidence of Covid-19 and associated deaths. These data are associated with the article "Spatial Analysis of Global Variability in Covid-19 Burden". Data are stored in a comma separated value format and can be downloaded from the Data in Brief website.

Spatial Analysis of Global Variability in Covid-19 Burden.

BACKGROUND: Since the first occurrence of coronavirus disease 2019 (Covid-19), a number of online tools have become available to assist with tracking Covid-19 prevalence. Yet we are unaware of resources that provide country-specific Covid-19 incidence data. METHODS: We undertook a descriptive analysis of the global impact of Covid-19 using data reported on March 17, 2020. The prevalence of Covid-19 cases, fatalities attributed to Covid-19, and the case fatality rate for each of the 238 countries were accessed from the World Health Organization global Covid-19 tracking site, and we additionally calculated Covid-19 incidence based on country-specific population data. We determined the country-specific point prevalence and incidence of Covid-19 and associated deaths while using geocoded data to display their spatial distribution with geographic heat maps. RESULTS: The analysis included 193,197 Covid-19 cases and 7859 associated deaths. The point prevalence was highest in China (80,881), Italy (31,506), Iran (16,169), and Spain (11,312); no other country reported more than 10,000 cases. The incidence (per million population) was highest in San Marino (3389) followed by Iceland (645) and Italy (521); no other country had an incidence above 400 per million population. CONCLUSION: Countries with a high Covid-19 prevalence may not have a high incidence, and vice versa. Public health agencies that provide real-time infection tracking tools should report country-specific Covid-19 incidence metrics, in addition to prevalence data.