From Liver to Heart: Insights on Alcohol-Associated Liver Disease and Cardiovascular Outcomes, A Decade of Data from National Survey

doi:10.21203/rs.3.rs-5301471/v1

Background: Alcohol associated liver disease (AALD) and cardiovascular diseases (CVD) represent significant health burdens worldwide. This study aims to provide a comprehensive overview of the association between AALD and CVD outcomes including heart failure (HF) which was incompletely understood.

Methods: The current study utilizes data from the National Health and Nutrition and Examination Survey (NHANES) from 2011 - 2020; using a stratified, multistage probability cluster design. AALD in the NHANES was defined using clinical laboratory data and self-reported alcohol use, among which fibrosis-4 score of >2.67. CVD was defined as participants who self-reported heart failure, coronary artery disease or stroke. Data from NHANES were combined with death certificate data from the National Center of health Statistics from the National Death Index to ascertain mortality rates. All models were adjusted for potential confounding variables such as age, gender, race/ethnicity, education, income/poverty ratio, insurance, smoking, body mass index, systolic/diastolic blood pressure, and diabetes status. Analysis is conducted using weighted, logistic and cox linear regression.

Results: The initial sample included 23,206 participants aged 20 and older, with recorded cardiovascular status and AST/ALT levels. After excluding participants with hepatitis B, hepatitis C, metabolic dysfunction-associated fatty liver disease, and pregnant patients, the final unweighted sample size was 13,413. Participants reporting AALD had a higher percentage of college degrees (p<0.001) and were more likely to be daily smokers. Asians exhibited the highest rates of AALD compared to other demographics (p<0.001). Those with AALD also had higher mean systolic and diastolic blood pressure, as well as elevated fasting glucose levels (p<0.001). Comorbidities such as heart failure (HF), stroke, and coronary artery disease (CAD) were prevalent. The mortality rate among AALD participants with CVD was 25%, compared to 3% among those without CVD (p<0.001). After adjusting for potential confounding variables, no statistically significant associations were found between AALD status and HF or CAD. However, a clinically significant increase in the odds of stroke was observed within the AALD group (p<0.001).

Conclusions: Our findings indicate Asians have the highest rates of AALD. There is an increased prevalence of AALD with HF, CAD and stroke, and a significant increase in mortality with stroke.

Alcohol-associated liver disease (AALD) and cardiovascular diseases (CVD) represent significant public health challenges worldwide, contributing substantially to morbidity and mortality. The global burden of these diseases is underscored by their pervasive impact on health systems and societies. AALD, is replaced by the former name “alcoholic liver disease” [1]. AALD encompasses a spectrum of liver conditions, ranging from simple steatosis (fatty liver) to alcoholic hepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma (HCC) [2]. According to the World Health Organization (WHO), alcohol consumption is responsible for approximately 2.6 million deaths annually in 2019, with AALD being a major contributor to this toll [3]. The pathogenesis of AALD involves complex interactions between genetic, environmental, and immunological factors, leading to liver inflammation, fibrosis, and eventual liver failure in severe cases [4]. The prevalence of AALD varies globally, with higher rates observed in regions with elevated alcohol consumption. For instance, Europe and the Americas report some of the highest incidences of AALD, reflecting cultural and socioeconomic factors influencing drinking patterns [4]. The economic burden of AALD is also substantial, encompassing healthcare costs, lost productivity, and social consequences. On the other hand, Coronary Vascular Disease (CVD), encompassing conditions such as coronary artery disease, heart failure, and stroke, remains the leading cause of death globally [5]. The WHO estimates that CVD accounts for approximately 17.9 million deaths each year, representing 31% of all global deaths [6]. Risk factors for CVD include hypertension, diabetes, smoking, unhealthy diet, physical inactivity, and excessive alcohol consumption [7]. The relationship between alcohol consumption and CVD is complex. Moderate alcohol intake has been suggested to have cardioprotective effects, particularly through the elevation of high-density lipoprotein (HDL) cholesterol and antithrombotic properties. However, chronic heavy drinking is unequivocally harmful, exacerbating the risk of hypertension, cardiomyopathy, arrhythmias, and ischemic stroke. Moreover, individuals with AALD often present with comorbid cardiovascular conditions, complicating management and prognosis. This study aims to provide a comprehensive overview of the association between AALD and cardiovascular outcomes, including heart failure, which has not been fully understood.

Data Source

The current study utilizes data from the National Health and Nutrition and Examination Survey (NHANES); a nationwide cross-sectional survey that obtains demographic, questionnaire, and laboratory data using a stratified, multistage probability cluster design to provide a representative sample of the civilian, non-institutionalized U.S. population (CDC/NCHS, 2011–2020). The study uses data from four consecutive cycles (2011–2012, 2013–2014, 2015–2016, and 2017–2020). The 2019–2020 data were combined with the 2017–2018 cycle to provide an accurate weighting of the population due to the pause in data collection during the COVID-19 pandemic. All data and methods are made publicly available at the National Center for Health Statistics website (https://www.cdc.gov/nchs/nhanes/index.htm) [8]. The Institutional Review Board from the National Center for Health Statistics of the Centers for Disease Control and Prevention approved all protocols within NHANES including obtained informed consent from all participants.

Study Population

The initial sample consisted of 23,206 participants who were 20 years of age or older and had recorded responses of cardiovascular status and recorded levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Participants with presence of hepatitis B surface antigen and hepatitis C surface antibody were excluded from the study due to both diagnoses having been shown to be risk factors of liver disease. In addition, metabolic syndrome has been reported to increase the risk of non-alcoholic fatty liver disease. The criteria for metabolic syndrome includes comorbidities established by the National Cholesterol Education Program Adult Treatment Panel: waist circumference greater than 102 cm in men or greater than 88 cm in women; serum level of triglycerides of 150 mg/dL or greater; high-density lipoprotein (HDL) cholesterol level of less than 40 mg/dL in men or less than 50 mg/dL in women; systolic/diastolic blood pressure of 130/85 mm Hg or greater or taking hypertension medications; or fasting plasma glucose level of 100 mg/dL or greater or taking diabetes mellitus medications [9]. Participants with any combination of three or more of these commodities were excluded from the study. Finally, women participants who reported that they were currently pregnant at the time of their interview were excluded as well. The final unweighted sample size for analysis was 13,413 participants (Fig. 1).

