
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39232083
71754
10.1038/s41598-024-71754-z
Article
Association between the C-reactive protein to albumin ratio with asthma and mortality in adult: a population-based study
You Jun 1
He Yiwen 1
Xu Min 2
Qian Min qianmin@ctgu.edu.cn

1
1 grid.254148.e 0000 0001 0033 6389 Department of Emergency, Yichang Central People’s Hospital, The First College of Clinical Medical Science, China Three Gorges University, Yichang, 443000 China
2 Intensive Care Unit, Hospital of Traditional Chinese Medicine of Jingzhou City, Jingzhou, 434000 China
4 9 2024
4 9 2024
2024
14 205732 6 2024
30 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Asthma is a prevalent chronic disease characterized by airflow obstruction, causing breathing difficulties and wheezing. This study investigates the association between the C-reactive protein to albumin ratio (CAR) and asthma prevalence, as well as all-cause and respiratory mortality among asthma patients, using data from the 2001–2018 National Health and Nutrition Examination Survey. We included participants aged 20 years and older with complete CAR data, excluding those who were pregnant or lost to follow-up. The analysis employed weighted logistic regression and Cox proportional hazards models with stepwise adjustment, restricted cubic spline analysis for nonlinear relationships, and time-dependent ROC curves for predictive accuracy. Results showed that the highest CAR quartile significantly increased the risk of asthma (OR 1.56, 95% CI 1.38–1.78), all-cause mortality (HR 2.20, 95% CI 1.67–2.89), and respiratory mortality (HR 2.56, 95% CI 1.30–5.38). The impact of CAR on all-cause mortality was particularly significant in hypertensive patients. These findings highlight CAR’s potential as a valuable biomarker for predicting asthma prevalence and mortality, underscoring its role in asthma management and prognostication.

Keywords

C-reactive protein to albumin ratio
Asthma
Mortality
NHANES
Subject terms

Biomarkers
Epidemiology
Asthma
issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Asthma, a common chronic non-communicable disease worldwide, is marked by airflow obstruction causing breathing difficulties and wheezing1. During the latter half of the twentieth century, the global prevalence of asthma increased rapidly2. Although the overall prevalence has decreased slightly from 3.9 to 3.6% since 1990, asthma remains the second most common chronic respiratory disease globally3. There is a pervasive lack of diagnosis and inadequate treatment, with both childhood and adult asthma imposing a significant public health burden4,5.

The C-reactive protein to albumin ratio (CAR) represents a novel biomarker that is gradually coming into the research spotlight6. The CAR integrates the prognostic values of C-reactive protein (CRP), an acute phase reactant that rises in the presence of inflammation7, and albumin, a negative acute phase reactant that declines in concentration in reaction to inflammation8. Studies have confirmed that elevated CAR is associated with several adverse outcomes, including cancers9–11, sepsis6,12,13, COVID-1914–16, and cardiovascular diseases17–19.

Inflammation is known to play a key role in the pathogenesis and progression of asthma20,21. To date, no studies have specifically examined CAR and asthma prevalence and mortality. Given the importance of identifying reliable biomarkers for asthma management, this study aims to analyze the effect of CAR on the prevalence of asthma and the mortality from all causes and respiratory diseases in patients with asthma.

Methods

Study population

The National Health and Nutrition Examination Survey (NHANES) is a study employing a complex sampling design to assess the health and nutritional status of the U.S. population. It collects participants’ basic information, questionnaire responses, physical examination results, and various laboratory test data. The survival status of participants in the NHANES as of December 31, 2019, a prerequisite for the conduct of the cohort study, can be obtained by the NHANES through interfacing with the National Center for Health Statistics (NCHS) death data.

Data from NHANES for the years 2001–2018 were utilized in this study. Participants who lacked complete CAR data (C-reactive protein, albumin), were less than 20 years of age, lacked pertinent asthma survey information, were pregnant, or lost to follow-up were excluded from this study (Fig. 1). As all study participants provided informed consent and the NCHS Institutional Review Board approved this study, no additional informed consent or ethical review was required. All methods were performed in accordance with the relevant guidelines and regulations.Fig. 1 Participant Selection Flowchart. NHANES National health and nutrition examination survey, CAR C-reactive protein to albumin ratio.

