Prevalence of Albuminuria Across Cardiovascular‐Kidney‐Metabolic Phenotypes in the United States

Albuminuria is an integrative biomarker of cardiovascular, kidney and metabolic (CKM) health and is associated with increased risk of chronic kidney disease (CKD) progression and cardiovascular events [1]. However, it is undermeasured in clinical practice, even within guideline-recommended groups such as patients with diabetes and hypertension [2, 3]. Therefore, the actual prevalence of albuminuria within CKM phenotypes is unknown. We examined albuminuria prevalence across CKM phenotypes using data from the National Health and Nutrition Examination Survey (NHANES) 2011–2020. Urine albumin-to-creatinine ration (UACR) is measured in all NHANES participants, which is distinct from risk-driven testing in clinical settings. We excluded patients who did not provide a urine sample (N = 556); and those who were pregnant, received dialysis, or were < 20 years old. To ensure accurate phenotype classification, we required complete data on all five component conditions: diabetes, hypertension, obesity, cardiovascular disease and chronic kidney disease. Participants with missing data on any component condition were excluded from phenotype assignment (N = 2291, 9.5% of the sample). The primary driver of missingness was CKD status (5.8%), attributable to missing serum creatinine measurements required for eGFR calculation. We defined 17 mutually exclusive CKM phenotypes based on vital signs, labs, self-reported medical history (for cardiovascular disease only) and medication use. Phenotype classification was designed to characterise disease clustering patterns and their association with albuminuria (N = 217 could not be categorized meaningful phenotypes and were excluded). The analytic sample was N = 21 497. We calculated the prevalence of albuminuria by: “normal to mildly increased” (UACR 0–29 mg/g), “moderately increased” (30–299 mg/g), and “severely increased” (≥ 300 mg/g) [4]. Prevalence estimates were age-standardised to the 2010 US Census. Analyses were performed in SAS v9.4 with appropriate survey procedures; data are publicly available at (https://wwwn.cdc.gov/nchs/nhanes/default.aspx). The mean (SD) age of the population was 48.2 (17) years, and 51.0% were women. The prevalence of moderate and severe albuminuria appeared to increase with higher CKM comorbidity burden (Table 1). Among participants with no CKM conditions, the prevalence of moderate albuminuria was 4.4% (95% CI 3.4%–5.3%). The prevalence of moderate albuminuria among individuals with single CKM conditions ranged from 4.4% (2.8%–5.9%) in those with obesity alone to 11.3% (5.6%–16.9%) in those with diabetes alone. In participants with concurrent diabetes and hypertension, the prevalence of moderate albuminuria was 17.5% (11.4%–23.6%) and severe albuminuria was 4.3% (2.1%–6.5%). In participants with concurrent hypertension, cardiovascular disease, and low eGFR, the prevalence of moderate albuminuria was 54.2% (44.8%–63.6%) and severe albuminuria was 4.8% (1.1%–8.5%). In participants with concurrent diabetes, hypertension and cardiovascular disease but preserved eGFR, the prevalence of moderate albuminuria was 29.9% (14.2%–45.5%) and severe albuminuria was 11.3% (1.2%–21.3%). For individuals with concurrent diabetes, hypertension, and low eGFR but without cardiovascular disease, the prevalence of severe albuminuria was 50.3% (43.6%–57.1%), noting that the age-adjusted prevalence of moderate albuminuria could not be calculated due to no participants meeting these criteria in the 20–39 year old age group (crude values provided). None of the participants with diabetes alone and moderate–severe albuminuria were prescribed an angiotensin converting enzyme inhibitor/angiotensin receptor blocker (ACEi/ARB), glucagon-like peptide-1 receptor agonist (GLP1-RA) or sodium-glucose co-transporter-2 inhibitor (SGLT2i). Only 30.2% of individuals with hypertension alone and moderate–severe albuminuria were prescribed an ACEi/ARB. Similarly, only 27.5% of individuals with hypertension, obesity and moderate–severe albuminuria were prescribed an ACEi/ARB. Among individuals with diabetes, hypertension, and moderate–severe albuminuria, only 55.8% were prescribed any antiproteinuric therapy, with ACEi/ARB predominating. None of the participants with moderate–severe albuminuria were prescribed any antiproteinuric therapy