Alcohol Associated Liver Disease

Serum ALT and AST were used to determine the presence of AALD due to its common use as a screening test and monitoring biomarker for liver disease [10]. From 2011–2016, serum ALT and AST were measured using the Beckman UniCel DxC800 Cynchron (Beckman Coulter, Brea, CA). During the 2017–2020 NHANES cycle, the Roche Cobas 6000 Chemistry Analyzer was used to determine AST and ALT concentrations (Roche Diagnostics Corporation, Indianapolis, IN 46250). The kinetic rate reaction was used to determine serum ALT levels, while enzymatic reaction rates determined levels of AST. Participants with the AST/ALT ratio of greater than 2 U/L or reported high amounts of alcohol consumption (≥ 20 g/day for men and ≥ 10 g/day for women were labeled as AALD positive [11] [12].

Heart Disease and All-Cause Mortality Outcomes

The primary outcome is the prevalence of heart disease along with all-cause mortality. Heart disease was defined as participants who self-reported heart failure, coronary artery disease or stroke during the interview phase of NHANES by answering the question, “Has a doctor or other hearth professional ever told you that you had heart failure?’. Similar question structures were asked to ascertain stroke and coronary artery disease status. Data from NHANES were combined with death certificate data from the National Center of health Statistics from the National Death Index to ascertain mortality rates as well as follow-up time from the participants interview date. Data was limited to 2018, thus survival analysis was restricted to restricted to participants through the year 2018 [13].

Statistical Analysis

All analyses were conducted using the recommended subsample weights, strata, and primary sampling unit to account for the complex survey design utilized within NHANES. Demographic and clinical characteristics were reported using means, 95% confidence intervals for continuous variables, and percentages, 95% confidence intervals for categorical variables. Descriptive statistics were reported within each survey cycle and between patients with AALD and without AALD. Trends in the prevalence of AALD were assessed across the time points within the overall population and within demographic subgroups. In addition, demographic and clinical characteristics were reported between respondents with and without advanced fibrosis among AALD patients. Fibrosis status was calculated using the FIB-4 Score using the formula: ((Age x AST)/(Platelet count x sqrt(ALT)). FIB-4 scores greater than 2.67 were considered advanced fibrosis. Trends in the prevalence of advanced fibrosis were also assessed across the time points within AALD patients and within demographic subgroups. Weighted linear regression and Chi-squared analyses were used for between group comparisons of continuous and categorical variables, respectively.

Among the AALD subgroup, differences in probabilities of survival relative to demographic characteristics were assessed using Kaplan-Meier Curves followed by the LogRank Test. Univariate and multivariable Cox regression were used to ascertain the risk of all-cause mortality among the AALD subgroup. Weighted odds ratios and 95% CI were calculated using logistic regression to ascertain the association between ALFD and heart disease prevalence. Cox regression was used to ascertain the risk of all-cause mortality over time relative to heart disease. All models were adjusted for potential confounding variables such as age, gender, race/ethnicity, education status, income/poverty ratio, insurance status, income/poverty ratio, smoking status, diabetic status, and hypertension status. All p-values were two-sided and p < 0.05 was considered statistically significant. All data analyses were conducted using STATA version 18 (STATACorp; College Station, TX).

Study Population and AALD

Of the study participants, 79.3% reported no AALD, while 20.7% had AALD (Table 1). No statistical differences in age or sex were observed between the groups. However, the percentage of non-Hispanic whites and non-Hispanic blacks were lower among the AALD group compared to the No AALD group (p < 0.001). Conversely, a higher percentage of non-Hispanic Asians were observed within the AALD group. In addition, participants who reported AALD showed a higher percentage of college-educated participants compared to the No AALD group (p < 0.001). More participants who were daily smokers were more likely to be within the AALD group. AALD participants observed a higher percentage of privately insured participants, but a lower percentage of participants with an income to poverty ratio of less than one. Among clinical covariates, AALD participants showed higher mean systolic and diastolic blood pressure as well as fasting glucose levels (p < 0.001). Furthermore, a lower percentage of participants with AALD reported having diabetes. No statistical differences were seen within hypertension prevalence between the groups. Participants with AALD observed a larger mean FIB-4 Score compared to those without AALD (1.14 vs 1.03). Furthermore, a larger percentage of AALD participants observed advanced fibrosis compared to participants without AALD. No statistically significant trends were seen across the NHANES cycle within the overall population or demographic subgroups (Table 2).