C-reactive protein to albumin ratio

In this study, CAR was calculated as CRP (mg/L) divided by ALB (g/L). Both CRP and ALB were collected at the Mobile Examination Center and then sent to a laboratory for analysis. Before collection, blood samples were screened based on certain exclusion criteria. Furthermore, NHANES conducted quality control on the collection process and test results.

Asthma

With reference to existing research22,23, Individuals who responded “yes” to the question “Has a doctor or other health professional ever told you that you have asthma?” within the questionnaire were considered to have asthma.

Covariates

Several potential covariates (demographics, living status, disease status, biochemical indicators) were included in our study. Demographic information included sex, age, race, poverty level (non-poverty: poverty-income ratio > 1, poverty: poverty-income ratio < 1), marital status, and education. Lifestyle status included smoking, drinking alcohol, and body mass index. Disease status consisted of hypertension, coronary heart disease (CHD), diabetes mellitus, neoplasm, stroke, and rheumatoid arthritis. CHD, stroke, and rheumatoid arthritis disease status were provided by the questionnaire, while hypertension and diabetes mellitus status were determined by combining the questionnaire and actual measurements of blood pressure, fasting blood glucose, oral glucose tolerance test, and glycated hemoglobin. The biochemical indicators used were TC and AST.

Statistical analysis

Considering the weighted analysis better reflects the true distribution of the overall population, the characteristics of all participants were evaluated according to the CAR quartiles. Continuous variables describing the total population characteristics were expressed as weighted means and standard deviations. In Categorical variables, the weighted percentages were employed. Comparisons between quartiles were conducted in t-tests or chi-square analyses. The characteristics of asthma patients were assessed based on survival status, with continuous variables expressed as means and standard deviations or medians and interquartile ranges and compared using t-tests. Categorical variables were described using frequencies and percentages, with differences assessed using chi-square tests. Logistic regression models, adjusted for multiple covariates, were employed to explore the associations between CAR and asthma prevalence. Three progressively adjusted models were used. Similarly, Cox proportional hazards models evaluated the relationship between CAR and mortality outcomes. Since the NHANES data is a nationally representative sample and not clustered by study centers or states, random effects were not included in our Cox models. Kaplan–Meier survival curves and log-rank tests were used to compare survival rates across CAR quartiles. Restricted cubic spline (RCS) analysis explored potentially non-linear relationships and identified threshold effects. Subgroup analyses assessed consistency across different groups. Model predictive accuracy over 3-, 5-, and 10-year periods was evaluated using time-dependent receiver operating characteristic (ROC) curves and the area under the curve (AUC). Random survival forest models were employed to demonstrate the importance of CAR. Sensitivity analyses were conducted using unweighted logistic regression and updated Cox models. The R software (version 4.3.3) was employed to facilitate all statistical analyses in this study.

Results

Baseline characteristics

The study included 33,565 participants, 4391 of whom had asthma. Mean age was 47.32 ± 16.87 years, with 48.9% male and 51.1% female. The prevalence of asthma was 13.7%. As shown in Table 1, participants were classified into four groups based on their weighted CAR quartiles: Q1: < 0.017; Q2: 0.017–0.043; Q3: 0.043–0.103; Q4: > 0.103. A comparison of the highest and lowest quartiles of the CAR group revealed that the latter had higher proportions of Mexican Americans, non-Hispanic whites, females, and smokers, and participants' mean age, BMI, and biochemical indicators showed significant trends with increasing CAR quartile. These subjects also had a significantly increased prevalence of hypertension, coronary heart disease, diabetes, cancer, stroke, and rheumatoid.Table 1 Quartiles of C-reactive protein to albumin ratio, the participants' fundamental characteristics.

