Association between obesity and liver enzyme levels: a cross-sectional observational study among individuals visiting a diagnostic laboratory in Burdwan, West Bengal

INTRODUCTION

According to the World Health Organization (WHO), 650 million people worldwide are obese and over 1.9 billion people are overweight. Over the past 40 years, there has been a considerable increase in overweight and obesity among individuals in the age range of 5 to 19 years.¹ Obesity is a risk factor for several chronic noncommunicable diseases such as cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), musculoskeletal disorders, and cancers. Apart from this, it also has severe pathophysiological, psychological, social, and financial consequences for individuals and their families.² As a result, individuals with overweight and obesity have a lower quality of life (QoL).

Liver enzymes are considered to be important markers for liver dysfunction, and elevated levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) have been considered indicators of liver fibrosis, hepatocellular carcinoma, non-alcoholic steatohepatitis (NASH), and non-alcoholic fatty liver disease (NAFLD). The metabolic activities in the liver depend on the sources of dietary nutrition, and when there is excess energy consumption through food, it starts accumulating in various organs in the form of fat droplets.³ Obesity also directly affects the liver by causing metabolic changes and leading to the development of NASH and NAFLD.⁴

Liver biopsy is an invasive, risky, and expensive procedure. On the other hand, liver function tests (LFTs), which measure the levels of liver enzymes, are cost-effective and non-invasive, and have potential in clinical settings. Therefore, the aim of this study was to identify the link between obesity and liver enzymes, specifically AST, ALT, and ALP, and to explore the associations between obesity and various sociodemographic, behavioural, and dietary parameters.

METHODS

The study was an institution-based cross-sectional observational study conducted at a diagnostic laboratory located in Burdwan city, Purba Bardhaman district, West Bengal, India from December 2023 to November 2024. All participants belonged to the age range of 18 to 59 years and were residents of Burdwan for more than one year. People who were already diagnosed with chronic liver diseases including hepatitis B, hepatitis C, alcoholic liver disease, and cirrhosis were excluded from the study. Additionally, people who had had active infection within the last month, were taking drugs known to alter liver enzyme levels, and had a history of psychiatric illness were excluded. Sample size was calculated using the formula of Charan and Biswas (2013), and based on this, 390 individuals were recruited for the study out of around 2500 eligible individuals using a systematic random sampling method. Informed consent was obtained from the participants before the study.⁵

Structured schedules were prepared to collect information from the participants regarding sociodemographic variables, behavioural variables, and health-related information. Questions were available in both Bengali and English. The sociodemographic variables comprised of age, gender, marital status, education level and type of occupation as per the Kuppuswamy scale, socioeconomic status, employment status, and family income.⁶ Also, the socioeconomic status of the participants was calculated using the modified B. G. Prasad’s socioeconomic status (SES) scale.⁷ Behavioural information comprised of alcohol and tobacco use, physical activity status, and diet. For the anthropometric measurements, a flexible non-stretchable measuring tape was used to measure the height and a calibrated portable weighing machine was used to measure the weight. Basal mass index (BMI) was calculated using the values for height and weight, and this was used to categorize the participants based on their obesity status. Lastly, blood samples were collected from the participants and fasting blood glucose, serum lipid profile, and levels of AST, ALT, and ALP were determined using standard procedures.

Microsoft Excel was used to collect and organize participant data, and for carrying out preliminary calculations and generating graphs. Data analysis was performed using Jamovi software, v2.3.28, which was used to test relationships between variables, assess the significance of the relationships, and evaluate differences in the data.

Descriptive statistics were computed and chi-square tests were performed for categorical variables. Students’ t-tests were used to compare continuous variables across the BMI categories and Pearson correlation was done to assess the relationships between continuous variables. The significance level was set at p<0.05. For multiple binary logistic regression analyses, variables with p<0.1 in bivariate analysis were considered.

RESULTS

Sociodemographic variables

Out of a total of 390 participants, 261 were male (66.9%) and 129 were female (33.1%). With regards to age, 44 individuals (11.3%) belonged to the age range of 18-29, 65 (16.7%) belonged to the age range of 30-39, 73 (18.7%) belonged to the age range of 40-49, and 79 (20.3%) belonged to the age range of 50-59. Around 57.7% of males and 29% of females had completed graduation, while 58.5% of males and females were currently married. With respect to occupation, 4.9% of males and 2.6% of females were professionals, 22.6% of males and 10% of females owned businesses, and 19.7% of females were homemakers.

Behavioural variables

A total of 115 (29.5%) participants were found to smoke tobacco, while 68 (17.4%) used smokeless tobacco and 158 (40.5%) were regular alcohol users. In contrast, 67.4% of participants had never smoked, 76.2% had never used smokeless tobacco, and 53.3% had never consumed alcohol.