Table 1

Survey-weighted characteristics of the study population by alcoholic associated liver disease (AALD) status.
Variables	No AALD (n = 11,130)	Yes AALD (n = 2,283)	p-value¹
Age (years), mean (95% CI)	44.4 (43.7, 45.1)	45.0 (43.9, 46.1)	0.16
Sex, % (95% CI) Male Female	48.1 (46.8, 49.2) 51.9 (50.7, 53.2)	47.9 (45.3, 50.7) 52.0 (49.3, 54.7)	0.97
Race, % (95% CI) Non-Hispanic White Non-Hispanic Black Non-Hispanic Asian Mexican American Other Hispanic Multiracial	63.6 (59.8, 67.3) 11.0 (9.23, 13.1) 5.82 (4.88, 6.93) 9.40 (7.68, 11.5) 7.14 (56.9, 8.61) 3.00 (2.57, 3.49)	75.9 (72.6, 79.1) 9.02 (7.43, 10.9) 2.04 (1.84, 3.13) 5.36 (4.17, 6.86) 4.36 (3.33, 5.65) 2.88 (2.18, 3.79)	< 0.001
Education, % (95% CI ) < High School High School Some College College and Above	13.2 (11.7, 14.8) 21.6 (20.2, 23.1) 31.5 (29.8, 33.2) 33.7 (31.2, 36.4)	7.37 (5.86, 9.20) 15.9 (14.0, 10.2) 30.6 (27.9, 33.4) 46.1 (41.9, 50.3)	< 0.001
Marital Status, % (95% CI) Married Widowed Divorced Separated Never Married Other	54.6 (52.7, 56.9) 7.54 (6.90, 8.23) 12.3 (11.2, 13.4) 1.54 (1.28, 1.84) 17.1 (15.4, 18.9) 6.70 (5.94, 7.56)	55.6 (52.7, 58.7) 6.09 (5.03, 7.36) 13.7 (11.9, 15.7) 1.82 (1.23, 2.71) 15.7 (13.4, 18.2) 6.92 (5.46, 8.74)	0.22
Insurance Status, % (95% CI) Private Medicare Medicaid Other	53.8 (51.6, 55.9) 13.8 (12.6, 14.9) 7.48 (6.62, 8.45) 24.9 (23.2, 26.9)	61.3 (57.7, 64.8) 12.9 (10.9, 15.1) 4.50 (3.61, 5.61) 21.3 (18.6. 24.3)	< 0.001
Income to Poverty Ratio, % (95% CI) < 1 ≥ 1	14.9 (13.4, 16.6) 85.1 (83.3, 86.6)	10.3 (8.48, 12.5) 89.7 (87.5, 91.5)	< 0.001
Smoking Status, % (95% CI) Never Former Current non-daily Current Daily	0.06 (0.022, 0.16) 20.5 (19.4, 21.7) 62.4 (60.8, 64.0) 17.0 (15.6, 18.4)	0.01 (0.001, 0.076) 25.7 (23.0, 28.5) 49.9 (46.8, 53.2) 24.3 (22.1, 26.7)	< 0.001
Alcohol Consumption (g/day), mean (95% CI)	1.68 (1.56, 1.80)	38.5 (36.5, 40.6)	< 0.001
BMI (kg/m^2), mean (95% CI)	27.6 (27.4, 27.8)	26.5 (26.3, 26.8)	< 0.001
Waist Circumference (cm), mean (95% CI)	94.6 (94.1, 95.1)	93.2 (92.5, 93.9)	0.001
Triglycerides (mg/dL), mean (95% CI)	115.6 (112.9, 118.2)	120.9 (113.2, 128.6)	0.19
HDL (mg/dL), mean (95% CI)	56.6 (56.1, 57.2)	64.6 (63.6, 65.6)	< 0.001
LDL (mg/dL), mean (95% CI)	111.9 (110.7, 113.1)	110.8 (107.5, 114.1)	0.52
Diabetes Status, % (95% CI)	3.17 (2.71, 3.71)	1.35 (0.87, 2.11)
Hypertension Status, % (95% CI)	17.8 (16.9, 18.8)	18.1 (16.2, 20.3)	0.75
Fibrosis-4 score > 2.67, % (95% CI)	2.23 (1.86, 2.68)	3.90 (2.96, 5.12)	0.001
¹Weighted Linear regression to compare continuous variables between patients with and without AALD. Weighted Chi-squared analysis to compare categorical variables between the groups.

Table 2

Trends in AALD prevalence over time within the overall population and stratification by participant demographic characteristics and SES. P-values calculated using Weighted Logistic Regression following stratification.
Variables (N = 13,413)	2011–2012 (n = 2,916)	2013–2014 (n = 3,183)	2015–2016 (n = 2,903)	2017–2020 (n = 4,411)	p-trend
	% (95% CI)	% (95% CI)	% (95% CI)	% (95% CI)
Overall	22.0 (19.5, 24.7)	20.3 (17.8, 23.0)	19.4 (16.2, 23.1)	20.9 (19.2, 22.9)	0.45
Age (years)
20–29	23.0 (18.3, 28.5)	19.6 (16.3, 23.3)	15.0 (12.2, 18.3)	19.9 (16.1, 24.3)	0.045
30–39	18.6 (14.8, 23.3)	17.3 (12.7, 22.9)	17.5 (13.3, 22.6)	21.8 (18.1, 25.9)	0.48
40–49	22.5 (18.2, 27.4)	22.1 (16.8, 28.5)	25.6 (20.2, 31.9)	22.9 (17.9, 28.9)	0.79
50–59	22.9 (15.7, 32.3)	20.5 (15.9, 26.0)	24.2 (18.1, 31.7)	21.6 (17.3, 26.6)	0.83
60–69	23.7 (16.6, 32.7	24.9 (19.3, 31.4)	17.2 (10.4, 27.0)	20.1 (15.2, 25.8)	0.41
≥ 70	22.3 (18.3, 26.9)	18.9 (15.0, 23.6)	18.3 (13.5, 24.3)	18.9 (15.2, 23.3)	0.62
Sex Male Female	22.5 (20.6, 24.5) 21.6 (17.9, 25.9)	20.3 (16.5, 24.7) 20.2 (18.1, 22.6)	19.5 (15.5, 24.3) 19.4 (15.9, 23.4)	20.3 (16.9, 24.3) 21.6 (19.3, 24.1)	0.69 0.69
Race Non-Hispanic White Non-Hispanic Black Non-Hispanic Asian Mexican American Other Hispanic Multiracial	25.1 (21.1, 29.6) 18.4 (15.9, 21.2) 12.2 (9.11, 16.2) 11.5 (8.53, 15.5) 13.9 (10.4, 18.5) 23.0 (14.0, 35.4)	22.9 (19.8, 26.4) 18.1 (15.3, 21.3) 9.64 (6.35, 14.4) 14.7 (9.50, 22.0) 14.6 (9.51, 21.7) 14.6 (7.02, 27.9)	22.9 (18.3, 28.4) 14.9 (12.6, 17.7) 6.75 (4.55, 9.90) 10.7 (8.99, 12.6) 10.8 (8.19, 14.2) 22.3 (13.8, 34.1)	23.9 (21.1, 26.9) 18.9 (16.9, 21.0) 10.6 (8.13, 13.6) 14.5 (11.9, 17.4) 15.2 (10.8, 20.9) 19.9 (12.2, 30.8)	0.65 0.90 0.17 0.84 0.94 0.57
Insurance Status, % (95% CI) Private Medicare Medicaid Other	24.8 (20.8, 29.3) 20.4 (14.9, 27.1) 11.9 (7.86, 17.9) 19.0 (15.2, 23.6)	22.3 (19.5, 25.3) 20.5 (15.8, 26.3) 14.9 (11.6, 19.1) 17.0 (13.0, 21.9)	20.0 (16.3, 26.7) 19.8 (14.1, 27.2) 13.8 (9.01, 20.7) 17.0 (13.5, 21.2)	23.6 (21.3, 25.9) 17.9 (15.1, 21.3) 13.1 (9.57, 17.7) 19.8 (15.8, 24.4)	0.53 0.45 0.80 0.86
Income to Poverty Ratio, % (95% CI) < 1 ≥ 1	15.8 (12.7, 19.4) 23.6 (20.7, 26.7)	15.8 (11.8, 20.9) 21.4 (18.6, 24.5)	12.3 (8.41, 17.6) 20.8 (17.4, 24.8)	19.0 (14.7, 24.2) 22.4 (20.6, 24.4)	0.62 0.49
Diabetes
No	22.3 (19.8, 25.1)	20.6 (18.1, 23.3)	19.8 (16.5, 23.6)	21.2 (19.3, 23.3)	0.45
Yes	6.28 (3.11, 12.3)	9.53 (3.79, 21.9)	9.89 (3.70, 23.9)	13.6 (6.94, 24.9)	0.55
Hypertension
No	22.3 (19.6, 25.2)	20.4 (18.0, 23.0)	18.9 (15.1, 23.4)	20.9 (18.8, 23.1)	0.32
Yes	20.8 (17.6, 24.5)	19.8 (15.5, 24.7)	22.2 (18.4, 26.5)	21.5 (18.1, 25.3)	0.56