Characteristics	Quartiles of C-reactive protein to albumin ratio	P value	
Quartile 1	Quartile 2	Quartile 3	Quartile 4	
< 0.017	0.017–0.043	0.043–0.103	> 0.103	
Sex (%)					< 0.001	
 Female	45.3	44.3	51.4	63.2		
 Male	54.7	55.7	48.6	36.8		
Age, years	42.83 (16.39)	48.01 (16.91)	49.29 (16.73)	49.16 (16.63)	< 0.001	
Race (%)					< 0.001	
 Mexican American	6.8	8.6	8.5	8.9		
 Non-Hispanic White	70.2	70.5	69.5	66.2		
 Non-Hispanic Black	8.9	9	10.3	14.2		
 Other	14.1	11.9	11.6	10.7		
Poverty level (%)					< 0.001	
 Non-poverty	89.3	89.5	87.7	84.9		
 Poverty	10.7	10.5	12.3	15.1		
Marital status (%)					< 0.001	
 No	36.6	33.6	34.6	38.2		
 Yes	63.4	66.4	65.4	61.8		
Education level (%)					< 0.001	
 High School or above	13.8	16.2	17.5	19.9		
 Below high school	86.2	83.8	82.5	80.1		
Smoking (%)					< 0.001	
 No	80.8	79.4	77.3	75.5		
 Yes	19.2	20.6	22.7	24.5		
Drinking (%)					< 0.001	
 No	37.5	37.8	40.4	45.6		
 Yes	62.5	62.2	59.6	54.4		
Asthma (%)					< 0.001	
 No	87.9	87.9	86.8	82.3		
 Yes	12.1	12.1	13.2	17.7		
Hypertension (%)					< 0.001	
 No	75.6	64.7	58.5	52.7		
 Yes	24.4	35.3	41.5	47.3		
CHD (%)					< 0.001	
 No	97.6	96.6	96	95.4		
 Yes	2.4	3.4	4	4.6		
Diabetes (%)					< 0.001	
 No	93.4	89.5	85.9	78.4		
 Yes	6.6	10.5	14.1	21.6		
Cancer (%)					< 0.001	
 No	92.4	90.5	90.1	88.9		
 Yes	7.6	9.5	9.9	11.1		
Stroke (%)					< 0.001	
 No	98.4	97.4	97.1	95.7		
 Yes	1.6	2.6	2.9	4.3		
Rheumatoid (%)					< 0.001	
 No	97.6	96.7	95.7	93.7		
 Yes	2.4	3.3	4.3	6.3		
BMI, kg/m2	24.72 (4.22)	27.56 (4.90)	29.87 (5.94)	33.09 (8.17)	< 0.001	
TC, mg/dL	188.89 (39.20)	196.74 (41.29)	201.21 (43.60)	198.42 (42.93)	< 0.001	
AST, U/L	24.51 (10.72)	25.07 (11.95)	25.56 (14.00)	25.19 (21.24)	< 0.001	
CRP, mg/L	0.42 (0.19)	1.22 (0.33)	2.85 (0.73)	11.49 (12.76)	< 0.001	
Albumin, g/dL	44.23 (2.94)	43.14 (2.96)	42.40 (2.99)	40.45 (3.26)	< 0.001	
Continuous variables were analyzed using the mean ± standard deviation, with P values obtained from weighted linear regression. Categorical variables were evaluated using percentages, with P values calculated from the weighted chi-square test.

CHD coronary heart disease, BMI body mass index, TC Total cholesterol, AST aspartate aminotransferase, CRP C-reactive protein.

As of December 31, 2019, 628 (14.3%) all-cause mortality events occurred in 4,391 asthma patients, with a mean follow-up period of 77.0 (34.8, 117) months. Table 2 shows the characteristics of asthma patients after grouping them according to their survival status up to the cut-off date. All-cause mortality was higher among asthmatics with higher mean age, male, Non-Hispanic Black, unmarried, and low education rates, and individuals with hypertension, coronary heart disease, diabetes, cancer, stroke, and rheumatoid continued to have higher all-cause mortality rates. Moreover, AST, CRP, albumin, and CAR were significantly elevated in asthmatics who died compared with survivors.Table 2 According to the grouping based on survival status, the basic characteristics of asthma participants.

