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LIU Li, SHAO Yu Han, FENG En Qiang, SHAO Zhu Gang, XING Dong Ming. Risk of Developing Non-Alcoholic Fatty Liver Disease Over Time in a Cohort of the Elderly in Qingdao, China[J]. Biomedical and Environmental Sciences, 2023, 36(8): 760-767. doi: 10.3967/bes2023.101
Citation: LIU Li, SHAO Yu Han, FENG En Qiang, SHAO Zhu Gang, XING Dong Ming. Risk of Developing Non-Alcoholic Fatty Liver Disease Over Time in a Cohort of the Elderly in Qingdao, China[J]. Biomedical and Environmental Sciences, 2023, 36(8): 760-767. doi: 10.3967/bes2023.101

Risk of Developing Non-Alcoholic Fatty Liver Disease Over Time in a Cohort of the Elderly in Qingdao, China

doi: 10.3967/bes2023.101
Funds:  This work was supported by grants from Qingdao Outstanding Health Professional Development Fund and Qingdao Science and Technology Fund [21-1-4-rkjk-1-nsh].
More Information
  • Author Bio:

    LIU Li, female, born in 1986, PhD, majoring in community health and chronic non-communicable disease

  • Corresponding author: XING Dong Ming, E-mail: xdm_tsinghua@163.com Tel: 86-15726227711.
  • No potential conflicts of interest.
  • Received Date: 2023-02-28
  • Accepted Date: 2023-05-22
  • No potential conflicts of interest.
  • 加载中
  • [1] Hyysalo J, Männistö VT, Zhou Y, et al. A population-based study on the prevalence of NASH using scores validated against liver histology. J Hepatol, 2014; 60, 839−46. doi:  10.1016/j.jhep.2013.12.009
    [2] Kabarra K, Golabi P, Younossi ZM. Nonalcoholic steatohepatitis: global impact and clinical consequences. Endocr Connect, 2021; 10, R240−7. doi:  10.1530/EC-21-0048
    [3] Zhou JH, Zhou F, Wang WX, et al. Epidemiological features of NAFLD from 1999 to 2018 in China. Hepatology, 2020; 71, 1851−64. doi:  10.1002/hep.31150
    [4] Stepanova M, Rafiq N, Younossi ZM. Components of metabolic syndrome are independent predictors of mortality in patients with chronic liver disease: a population-based study. Gut, 2010; 59, 1410−5. doi:  10.1136/gut.2010.213553
    [5] Niriella MA, Pathmeswaran A, De Silva ST, et al. Incidence and risk factors for non-alcoholic fatty liver disease: a 7-year follow-up study among urban, adult Sri Lankans. Liver Int, 2017; 37, 1715−22. doi:  10.1111/liv.13478
    [6] Jarvis H, Craig D, Barker R, et al. Metabolic risk factors and incident advanced liver disease in non-alcoholic fatty liver disease (NAFLD): a systematic review and meta-analysis of population-based observational studies. PLoS Med, 2020; 17, e1003100. doi:  10.1371/journal.pmed.1003100
    [7] Ko YH, Wong TC, Hsu YY, et al. The correlation between body fat, visceral fat, and nonalcoholic fatty liver disease. Metab Syndr Relat Disord, 2017; 15, 304−11. doi:  10.1089/met.2017.0001
    [8] Ruhl CE, Everhart JE. Determinants of the association of overweight with elevated serum alanine aminotransferase activity in the United States. Gastroenterology, 2003; 124, 71−9. doi:  10.1053/gast.2003.50004
    [9] Praveenraj P, Gomes RM, Kumar S, et al. Prevalence and predictors of non-alcoholic fatty liver disease in morbidly obese south Indian patients undergoing bariatric surgery. Obes Surg, 2015; 25, 2078−87. doi:  10.1007/s11695-015-1655-1
    [10] Ioannou GN, Boyko EJ, Lee SP. The prevalence and predictors of elevated serum aminotransferase activity in the United States in 1999-2002. Am J Gastroenterol, 2006; 101, 76−82. doi:  10.1111/j.1572-0241.2005.00341.x
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Risk of Developing Non-Alcoholic Fatty Liver Disease Over Time in a Cohort of the Elderly in Qingdao, China

doi: 10.3967/bes2023.101
Funds:  This work was supported by grants from Qingdao Outstanding Health Professional Development Fund and Qingdao Science and Technology Fund [21-1-4-rkjk-1-nsh].
  • Author Bio:

  • Corresponding author: XING Dong Ming, E-mail: xdm_tsinghua@163.com Tel: 86-15726227711.
  • No potential conflicts of interest.
No potential conflicts of interest.
LIU Li, SHAO Yu Han, FENG En Qiang, SHAO Zhu Gang, XING Dong Ming. Risk of Developing Non-Alcoholic Fatty Liver Disease Over Time in a Cohort of the Elderly in Qingdao, China[J]. Biomedical and Environmental Sciences, 2023, 36(8): 760-767. doi: 10.3967/bes2023.101
Citation: LIU Li, SHAO Yu Han, FENG En Qiang, SHAO Zhu Gang, XING Dong Ming. Risk of Developing Non-Alcoholic Fatty Liver Disease Over Time in a Cohort of the Elderly in Qingdao, China[J]. Biomedical and Environmental Sciences, 2023, 36(8): 760-767. doi: 10.3967/bes2023.101
  • Nonalcoholic fatty liver disease (NAFLD) is characterized by fat accumulation in the liver in the absence of alcohol consumption and comprises a variety of conditions such as simple steatosis, nonalcoholic steatohepatitis, fibrosis, and cirrhosis[1]. More than one-quarter of the world’s population experience NAFLD[2]. The prevalence of NAFLD in China increased from 23.8% in 2001 to 32.9% in 2018, indicating that hepatitis B virus is the primary cause of chronic liver disease[3]. However, NAFLD is considered one of the most important etiologies of chronic liver diseases. The current annual medical and social costs of NAFLD are estimated to be $103 billion in the United States and €35 billion in the European countries. Therefore, it is critical to explore the etiology of NAFLD to prevent its morbidity.

    Age, smoking status, physical activity, obesity, hypertension, diabetes, dyslipidemia, and high alanine aminotransferase (ALT) levels are reportedly associated with NAFLD[4-7]. However, these conclusions remain controversial[8-10]. Moreover, no study has investigated the longitudinal relationship between changes in risk factors and the progression of NAFLD in the older adults in China. Therefore, our study aims to clarify the impact of certain factors on the development of NAFLD over time, based on a large Chinese elderly cohort study conducted in Qingdao, China.

    Based on the National Basic Public Health Service (BPHS) project, two health examinations for residents aged ≥ 65 years were conducted in 2018 and 2021 in five community centers in Qingdao, Shandong Province, China. All Chinese citizens can use the BPHS project’s services in community health centers. The BPHS includes 12 service categories, one of which is the health management of the elderly, which in 2018 and 2021 included: (1) a standard questionnaire including questions about age, sex, marital status, smoking status, alcohol consumption, education, and dietary habits; (2) measurement of height, weight, and blood pressure; and (3) detection of the levels of fasting plasma glucose (FPG), ALT, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL), and performing ultrasonography of the liver. ALT and TG levels were determined using enzymatic techniques, and HDL was measured using a direct method. FPG levels were determined using the glucose oxidase method. A written informed consent was obtained from all participants. This study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of the Qingdao Municipal Center for Disease Control and Prevention.

    A total of 57,808 individuals aged ≥ 65 years participated in the health examination in 2018, and 47,862 individuals underwent a health check-up in 2021. Of the 47,862 participants, those with incomplete information on height, weight, and ultrasonography of the liver (n = 6,282), as well as those with ALT levels higher than three times of the upper limit (n = 236) were excluded. An additional 3,101 participants were excluded because of high alcohol consumption (> 140 g/week for men and > 70 g/week for women), the presence of hepatitis B surface antigen, a history of schistosomiasis, viral hepatitis, hepatic cirrhosis, liver carcinoma, and autoimmune liver disease. Finally, the data from 38,243 individuals were included in this study.