Study Population and Advanced Fibrosis

Advanced fibrosis status was reported in 5.69% of the AALD participants (Unweighted N = 2,283) (Table 3). Statistical differences in age and race/ethnicity were observed between the groups. The mean age of participants with advanced fibrosis was 64.1 years compared to 44.3 years within the comparison group. The percentage of non-Hispanic whites were higher among the advance fibrosis group compared to the non-advanced group (p = 0.01). Furthermore, advanced fibrotic participants showed a higher proportion of participants with less than high school education (10.7% vs 7.23%), on Medicare insurance (46.6% vs 11.5%), and those who are widowed (18.5% vs 5.59%) (p < 0.001). More participants who were never/former smokers were more likely to be within the advanced fibrosis group (33.3% vs 25.4%). Laboratory values show higher HDL levels among the advanced fibrosis group (p = 0.069). Conversely, LDL (p = 0.01) and triglyceride levels (p = 0.001) were statistically lower among advanced fibrosis participants. In addition, a larger proportion of advanced fibrotic participants reported having been told of their diabetes and hypertension diagnoses. In terms of advanced fibrotic trends, no statistically significant trends were seen across the NHANES cycles (p = 0.96). Furthermore, stratification analysis did not show statistically significant trends within each subgroup (Table 4).

Table 3

Survey-weighted characteristics of the AALD patients by FIB-4 categories.
Variables	FIB-4 Score < 2.67 (n = 2,153)	FIB-4 Score > 2.67 (n = 130)	p-value¹
Age (years), mean (95% CI)	44.3 (43.2, 45.3)	64.1 (59.9, 68.2)	< 0.001
Sex, % (95% CI) Male Female	47.9 (45.3, 50.7) 52.1 (49.3, 54.7)	47.8 (34.8, 61.1) 52.1 (38.8, 65.2)	0.98
Race, % (95% CI) Non-Hispanic White Non-Hispanic Black Non-Hispanic Asian Mexican American Other Hispanic Multiracial	75.9 (72.3, 79.0) 8.84 (7.24, 10.7) 2.43 (1.85, 3.17) 5.59 (4.26, 7.07) 4.42 (3.36, 5.78) 2.97 (2.23, 3.92)	79.2 (71.6, 85.2) 13.5 (8.94, 19.9) 1.76 (0.71, 4.26) 1.94 (0.73, 5.07) 2.76 (1.41, 5.36) 0.79 (0.24, 2.56)	0.01
Education, % (95% CI ) < High School High School Some College College and Above	7.23 (5.69, 9.14) 15.8 (13.8, 18.0) 30.6 (27.8, 33.5) 46.3 (42.2, 50.5)	10.7 (6.84, 16.4) 20.2 (12.1, 31.9) 29.1 (19.9, 40.4) 39.9 (28.6, 52.5)	0.38
Marital Status, % (95% CI) Married Widowed Divorced Separated Never Married Other	55.9 (52.9, 58.8) 5.59 (4.52, 6.89) 13.7 (11.9, 15.6) 1.73 (1.15, 2.61) 16.1 (13.8, 18.7) 6.98 (5.47, 8.89)	52.4 (40.9, 63.5) 18.5 (12.3, 27.0) 14.9 (7.21, 28.2) 4.00 (1.03, 14.3) 4.85 (2.49, 9.23) 5.39 (2.12, 12.9)	< 0.001
Insurance Status, % (95% CI) Private Medicare Medicaid Other	62.5 (58.9, 65.9) 11.5 (9.63, 13.7) 4.38 (3.45, 5.53) 21.6 (18.8, 24.7)	31.1 (18.6, 46.6) 46.6 (34.9, 58.7) 7.62 (3.39, 16.2) 14.7 (8.90, 23.2)	< 0.001
Income to Poverty Ratio, % (95% CI) < 1 ≥ 1	10.2 (8.34, 12.3) 89.8 (87.7, 91.7)	14.1 (8.12, 23.2) 85.9 (76.8, 91.9)	0.23
Smoking Status, % (95% CI) Never Former Current non-daily Current Daily	0.01 (0.001, 0.08) 25.4 (22.7, 28.2) 50.2 (47.1, 53.4) 24.4 (22.0, 26.9)	0 33.3 (22.5, 28.2) 43.9 (32.9, 53.4) 22.8 (13.8, 32.2)	0.39
Alcohol Consumption (g/day), mean (95% CI)	38.8 (36.7, 40.8)	32.2 (24.6, 39.7)	0.09
BMI (kg/m^2), mean (95% CI)	26.5 (26.3, 26.8)	25.7 (24.1, 27.2)	0.27
Waist Circumference (cm), mean (95% CI)	93.2 (92.5, 93.9)	94.0 (89.7, 98.4)	0.71
Triglycerides (mg/dL), mean (95% CI)	121.6 (113.6, 129.6)	104.1 (97.2, 111.0)	0.001
HDL (mg/dL), mean (95% CI)	64.4 (63.3, 65.4)	70.0 (64.1, 75.9)	0.069
LDL (mg/dL), mean (95% CI)	111.5 (107.8, 112.2)	95.3 (88.8, 107.8)	0.01
Diabetes, % (95% CI)	1.29 (0.80, 2.08)	2.91 (1.32, 6.31)	0.07
Hypertension, % (95% CI)	17.4 (15.4, 19.6)	36.3 (26.5, 47.4)	< 0.001
¹Weighted Linear regression to compare continuous variables between patients with and without AALD. Weighted Chi-squared analysis to compare categorical variables between the groups.