in the following subgroups: diabetes alone, obesity alone, and cardiovascular disease alone. Only 3% of individuals with diabetes, obesity and moderate–severe albuminuria were prescribed antiproteinuric therapy (SGLT2i and GLP1-RA, no ACEi/ARB). Among participants with moderate–severe albuminuria, blood pressure control was similar between those prescribed antiproteinuric therapies and those not prescribed antiproteinuric medications. In this study, we describe the prevalence of albuminuria across non-overlapping CKM phenotypes in a nationally representative sample of US adults. Even within the single comorbidity subgroups, the burden of albuminuria was substantial. For example, of the 133 participants with CVD, approximately 4.9% (0.8%–9.1%) had UACR ≥ 30 mg/g—meeting criteria for CKD [4]. This is clinically meaningful given albuminuria's strong prognostic value for both CKD progression and cardiovascular events [1] and represents an opportunity for CKD care to be integrated into cardiovascular clinics through the use of cardio-renal protective medications (e.g., SGLT2i, ACEi/ARB, etc.). Similarly, approximately 4.4% (2.8%–5.9%) of individuals with obesity alone and 6.8% (5.8%–7.8%) of individuals with hypertension alone had UACR 30–299 mg/g, again consistent with a diagnosis of albuminuric CKD despite preserved eGFR. These findings are especially informative given that clinical practice guidelines, such as the 2025 AHA/ACC/Multi-specialty blood pressure guidelines, now incorporate albuminuria screening for specific cardiovascular risk groups and may lead to greater CKD identification. Further work is needed to understand the causal pathway for CKD development in these single-comorbidity groups and the optimal therapeutic approach to prevent CKM syndrome progression. Our findings extend the literature on low use of ACEi/ARB in the United States [5, 6]. Despite 11.3% of participants with diabetes alone having moderate–severe albuminuria, none were prescribed antiproteinuric therapies; this is a group in which ACEi/ARB were guideline-recommended during the study period, with emerging evidence for SGLT2i use as well [4]. Similarly low rates of ACEi/ARB use were found in other guideline-directed groups such as diabetes and hypertension (58.3%), hypertension and cardiovascular disease (48.9%), diabetes, hypertension and obesity (54.9%). This suggests that either albuminuria is not being tested in clinical environments and thus CKD is underrecognized, or clinicians are reticent to treat albuminuria when eGFR remains > 60 mL/min/1.73m2. However, once eGFR declines, it becomes challenging to slow disease progression. As the treatment landscape evolves, it will be critical to optimise albuminuria identification and management across primary care and subspecialty settings. Limitations of this study include potential misclassification of CKM phenotype, small sample size for certain phenotypes and single UACR measurement from a spot urine sample rather than first-morning void. Prevalence estimates may be underestimated due to treatment with anti-proteinuric therapy lowering UACR values. Small sample size may contribute to unstable estimates or under-estimation, particularly for the severe albuminuria category. Guideline-recommended indications for SGLT2i and GLP1-RA evolved during the study period, which limits interpretation of their implementation. For example, during the majority of the study period, SGLT2i and GLP1-RA were only indicated for the treatment of diabetes. Therefore, the prescription rates presented in this study should be interpreted in the context of the approved medication indication at the time of data collection. CKD is a growing public health challenge as the population ages. Moderate–severe albuminuria is common among those with multiple CKM comorbidities but is also found among those with a single CKM condition. Identification and timely initiation of therapies for albuminuria could substantially reduce the future burden of kidney failure and cardiovascular disease. Dr. Ashish Verma is supported by the American Heart Association Career Development Award (24CDA1274501) and the Boston University Department of Medicine Career Investment Award. The authors declare no conflicts of interest. Data are publicly available at https://wwwn.cdc.gov/nchs/nhanes/default.aspx. The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/dom.70607.