    A balanced diet was defined as consuming adequate types of food with an appropriate ratio of vegetable-to-meat intake. Overweight was defined as body mass index (BMI) ≥ 24.0 kg/m2, and obesity was defined as BMI ≥ 28.0 kg/m2. Hypertension was defined as systolic blood pressure of ≥ 140 mmHg and (or) diastolic blood pressure of ≥ 90 mmHg. Moreover, dyslipidemia was defined as presence of at least one of the following: TC levels of ≥ 5.72 mmol/L, TG levels of ≥ 1.70 mmol/L, HDL levels of < 0.91 mmol/L, or lipoprotein cholesterol (LDL) levels of > 3.64 mmol/L. Diabetes was defined as an FPG level of ≥ 7.0 mmol/L or a history of previously diagnosed diabetes.

    NAFLD was diagnosed using established ultrasound criteria for fatty liver (at least two of the following abnormal findings: increased echogenicity of the liver relative to that of the kidney and spleen, obliteration of the vascular architecture of the liver, and deep attenuation of the ultrasonic signal), safe alcohol consumption (Asian standards: < 140 g/week for males and < 70 g/week for females), and the absence of HbsAg and anti-HCV. Abnormal ALT levels were defined as levels of > 40 IU/L according to the conventional value.

    Statistical analyses were performed using SPSS (version 17.0; SPSS, Chicago, IL), and statistical significance was set at a two-sided P-value of < 0.05. Data are presented as mean ± standard deviation for continuous variables and as n (%) for categorical variables. The normality of the variables was examined using the Kolmogorov-Smirnov test. Group differences were compared using the Student’s t-test for continuous variables since data were normally distributed. For categorical variables, we used the χ2 test to compare differences. Moreover, multivariate logistic regression models were used to calculate the unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for cross-sectional associations. Longitudinal analyses were conducted on 19,919 participants without NAFLD in 2018, and multinomial logistic regression models were used to examine the association between changes in possible risk factors and NAFLD over time. Supplementary Table S1 (available in www.besjournal.com) displayed different groups defined by variable status over time.

    Variable status over timeIn 2018In 2021
    BMI status
    Remained normalNormalNormal
    Weight lossObeseOverweight or normal
    OverweightNormal
    Remained overweightOverweightOverweight
    Remained obesityObeseObese
    Weight gainNormalOverweight or obese
    OverweightObese
    Hypertension
    Never hypertensiveNo hypertensionNo hypertension
    Remained hypertensionHypertensionHypertension
    Developed hypertensionNo hypertensionHypertension
    No longer having hypertensionHypertensionNo hypertension
    Diabetes
    Never diabeticNo diabetesNo diabetes
    Remained diabetesDiabetesDiabetes
    Developed diabetesNo diabetesDiabetes
    No longer having diabetesDiabetesNo diabetes
    Dyslipidemia
    Never dyslipidemicNo dyslipidemiaNo dyslipidemia
    Remained dyslipidemiaDyslipidemiaDyslipidemia
    Developed dyslipidemiaNot dyslipidemiaDyslipidemia
    No longer having dyslipidemiaDyslipidemiaNot dyslipidemia
    ALT levels
    Never abnormalNormalNormal
    Remained abnormalAbnormalAbnormal
    Developed abnormalNormalAbnormal
    No longer abnormalAbnormalNormal
      Note. BMI, body mass index; ALT, alanine aminotransferase.

    Table S1.  Different groups classified according to variable status over time in longitudinal analyses

    Of the 38,243 individuals aged ≥ 65 years, the prevalence of NAFLD in 2018 and 2021 was 48.96% and 47.91%, respectively (Table 1). The mean values of BMI, TC, TG, LDL, and ALT and the prevalence of hypertension, diabetes, and dyslipidaemia were notably high, while the HDL levels were lower in the participants with NAFLD than that of the participants without NAFLD (P < 0.001).