Characteristics	Total	All-cause Mortality	P value	
(N = 4391)	No (N = 3763)	Yes (N = 628)	
Sex, n (%)				0.001	
 Female	2499 (56.9%)	2181 (58.0%)	318 (50.6%)		
 Male	1892 (43.1%)	1582 (42.0%)	310 (49.4%)		
Age, years	48.3 (17.9)	45.2 (16.6)	67.1 (13.5)	< 0.001	
Race, n (%)				< 0.001	
 Mexican American	459 (10.5%)	419 (11.1%)	40 (6.37%)		
 Non-Hispanic Black	1025 (23.3%)	891 (23.7%)	134 (21.3%)		
 Non-Hispanic White	2147 (48.9%)	1756 (46.7%)	391 (62.3%)		
 Other	760 (17.3%)	697 (18.5%)	63 (10.0%)		
Poverty level, n (%)				0.056	
 Non-poverty	3445 (78.5%)	2971 (79.0%)	474 (75.5%)		
 Poverty	946 (21.5%)	792 (21.0%)	154 (24.5%)		
Marital status, n (%)				< 0.001	
 No	1982 (45.1%)	1651 (43.9%)	331 (52.7%)		
 Yes	2409 (54.9%)	2112 (56.1%)	297 (47.3%)		
Education level, n (%)				< 0.001	
 Below high school	1023 (23.3%)	788 (20.9%)	235 (37.4%)		
 High School or above	3368 (76.7%)	2975 (79.1%)	393 (62.6%)		
Smoking, n (%)				0.144	
 No	3308 (75.3%)	2850 (75.7%)	458 (72.9%)		
 Yes	1083 (24.7%)	913 (24.3%)	170 (27.1%)		
Drinking, n (%)				< 0.001	
 No	1817 (41.4%)	1495 (39.7%)	322 (51.3%)		
 Yes	2574 (58.6%)	2268 (60.3%)	306 (48.7%)		
Hypertension, n (%)				 < 0.001	
 No	2330 (53.1%)	2177 (57.9%)	153 (24.4%)		
 Yes	2061 (46.9%)	1586 (42.1%)	475 (75.6%)		
CHD, n (%)				 < 0.001	
 No	4150 (94.5%)	3622 (96.3%)	528 (84.1%)		
 Yes	241 (5.49%)	141 (3.75%)	100 (15.9%)		
Diabetes, n (%)				 < 0.001	
 No	3470 (79.0%)	3076 (81.7%)	394 (62.7%)		
 Yes	921 (21.0%)	687 (18.3%)	234 (37.3%)		
Cancer, n (%)				 < 0.001	
 No	3885 (88.5%)	3409 (90.6%)	476 (75.8%)		
 Yes	506 (11.5%)	354 (9.41%)	152 (24.2%)		
Stroke, n (%)				 < 0.001	
 No	4134 (94.1%)	3585 (95.3%)	549 (87.4%)		
 Yes	257 (5.85%)	178 (4.73%)	79 (12.6%)		
Rheumatoid, n (%)				 < 0.001	
 No	4035 (91.9%)	3499 (93.0%)	536 (85.4%)		
 Yes	356 (8.11%)	264 (7.02%)	92 (14.6%)		
BMI, (kg/m2)	29.1 (24.9, 34.6)	29.2 (24.9, 34.7)	28.6 (25.1, 33.9)	0.147	
TC, mg/dL	189 (163, 218)	189 (163, 217)	192 (162, 225)	0.062	
AST, U/L	22.0 (19.0, 27.0)	22.0 (19.0, 27.0)	23.0 (19.0, 28.0)	0.009	
CRP, mg/L	2.50 (1.00, 5.98)	2.30 (0.90, 5.61)	3.75 (1.78, 8.80)	< 0.001	
Albumin, g/dL	42.0 (40.0, 44.0)	42.0 (40.0, 44.0)	41.0 (38.0, 43.0)	< 0.001	
CAR	0.06 (0.02, 0.15)	0.05 (0.02, 0.14)	0.09 (0.04, 0.22)	< 0.001	
For continuous variables, the conformity to the normal distribution was expressed in terms of the mean and standard deviation, while nonconformity to the normal distribution was expressed as the median and interquartile range. About categorical variables, frequencies, and percentages were employed to describe the distributions, and chi-square tests were utilized to examine between-group differences about categorical variables.

CHD coronary heart disease, BMI body mass index, TC total cholesterol, AST aspartate aminotransferase, CRP C-reactive protein, CAR C-reactive protein to albumin ratio.

