Article Text

Original research
Self-management behaviours in adults with non-alcoholic fatty liver disease: a cross-sectional survey from China
  1. Run Zhou1,
  2. Binbin Zhang2,3,4,
  3. Wei Zhang5,
  4. Tingting Kong1,
  5. Jie Fu1,
  6. Jie Li6,
  7. Junping Shi2,3,4
  1. 1School of Nursing, Hangzhou Normal University, Hangzhou, Zhejiang, China
  2. 2Department of Infectious Diseases and Hepatology, The Affiliated Hospital of Hangzhou Normal University, HangZhou, Zhejiang, China
  3. 3Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou, Zhejiang, China
  4. 4Institute of Hepatology and Metabolic Diseases, Hangzhou Normal University, Hangzhou, Zhejiang, China
  5. 5Department of Teaching, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
  6. 6Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China
  1. Correspondence to Dr Junping Shi; 20131004{at}hznu.edu.cn; Jie Li; lijier{at}sina.com

Abstract

Objectives The prevalence of non-alcoholic fatty liver disease (NAFLD) in China has significantly increased due to changing lifestyles and rising obesity rates. Effective self-management behaviours are crucial for reversing NAFLD. This study aimed to assess the current self-management status and the influencing factors among the Chinese NAFLD population.

Design A cross-sectional study.

Setting This was a study conducted between 30 May 2022 and 30 May 2023 at a tertiary care hospital.

Participants A total of 380 patients diagnosed with NAFLD were included in this study. NAFLD patients included in this study were diagnosed by FibroScan and had a controlled attenuation parameter ≥248 dB/m.

Primary outcomes and measures The primary outcomes were self-management, demographic characteristics and clinical features of patients with NAFLD. Self-management-related domains were assessed using the self-management questionnaire of NAFLD.

Results The study included 380 patients with an average age of 42.79±13.77 years, with 62.89% being male. The mean score on the self-management scale was 80.92±18.31, indicating a low level of self-management behaviours. Among the five dimensions of the self-management scale, lifestyle management received the highest score (10.68±2.53), while disease knowledge management received the lowest score (9.29±2.51). Furthermore, gender (β=0.118, p=0.009), education level (β=0.118, p=0.010), body mass index (BMI) (β=−0.141, p=0.002) and sleep quality (β=0.387, p<0.001) were found to influence the self-management behaviours of patients to some extent.

Conclusions This cross-sectional survey in China revealed impaired self-management behaviours among adults with NAFLD. The study identified significant associations between self-management behaviours and gender, education level, BMI and sleep quality. Healthcare providers should focus on optimising the care of NAFLD patients to enhance their self-management behaviours.

  • Chronic Disease
  • Self Care
  • Quality of Life

Data availability statement

Data are available on reasonable request. Not applicable.

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STRENGTHS AND LIMITATIONS OF THIS STUDY

  • This study represents the most comprehensive analysis to date on the demographic and clinical characteristics of non-alcoholic fatty liver disease (NAFLD) self-management.

  • Followed rigorous methodological and reporting guidelines.

  • The selection bias may exist in this study because the subjects of this study primarily consisted of NAFLD participants from a tertiary hospital.

  • The inclusion of patients with NAFLD in this study, without the exclusion of patients with comorbid type 2 diabetes, may affect the results.

  • The cross-sectional nature of the survey allows comment only on association and not causation.

Introduction

Non-alcoholic fatty liver disease (NAFLD) is a preventable and treatable chronic liver disease characterised by the accumulation of more than 5% of liver fat cells.1 As NAFLD progresses, it can lead to non-alcoholic steatohepatitis, liver fibrosis, cirrhosis, hepatocellular carcinoma and even liver failure.2 Additionally, NAFLD is associated with adverse outcomes in extrahepatic diseases, such as cardiovascular disease and type 2 diabetes,3 contributing to a significant economic burden and becoming a growing public health concern. The prevalence of NAFLD has increased, affecting 29.62% of the Asian population.4 In China, the prevalence of NAFLD is alarmingly rising at a rate of 2.16% per year from 2020 to 2040, with a projected prevalence of up to 55.7% in 2040,5 making it the fastest-growing NAFLD epidemic in the world.6