    Characteristics In 2018 In 2021
    NAFLD
    (n = 18,725)
    No NAFLD
    (n = 19,518)
    P value* NAFLD
    (n = 18,324)
    No NAFLD
    (n = 19,919)
    P value*
    Sex
    Male 7,697 (41.10) 8,004 (41.00) 7,421 (40.50) 8,280 (41.60)
    Female 11,028 (58.90) 11,514 (59.00) 0.847 10,903 (59.50) 1,1639 (58.40) 0.034
    Age (years)
    65– 9,724 (51.90) 9,262 (47.50) 5,050 (27.60) 4,838 (24.30)
    70– 7,461 (39.80) 7,825 (40.10) 10,952 (59.80) 10,977 (55.10)
    ≥ 75 1,540 (8.30) 2,431 (12.50) < 0.001 2,322 (12.70) 4,104 (20.60) < 0.001
    Education
    Low 4,371 (23.30) 4,786 (24.50) 4,458 (24.30) 4,699 (23.60)
    Intermediate 13,309 (71.10) 13,551 (69.40) 12,814 (69.90) 14,046 (70.50)
    High 1,045 (5.60) 1,181 (6.10) 0.002 1,052 (5.70) 1,174 (5.90) 0.221
    Current smoking
    No 16,807 (89.80) 16,799 (86.10) 16,422 (89.60) 1,6916 (84.90)
    Yes 2,603 (13.90) 1,991 (10.20) < 0.001 2767 (15.10) 2,072 (10.40) < 0.001
    Current drinking
    No 16,524 (88.20) 17,054 (87.40) 16,115 (87.90) 1,7551 (88.10)
    Yes 2,359 (12.60) 2,303 (11.80) 0.009 2,209 (12.10) 2,368 (11.90) 0.615
    BMI (kg/m2) 26.90 ± 3.40 24.27 ± 3.12 < 0.001 27.40 ± 3.30 24.29 ± 3.19 < 0.001
    Systolic blood pressure (mmHg) 149.47 ± 21.69 144.21 ± 21.43 < 0.001 151.92 ± 19.99 147.31 ± 20.90 < 0.001
    Diastolic blood pressure (mmHg) 82.71 ± 11.69 80.42 ± 11.60 < 0.001 82.81 ± 11.24 80.80 ± 11.31 < 0.001
    FPG (mmol/L) 6.52 ± 2.07 5.90 ± 1.67 < 0.001 6.86 ± 2.17 6.21 ± 1.76 < 0.001
    TC (mmol/L) 5.64 ± 3.68 5.50 ± 6.21 0.005 5.66 ± 1.20 5.48 ± 1.34 < 0.001
    TG (mmol/L) 1.78 ± 1.11 1.33 ± 0.71 < 0.001 1.86 ± 1.28 1.29 ± 0.71 < 0.001
    HDL (mmol/L) 1.44 ± 0.31 1.53 ± 0.59 < 0.001 1.44 ± 2.29 1.54 ± 0.34 < 0.001
    LDL (mmol/L) 3.14 ± 0.82 3.05 ± 2.42 < 0.001 3.34 ± 0.96 3.19 ± 0.97 < 0.001
    ALT (IU/L) 24.51 ± 14.94 19.94 ± 11.19 < 0.001 25.55 ± 14.60 20.56 ± 14.52 < 0.001
    Marital status
    Single or widowed 2,773 (14.80) 2,973 (15.20) 2,788 (15.20) 2,958 (14.90)
    Married 15,952 (85.20) 16,545 (84.80) 0.247 15,536 (84.80) 16,961 (85.10) 0.323
    Regular physical activity
    Yes 13,005 (69.50) 13,437 (68.80) 11,909 (65.00) 13,386 (67.20)
    No 5,720 (30.50) 6,081 (31.20) 0.198 6,415 (35.00) 6,533 (32.80) < 0.001
    Dietary habits
    Balanced 17,536 (93.70) 17,574 (90.00) 16,745 (91.40) 1,8365 (92.20)
    Unbalanced 1,873 (10.00) 1,230 (6.30) < 0.001 1,579 (8.60) 1,554 (7.80) 0.041
    ALT levels
    Normal 17,070 (91.20) 18,899 (96.80) 16,487 (90.00) 19,171 (96.20)
    Abnormal 1,655 (8.80) 619 (3.20) < 0.001 1,837 (10.00) 748 (3.80) < 0.001
    BMI status
    Normal 3,462 (18.50) 9,391 (48.10) 2,563 (14.00) 9,694 (48.70)
    Overweight 8,759 (46.80) 7,950 (40.70) 8,614 (47.00) 7,920 (39.80)
    Obesity 6,504 (34.70) 2,177 (11.20) < 0.001 7,147 (39.00) 2,305 (11.60) < 0.001
    Diabetes
    No 14,015 (74.80) 16,976 (87.00) 12,594 (68.70) 16,615 (83.40)
    Yes 4,710 (25.20) 2,542 (13.00) < 0.001 5,730 (31.30) 3,304 (16.60) < 0.001
    Hypertension
    No 5,951 (31.80) 8,107 (41.50) 4,842 (26.40) 7,017 (35.20)
    Yes 12,774 (68.20) 11,411 (58.50) < 0.001 13,482 (73.60) 12,902 (64.80) < 0.001
    Dyslipidemia
    No 6,190 (33.10) 9,953 (51.00) 5,528 (30.20) 9,245 (46.40)
    Yes 12,535 (66.90) 9,565 (49.00) < 0.001 12,796 (69.80) 10,674 (53.60) < 0.001
      Note. BMI, body mass index; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglycerides; HDL, high-density lipoprotein cholesterol; LDL, lipoprotein cholesterol; ALT, alanine aminotransferase; NAFLD, nonalcoholic fatty liver disease. Data are presented as mean ± SD for continuous variables, and n (%) for categorical variables. *P values in the t-tests for differences in means or in the Chi-square tests for differences in proportions.