Association between the CAR and asthma

This study has findings indicating a positive fluctuation between CAR levels and the prevalence of asthma (Table 3). Furthermore, a significant dose–response relationship was observed across all models. In the final model, Model 3, an increase of 0.1 in CAR was found to be associated with an increase in the odds of asthma by 5% (OR 1.03, 95% CI 1.02–1.05). This association became increasingly pronounced as the CAR quartiles were considered. Specifically, after adjusting for demographic factors in Model 2 and including additional variables such as poverty status and health conditions in Model 3, the association remained robust. participants in the top quartile of CAR (> 0.103) exhibited a 49% higher likelihood of asthma relative to the 1st quartile (Q4: OR 1.49, 95% CI 1.30–1.70). Moreover, a significant trend (P for trend < 0.001) of increasing asthma risk with rising CAR levels was evident in all three models.Table 3 The association between the CAR and asthma.

Exposure	Model 1 OR (95% CI)	Model 2 OR (95% CI)	Model 3 OR (95% CI)	
CAR (continuous)	1.05 (1.03, 1.06)	1.05 (1.03, 1.06)	1.03 (1.02, 1.05)	
 CAR Quartile 1	reference	reference	reference	
 CAR Quartile 2	1.00 (0.88, 1.14)	1.07 (0.94, 1.23)	1.07 (0.93, 1.23)	
 CAR Quartile 3	1.01 (0.98, 1.24)	1.18 (1.05, 1.33)	1.15 (1.02, 1.30)	
 CAR Quartile 4	1.56 (1.38, 1.78)	1.62 (1.42, 1.84)	1.49 (1.30, 1.70)	
 P for trend	 < 0.001	 < 0.001	 < 0.001	
CAR (continuous): CAR multiplied by 10. CAR weighted Quartiles Q1: < 0.017; Q2: 0.017–0.043; Q3: 0.043–0.103; Q4: > 0.103. The Model 1 analysis did not incorporate any adjustments for covariates. Conversely, Model 2 incorporated adjustments for age, sex, and race. Finally, Model 3 was further refined to account for additional covariates, including age, sex, race, poverty status, body mass index, tobacco and alcohol use, hypertension, coronary heart disease, diabetes, cancer, stroke, rheumatoid, total cholesterol, and aspartate aminotransferase.

OR odds ratio, CI confidence interval, CAR C-reactive protein to albumin ratio.

CAR and survival status of asthma patients

Kaplan–Meier survival curve analysis demonstrated a notable correlation between CAR levels and all-cause mortality among asthma patients (Fig. 2), as indicated by a Log-rank test result of P < 0.0001. Furthermore, asthmatics in the higher quartiles (Q3 and Q4) demonstrated substantially lower survival rates compared to the overall asthma patient population.Fig. 2 Kaplan–Meier survival curve analysis of all-cause mortality based on CAR quartiles in patients with asthma. CAR in asthma patients Quartiles Q1: < 0.023; Q2: 0.023–0.059; Q3: 0.059–0.149; Q4: > 0.149. Abbreviations: CAR C-reactive protein to albumin ratio, KM Kaplan–Meier survival curve.

Subsequently, three stepwise-adjusted Cox proportional hazards models were utilized to evaluate the correlation between CAR and mortality in asthma patients (Table 4). The findings demonstrated a significant association between CAR levels and all-cause mortality and mortality from respiratory diseases. Specifically, in Model 3 (detailed in Supplementary Tables S1 and S2), each 0.1 increase in CAR was associated with a 7% mortality risk increase (all-cause mortality: HR 1.07, 95% CI 1.05–1.09; respiratory mortality: HR 1.07, 95% CI 1.00–1.13). Furthermore, patients with the highest CAR quartile (> 0.149) exhibited a more than twofold elevated risk of all-cause mortality (HR 2.20, 95% CI 1.67–2.89) and respiratory disease mortality (HR 2.56, 95% CI 1.30–5.38) compared to asthmatics in the 1st quartile. All model trend checks were statistically significant. Figure 3 demonstrates the nonlinear relationship between CAR and the all-cause mortality risk in asthmatics (P for nonlinearity < 0.001). A threshold value of CAR at 0.1357 was identified as pivotal, with CAR's impact on mortality risk being more substantial below this point (Table 5).Table 4 Association between CAR and all-cause mortality and respiratory disease mortality in asthma patients.