Currently, there are no Food and Drug Administration-approved specific drug therapies for NAFLD, and lifestyle interventions aimed at weight loss are the most established treatments for NAFLD, such as reducing the intake of fatty, high-sugar, and high-carbohydrate foods, increasing physical activity, and reducing sedentary time.7 However, changing and maintaining healthy lifestyle behaviours in patients with NAFLD remains challenging. For instance, Eduardo Vilar-Gomez et al’s team conducted 52 weeks of professional lifestyle coaching for patients diagnosed with non-alcoholic steatohepatitis through liver biopsy, but less than 30% of the participants achieved their weight loss goals.8

In 2021, the European Liver Association emphasised that the effectiveness of lifestyle interventions for individuals with NAFLD depends on their self-management.9 Self-management is defined as the active participation of patients in the medical process to improve their disease, encompassing prevention, treatment and rehabilitation behaviours aimed at alleviating their disease symptoms.10 A growing body of evidence supports the positive impact of self-management on the overall health outcomes of patients with various conditions, including diabetes, Parkinson’s and chronic obstructive pulmonary disease.11–13

However, while investigations of dietary and exercise behaviours of NAFLD patients are relatively common, comprehensive studies on self-management behaviours of NAFLD patients, encompassing clinic adherence, disease perceptions and treatment beliefs, are scarce.14 15 The lack of relevant data hinders the ability to provide robust clinical intervention support for the high prevalence of NAFLD patients in China. Additionally, health management behaviours in NAFLD may be influenced by various factors, including age, gender, socioeconomic status, occupation nature, education level, sleep quality and comorbidities.

Therefore, this study aims to assess the self-management behaviours of individuals with NAFLD in a Chinese population, and further investigate the impact of different factors on the self-management ability of the NAFLD population, providing guidance and assistance for the effective management of the NAFLD lifestyle in clinical practice.

Materials and methods

Study design and study population

This cross-sectional study followed the Strengthening the Reporting of Observational Studies in Epidemiology reporting guidelines16 (online supplemental material 1). Patients with NAFLD were recruited for a survey conducted from 30 May 2022 to 30 May 2023, at the Department of Hepatology, Affiliated Hospital of Hangzhou Normal University, China. The inclusion criteria are an age of ≥18 years, controlled attenuation parameter (CAP)≥248 dB/m by FibroScan and willingness to provide written informed consent. The exclusion criteria include patients with excessive alcohol consumption, other chronic liver diseases, malignant tumours, cognitive impairment, use of corticosteroid medications and so on.

Patient and public involvement

Patients and the public were not involved in the design, development and conduct of this study.

Data collection

General data and clinical characteristic variables

Basic sociodemographic and clinical data were collected by analysing patients’ medical records and general information questionnaires. The following demographic sociology information includes gender, age, residence, marital status, education level, labour intensity of work and monthly income. Clinical parameters were obtained from the medical records: height, weight, waist circumference, body mass index (BMI), body fat, CAP, liver stiffness, sleep quality and comorbidities.

A waist circumference ≥85 cm in women or ≥90 cm in men was considered central obesity.17 According to the Asian BMI classification, its range ≥28 kg/m2 is considered obese, ≥24 and <28 kg/m2 is considered overweight, ≥18.5 and <24 kg/m2 is considered normal, and<18.5 kg/m2 is considered underweight.18 Classification by body fat is set by WHO as body fat per cent ≥25% for men and body fat per cent ≥35% for women.19 20 In addition, CAP and liver stiffness were monitored by FibroScan. According to FibroScan diagnosis of NAFLD, CAP≥280 dB/m is considered as severe fatty liver, CAP: 268–279 dB/m is considered as moderate fatty liver, CAP: 248–267 dB/m is considered as mild fatty liver.21 The progression of liver fibrosis can be assessed by liver stiffness, with liver stiffness ≤7.4 kPa indicating no significant fibrosis, and liver stiffness>7.4 kPa indicating significant fibrosis.22 Based on the patient’s history and clinical examination, an experienced physician diagnosed complications (such as hypertension, hyperlipidaemia, type 2 diabetes, cardiovascular disease, hyperuric acid and depression).