    Table 1.  Demographic characteristics of the individuals in 2018 and 2021 (in our study)

    In the cross-sectional analysis, current drinking (OR: 1.19, 95% CI: 1.11–1.29) and non-balanced dietary habits (OR: 1.63, 95% CI: 1.50–1.77) increased the risk of NAFLD, and older age (P < 0.001) was negatively associated with NAFLD in the adjusted model in 2018. Compared with those with normal weight, individuals with obesity had a 6.98 fold higher odds (95% CI: 6.54–7.44) and a 10.34 fold higher odds (95% CI: 9.68–11.05) of developing NAFLD in 2018 and 2021, respectively. After adjusting for confounders, abnormal ALT levels, obesity, hypertension, diabetes, and dyslipidemia were all risk factors (P < 0.001 for all comparisons) for NAFLD (Table 2).

    Characteristics In 2018 (n = 38,243) In 2021 (n = 38,243)
    Unadjusted OR (95% CI)a Adjusted OR (95% CI)b Unadjusted OR (95% CI)a Adjusted OR (95% CI)b
    Sex
    Male 1.00 1.00 1.00 1.00
    Female 0.99 (0.96−1.04) 1.04 (0.99−1.09) 1.05 (1.01−1.09) 1.03 (0.99−1.08)
    Age (years)
    65– 1.00 1.00 1.00 1.00
    70– 0.91 (0.87−0.95)* 0.95 (0.91−0.99) 0.96 (0.91−1.01) 0.95 (0.90−1.01)
    ≥ 75 0.60 (0.56−0.65)* 0.71 (0.66−0.77)* 0.54 (0.51−0.58)* 0.64 (0.60−0.69)*
    Education
    Low 1.00 1.00 1.00 1.00
    Intermediate 1.03 (0.94−1.13) 0.88 (0.79−0.97)** 0.96 (0.92−1.01) 0.97 (0.92−1.03)
    High 1.11 (1.02−1.21)*** 0.97 (0.88−1.06) 0.95 (0.86−1.04) 0.93 (0.83−1.03)
    Current smoking
    No 1.00 1.00 1.00 1.00
    Yes 1.42 (1.33−1.51)* 1.06 (0.98−1.14) 1.03 (0.97−1.09) 1.02 (0.94−1.10)
    Current drinking
    No 1.00 1.00 1.00 1.00
    Yes 1.08 (1.02−1.15)* 1.19 (1.11−1.29)*** 1.02 (0.96−1.08) 1.00 (0.93−1.08)
    Marital status
    Single or widowed 1.00 1.00 1.00 1.00
    Married 0.98 (0.91−1.12) 1.01 (0.95−1.08) 0.97 (0.92−1.03) 0.98 (0.92−1.04)
    Regular physical activity
    No 1.00 1.00 1.00 1.00
    Yes 0.97 (0.93−1.02) 0.93 (0.89−0.98)** 1.03 (0.98−1.07) 1.04 (0.99−1.10)
    Dietary habits
    Balanced 1.00 1.00 1.00 1.00
    Unbalanced 1.63 (1.51−1.76)* 1.63 (1.50−1.77)* 1.11 (1.04−1.20) 0.93 (0.86−1.01)
    ALT levels
    Normal 1.00 1.00 1.00 1.00
    Abnormal 2.96 (2.69−3.25)* 2.22 (2.00−2.46)* 2.86 (2.62−3.12)* 2.17 (1.97−2.39)*
    BMI status
    Normal 1.00 1.00 1.00 1.00
    Overweight 2.99 (2.84−3.14)* 2.70 (2.56−2.84)* 4.11 (3.90−4.34)* 3.77 (3.57−3.98)*
    Obesity 8.10 (7.61−8.63)* 6.98 (6.54−7.44)* 11.73 (11.00−12.50)* 10.34 (9.68−11.05)*
    Diabetes
    No 1.00 1.00 1.00 1.00
    Yes 2.24 (2.13−2.37)* 1.87 (1.77−1.99)* 2.29 (2.18−2.40)* 2.03 (1.93−2.15)*
    Hypertension
    No 1.00 1.00 1.00 1.00
    Yes 1.53 (1.46−1.59)* 1.20 (1.15−1.26)* 1.51 (1.45−1.58)* 1.18 (1.12−1.24)*
    Dyslipidemia
    No 1.00 1.00 1.00 1.00
    Yes 2.11 (2.02−2.20)* 1.81 (1.73−1.89)* 2.00 (1.92−2.09)* 1.81 (1.73−1.90)*
      Note. BMI, body mass index; ALT, alanine aminotransferase. aModel 1: Unadjusted. bModel 2: Adjusted for age, sex, education, current smoking, current drinking, regular physical activity, dietary habits, ALT levels, BMI status, diabetes, hypertension, and dyslipidemia. *P < 0.001 for testing the null hypothesis that the odds ratio is equal to the odds ratio in the reference category. **P < 0.01 for testing the null hypothesis that the odds ratio is equal to the odds ratio in the reference category. ***P < 0.05 for testing the null hypothesis that the odds ratio is equal to the odds ratio in the reference category.