Table 4

Trends in Advanced Fibrosis (FIB-4 > 2.67) over time within AALD patients and stratification by participant demographic characteristics and SES.
Variables (N = 13,413)	2011–2012 (n = 2,916)	2013–2014 (n = 3,183)	2015–2016 (n = 2,903)	2017–2020 (n = 4,411)	p-trend
	% (95% CI)	% (95% CI)	% (95% CI)	% (95% CI)
Overall	3.45 (2.17, 5.45)	4.41 (2.45, 6.93)	5.02 (2.58, 9.52)	3.09 (2.07, 4.57)	0.96
Age (years)
20–29	0	0.63 (0.15, 2.62)	1.92 (0.26, 12.9)	5.26 (0.13, 2.17)	0.38
30–39	0.60 (0.14, 2.46)	2.51 (0.47, 12.4)	0.90 (0.13, 5.84)	0.45 (0.06, 3.59)	0.33
40–49	0.37 (0.05, 2.52)	0.91 (0.19, 4.19)	3.66 (1.03, 12.2)	2.75 (0.73, 9.79)	0.29
50–59	4.09 (0.97, 15.6)	6.35 (2.01, 18.3)	4.15 (0.80, 18.9)	2.88 (1.35, 6.02)	0.77
60–69	3.47 (0.70, 15.4)	2.17 (0.89, 5.23)	11.4 (3.39, 32.3)	2.16 (0.64, 7.02)	0.65
≥ 70	21.4 (13.9, 38.9)	22.8 (12.6, 37.7)	16.7 (9.18, 28.5)	17.3 (10.4, 27.3)	0.35
Sex Male Female	4.33 (2.06, 8.87) 2.59 (0.99, 6.57)	2.76 (1.03, 7.15) 5.47 (3.16, 9.28)	4.61 (0.19, 10.6) 5.39 (2.46, 11.2)	3.91 (2.49, 6.08) 2.39 (1.17, 4.86)	0.394 0.96
Race Non-Hispanic White Non-Hispanic Black Non-Hispanic Asian Mexican American Other Hispanic Multiracial	3.59 (2.06, 6.19) 4.36 (2.02, 9.19) 3.31 (0.76, 13.3) 1.36 (0.19, 8.92) 3.39 (0.88, 12.1) 0	4.29 (2.25, 8.05) 6.57 (2.61, 15.6) 3.20 (0.45, 19.3) 1.15 (0.26, 4.96) 1.86 (0.41, 7.99) 2.49 (0.30, 17.6)	5.43 (2.51, 11.4) 6.83 (4.10, 11.2) 0 1.03 (0.13, 7.53) 4.42 (1.51, 12.2) 0	2.29 (1.79, 4.96) 5.69 (3.65, 8.76) 3.91 (1.18, 12.1) 2.00 (0.31, 11.9) 1.11 (0.13, 8.95) 2.29 (0.49, 9.99)	0.93 0.80 0.72 0.88 0.49 0.52
Insurance Status, % (95% CI) Private Medicare Medicaid Other	0.95 (0.21, 4.13) 21.7 (13.3, 33.2) 1.49 (0.18, 11.1) 1.61 (0.76, 3.37)	1.63 (0.54, 4.79) 15.1 (7.89, 26.9) 15.5 (4.76, 40.1) 2.32 (0.79, 6.66)	4.52 (1.65, 11.8) 9.20 (4.51, 17.9) 4.24 (0.97, 16.6) 3.58 (0.92, 12.9)	1.09 (1.65, 11.8) 11.7 (4.51, 17.9) 2.88 (0.97, 16.6) 3.48 (0.82, 12.9)	0.31 0.085 0.45 0.34
Income to Poverty Ratio, % (95% CI) < 1 ≥ 1	6.20 (2.66, 13.7) 3.10 (1.89, 5.05)	5.51 (2.22, 12.6) 4.23 (2.38, 7.42)	3.63 (1.08, 11.5) 4.88 (2.22, 10.4)	4.99 (2.26, 10.6) 2.60 (1.52, 4.41)	0.55 0.84
Diabetes
No	3.37 (2.09, 5.39)	4.15 (2.45, 6.96)	4.93 (2.52, 9.45)	2.98 (1.96, 4.51)	0.97
Yes	18.7 (2.64, 66.2)	2.75 (0.31, 20.1)	9.76 (1.89, 37.7)	7.84 (2.11, 25.1)	0.87
Hypertension
No	2.52 (1.31, 4.79)	3.49 (1.91, 6.29)	4.33 (2.07, 8.83)	1.94 (11.4, 3.28)	0.67
Yes	7.98) (5.11, 12.3)	6.73 (3.01, 14.4)	8.03 (2.66, 21.8)	8.69 (4.99, 14.7)	0.69
P-values calculated using Weighted Logistic Regression following stratification.

Survival Analysis

Statistical differences in survival probabilities were observed between age categories. Age groups less than 70 years of age ranged from 92–98%. However, participants over 70 years of age showed a survival probability of 55% (p < 0.001) (Fig. 2). Differences in the probability of survival were also observed relative to BMI categories, insurance status, and marital status. Underweight participants reported lower survival probabilities compared to the other BMI categories (83% vs 93%) (p = 0.005). In addition, participants with Medicare and Medicaid insurance observed the lowest probability of survival compared to private insurance status. Finally, widowed participants reported 60% probability of survival compared to 94% within the married category (p < 0.001).