Assessment of the self-management level

The questionnaire (online supplemental material 2) used in this study is a self-management questionnaire developed for Chinese NAFLD population.23 The Cronbach’s α coefficient of the scale was 0.899, and the content validity index of each item was greater than 0.800, which had good reliability and validity. The scale was based on NAFLD clinical guidelines and included five dimensions of disease control and prevention, daily life management, disease knowledge management, psychological cognitive management, and bad lifestyle management, with 31 items. The scale is scored on a 5-point scale from 1 to 5 Likert scale, from ‘never’ to ‘always’, and the total score is the sum of the scores of each item. The higher the score on this scale, the better the patient's self-management behaviors. Scale scores 31–92 represent poor self-management behaviours, 93–123 represent moderate self-management behaviours and 124–155 represent good levels of self-management.

Statistical analysis

The data obtained were checked by two researchers and then included. Data were entered and analysed by using the Statistical Package for the Social Sciences (SPSS, V.26). Continuous variables were expressed as mean±SD (normal distribution) or median (quartile) (skewed distribution), and categorical variables were expressed in frequency. The Kruskal-Wallis analysis was used to derive a normal distribution of self-management scores. For univariate analysis, an independent sample t-test was used for comparison between two groups, and a one-way analysis of variance test was used for comparison between multiple groups. In addition, multiple linear regression was used to analyse the influencing factors of the self-management behaviours of NAFLD patients. A p<0.05 involved in this study was considered significant.

Results

Self-management scores of NAFLD patients

Due to the lack of data on key variables, out of 396 participants, we ultimately selected 380 participants. Table 1 presents the self-management levels in this study, with a mean total self-management score of 80.92±18.31, indicating a low level among the patients. Table 2 provides the details of self-management behaviours among NAFLD patients. Among the 31 items on the self-management scale, smoking management had the highest mean score (4.38±1.20), followed by alcohol consumption management (4.02±1.33). However, the item relating to the ability to correctly understand the meaning of test results received the lowest mean score (1.43±0.78).

Table 1

The NAFLD self-management questionnaire score in overall and five domains (n=380)

Table 2

The status of self-management behaviours among NAFLD participants (n=380)

Demographic characteristics of patients diagnosed with NAFLD

The demographic characteristics of the patients diagnosed with NAFLD are summarised and compared in table 3. The participants were aged between 18 and 94 years. The mean age was 42.79±13.77 years. Most participants were male (62.89%), married (77.89%), living in the city (74.74%) and working in non-manual labour (72.37%). Almost one-third of the patients had a college education or higher (32.89%). Approximately 60% of the patients’ monthly income was more than RMB4000. In addition, patients who were female (t=−4.058, p<0.001), had higher levels of education (F=5.303, p=0.005) and had physically demanding jobs (t=2.222, p=0.027) were more likely to do better in self-management behaviours.

Table 3

Comparison of self-management scores of NAFLD patients with general characteristics (n=380)

Clinical characteristics of patients diagnosed with NAFLD

Table 4 summarises and compares the clinical characteristics of patients diagnosed with NAFLD. The majority of patients were centrally obese (79.74%), had above normal body fat percentage (75.79%), severe NAFLD (78.16%), liver stiffness <7.4 kPa (74.74%) and did not have comorbidities (77.11%). Approximately 40% of patients had an obese BMI (38.16%), and only 27.37% of patients reported good sleep quality. The analysis revealed that patients with higher BMI (F=13.788, p<0.001), poorer sleep quality (F=46.013, p<0.001) and comorbidities (t=−2.441, p=0.015) exhibited worse self-management behaviours.