    Table 2.  A cross-sectional analysis of relative risk factors for NAFLD in 2018 and 2021

    As shown in Table 3, among the elderly without NAFLD in 2018, 19.90% had developed NAFLD in 3 years (Table 3). In the longitudinal analyses, current drinking [relative risk reduction (RRR): 1.20, 95% CI: 1.05–1.38] and unbalanced dietary habits (RRR: 1.45, 95% CI: 1.28–1.64) were positively correlated with developing NAFLD, while regular physical activity (RRR: 0.73, 95% CI: 0.66–0.81) was negatively associated with NAFLD after adjusting for the confounders. Individuals who remained with overweight or obesity were at an increased risk of developing NAFLD, as the category with the greatest risk for NAFLD was weight gain, which resulted in a change in the BMI status (RRR: 7.99, P < 0.001). Remained hypertension (RRR: 1.70, P < 0.001), remained diabetes (RRR: 3.87, P < 0.001), remained dyslipidemia (RRR: 1.14, P < 0.05), developed hypertension (RRR: 1.90, 95% CI: 1.70–2.12), developed diabetes (RRR: 4.14, 95% CI: 3.78–4.54), and developed dyslipidemia (RRR: 1.46, 95% CI: 1.30–1.63) could increase the incidence of NAFLD, while no longer having hypertension or dyslipidemia could minimize the risks of developing NAFLD. No significant association between ALT levels change and NAFLD was detected, as compared to those with normal ALT levels from 2018 to 2021 (P > 0.05).