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Diabetes Obesity and Metabolism
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2026-02-26
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https://doi.org/10.1111/dom.70607
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Chronic Kidney Disease and Diabetes
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article

Prevalence of Albuminuria Across Cardiovascular‐Kidney‐Metabolic Phenotypes in the United States

Sophie E. Claudel, Sushrut S Waikar, Ashish Verma, Donald M Lloyd-Jones
Diabetes Obesity and Metabolism
Chronic Kidney Disease and Diabetes
article

Prevalence of Albuminuria Across Cardiovascular‐Kidney‐Metabolic Phenotypes in the United States

Sophie E. Claudel, Sushrut S Waikar, Ashish Verma, Donald M Lloyd-Jones
article en

Abstract

Albuminuria is an integrative biomarker of cardiovascular, kidney and metabolic (CKM) health and is associated with increased risk of chronic kidney disease (CKD) progression and cardiovascular events [1]. However, it is undermeasured in clinical practice, even within guideline-recommended groups such as patients with diabetes and hypertension [2, 3]. Therefore, the actual prevalence of albuminuria within CKM phenotypes is unknown. We examined albuminuria prevalence across CKM phenotypes using data from the National Health and Nutrition Examination Survey (NHANES) 2011–2020. Urine albumin-to-creatinine ration (UACR) is measured in all NHANES participants, which is distinct from risk-driven testing in clinical settings. We excluded patients who did not provide a urine sample (N = 556); and those who were pregnant, received dialysis, or were < 20 years old. To ensure accurate phenotype classification, we required complete data on all five component conditions: diabetes, hypertension, obesity, cardiovascular disease and chronic kidney disease. Participants with missing data on any component condition were excluded from phenotype assignment (N = 2291, 9.5% of the sample). The primary driver of missingness was CKD status (5.8%), attributable to missing serum creatinine measurements required for eGFR calculation. We defined 17 mutually exclusive CKM phenotypes based on vital signs, labs, self-reported medical history (for cardiovascular disease only) and medication use. Phenotype classification was designed to characterise disease clustering patterns and their association with albuminuria (N = 217 could not be categorized meaningful phenotypes and were excluded). The analytic sample was N = 21 497. We calculated the prevalence of albuminuria by: “normal to mildly increased” (UACR 0–29 mg/g), “moderately increased” (30–299 mg/g), and “severely increased” (≥ 300 mg/g) [4]. Prevalence estimates were age-standardised to the 2010 US Census. Analyses were performed in SAS v9.4 with appropriate survey procedures; data are publicly available at (https://wwwn.cdc.gov/nchs/nhanes/default.aspx). The mean (SD) age of the population was 48.2 (17) years, and 51.0% were women. The prevalence of moderate and severe albuminuria appeared to increase with higher CKM comorbidity burden (Table 1). Among participants with no CKM conditions, the prevalence of moderate albuminuria was 4.4% (95% CI 3.4%–5.3%). The prevalence of moderate albuminuria among individuals with single CKM conditions ranged from 4.4% (2.8%–5.9%) in those with obesity alone to 11.3% (5.6%–16.9%) in those with diabetes alone. In participants with concurrent diabetes and hypertension, the prevalence of moderate albuminuria was 17.5% (11.4%–23.6%) and severe albuminuria was 4.3% (2.1%–6.5%). In participants with concurrent hypertension, cardiovascular disease, and low eGFR, the prevalence of moderate albuminuria was 54.2% (44.8%–63.6%) and severe albuminuria was 4.8% (1.1%–8.5%). In participants with concurrent diabetes, hypertension and cardiovascular disease but preserved eGFR, the prevalence of moderate albuminuria was 29.9% (14.2%–45.5%) and severe albuminuria was 11.3% (1.2%–21.3%). For individuals with concurrent diabetes, hypertension, and low eGFR but without cardiovascular disease, the prevalence of severe albuminuria was 50.3% (43.6%–57.1%), noting that the age-adjusted prevalence of moderate albuminuria could not be calculated due to no participants meeting these criteria in the 20–39 year old age group (crude values provided). None of the participants with diabetes alone and moderate–severe albuminuria were prescribed an angiotensin converting enzyme inhibitor/angiotensin receptor blocker (ACEi/ARB), glucagon-like peptide-1 receptor agonist (GLP1-RA) or sodium-glucose co-transporter-2 inhibitor (SGLT2i). Only 30.2% of individuals with hypertension alone and moderate–severe albuminuria were prescribed an ACEi/ARB. Similarly, only 27.5% of individuals with hypertension, obesity and moderate–severe albuminuria were prescribed an ACEi/ARB. Among