---
title: "TyG index linked to microalbuminuria in 33,416 adults: stronger association in diabetes"
id: "plos-one-1-tyg-index-is-associated-with-microalbuminuria-in-a-large-population-based-study"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-1-tyg-index-is-associated-with-microalbuminuria-in-a-large-population-based-study"
content_type: "clinical_feed_article"
specialty: "General"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437"
published_at: "2026-08-05T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# TyG index linked to microalbuminuria in 33,416 adults: stronger association in diabetes
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-1-tyg-index-is-associated-with-microalbuminuria-in-a-large-population-based-study
- **Specialty:** [General](https://medichelpline.com/clinical-feed/general.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437)
- **Published At:** 2026-08-05T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This large cross-sectional analysis used data from 33,416 Chinese adults to evaluate the association between the **triglyceride–glucose (TyG) index** and **microalbuminuria** (UACR ≥ 30 mg/g). - Mean age was 57.7 years; 33.2% were male; 22.8% had diabetes; overall microalbuminuria prevalence was 14.5%. - TyG index was normally distributed (mean ≈ 8.8). Higher TyG quartiles showed progressively greater proportions of microalbuminuria, CKD, diabetes, and hypertension. - Multivariable logistic regression showed a persistent positive association: fully adjusted OR per 1-unit TyG increase = **1.28** (95% CI 1.20–1.36; P < 0.001). - Restricted cubic spline analysis indicated a linear relationship between TyG and microalbuminuria risk (P overall < 0.001; P for non-linearity = 0.187). - Associations were present in participants without diabetes (OR 1.13; 95% CI 1.04–1.23) and with diabetes (OR 1.46; 95% CI 1.32–1.60); the interaction by diabetes status was statistically significant (P < 0.001, FDR-corrected P = 0.008), indicating a stronger estimated effect among those with diabetes. - Sensitivity and subgroup analyses (including adjustment sets, VIF checks, and RCS modeling) supported the robustness of findings. - Authors note the cross-sectional design precludes causal inference and call for longitudinal studies to establish temporality. - The TyG index may be a simple, accessible marker to identify individuals with higher odds of microalbuminuria across glycemic status, pending prospective confirmation.
## Clinical Analysis & Structured Key Points
[ Skip to main content ](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#main-content) Advertisement * [plos.org](https://plos.org/) * [Create account](https://community.plos.org/registration/new) * [Sign in](https://journals.plos.org/user/secure/login?page=%2Fplosone%2Farticle%3Fid%3D10.1371%2Fjournal.pone.0355437) * * About * Browse * Publish * [](https://journals.plos.org/plosone/ "PLOS One") * Search [advanced search](https://journals.plos.org/plosone/search) * [Browse Topics](https://journals.plos.org/plosone/subjectAreaBrowse) Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click [here](https://github.com/PLOS/plos-thesaurus/blob/master/README.md "Link opens in new window"). [](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437) [](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437) * 0 [Save](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0355437#savedHeader) [Total Mendeley and Citeulike bookmarks.](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0355437#savedHeader) * 0 [Citation](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0355437#citedHeader) [Paper's citation count computed by Dimensions.](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0355437#citedHeader) * 22 [View](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0355437#viewedHeader) [PLOS views and downloads.](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0355437#viewedHeader) * 0 [Share](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0355437#discussedHeader) [Sum of Facebook, Twitter, Reddit and Wikipedia activity.](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0355437#discussedHeader) Open Access Peer-reviewed Research Article # TyG index is associated with microalbuminuria in a large population-based study: independent and exploratory interaction analyses * Xiaomin Lin, Roles Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – original draft Affiliation Department of Clinical Laboratory, Jieyang People’s Hospital, Jieyang, Guangdong, China ⨯ * Xudong Huang Roles Conceptualization, Supervision, Validation, Writing – review & editing * E-mail: 6g339@163.com Affiliation Department of Clinical Laboratory, Jieyang People’s Hospital, Jieyang, Guangdong, China [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0009-0008-8573-1596 ](https://orcid.org/0009-0008-8573-1596 "ORCID Registry") ⨯ # TyG index is associated with microalbuminuria in a large population-based study: independent and exploratory interaction analyses * Xiaomin Lin, * Xudong Huang ![PLOS](https://journals.plos.org/resource/img/logo-plos-full-color.svg) x * Published: August 5, 2026 * * [Article](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437) * [Authors](https://journals.plos.org/plosone/article/authors?id=10.1371/journal.pone.0355437) * [Metrics](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0355437) * [Comments](https://journals.plos.org/plosone/article/comments?id=10.1371/journal.pone.0355437) * [Media Coverage](http://plos.altmetric.com/details/doi/10.1371/journal.pone.0355437) * [Abstract](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#abstract0) * [Introduction](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#sec005) * [Methods](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#sec006) * [Results](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#sec014) * [Discussion](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#sec019) * [Conclusion](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#sec020) * [Supporting information](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#sec021) * [References](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#references) * [Reader Comments](https://journals.plos.org/plosone/article/comments?id=10.1371/journal.pone.0355437) * [Figures](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437) ## Abstract ### Background Insulin resistance surrogates are associated with microalbuminuria; however, population-scale evidence for the triglyceride–glucose (TyG) index remains scarce. We examined the cross-sectional association between TyG index and microalbuminuria in a large Chinese cohort and explored whether diabetes modifies this link. ### Methods We analyzed 33,416 adults from eight regional centers. Microalbuminuria was defined as urinary albumin-to-creatinine ratio ≥ 30 mg/g. Multivariate logistic regression and restricted cubic splines were used to estimate odds ratios (ORs) per 1-unit TyG increase and the potential nonlinear relationship between TyG index and microalbuminuria risk. The effects of diabetes and other factors were tested using interaction terms. ### Results The mean age was 57.7 ± 9.3 years, and the microalbuminuria prevalence was 14.5%. TyG index was independently associated with microalbuminuria after adjustment for age, sex, body mass index, waist, hip circumference, blood pressure, lipids, liver function indices, sleep variables, estimated glomerular filtration rate, smoking, alcohol, and diabetes (OR, 1.28; 95% confidence interval [CI], 1.20–1.36; _P_ < 0.001). Restricted cubic spline analysis demonstrated a linear association between TyG index and the odds of microalbuminuria (_P_ for overall association < 0.001; _P_ for non-linearity = 0.187). The association was present in participants with (OR, 1.46; 95% CI, 1.32–1.60) and without diabetes (OR, 1.13; 95% CI, 1.04–1.23). The interaction with diabetes status was significant (_P_ < 0.001; false discovery rate-corrected _P_ = 0.008), indicating a stronger association in patients with diabetes. The sensitivity analyses confirmed the robustness of the main findings. ### Conclusions The TyG index was linearly associated with microalbuminuria. This association was observed in patients with and without diabetes, with a stronger estimated effect among those with diabetes. TyG may serve as a simple, readily available marker for identifying individuals with higher odds of microalbuminuria across glycemic status; however, longitudinal studies are needed to establish temporal relationships. ## Figures ![Fig 3](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.g003) ![Fig 1](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.g001) ![Table 1](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.t001) ![Table 2](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.t002) ![Fig 2](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.g002) ![Table 3](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.t003) ![Table 4](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.t004) ![Fig 3](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.g003) ![Fig 1](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.g001) ![Table 1](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.t001) ![Table 2](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.t002) **Citation:** Lin X, Huang X (2026) TyG index is associated with microalbuminuria in a large population-based study: independent and exploratory interaction analyses. PLoS One 21(8): e0355437. https://doi.org/10.1371/journal.pone.0355437 **Editor:** Santhi Silambanan, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), INDIA **Received:** January 13, 2026; **Accepted:** July 21, 2026; **Published:** August 5, 2026 **Copyright:** © 2026 Lin, Huang. This is an open access article distributed under the terms of the [Creative Commons Attribution License](http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. **Data Availability:** The data underlying this study are third-party data owned by the original investigators and are publicly available in the [Supporting Information](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#sec021) of Ye et