Considering physical activity related to work, 161 (41.3%) were sedentary workers and 152 (39%) were moderate intensity workers. Most participants spent an average of four to eight hours on work and more than 60 minutes travelling every day to and from work. Apart from this, 124 (31.8%) participants performed high-intensity exercises, 130 (33.3%) performed medium-intensity exercises, and 136 (34.9%) performed low-intensity exercises.

Dietary characteristics

The average consumption of cooking oil for the participants was 32.1 ml/day and that of ghee and butter was 13.2 gm/day. The average sugar and salt consumptions were 21.2 gm and 6.3 gm respectively. A total of 221 participants consumed fast foods on four or more days per week.

Relationship between obesity and sociodemographic, behavioural, and dietary variables

Chi-square tests were performed to understand the association between obesity and sociodemographic variables, behavioural variables, and dietary variables (Tables 1-3).

All Pearson’s r values were statistically significant (p<0.05), *moderate correlation (Pearson’s r=0.4 to <0.6), #high correlation (Pearson’s r>0.6)

*Statistically significant (p<0.05), model characteristics: R2 (McFadden)=0.507, AUC=0.926

The Pearson’s correlation matrix showed that BMI had high correlation with SBP, DBP, and fasting plasma glucose (Table 4). SBP correlated strongly with DBP and fasting plasma glucose. Correlation between AST and ALT was also high among the study participants. Univariate logistic regression analysis between various independent variables and obesity was carried out and it was seen that increase in sugar consumption, SBP, fasting plasma glucose levels and AST levels increased the likelihood of being obese (Table 5).

DISCUSSION

There has been a considerable increase in obesity globally, which has in turn increased the risk for many chronic diseases such as metabolic syndrome, diabetes, CVD, and NAFLD. Several studies have attempted to identify the links between obesity and different sociodemographic, behavioural, dietary, and health-related factors. One of these is high levels of liver enzymes namely ALT, AST, and ALP.⁸ Changes in the levels of these enzymes have been linked to changes in liver function.⁹ This study was carried out to explore the link between obesity prevalence and liver enzyme levels, so that liver enzymes can be used as biomarkers for liver dysfunction in people with overweight and obesity.

In this study, high levels of AST were found in 67.44% of the participants, high levels of ALT were found in 42.56% of the participants, and high levels of ALP were found in 45.13% of the participants. In all three cases, the levels were higher in obese individuals than in non-obese individuals, with t-values ranging from -3.59 to -10.08. Obesity and liver enzyme levels have been demonstrated to have a significant relationship among Italians.¹⁰ Another report demonstrated the link between increased ALT activity and high BMI and waist circumference.¹¹ A large cohort study of 9748 individuals also found a significant association between high levels of ALT and high BMI and waist circumference.¹²

The associations between obesity and sociodemographic variables, use of addictive substances, and levels of physical activity were not statistically significant. However, physical inactivity has been significantly associated with obesity in other studies.^13,14 Regarding smoking, there have been mixed reports with some studies indicating a negative relationship between obesity and smoking, while some studies indicating a positive relationship between obesity and smoking.^15-17 The reason for smokers to have a lower body weight may be attributed to the fact that cigarettes contain about 10-15 mg of nicotine, which lowers the appetite and increases the metabolism of individuals.^18,19 For the same reason, people who quit smoking tend to overeat to replace cigarettes with food resulting in increased body weight among past smokers compared to current smokers.^20,21 Alcohol use has also been linked to obesity in several studies.^22,23 With respect to dietary variables, cooking oil and sugar consumption were significantly associated with obesity, while butter/ghee, salt, and fast-food consumption had no significant association with obesity. High consumption of sunflower oil has particularly been linked to abdominal obesity.²⁴ While ghee consumption has been linked to increased serum triglyceride levels, it has been found to have no significant association with body weight.^25,26 Increased sugar consumption has been linked to liver fibrosis, liver disease, and NAFLD.^27,28 In contrast to findings of our study, high salt intake has been associated with increased risk of obesity, while high fast-food consumption is considered to be one of the most important causes of obesity worldwide.^29-33

CONCLUSION

The findings of this study have highlighted significant correlations between obesity and elevated levels of liver enzymes, indicating that obesity may be a risk factor for liver disease. Also, the presence of high liver enzyme levels among obese individuals can serve as markers for metabolic liver disease. However, this study has certain limitations. This study is cross-sectional, and so, it was not possible to track changes in the relationship between obesity and liver enzyme levels over a period of time. The study was carried out in a single diagnostic laboratory setting, and hence, the results may not be generalizable to other demographic groups. Future research must aim to identify and target high-risk individuals and encourage them to follow a healthier lifestyle to avoid long-term health complications.

Funding: No funding sources

Conflict of interest: None declared

Ethical approval: The study was approved by the Institutional Ethics Committee

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