Age patterns of nonalcoholic fatty liver disease incidence: heterogeneous associations with metabolic changes - PubMed (original) (raw)

Age patterns of nonalcoholic fatty liver disease incidence: heterogeneous associations with metabolic changes

Yansong Lin et al. Diabetol Metab Syndr. 2022.

Abstract

Background: As the nonalcoholic fatty liver disease (NAFLD) epidemic matures, understanding how metabolic changes in NAFLD development vary over the age distribution is important to guide precise prevention. We aimed to clarify metabolic trends in age-specific NAFLD incidence.

Methods: We conducted a 4-year longitudinal retrospective cohort study enrolling 10,240 consecutive healthy individuals who received annual physical examination during 2012-2019. Baseline and dynamic changes in metabolism and hepatic steatosis determined with ultrasound were collected and analyzed stratified by age into the following groups: 20-34, 35-49, 50-64, and over 65 years.

Results: Overall, 1701 incident NAFLD participants (16.6%) were identified. Adjusted Cox regression analysis showed that the baseline and increased body mass index were the main risk factors for NAFLD in people ≤ 65 years old. Baseline high-density lipoprotein (HR = 0.56; 95% CI 0.39-0.78) was a protective factor for newly onset NAFLD in the 50-to-64-year-old group, while baseline SBP (HR = 1.03; 95% CI 1.01-1.05), baseline uric acid (HR = 1.04; 95% CI 1.01-1.07), triglyceride increase (HR = 4.76; 95% CI 3.69-6.14), fasting blood glucose increase (HR = 1.32; 95% CI 1.06-1.65) were independently associated with incident NAFLD in over-65-year-old group.

Conclusions: NAFLD incidence attributable to potentially metabolic risk factors varied substantially across age groups in a cohort of Chinese people. The adoption of age targeted metabolic prevention strategies might reduce the burden of NAFLD.

Keywords: Aging; Incidence rate; Metabolic disorder; Nonalcoholic fatty liver disease; Risk factors.

© 2022. The Author(s).

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1

Fig. 1

The incidence of NAFLD in different age (A), gender (B) and obesity status (C), as well as the ratio of new-onset metabolic abnormalities along with incident NAFLD (D) during follow up. (*p < 0.05; **p < 0.01; ***p < 0.001)

Fig. 2

Fig. 2

The cumulative incidence of NAFLD in the quartiles (Q) of baseline risk factors for the new-onset of NAFLD. A–D Baseline BMI; E–H baseline SBP. The corresponding quartiles of the variables were shown on the right side of the picture. Because all patients with completed follow-up for 4 years, therefore the numbers of patients at risk for each K–M curves were not shown

Fig. 3

Fig. 3

The cumulative incidence of NAFLD in the quartiles (Q) of dynamic changes of risk factors for the new-onset of NAFLD. A–D ΔBMI; E–H ΔTG; I–L ΔFBG. The corresponding quartiles of the variables were shown on the right side of the picture. Because all patients with completed follow-up for 4 years, therefore the numbers of patients at risk for each K–M curves were not shown

Fig. 4

Fig. 4

The cumulative incidence of NAFLD in the quartiles (Q) of baseline risk factors for the new-onset of NAFLD. A–D Baseline HDL-c; E–H baseline UA. The corresponding quartiles of the variables were shown on the right side of the picture. Because all patients with completed follow-up for 4 years, therefore the numbers of patients at risk for each K–M curves were not shown

Fig. 5

Fig. 5

Forest plot of the risk factors for incidence of NAFLD (A) and receiver operator characteristic (ROC) curve of factors that predict incidence of NAFLD in different groups (B)

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