Study design and population
The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. In the current study, we employed data from four NHANES cycles (2011–2012, 2013–2014, 2015–2016, and 2017–2018) to investigate the association between uACR and T2MD among male and female individuals. The ethics review committee of the National Center for Health Statistics (NCHS) approved the NHANES' research plan. All participants provided written informed consent. Further details can be obtained from the website www.cdc.gov/nchs/nhanes/irba98.htm. In the NHANES study from 2011 to 2018, 10,654 participants aged > 18 years with complete laboratory urine data and diabetes data were included. Demographic, examination, laboratory, and questionnaire data were collected. Individuals with missing values for the covariates (see “Potential covariates” section; n = 5347) were excluded. Finally, 5307 subjects were included in our study.
Definition of uACR and diabetes
Professionally trained researchers obtained 5 mL of self-collected urine from each participant, and sent frozen urine samples (≤ − 20 °C) to the laboratory. Specimen stability was demonstrated at 5 °C and temperatures less than or equal to − 20 °C. Urine albumin was measured using solid-phase fluorescent immunoassay, and urine creatinine was measured using the Roche/Hitachi Modular P Chemistry Analyzer in 2011 and Roche/Hitachi Cobas 6000 chemistry analyzer in 2013. Urine albumin and creatinine levels were standardized and calibrated with the gold standard method according to the recommendations of the National Health and Nutrition Examination Survey. The exposure variable was uACR, where uACR = urine albumin/urine creatinine.
The primary outcome of this study was diabetes. Diabetes as diagnosed according to the standards of the American Diabetes Association  and participants’ self-reported questionnaires. diabetes was diagnosed. Each of the following conditions was diagnosed as diabetes: fasting plasma glucose ≥ 7 mmol/L, self-reported physician diagnosis of diabetes, or current use of diabetes medication to lower blood glucose level.
Covariates were included as potential confounders in the final multivariate logistic regression models if the estimates of uACR for diabetes changed by more than 10% , or were known as traditional risk factors for diabetes. The following variables were used to construct the fully adjusted model: continuous variables included age, poverty income ratio, body mass index (BMI, kg/m2), systolic blood pressure (SBP, mmHg), diastolic blood pressure (DBP, mmHg), alcohol intake (drinks per day), fasting blood glucose (FBG, mg/dL), triglycerides (TG, mg/dL), total cholesterol (TC, mg/dL), high-density lipoprotein cholesterol (HDL-C, mg/dL), low-density lipoprotein cholesterol (LDL-C, mg/dL), and estimated glomerular filtration rate (eGFR, mL/min/1.73 m2). Categorical variables included sex (male or female), race (non-Hispanic white, non-Hispanic black, Mexican American, other Hispanic, or others), smoking status (never, former, or current), hypertension, antihypertensive drugs, and lipoprotein-lowering drugs. Furthermore, eGFR was calculated using the Chronic Kidney Disease (CKD) Epidemiology Collaboration equation . Hypertension was defined as a self-reported physician diagnosis of hypertension, SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg, or the use of antihypertensive drugs .
Continuous variables were compared using one-way analysis of one-way ANOVA among the different groups. Categorical variables were compared using the chi-squared test or Fisher’s exact test among the different groups. Continuous variables are summarized as mean ± standard deviation, while categorical variables are expressed as counts (percentage). Because of the skewed distribution of uACR in this study, Log10 conversion (Lg uACR) was carried out in the data analysis. Multivariate logistic regression analysis was used to evaluate the prevalence of diabetes based on the uACR (continuous and categorical variables). Three models were constructed for regression analysis: Model 1 was adjusted for none and Model 2 for age, sex (only for the overall population), race, poverty income ratio, BMI, SBP, DBP, current smoking, alcohol intake, FPG, TG, TC, HDL, and LDL. In model 3, eGFR, antihypertensive drugs, and lipoprotein-lowering drugs were considered, in addition to model 2 adjustments. A generalized additive model and fitted smoothing curve (penalized spline method) were used to characterize the shape of the relationship between uACR and diabetes. Furthermore, possible modifications of the association between uACR and diabetes were assessed for the following variables: age (< 65 vs. ≥ 65 years), race (non-Hispanic white vs. non-Hispanic black vs. Mexican American vs. other Hispanic vs. other races), BMI (< 24 vs. ≥ 24 kg/m2), smoking status (never vs. former vs. current), hypertension (yes vs. no), and eGFR (< 60 vs. ≥ 60 mL/min/1.73 m2).
Statistical analyses were conducted using R, version 4.2.0 (R Foundation) and Empower Stats (http://www.empowerstats.com, X&Y Solutions, Inc., Boston, MA). A two‐tailed P value < 0.05 was considered statistically significant.