Exposure	Model 1 HR (95% CI)	Model 2 HR (95% CI)	Model 3 HR (95% CI)	
All-cause mortality	
 CAR (continuous)	1.12 (1.10, 1.14)	1.09 (1.07, 1.11)	1.07 (1.05, 1.09)	
 CAR Quartile 1	reference	reference	reference	
 CAR Quartile 2	1.66 (1.26, 2.18)	1.09 (0.83, 1.44)	1.16 (0.88, 1.55)	
 CAR Quartile 3	2.34 (1.81, 3.03)	1.66 (1.29, 2.15)	1.64 (1.25, 2.16)	
 CAR Quartile 4	3.06 (2.39, 3.92)	2.33 (1.81, 3.00)	2.20 (1.67, 2.89)	
 P for trend	< 0.001	< 0.001	< 0.001	
Respiratory disease mortality	
 CAR (continuous)	1.12 (1.06, 1.18)	1.09 (1.03, 1.14)	1.07 (1.00, 1.13)	
 CAR Quartile 1	reference	reference	reference	
 CAR Quartile 2	1.34 (0.65, 2.79)	0.89 (0.43, 1.85)	0.98 (0.45, 2.14)	
 CAR Quartile 3	2.46 (1.28, 4.73)	1.76 (0.91, 3.40)	2.05 (1.01, 4.14)	
 CAR Quartile 4	2.48 (1.70, 6.04)	1.62 (1.30, 4.71)	2.56 (1.30, 5.38)	
 P for trend	< 0.001	0.002	0.001	
CAR (continuous): CAR multiplied by 10. CAR in asthma patients Quartiles Q1: < 0.023; Q2: 0.023–0.059; Q3: 0.059–0.149; Q4: > 0.149. The Model 1 analysis did not incorporate any adjustments for covariates. Conversely, Model 2 incorporated adjustments for age, sex, and race. Finally, Model 3 was further refined to account for additional covariates, including age, sex, race, poverty status, body mass index, tobacco and alcohol use, hypertension, coronary heart disease, diabetes, cancer, stroke, rheumatoid, total cholesterol, and aspartate aminotransferase.

HR hazard rate, CI confidence interval, CAR C-reactive protein to albumin ratio.

Fig. 3 Restricted cubic spline analysis of the association between CAR and the risk of all-cause mortality in asthma patients. Abbreviations: HR hazard rate, CI confidence interval, CAR C-reactive protein to albumin ratio.

Table 5 Inflection point and segmentation effects of CAR.

Items	HR (95% CI), P value	
Linear regression	1.07 (1.05, 1.09), < 0.001	
Two-piecewise linear regression	
 Inflection point	0.1357	
 < 0.1357	1.55(1.29–1.87), < 0.001	
 > 0.1357	1.04(1.02–1.07), 0.002	
 P for the likelihood ratio test	< 0.001	
The regression model results are all based on Model 3 (CAR multiplied by 10).

HR hazard rate, CI confidence interval.

Subgroup analysis and model evaluation

As indicated in Table 6, subgroup analysis suggests a potential interaction effect between hypertension and the CAR and all-cause mortality among asthma patients (P for interaction = 0.011). Specifically, individuals without hypertension demonstrated a heightened risk of all-cause mortality. Each 0.1 increase in CAR is associated with a 15% increase in the risk of asthma mortality (HR 1.15, 95% CI 1.08–1.21). The correlation between CAR and all-cause mortality in asthmatics was relatively consistent across the other subgroups.Table 6 Subgroup analysis by CAR on asthma mortality.

