Frontiers in nutrition · 2025
Association between GNRI and risk of non-alcoholic fatty liver disease in non-obese individuals: a Chinese longitudinal prospective cohort study.
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Shen Linlin, Chen Siyu, Guo Haoran, Wang Zhiyan, Yang Jiashu, Chen Ke, Yuan Hui
Аннотация
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic liver disorder characterized by excessive hepatic fat accumulation without significant alcohol consumption. While obesity is a major risk factor, many non-obese individuals also develop NAFLD. However, research on this subgroup remains limited, and its underlying risk factors are unclear. Nutritional status plays a key role in NAFLD pathogenesis. The geriatric nutritional risk index (GNRI), widely used to assess nutrition, is linked to adverse health outcomes. However, its association with NAFLD in non-obese individuals remains poorly understood.
METHODS: A post-hoc evaluation was conducted using longitudinal data from the Dryad repository, derived from health screenings of non-obese individuals at Wenzhou People's Hospital (2010-2014). Participants with baseline NAFLD, alcohol abuse, metabolic disorders, or liver diseases were excluded. The Geriatric Nutritional Risk Index (GNRI) was calculated using serum albumin and weight-to-ideal weight ratios (Lorentz equations). Eligible participants were categorized into quartiles based on GNRI values. NAFLD was diagnosed via ultrasound following Chinese Liver Disease Association criteria. Cox proportional hazards regression (adjusted for confounders in three models), Kaplan-Meier analysis, and restricted cubic splines were employed to evaluate associations between GNRI and NAFLD incidence. Linear trends and subgroup interactions were tested. Statistical analyses were performed using R (v4.0).
RESULTS: The participants in higher GNRI groups had a higher risk of developing NAFLD, even after adjusting for confounding factors. This association was consistent across different body mass index (BMI) levels, although the trend was less significant in the higher BMI group. Furthermore, subgroup analysis revealed a consistent association between GNRI and NAFLD incidence in different sex, age, BMI, and systolic blood pressure (SBP) groups. However, there were some interactions observed in different alanine aminotransferase (ALT) groups.
CONCLUSION: Our findings suggest that GNRI may serve as a useful indicator for predicting the risk of NAFLD in non-obese individuals, providing valuable insights for early detection and intervention strategies for this condition.
METHODS: A post-hoc evaluation was conducted using longitudinal data from the Dryad repository, derived from health screenings of non-obese individuals at Wenzhou People's Hospital (2010-2014). Participants with baseline NAFLD, alcohol abuse, metabolic disorders, or liver diseases were excluded. The Geriatric Nutritional Risk Index (GNRI) was calculated using serum albumin and weight-to-ideal weight ratios (Lorentz equations). Eligible participants were categorized into quartiles based on GNRI values. NAFLD was diagnosed via ultrasound following Chinese Liver Disease Association criteria. Cox proportional hazards regression (adjusted for confounders in three models), Kaplan-Meier analysis, and restricted cubic splines were employed to evaluate associations between GNRI and NAFLD incidence. Linear trends and subgroup interactions were tested. Statistical analyses were performed using R (v4.0).
RESULTS: The participants in higher GNRI groups had a higher risk of developing NAFLD, even after adjusting for confounding factors. This association was consistent across different body mass index (BMI) levels, although the trend was less significant in the higher BMI group. Furthermore, subgroup analysis revealed a consistent association between GNRI and NAFLD incidence in different sex, age, BMI, and systolic blood pressure (SBP) groups. However, there were some interactions observed in different alanine aminotransferase (ALT) groups.
CONCLUSION: Our findings suggest that GNRI may serve as a useful indicator for predicting the risk of NAFLD in non-obese individuals, providing valuable insights for early detection and intervention strategies for this condition.