Univariate Cox regression showed a 5-fold increase in the risk of all-cause mortality among 60–69-year age group compared to the 20–29-year age group (HR (95% CI) = 5.26 (1.38, 20.0); p = 0.016). Furthermore, the risk of all-cause mortality was 27-times higher among participants over 70 years of age compared to the youngest age group. Mortality risk within the adjusted model showed larger risks within the same age groups. Non-Hispanic Asians observed the lowest risk of mortality compared to Whites (HR (95% CI) = 0.26 (0.073, 0.91); p = 0.035). Furthermore, Mexican Americans and other Hispanic categories, although not significant, showed a decreased risk of mortality compared to the White group. Participants with Medicare or Medicaid insurance reported a 12-fold and 6.8-fold increase in the risk of mortality compared to participants with private insurance (p < 0.001). Within the adjusted model, the other Hispanic category showed a 75% decrease in the risk of mortality compared the White group. In addition, participants with underweight BMI status showed a 5-fold increase in mortality risk compared to normal BMI. Medicare insurance status did not show an association with mortality risk. However, participants with Medicaid insurance reported a 3-fold increase in mortality risk compared to private insurance status (HR (95% CI) = 2.97 (1.39, 6.34); p = 0.006) (Table 5).

Table 5

Cox Regression to assess the risk of all-cause mortality relative to demographic characteristics among AFLD patients.
Variables (N = 2,283)	Univariate		Multivariable
	HR (95% CI)	p-value	HR (% CI)	p-value
Age (years)
20–29	REF		REF
30–39	2.53 (0.56, 11.4)	0.22	3.31 (0.60, 18.3)	0.16
40–49	2.37 (0.50, 11.3)	0.27	4.11 (0.89, 18.9)	0.068
50–59	2.45 (0.58, 10.3)	0.22	3.91 (0.52, 29.8)	0.18
60–69	5.26 (1.38, 20.0)	0.016	10.2 (1.56, 66.5)	0.016
≥ 70	27.3 (9.85, 75.7)	< 0.001	55.7 (8.91, 347.6)	< 0.001
Sex Male Female	REF 0.93 (0.57, 1.50)	0.75	REF 0.69 (0.39, 1.22)	0.19
Race Non-Hispanic White Non-Hispanic Black Non-Hispanic Asian Mexican American Other Hispanic Multiracial	REF 1.13 (0.68, 1.84) 0.26 (0.073, 0.91) 0.43 (0.17, 1.08) 0.26 (0.058, 1.17) 0.38 (0.08, 1.67)	0.63 0.035 0.072 0.077 0.19	REF 0.78 (0.38, 1.58) 0.45 (0.074, 2.75) 0.43 (0.14, 1.33) 0.25 (0.056, 1.11) 0.31 (0.055, 1.70)	0.48 0.38 0.14 0.068 0.17
BMI
18.5 to 25	REF		REF
< 18.5	5.36 (2.11, 13.6)	0.001	4.99 (1.94, 12.8)	0.001
25 to 29.9	1.55 (0.98, 2.43)	0.057	1.52 (0.84, 2.75)	0.16
> 30	0.98 (0.45, 2.16)	0.96	1.18 (0.52, 2.67)	0.68
Education < High School High School Some College College and Above	REF 1.46 (0.58, 3.64) 0.66 (0.29, 1.51) 0.32 (0.15, 0.67)	0.41 0.31 0.003	REF 2.04 (0.65, 6.39) 0.85 (0.36, 1.96) 0.47 (0.17, 1.28)	0.22 0.69 0.14
Marital Status Married Widowed Divorced Separated Never Married Other	REF 7.42 (3.55, 15.5) 1.11 (0.59, 2.07) 1.62 (0.22, 12.1) 0.87 (0.39, 1.93) 1.14 (0.43, 3.05)	< 0.001 0.75 0.63 0.74 0.77	REF 1.89 (0.83, 4.31) 0.98 (0.47, 2.05) 2.69 (0.29, 24.3) 2.58 (0.76, 8.69) 1.69 (0.49, 5.93)	0.13 0.96 0.37 0.12 0.39
Insurance Status, % (95% CI) Private Medicare Medicaid Other	REF 11.9 (7.76, 18.3) 6.84 (2.98, 15.7) 2.69 (1.28, 5.70)	< 0.001 < 0.001 0.01	REF 1.15 (0.42, 3.13) 2.97 (1.39, 6.34) 1.42 (0.61, 3.26)	0.77 0.006 0.40
Income to Poverty Ratio, % (95% CI) < 1 ≥ 1	REF 0.45 (0.23, 0.91)	0.026	REF 0.47 (0.18, 1.25)	0.13
Smoking Status, % (95% CI) Never/Former Current non-daily Current Daily	REF 0.53 (0.32, 0.88) 0.93 (0.48, 1.76)	0.016 0.81	REF 0.93 (0.52, 1.68) 1.14 (0.53, 2.47)	0.82 0.74
Diabetes
No	REF		REF
Yes	0.20 (0.025, 1.61)	0.13	0.27 (0.031, 2.34)	0.23
Hypertension
No	REF		REF
Yes	2.87 (1.49, 5.52)	0.002	1.14 (0.56, 2.30)	0.71
Univariate Cox Regression with no Adjustments.
Multivariable Cox Regression adjusting for all other variables within the model.

AALD and Heart Disease

Of the cardiovascular outcomes, participants with COPD constituted the largest percentage of the overall population followed participants with stroke (5.49%, and 2.04%, respectively). Heart failure and CAD were prevalent in 1.21% and 1.97% of the total population, respectively. The composite outcome of heart disease prevalence comprised of 4.33% of the population. Although not statistically significant, a slightly lower percentage of participants with heart disease was observed within the AALD group (3.71% vs 4.49%). Similar differences are seen with respect to heart failure and CAD. Conversely, a slightly larger percentage of participants within the AALD group reported COPD and cancer. After controlling for potential confounding variables, logistic regression did not show statistically significant associations between AALD status with the cardiovascular outcomes (Table 3). However, a clinically noticeable increase in the odds of stroke was seen within the AALD group (OR (95% CI) = 2.24 (0.77, 6.56).