    CharacteristicsNo (%) of NAFLDNo (%) of not NAFLDModel 1Model 2
    RRR (95% CI)aRRR (95% CI)b
    Sex
    Male1,583 (40.80)6,421 (41.10)1.001.00
    Female2,299 (59.20)9,215 (58.90)1.01 (0.94−1.09)0.97 (0.90−1.06)
    Age (years)
    65−1,845 (47.50)7,417 (47.40)1.001.00
    70−1,553 (40.00)6,272 (40.10)0.99 (0.92−1.08)0.98 (0.90−1.07)
    ≥ 75484 (12.50)1,947 (12.50)0.99 (0.89−1.18)0.97 (0.85−1.10)
    Education
    Low975 (25.10)3,811 (24.40)1.001.00
    Intermediate2,680 (69.00)10,871 (69.50)0.96 (0.89−1.05)0.94 (0.86−1.04)
    High227 (5.80)954 (6.10)0.93 (0.79−1.09)0.91 (0.76−1.09)
    Current smoking
    No3,363 (86.60)13,436 (85.90)1.001.00
    Yes519 (13.40)2,200 (14.10)0.94 (0.85−1.05)0.97 (0.84−1.11)
    Current drinking
    No3,401 (88.20)13,791 (88.20)1.001.00
    Yes481 (11.80)1,845 (11.80)0.94 (0.84−1.05)1.20 (1.05−1.38)**
    Marital status
    Single or widowed609 (15.70)2,364 (15.10)1.001.00
    Married3,273 (84.30)13,272 (84.90)0.96 (0.87−1.06)0.95 (0.85−1.06)
    Regular physical activity
    No2,983 (76.80)8,329 (53.90)1.001.00
    Yes899 (23.20)7,307 (46.70)0.34 (0.32−0.37)*0.73 (0.66−0.81)*
    Dietary habits in 2018
    Balanced3,349 (86.30)14,225 (91.00)1.001.00
    Unbalanced533 (13.70)1,411 (9.00)1.60 (1.44−1.79)*1.45 (1.28−1.64)*
    BMI status
    Remained normal538 (13.90)6,298 (40.30)1.001.00
    Weight loss238 (6.10)2,877 (18.40)0.97 (0.83−1.14)1.10 (0.93−1.30)
    Remained overweight728 (18.80)2,640 (16.90)3.23 (2.86−3.64)*3.76 (3.30−4.29)*
    Remained obesity146 (3.80)442 (2.80)3.87 (3.15−4.76)*4.49 (3.59−5.62)*
    Weight gain2,232 (57.50)3,379 (21.60)7.73 (6.98−8.57)*7.99 (7.02−9.09)*
    Hypertension
    Never hypertensive1,136 (29.30)4,249 (27.20)1.001.00
    Remained hypertension999 (25.70)4,268 (27.30)1.57 (1.32−1.78)**1.70 (1.53−1.89)*
    Developed hypertension1,345 (34.60)3,992 (25.50)1.26 (1.15−1.38)*1.90 (1.70−2.12)*
    No longer having hypertension402 (10.40)3,127 (20.00)0.48 (0.42−0.54)**0.72 (0.63−0.83)*
    Diabetes
    Never diabetic1,870 (48.20)11,163 (71.40)1.001.00
    Remained diabetes207 (5.30)376 (2.40)3.29 (2.76−3.92)*3.87 (3.18−4.71)*
    Developed diabetes1,523 (39.20)2,420 (15.50)3.76 (3.47−4.07)*4.14 (3.78−4.54)*
    No longer having diabetes282 (7.30)1,677 (10.70)1.00 (0.88−1.15)***1.08 (0.93−1.25)
    Dyslipidemia
    Never dyslipidemic1,074 (27.70)4,570 (29.20)1.001.00
    Remained dyslipidemia1,246 (32.10)4,304 (27.50)1.23 (1.12−1.35)*1.14 (1.02−1.26)***
    Developed dyslipidemia1,032 (26.60)3,577 (22.90)1.23 (1.12−1.35)*1.46 (1.30−1.63)*
    No longer having dyslipidemia530 (13.70)3,185 (20.40)0.71 (0.63−0.79)*0.72 (0.63−0.82)*
    ALT levels
    Never abnormal3,430 (88.40)14,202 (90.80)1.001.00
    Remained abnormal9 (0.20)34 (0.20)1.10 (0.53−2.29)0.63 (0.27−1.42)
    Developed abnormal331 (8.50)936 (6.00)1.47 (1.29−1.67)*1.12 (0.97−1.30)
    No longer abnormal112 (2.90)464 (3.00)0.99 (0.81−1.23)1.01 (0.80−1.27)
      Note. BMI, body mass index; ALT, alanine aminotransferase. aModel 1: Unadjusted. bModel 2: Adjusted for age (2018), sex, education, smoking status (2018), marital status (2018), drinking status (2018), regular physical activity (2018), dietary habits (2018), BMI status, diabetes status, hypertension status, dyslipidemia status, and ALT levels over time. *P < 0.001 for testing the null hypothesis that the odds ratio is equal to the odds ratio in the reference category. **P < 0.01 for testing the null hypothesis that the odds ratio is equal to the odds ratio in the reference category. ***P < 0.05 for testing the null hypothesis that the odds ratio is equal to the odds ratio in the reference category.