individuals with diabetes, hypertension, and moderate–severe albuminuria, only 55.8% were prescribed any antiproteinuric therapy, with ACEi/ARB predominating. None of the participants with moderate–severe albuminuria were prescribed any antiproteinuric therapy in the following subgroups: diabetes alone, obesity alone, and cardiovascular disease alone. Only 3% of individuals with diabetes, obesity and moderate–severe albuminuria were prescribed antiproteinuric therapy (SGLT2i and GLP1-RA, no ACEi/ARB). Among participants with moderate–severe albuminuria, blood pressure control was similar between those prescribed antiproteinuric therapies and those not prescribed antiproteinuric medications. In this study, we describe the prevalence of albuminuria across non-overlapping CKM phenotypes in a nationally representative sample of US adults. Even within the single comorbidity subgroups, the burden of albuminuria was substantial. For example, of the 133 participants with CVD, approximately 4.9% (0.8%–9.1%) had UACR ≥ 30 mg/g—meeting criteria for CKD [4]. This is clinically meaningful given albuminuria's strong prognostic value for both CKD progression and cardiovascular events [1] and represents an opportunity for CKD care to be integrated into cardiovascular clinics through the use of cardio-renal protective medications (e.g., SGLT2i, ACEi/ARB, etc.). Similarly, approximately 4.4% (2.8%–5.9%) of individuals with obesity alone and 6.8% (5.8%–7.8%) of individuals with hypertension alone had UACR 30–299 mg/g, again consistent with a diagnosis of albuminuric CKD despite preserved eGFR. These findings are especially informative given that clinical practice guidelines, such as the 2025 AHA/ACC/Multi-specialty blood pressure guidelines, now incorporate albuminuria screening for specific cardiovascular risk groups and may lead to greater CKD identification. Further work is needed to understand the causal pathway for CKD development in these single-comorbidity groups and the optimal therapeutic approach to prevent CKM syndrome progression. Our findings extend the literature on low use of ACEi/ARB in the United States [5, 6]. Despite 11.3% of participants with diabetes alone having moderate–severe albuminuria, none were prescribed antiproteinuric therapies; this is a group in which ACEi/ARB were guideline-recommended during the study period, with emerging evidence for SGLT2i use as well [4]. Similarly low rates of ACEi/ARB use were found in other guideline-directed groups such as diabetes and hypertension (58.3%), hypertension and cardiovascular disease (48.9%), diabetes, hypertension and obesity (54.9%). This suggests that either albuminuria is not being tested in clinical environments and thus CKD is underrecognized, or clinicians are reticent to treat albuminuria when eGFR remains > 60 mL/min/1.73m2. However, once eGFR declines, it becomes challenging to slow disease progression. As the treatment landscape evolves, it will be critical to optimise albuminuria identification and management across primary care and subspecialty settings. Limitations of this study include potential misclassification of CKM phenotype, small sample size for certain phenotypes and single UACR measurement from a spot urine sample rather than first-morning void. Prevalence estimates may be underestimated due to treatment with anti-proteinuric therapy lowering UACR values. Small sample size may contribute to unstable estimates or under-estimation, particularly for the severe albuminuria category. Guideline-recommended indications for SGLT2i and GLP1-RA evolved during the study period, which limits interpretation of their implementation. For example, during the majority of the study period, SGLT2i and GLP1-RA were only indicated for the treatment of diabetes. Therefore, the prescription rates presented in this study should be interpreted in the context of the approved medication indication at the time of data collection. CKD is a growing public health challenge as the population ages. Moderate–severe albuminuria is common among those with multiple CKM comorbidities but is also found among those with a single CKM condition. Identification and timely initiation of therapies for albuminuria could substantially reduce the future burden of kidney failure and cardiovascular disease. Dr. Ashish Verma is supported by the American Heart Association Career Development Award (24CDA1274501) and the Boston University Department of Medicine Career Investment Award. The authors declare no conflicts of interest. Data are publicly available at https://wwwn.cdc.gov/nchs/nhanes/default.aspx. The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/dom.70607.

Diabetes Obesity and Metabolism
Boston University (US), Boston Medical Center (US)
Zero hunger
Openalex Percentile: Top 48%
Chronic Kidney Disease and Diabetes
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