Heart Disease and All-Cause Mortality

The mortality rate within the overall population was approximately 40%. After stratification by heart disease status, the mortality rate among heart disease patients was 25% compared to 3% among participants without heart disease. After further stratification by AALD status, participants with heart disease observed mortality rates that are statistically higher compared to those without heart disease (Fig. 1). Cox regression reported an 86% increase in the risk of all-cause mortality within participants with heart disease compared to those without heart disease (HR (95% CI) = 1.86 (1.15, 3.01; p = 0.012) (Table 4). Furthermore, participants with heart failure and COPD showed higher risks of mortality within the overall population. After stratification by AALD status, the risk of all-cause mortality was still significantly higher among heart diseased participants without AALD, but not participants with AALD. Similar trends are observed relative to heart failure status. Conversely, the risk of mortality among subjects with stroke and COPD were not statistically significant within the population that reported no AALD. However, among participants who were prevalent with AALD Showed an increased risk of mortality relative to COPD and stoke.

This study provides an in-depth analysis of the association between AALD and CVD, utilizing data from the NHANES spanning from 2011 to 2020. The study, characterized by a stratified, multistage probability cluster design, included a final unweighted sample size of 13,413 participants and adjusted for a comprehensive set of confounding variables. AALD was identified based on clinical laboratory data and self-reported alcohol use, with a fibrosis-4 (FIB-4) score greater than 2.67 indicating significant liver fibrosis. Cardiovascular conditions were assessed through self-reports of heart failure, CAD, and stroke. Key findings include a higher prevalence of AALD among Asians compared to other demographics, with higher rates of college education and daily smoking observed among AALD participants. Those with AALD exhibited higher mean systolic and diastolic blood pressure as well as elevated fasting glucose levels, indicating a generally poorer health status. The mortality rate among participants with both AALD and CVD was significantly higher (25%) compared to those without CVD (3%). Although no statistically significant associations were found between AALD status and heart failure (HF) or coronary artery disease (CAD) after adjusting for confounding variables, a clinically significant increase in the odds of stroke was observed within the AALD group.

The higher prevalence of AALD among Asians and individuals with higher education levels and daily smoking habits underscores the need for targeted public health interventions. These findings indicate that cultural, educational, and behavioral factors play a significant role in the development of AALD, aligning with previous research that suggests certain demographic groups may be more susceptible due to genetic predispositions, lifestyle choices, and socioeconomic factors. For instance, genetic polymorphisms in alcohol-metabolizing enzymes prevalent among Asians can lead to variations in susceptibility to alcohol-related liver damage [14], while the association with higher education levels and daily smoking habits points to the influence of socioeconomic and lifestyle factors on AALD prevalence. The AALD prevalence is higher in whites and blacks, but the trend is increasing in Mexican Americans' and Hispanics, while it decreased among other demographics [Table 2]. The prevalence in private insurance is significantly greater than Medicaid, but the usage trends have been increasing in Medicaid [Table 2]. The trends of advanced fibrosis has been increasing in blacks and Asians, while it is decreasing among whites and Mexicans [Table 4]. There is an increasing trends in usage of private and Medicaid insurance, while usage of Medicare is decreasing [Table 4]. The study's findings on the high prevalence of AALD in Asian populations also resonate with research published in Liver International, which discusses genetic predispositions and environmental factors contributing to higher rates of liver disease in Asian populations [15].

Elevated blood pressure and fasting glucose levels among AALD participants highlight the broader health impacts of chronic alcohol consumption, stressing the need for integrated healthcare approaches to manage these comorbidities effectively. These indicators, well-known risk factors for both liver disease and cardiovascular conditions, are consistent with the study's findings that individuals with AALD exhibit higher markers of poor cardiovascular and metabolic health. Chronic alcohol consumption can lead to hypertension and insulin resistance, which are established risk factors for liver disease and cardiovascular conditions [16]. The elevated prevalence of heart failure, stroke, and coronary artery disease among those with AALD further highlights the compounded health risks faced by this population.

The significantly higher mortality rate among participants with both AALD and CVD (25%) compared to those without CVD (3%) emphasizes the severe health implications of these comorbid conditions. This stark difference highlights the critical need for early detection and integrated management of both AALD and CVD to reduce mortality risk. Comprehensive screening programs that include both liver and cardiovascular health assessments are crucial, as they can help identify at-risk individuals and implement timely interventions. The heightened vulnerability of individuals with coexisting AALD and CVD also emphasizes the importance of coordinated healthcare approaches to address these interrelated health issues effectively [17].

The study's findings indicate that, after adjusting for confounders, there are no statistically significant associations between AALD and HF or CAD. However, the clinically significant increase in the odds of stroke within the AALD group is particularly concerning. This suggests that while AALD may not directly influence the incidence of HF or CAD, it substantially impacts stroke risk. This could be due to shared pathophysiological mechanisms such as chronic inflammation, endothelial dysfunction, and coagulation abnormalities associated with chronic alcohol use and liver disease, which contribute to the increased stroke risk in AALD patients [18]. This study aligns with other research findings on the relationship between liver disease and cardiovascular health. For instance, a study published in the Journal of Hepatology indicated that liver diseases, including AALD, are associated with an increased risk of cardiovascular events, particularly stroke [19]. Another study in Hepatology explored the role of systemic inflammation and endothelial dysfunction in patients with AALD, suggesting these pathways as potential mechanisms for the increased cardiovascular risk observed in these patients [20].

Given the intertwined nature of AALD, public health strategies should prioritize reducing alcohol consumption through regulatory measures, public awareness campaigns, and support for smoking cessation. Routine screening for liver disease and cardiovascular risk factors in individuals with significant alcohol use is essential for early intervention and management. The integration of care services involving hepatologists, cardiologists, nutritionists, and mental health professionals is crucial for addressing the multifaceted needs of individuals with AALD and CVD. Future research should aim to elucidate the underlying mechanisms linking AALD with increased stroke risk and explore potential interventions to mitigate this risk. Longitudinal studies could provide more insight into the causal relationships between chronic alcohol use, liver disease, and cardiovascular outcomes [21]. Additionally, research should consider the impact of genetic and environmental factors on different demographic groups to develop targeted prevention and treatment strategies.