Table 4

Comparison of self-management scores of NAFLD patients with clinical characteristics (n=380)

Influencing factors of self-management behaviours in patients with NAFLD

Multiple linear regression analysis (table 5) was conducted to explore the association between demographic and clinical characteristics and self-management behaviours. The results demonstrated that gender, education level, BMI and sleep quality were independently associated with self-management behaviours scores. Notably, sleep quality emerged as the strongest influencing factor (β=0.387), followed by BMI (β=−0.141).

Table 5

Multiple linear regression analysis of influencing factors of self-management in patients with NAFLD

Discussion

This study offers essential evidence regarding self-management behaviours among patients with various characteristics of NAFLD, filling a gap in limited global data on this specific population. Our study revealed a relatively low self-management score (80.92±18.31) among NAFLD patients, likely influenced by the high proportion (78.16%) of patients with severe NAFLD. Additionally, among demographic and clinical characteristics, gender, education, BMI and sleep quality emerged as key factors influencing self-management levels.

Current status of NAFLD self-management behaviours

The study revealed that approximately 83.42% of patients actively followed medical advice regarding timely and appropriate medication use when required. This level of medication compliance is consistent with patients with type 2 diabetes.24 However, adherence to daily lifestyle management, such as regular exercise, was lower at 37.37%. The high medication adherence suggests a preference among patients to rely on medication rather than making behavioural changes. Given the absence of specific drug treatments for NAFLD, interventions focusing on lifestyle changes face significant challenges as the primary clinical approach.

Regarding disease control, surprisingly, only about 39.74% (151 cases) of patients regularly measured their weight, while a mere 8.95% (34 cases) paid attention to their waist circumference. Waist circumference is closely related to visceral fat accumulation and serves as a comprehensive indicator of total fat and fat distribution.25 Elevated waist circumference is associated with an increased risk of adverse health effects, including metabolic syndrome, cardiovascular diseases and cognitive functioning issues.26 27 As a result, it is recommended that all patients near or above the waist circumference cut-off values (90.0 cm for men; 85.0 cm for women) undergo abdominal ultrasound for early detection of problems and timely intervention.17

In the dimension of disease knowledge management, only 11.05% of patients demonstrated a mostly accurate understanding of their test results, indicating insufficient knowledge about the disease. Healthcare professionals are urged to emphasise explaining the normal range of disease indicators when discussing medical reports with patients, thereby enhancing patients’ awareness of the severity of their condition. Furthermore, among poor lifestyle behaviours, while most patients were more aware of the dangers of smoking and alcohol consumption, other poor habits such as staying up late, skipping breakfast and being sedentary were observed in nearly 70% of patients. The lesser awareness of sedentary behaviour’s risks could be attributed to its relatively lower recognition. Notably, Wilmot reported that a higher risk of myocardial infarction is associated with sedentary behaviour.28 Thus, healthcare professionals can adopt innovative health education approaches, such as community lectures, case presentations and videos, to raise awareness among patients about changing these behaviours and improving self-management.

The factors influencing self-management behaviours in NAFLD

The analysis of influencing factors revealed that health management was more active among women and patients with higher levels of education. Female patients exhibited characteristics such as attentiveness, greater concern for appearance, lower working pressure and a higher willingness to invest time and energy in maintaining weight and overall health.29 30 Additionally, patients with higher education levels demonstrated better learning and understanding abilities were more adept at accessing medical resources and disease-related information through various means, and thus exhibited a greater awareness of active weight management, disease prevention and treatment.31 32 As a result, health education models should be adapted to meet the diverse needs of patients of different genders and cultural backgrounds. For patients with relatively lower literacy levels, simple and easy-to-understand communication methods should be used to continually assess their knowledge and ensure comprehension and mastery.