Variable	HR (95% CI)	P value	P for interaction	
Sex			0.598	
 Female	1.07 (1.03, 1.11)	0.001		
 Male	1.08 (1.05, 1.11)	< 0.001		
Race			0.409	
 Mexican American	1.10 (0.96, 1.26)	0.178		
 Non-Hispanic Black	1.07 (1.02, 1.12)	0.003		
 Non-Hispanic White	1.07 (1.04, 1.11)	< 0.001		
 Other	1.20 (1.06, 1.34)	0.003		
Poverty level			0.608	
 Non-poverty	1.06 (1.03, 1.09)	< 0.001		
 Poverty	1.08 (1.03, 1.12)	< 0.001		
Marital status			0.984	
 No	1.07 (1.04, 1.10)	< 0.001		
 Yes	1.07 (1.03, 1.11)	0.001		
Education level			0.282	
 Below high school	1.10 (1.06, 1.14)	< 0.001		
 High School or above	1.06 (1.03, 1.09)	< 0.001		
Smoking			0.577	
 No	1.07 (1.04, 1.10)	< 0.001		
 Yes	1.08 (1.04, 1.12)	< 0.001		
Drinking			0.909	
 No	1.08 (1.04, 1.11)	< 0.001		
 Yes	1.07 (1.04, 1.11)	< 0.001		
Hypertension			0.011	
 No	1.15 (1.08, 1.21)	< 0.001		
 Yes	1.06 (1.04, 1.09)	< 0.001		
CHD			0.199	
 No	1.07 (1.04, 1.09)	< 0.001		
 Yes	1.12 (1.05, 1.20)	< 0.001		
Diabetes			0.904	
 No	1.07 (1.04, 1.11)	< 0.001		
 Yes	1.08 (1.05, 1.12)	< 0.001		
Cancer			0.979	
 No	1.07 (1.04, 1.10)	< 0.001		
 Yes	1.10 (1.06, 1.15)	< 0.001		
Stroke			0.147	
 No	1.08 (1.05, 1.10)	< 0.001		
 Yes	1.02 (0.95, 1.09)	0.624		
Rheumatoid			0.186	
 No	1.08 (1.05, 1.11)	< 0.001		
 Yes	1.04 (0.97, 1.12)	0.226		
The regression model results are all based on Model 3 (CAR multiplied by 10).

CHD coronary heart disease, HR hazard rate, CI confidence interval.

ROC curves (Fig. 4) indicated that the fully adjusted model exhibited significantly greater predictive capacity than the unadjusted model. Furthermore, predictive accuracy was observed to improve with longer follow-up periods, and AUC values demonstrated an upward trend over time. Figure 5 illustrates the significance of CAR in forecasting all-cause mortality in asthma patients within the context of a randomized survival forest model.Fig. 4 Comparative ROC curves for all-cause and respiratory disease mortality over different periods. (A) 3-year ROC curve for all-cause mortality, (B) 5-year ROC curve for all-cause mortality, (C) 10-year ROC curve for all-cause mortality, (D) 3-year ROC curve for respiratory disease mortality, (E) 3-year ROC curve for respiratory disease mortality, (F) 3-year ROC curve for respiratory disease mortality. Abbreviations: ROC receiver operating characteristic, AUC Area under the curve.

Fig. 5 Variable importance in random survival forest models for all-cause and respiratory disease mortality. (A) Variable importance for all-cause mortality, (B) Variable importance for respiratory disease mortality. Incorporate the same variables as Model 3. Abbreviations: CAR C-reactive protein to albumin ratio, CHD coronary heart disease, BMI Body mass index, TC total cholesterol, AST aspartate aminotransferase.

Sensitive analysis

Sensitivity analyses were conducted using unweighted logistic regression (Supplementary Table S3) and updated adjusted models (Supplementary Table S4) to examine the association between the CAR and the incidence and mortality of asthma. The updated adjusted models incorporated additional adjustments for aspartate aminotransferase, chronic bronchitis, and liver disease. The results consistently demonstrated that elevated CAR was positively correlated with an increased risk of asthma incidence, all-cause mortality, and respiratory disease mortality. These associations remained significant across different models and adjustments, thereby reinforcing the robustness of our findings, and highlighting CAR as a reliable predictor of mortality outcomes.

Discussion

The results of our study identified a significant association between the CAR and asthma prevalence, as well as all-cause and respiratory disease mortality in patients with asthma. Higher CAR levels were associated with an increased likelihood of asthma. Asthma patients with elevated CAR showed significantly higher both overall mortality and mortality due to respiratory disease. The mortality rate in the highest CAR quartile was more than twice that of the lowest quartile, underscoring CAR's value as a prognostic biomarker for asthma outcomes.