    Table 3.  Change in risk factors from 2018 to 2021 and the risk of developing NAFLD among participants without NAFLD in 2018 (n = 19,518)

    To the best of our knowledge, this is the first study to evaluate how over-time changes in the status of hypertension, diabetes, dyslipidemia, and ALT levels affect the incidence of NAFLD in the older adults in China. Moreover, the current study revealed that regular physical activity reduced the risk of NAFLD, whereas drinking and unbalanced dietary habits increased the risk.

    Obesity was identified as the most important risk factor for NAFLD, as its prevalence increased in proportion to obesity. Overweight and weight gain could predict the development of NAFLD[5,6]. Consistent with these studies, our findings revealed that overweight and obesity were associated with NAFLD. Further comparisons revealed that compared with those who maintained a normal weight, participants with long-term overweight and obesity had a 3.76 and 4.49 increased risk of developing NAFLD, respectively. Moreover, our study suggested that the category with the greatest risk for NAFLD was weight gain, which resulted in changes in the BMI status (RRR: 7.99, P < 0.001).

    Our study showed that diabetes was significantly associated with an increased risk of NAFLD, which was consistent with the findings of the American study[4]. Furthermore, patients who remained with diabetes or developed it during the study period had a higher risk of NAFLD than those who did not. However, an Indian cohort study did not reveal a significant association between diabetes and NAFLD[9]. The discrepancy between our study and the Indian study might be related to the sample size. Individuals in the Indian study were from a clinical cohort, thus, the conclusion might not apply to the general population.

    Many studies reported that higher TG levels (OR: 5.03, P < 0.001) and lower HDL levels (OR: 3.99, P < 0.001) are risk factors for NAFLD[7]. Our study not only revealed that dyslipidemia was associated with NAFLD, but also suggested that the presence of dyslipidemia was a more important risk factor. Consistent with other studies’ findings, our results supported a positive association between hypertension and incident NAFLD[7]. Moreover, no longer having hypertension or dyslipidemia was a protective factor for the development of NAFLD, indicating that NAFLD could be reversed when patients with hypertension or hyperlipidemia control their blood pressure and lipids to the normal levels.

    ALT levels are positively associated with NAFLD and to some extent, can be used as a diagnostic marker for NAFLD. However, 25% of patients with NAFLD showed normal ALT levels clinically; however, the elevation of ALT levels is a non-invasive indicator of NAFLD[8,10]. A positive association between ALT levels and NAFLD was observed in the cross-sectional analysis of our study; however, this relationship was not detected in the longitudinal analysis. Therefore, further studies are required to verify the impact of ALT levels on NAFLD.

    Our study had several strengths, as it is the first study to examine how changes in the status of hypertension, diabetes, dyslipidaemia, and ALT levels over time impact incident NAFLD in the elderly in China. Moreover, the sample size was large enough, increasing the statistical power to detect the association between relative factors and NAFLD. However, this study had some limitations. First, the participants were not from a population-based sample and might not be representative of the entire population. Second, residual confounders might have been ignored in the analysis, although some confounders were controlled in the current study. Third, the diagnostic criteria for NAFLD were based on ultrasonography, which might not be sensitive to mild NAFLD and could not clarify its severity. However, ultrasonography, as a non-invasive method, has been widely used in population-based studies because of its high diagnostic value in detecting NAFLD.

    In conclusion, our study revealed that alcohol drinking, unbalanced dietary habits, long-term overweight or obesity, over-time weight gain that results in a BMI category, and the presence of diabetes, hypertension, or dyslipidemia, can increase the risk of developing NAFLD, while regular physical activity and no longer having dyslipidemia or hypertension are protective factors against incident NAFLD. Therefore, the elderly individuals should control their weight, blood pressure, and blood glucose and lipid levels to normal levels to prevent the development of NAFLD.

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