al. (PLOS ONE, 2019; [https://doi.org/10.1371/journal.pone.0214776)](https://doi.org/10.1371/journal.pone.0214776). The authors did not collect these data and confirm that they did not have any special access privileges that other researchers would not have. **Funding:** The author(s) received no specific funding for this work. **Competing interests:** The authors have declared that no competing interests exist. ## Introduction Chronic kidney disease (CKD) is estimated to affect approximately 10% of the population, or 800 million individuals globally [[1](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref001)]. Microalbuminuria, as reflected by the urinary albumin-to-creatinine ratio (UACR), is recognized as an early marker of kidney injury [[2](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref002)–[4](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref004)]. Additionally, microalbuminuria often indicates vascular damage and is closely associated with cardiovascular complications of various diseases [[5](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref005)–[8](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref008)]. Given the important role of microalbuminuria in CKD and cardiovascular disease and the large and growing burden of cardiovascular disease and CKD worldwide, timely identification of individuals at high risk for microalbuminuria is critical in both the prevention and management of CKD and cardiovascular disease. Therefore, the early identification of individuals with increased albumin excretion remains a public health priority [[9](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref009)]. The triglyceride–glucose (TyG) index, a simple ln-based composite of fasting triglycerides and glucose, has emerged as a reliable proxy for insulin resistance (IR) [[10](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref010),[11](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref011)]. IR is a pathological condition characterized by diminished cellular response to insulin, leading to metabolic dysregulation that contributes to the pathogenesis of several chronic diseases [[12](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref012)]. Because insulin receptors are expressed in the vasculature and kidneys, in addition to classical insulin-targeting tissues, IR may influence the renal regulation of glucose uptake, glomerular function regulation, gluconeogenesis, and tubular transport [[13](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref013)]. According to previous studies, IR and/or its contributing variables may be harmful at the onset of CKD [[14](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref014)]. A recent study has suggested that the effect of IR on mortality in patients with albuminuric diabetic nephropathy may be mediated by its association with albuminuria [[15](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref015)]. Prior studies support a positive association between the TyG index and microalbuminuria as well as renal injury; however, these studies have predominantly focused on specific chronic disease populations, with relatively small sample sizes [[16](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref016)–[18](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref018)]. Evidence in the general population without diabetes remains sparse, and the potential difference in the association between TyG and microalbuminuria among individuals with and without diabetes remains unclear. Notably, the few general-population studies that included individuals without diabetes have generally reported null associations in that subgroup, leaving it unclear whether the TyG–microalbuminuria association extends beyond diabetes. The present large multicenter analysis was designed to address this gap. Therefore, we analyzed 33,416 adults from a nationwide multicenter population-based survey to quantify the cross-sectional association between the TyG index and microalbuminuria. Considering that the degree of IR varies in different populations, such as those with poor lifestyle, environmental, and psychological factors in the population without diabetes, this may lead to an increased susceptibility to microalbuminuria, which may affect the results of our study. Accordingly, we specifically focused on whether this association was consistent between individuals with and without diabetes. ## Methods ### Study design and data sources This cross-sectional study aimed to evaluate the relationship between the TyG index and microalbuminuria and to explore whether diabetes modifies this association by stratifying the population with and without diabetes. This was a secondary analysis of a publicly available dataset from Ye et al. [[19](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone.0355437.ref019)], which was not specified in the original study protocol. The original study by Ye et al. investigated the associations of self-reported sleep duration and daytime napping with renal hyperfiltration and microalbuminuria, which was also an outcome in that report. The