Moreover, we observed a negative correlation between the level of self-management in patients with NAFLD and BMI. Consistently, Huang et al demonstrated that health-related quality of life in patients with NAFLD worsened with increasing BMI, which also served as an independent risk factor for overall and six domain scores on the chronic liver disease questionnaire.33 Obesity is associated with a chronic low-grade inflammatory state and metabolic dysfunction, leading to impaired release and action of dopamine, which can affect patients’ ability to regulate appetite and eating behaviours, among other functions.34 Surprisingly, despite 83.69% of patients with NAFLD having a BMI greater than 24 kg/m2, only 9.74% frequently calculated their BMI. BMI is an internationally accepted standard for measuring body fatness and thinness, calculated by dividing weight in kilograms by height in metres squared.35 Consequently, healthcare professionals should emphasise the dangers of obesity and the importance of calculating BMI during interventions.

Furthermore, this study identified sleep quality as a core factor influencing patients’ self-management behaviours (β=0.387, p<0.001). This finding aligns with a cross-sectional study in elderly patients with coronary heart disease that indicated a positive correlation between sleep quality and self-management ability in patients.36 Sleep deprivation activates brain networks associated with reward, upregulates the gastric hunger/leptin ratio and reduces cognitive control and activity in the cerebral cortex, leading to excessive food consumption and energy imbalance that ultimately affect the patient’s daily lifestyle.37 38 Moreover, poor sleep quality adversely affects the disease prognosis in patients with NAFLD, with an association between sleep duration and severe steatosis and liver fibrosis showing a negative correlation.39 Guideline recommendations suggest that patients should ensure more than 7–9 hours of high-quality sleep to support the body’s energy expenditure, and music therapy and exercise are recommended as strategies for patients with poor sleep quality.40

Clinical values and limitations

To the best of our knowledge, this study represents the most comprehensive analysis to date of the demographic and clinical characteristics of NAFLD self-management. It significantly contributes to the field of self-management for patients diagnosed with NAFLD. However, several limitations need to be acknowledged. First, the subjects of this study primarily consisted of NAFLD participants from a tertiary hospital, potentially impacting the results due to geographical location, lifestyle and dietary habits. To strengthen the evidence base, future studies should expand the sample size and include participants from different regions and multiple centres. Furthermore, this study’s investigation included NAFLD patients who also had type 2 diabetes. This particular group of patients typically use hypoglycaemic medications and are often more concerned about their lifestyle,41 which may have influenced the results of the study. Additionally, the cross-sectional design employed in this study limited the ability to establish the direction of the relationships between the independent and dependent variables.

Conclusion

As of now, the level of self-management among NAFLD patients in China remains suboptimal. There is an urgent need for an effective strategy to enhance their self-management of the disease. In addition to seeking knowledge from health professionals, patients should consider reading, attending conferences and participating in education sessions when available and feasible. Furthermore, healthcare professionals should target gender, educational background, BMI and sleep quality as they influence patients’ motivation to manage their health to varying degrees.

Data availability statement

Data are available on reasonable request. Not applicable.

Ethics statements

Patient consent for publication

Ethics approval

This study was approved by the Affiliated Hospital of Hangzhou Normal University in China (2022(E2)-HS-162). The study was conducted in accordance with the principles of the Declaration of Helsinki. Patients' participation in the study was voluntary and anonymous. In addition, participants gave informed consent to participate in the study before taking part.

Acknowledgments

The authors would like to thank all participants who contributed to this study. We also appreciate the financial and technical support of the Zhejiang Provincial Natural Science Foundation of China under Grant, the National Natural Science Funds of China, and the Hangzhou Science and Technology Bureau biological medicine and health industry development Supported Science and Technology Special Project.

References

Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Footnotes

  • RZ and BZ contributed equally.

  • Contributors RZ and BZ conceived and coordinated the study, designed and wrote the paper. RZ, WZ, TK and JF carried out the data collection, data analysis and revised the paper. JL and JS designed the study, carried out the data analysis and revised the paper. All authors reviewed the results and approved the final version of the manuscript. JL and JS were responsible for the overall content.

  • Funding This research was supported by the Zhejiang Provincial Natural Science Foundation of China under Grant (No.LQ23H270016), the National Natural Science Funds of China (No.82204827), and the Hangzhou Science and Technology Bureau biological medicine and health industry development Supported Science and Technology Special Project (No.2021WJCY049).

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.