AALD

Alcohol-associated liver disease

AST

Aspartate aminotransferase

ALT

Alanine aminotransferase (ALT)

CAD

coronary artery disease

CDC

Centers for Disease Control

CVD

Cardiovascular diseases

FIB-4

Fibrosis-4

HCC

Hepatocellular carcinoma

HDL

High-density lipoprotein (HDL)

HF

Heart failure

NHANES

National Health and Nutrition and Examination Survey

WHO

World Health Organization

Acknowledgements: None

Institutional Review Board Approval: Not needed as the data has been collected from public databases.

Ethics approval and consent to participate: Not applicable.

Consent for publication: Not applicable.

Availability of data and material: Data has been collected from pubmed and google scholar

Conflict of interests: The authors declare that they have no competing interests.

Financial Disclosures/Funding: Not applicable.

Informed Consent: Not applicable

Authors' contributions: SC, as the first author generated the idea, collected articles, and contributed to most of the sections, and was a major contributor to writing the manuscript. TZ as a second author gathered relevant articles and contributed to the discussion section of the manuscript. KP as a third author contributed to collecting data and running statistics. JR and RW as a senior author reviewed the article and made necessary changes to the manuscript. All authors read and approved the final manuscript.

Acknowledgments: Not applicable.

Devarbhavi H, et al. Global burden of liver disease: 2023 update. J Hepatol. 2023;79(2):516–537. doi: 10.1016/j.jhep.2023.03.017.
Mackowiak B, Fu Y, Maccioni L, Gao B. Alcohol-associated liver disease. J Clin Invest. 2024;134(3):e176345. doi: 10.1172/JCI176345.
World Health Organization. (2024). Global status report on alcohol and health and treatment of substance use disorders. Geneva: World Health Organization.
Tom Ryu, Kyurae Kim, Sung Eun Choi, Katherine Po Sin Chung, Won-Il Jeong. New insights in the pathogenesis of alcohol-related liver disease: The metabolic, immunologic, and neurologic pathways. Liver Research, 2023 Mar, 7(1) 1–8. https://doi.org/10.1016/j.livres.2022.09.004
Vaduganathan, M, Mensah, G, Turco, J. et al. The Global Burden of Cardiovascular Diseases and Risk: A Compass for Future Health. JACC. 2022 Dec, 80 (25) 2361–2371. https://doi.org/10.1016/j.jacc.2022.11.005
World Health Organization.2021. Cardiovascular diseases. Geneva: World Health Organization; 2021.
Bays HE, Kulkarni A, German C, Satish P, Iluyomade A, Dudum R, Thakkar A, Rifai MA, Mehta A, Thobani A, Al-Saiegh Y, Nelson AJ, Sheth S, Toth PP. Ten things to know about ten cardiovascular disease risk factors – 2022. Am J Prev Cardiol. 2022;10:100342. doi: 10.1016/j.ajpc.2022.100342. PMID: 35517870; PMCID: PMC9061634.
CDC/NCHS, 2011–2020. NHANES - Questionnaires, Datasets, and Related Documentation.
Aguilar M, Bhuket T, Torres S, Liu B, Wong RJ. Prevalence of the metabolic syndrome in the United States, 2003–2012. JAMA. 2015;313(19):1973–1974. doi: 10.1001/jama.2015.4260
Hadizadeh, F., Faghihimani, E., Adibi, P., 2017. Nonalcoholic fatty liver disease: diagnostic biomarkers. World J. Gastrointest. Pathophysiol. 8, 11. https://doi.org/10.4291/wjgp.v8.i2.11.
Williams AL, Hoofnagle JH, Ratio of serum aspartate to alanine aminotransferase in chronic hepatitis. Relationship to cirrhosis. Gastroenterology. 1988;95(3):734–9.doi: 10.1016/s0016-5085(88)80022-2.
Wong T, Dang K, Ladhani S, Singal AK, Wong RJ. Prevalence of Alcoholic Fatty Liver Disease Among Adults in the United States, 2001–2016. JAMA. 2019; 321(17): 1723–1725.
NCHS Data Linkage - Mortality Data - Public-Use Files [Internet]. 2021 [cited 2022 Feb 16]; Available from: https://www.cdc.gov/nchs/data-linkage/mortality-public. htm.
Chen, L., et al. (2017). Genetic polymorphisms and alcohol consumption: implications for liver disease susceptibility. World Journal of Gastroenterology, 23(9), 1546–1561.
Xu H, Xiao P, Zhang F, Liu T, Gao Y. Epidemic characteristics of alcohol-related liver disease in Asia from 2000 to 2020: A systematic review and meta-analysis. Liver Int. 2022;42(9):1991–1998. doi: 10.1111/liv.15312. Epub 2022 May 27. PMID: 35593004.
Rehm, J., et al. (2019). The relationship between different dimensions of alcohol use and the burden of disease—an update. Addiction, 114(4), 519–530.
Mokdad, A. A., et al. (2018). Liver disease mortality in the United States: Findings from the Global Burden of Disease Study 2017. JAMA Network Open, 1(4), e180237.
O'Shea, R. S., et al. (2010). Alcoholic liver disease. Hepatology, 51(1), 307–328.
Platek AE, Szymanska A. Metabolic dysfunction-associated steatotic liver disease as a cardiovascular risk factor. Clin Exp Hepatol. 2023;9(3):187–192. doi: 10.5114/ceh.2023.130744. Epub 2023 Aug 28. PMID: 37790680; PMCID: PMC10544058.
Vairappan B. Endothelial dysfunction in cirrhosis: Role of inflammation and oxidative stress. World J Hepatol. 2015;7(3):443–59. doi: 10.4254/wjh.v7.i3.443. PMID: 25848469; PMCID: PMC4381168.
European Association for the Study of the Liver (2018). EASL Clinical Practice Guidelines: Management of alcohol-related liver disease. Journal of Hepatology, 69(1), 154–181.

No competing interests reported.

From Liver to Heart: Insights on Alcohol-Associated Liver Disease and Cardiovascular Outcomes, A Decade of Data from National Survey

Status:

Version 1

Abstract

Figures

Introduction

Methods

Data Source

Study Population

Alcohol Associated Liver Disease

Heart Disease and All-Cause Mortality Outcomes

Statistical Analysis

Results

Study Population and AALD

Study Population and Advanced Fibrosis

Survival Analysis

AALD and Heart Disease

Heart Disease and All-Cause Mortality

Discussion

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1