While there are no existing studies specifically examining the association between CAR and asthma, as well as the prognosis of asthmatics, this can be explained through the lens of systemic inflammation and nutritional status. CRP is a molecule synthesized primarily by hepatocytes that increases in concentration during inflammatory responses7. It is commonly used as a static measurement indicator and is correlated with the severity and prognosis of diseases24,25. Some studies have shown that CRP levels are significantly elevated in patients not receiving steroid treatment26 and in non-allergic asthma patients27, and CRP is negatively correlated with pulmonary function parameters such as FEV1/FVC ratio28,29. Conversely, albumin is a protein that is synthesized by the liver and is decreased during inflammation and malnutrition8. Factors such as malnutrition, fluid overload, inflammation, and liver dysfunction are all associated with hypoalbuminemia and adverse outcomes in various diseases30. Studies have also indicated that serum albumin levels are lower in asthma patients compared to the normal population31, and this difference is also present in asthmatic children32. These studies indirectly support our results, suggesting that CAR, as a combined marker, may provide comprehensive prognostic information. Additionally, the impact of CRP on albumin levels is relatively small, with a significant negative correlation only observed at extremely high CRP levels (500 mg/L)33. This implies that CAR can provide more reliable assessments of inflammation and nutritional status, as it is less affected by extreme inflammation.

We also revealed a potential nonlinear relationship between CAR and asthma outcomes. This nonlinear trend may be due to varying degrees of inflammation and nutritional deficiencies among patients with different CAR levels. When analyzed by subgroup, the effect of CAR on all-cause mortality was particularly significant among hypertensive patients (P for interaction = 0.011). The synergistic impact of hypertension and elevated CAR levels on asthma outcomes could be attributed to the cumulative effects of inflammation. Numerous studies have shown that hypertension increases oxidative stress and inflammation34,35. This finding highlights the necessity of considering hypertension when assessing the prognostic significance of CAR in patients with asthma.

CAR is likely associated with various diseases, as our analysis of non-asthmatic patients also found significant associations between CAR and mortality. However, the impact of CAR is particularly pronounced in asthmatic patients, where the highest CAR quartile was associated with a markedly greater risk of both all-cause and respiratory disease mortality compared to non-asthmatic patients (Supplementary Table S5). This underscores the research potential of CAR across different conditions, while also highlighting its unique prognostic value in the context of asthma.

The study is notable for its reliance on a large, nationally representative sample. However, there are also some limitations. The study population was limited to adults, and the reliance on self-reported asthma diagnosis may introduce classification bias. Additionally, CAR levels may be affected by various factors, including recent acute infections and nutritional status, which were not fully controlled for in this study. Our analysis did not account for the random effects of the NHANES dataset structure. However, given the nationally representative nature of NHANES, the likelihood of regional variability is minimized. To establish causality and explore the potential mechanisms of the association between CAR and asthma outcomes, future longitudinal studies are necessary.

Conclusion

The results of our study indicated a significant correlation between CAR and asthma prevalence, as well as all-cause and respiratory disease mortality in asthma patients. Higher CAR levels were correlated with an increased likelihood of asthma prevalence and significantly higher all-cause and respiratory disease mortality. The findings indicate that CAR is a valuable biomarker for predicting asthma outcomes.

Supplementary Information

Supplementary Tables.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-71754-z.

Acknowledgements

We thank NCHS for providing the NHANES data. We also acknowledge the participants and staff involved in NHANES for their valuable contributions to this research.

Author contributions

All authors were involved in the conceptualization and design of the study. The preparation of materials, collection of data, and analysis were conducted by J. Y. and Y. H. The initial draft was prepared by J. Y., and M. Q. provided feedback on multiple iterations of the draft. All authors read and approved the final draft.

Data availability

The datasets generated and/or analyzed during the current study are available in the NHANES repository, https://www.cdc.gov/nchs/nhanes/index.htm.

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

All participants provided informed consent before inclusion in the study. NHANES protocol was approved by the NCHS Research Ethics Review Board.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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