present study addresses an entirely different exposure—the TyG index—which was not examined in the original publication, and we additionally adjusted for the sleep variables identified in the parent study. Accordingly, no overlap exists between the exposure–outcome associations reported here and those in the original article, and these findings should be considered exploratory and hypothesis-generating. Data were obtained from the China Multicenter Longitudinal Study of Diabetes Cancer Risk Assessment. After applying the exclusion criteria (primary kidney disease, ACEI/ARB medication use, and extreme sleep duration), the study cohort comprised 33,850 participants from eight regional Chinese centers. The original study was approved by the Institutional Review Board of Ruijin Hospital, Shanghai Jiao Tong University, and all the participants provided written informed consent. The authors had no access to any identifying information during or after the analysis, therefore, additional ethical approval was not required for this retrospective analysis. ### Missing value handling Missing data were handled using complete-case analysis (listwise deletion) because the proportion of missing data was low (< 2% for all variables). This approach is unlikely to have introduced material bias given the low level of missingness; therefore, multiple imputations were not undertaken. Building on the original study, we excluded 434 individuals with incomplete covariate information, primarily those with missing smoking or alcohol consumption data. Ultimately, 33,416 participants were included in the study. The participant selection procedure is illustrated in [Fig 1](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355437#pone-0355437-g001). [![thumbnail](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0355437.g001)](https://journals.plos.org/plosone/article/figure/image?size=medium&id=10.1371/journal.pone.0355437.g001 "Click for larger image") Download: * [PNG larger image](https://journals.plos.org/plosone/article/figure/image?download&size=large&id=10.1371/journal.pone.0355437.g001) * [TIFF original image](https://journals.plos.org/plosone/article/figure/image?download&size=original&id=10.1371/journal.pone.0355437.g001) Fig 1. Process flow diagram for the study’s population inclusion. [ https://doi.org/10.1371/journal.pone.0355437.g001](https://doi.org/10.1371/journal.pone.0355437.g001) ### Clinical and laboratory measurements In the initial study, basic demographic information and laboratory data were collected by trained medical staff through standardized surveys. Demographic information included age, sex, smoking status, alcohol consumption, and family history of diabetes. Participants’ height, weight, hip circumference (HC), waist circumference (WC), diastolic blood pressure (DBP), and systolic blood pressure (SBP) were measured. Blood samples were collected early in the morning after an 8-hour fast the night before for biochemical tests, including triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), creatinine (Scr), serum urea nitrogen (BUN), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma–glutamyl transpeptidase (GGT), fasting blood glucose (FBG), glycated hemoglobin (HbA1c), fasting blood insulin, and postprandial blood insulin. Participants without a history of diabetes underwent a 75 g oral glucose tolerance test, whereas those with diabetes underwent a 100 g oral glucose tolerance test, after which a venous blood sample was drawn for postprandial blood glucose measurement at 120 min. ### UACR measurement UACR was measured after a urine sample was collected in the morning. Microalbuminuria was defined as a UACR ≥ 30 mg/g, which was calculated as follows: UACR = urine albumin (mg/dl) / urine creatinine (g/dl). ### Calculation and assessment of the TyG index The formula below was used to determine the TyG index: ![](https://journals.plos.org/plosone/article/file?type=thumbnail&id=10.1371/journal.pone.0355437.e001) ### Definitions FBG ≥ 7.0 mmol/L, PBG ≥ 11.1 mmol/L, or a documented medical history of diabetes were the criteria for diabetes mellitus. An average systolic blood pressure ≥ 130 mm Hg or a diastolic blood pressure ≥ 80 mm Hg after three measurements, or a history of hypertension, are considered indicators of hypertension. The estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease formula. CKD was defined as an eGFR < 60 ml/min, which was calculated as follows: eGFR(ml/min * 1.73 m2) = 186 * Scr(mg/dl)−1.154 * age(years)-0.203(female * 0.742) ### Statistical analysis and assessment of covariates Continuous variables are presented as means ± standard deviations or as medians; categorical variables are described as percentages. TyG was analyzed per 1-unit increase and across quartiles (Q1 = reference). Quartiles were selected a priori because they yielded four equally sized groups, allowing a test for a dose–response trend without imposing a specific functional form, limiting the influence of extreme values, and were consistent with the categorizati
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