Abstract
Background
We aimed to investigate the association between dietary carotenoids and acute respiratory infection (ARI) in the general US population.
Methods
We analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2003 − 2018 and 64,560 participants with complete records of dietary intake and ARI definition. Five major dietary carotenoids were evaluated: α-carotene, β-carotene, lycopene, β-cryptoxanthin, and lutein plus zeaxanthin. Survey-weight logistic regression and restricted cubic spline were applied.
Results
The relationship between dietary carotenoids and ARI risk followed a linear trend. Participants in the highest quartile of dietary carotenoid intake exhibited a 15% lower risk of ARI than those in the lowest quartile (multi-adjusted odds ratio [OR]: 0.85, 95% confidence interval [CI]: 0.72 − 0.99). Individually, the association with ARI was consistently significant for β-carotene (multi-adjusted OR, 95% CI: 0.82, 0.69 − 0.98), β-cryptoxanthin (0.77, 0.66 − 0.91), lycopene (0.86, 0.75 − 0.99), and lutein plus zeaxanthin (0.84, 0.71 − 0.99). There was a significant inverse relationship between total carotenoid intake and ARI among children aged 1 − 18 years(multi-adjusted OR, 95% CI: 0.74, 0.57 − 0.97 for the highest quartile, and 0.78, 0.63 − 0.96 for the third quartile compared with lowest quartile).
Conclusions
In this US national general population, our findings indicated that higher dietary carotenoid intake was inversely associated with ARI risk.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12887-025-06027-3.
Keywords: Acute respiratory infection, Dietary carotenoids, US general population
Introducion
Acute respiratory infections (ARIs) are the most common infectious disease worldwide, encompassing both upper and lower respiratory tract infections caused by various viral and bacterial pathogens [1, 2]. ARIs contribute substantially to global mortality and morbidity. Epidemiological evidence indicates that approximately 20% of mortality in children under five is attributable to ARIs [3]. Furthermore, longitudinal studies have demonstrated that lower respiratory infections in early childhood are associated with a nearly two-fold increase in premature mortality risk from respiratory disorders in adulthood [4]. In the US, lower respiratory infections cost $32.3 billion in 2016 [5, 6]. Given the substantial effects of ARIs on health and healthcare expenditures across the life course, identifying modifiable risk factors of ARIs and optimizing effective prevention and control strategies are urgently needed to reduce respiratory burden.
More recently, Salehi and colleagues have written an excellent review on dietary patterns and micronutrients in respiratory infections, underscoring the essential protective role of certain nutrients against respiratory diseases [7]. Carotenoids-lipid-soluble pigments and antioxidants naturally abundant in fruits, vegetables, and algae-possess anti-inflammatory, antioxidant, and immunomodulatory properties [8, 9], particularly in safeguarding cellular integrity against oxidative stress and enhancing immune responses [10]. Current studies exploring the beneficial effects of carotenoids on respiratory health have mainly focused on chronic respiratory diseases [8, 11, 12]. However, a literature search has failed to reveal the association between carotenoid intake and ARIs [7].
To fill this knowledge gap, we aimed to investigate the association between dietary carotenoids, both individually and as a whole, and risk for ARIs in a nationally representative sample of US children and adults.
Methods
Study participants
This study is cross-sectional in design, involving participants from the US National Health and Nutrition Examination Survey (NHANES), a series of nationally representative cross-sectional surveys of the non-institutionalized, civilian population of the US. NHANES uses a complex, multistage, stratified, clustered probability design to recruit nationally representative samples. From 1999 onwards, participants were invited in each 2-year NHANES cycle. Demographic and nutrition data were collected by personal structured interviews at home. Physical examinations and laboratory measurements were performed at mobile examination centers.
In this study, we used data from 8 consecutive survey cycles of NHANES (2003 − 2004, 2005 − 2006, 2007 − 2008, 2009 − 2010, 2011 − 2012, 2013 − 2014, 2015 − 2016, and 2017 − 2018) with age restrictions. A total of 64,560 participants with complete information on dietary carotenoid intake (through 24-h dietary recall) and medical history of respiratory tract infections were eligible for final inclusion. The conduct of NHANES was approved by the Institutional Review Board of the National Center for Health Statistics. Informed consent was obtained from all NHANES participants, including parental or guardian authorization for minors, in compliance with ethical guidelines related to pediatric research.
Dietary intake assessment
In NHANES 2003 − 2018, dietary intake data were obtained via two nonconsecutive 24-h dietary recall interviews. The first interview was carried out face-to-face at mobile examination centers, followed by telephone 3 − 10 days after the first interview. Total daily energy and 64 nutrients/food components from all foods and beverages were computed using the US Department of Agriculture Food and Nutrient Database. Total daily dietary carotenoid intake was defined as the sum of α-carotene, β-carotene, β-cryptoxanthin, lycopene, and lutein plus zeaxanthin (5 carotenoids). For each participant, the average dietary intake from the two separate 24-h dietary recall interviews was used to estimate dietary carotenoid exposure levels.
ARI definition
ARIs were defined based on the question “Did {you/SP} have flu, pneumonia, or ear infections that started during the last 30 days?” Participants who answered “yes” were considered as ARI cases.
Covariates
Covariates in this study were selected based on existing literature, including age, sex, race/ethnicity (Hispanics, non-Hispanic Black, non-Hispanic White, or other races), family poverty-income ratio (PIR, classified as < 1.0, 1.0 − 2.9, or ≥ 3.0), body mass index (BMI, kg/m2), smoke exposure (classified as unexposed: serum cotinine levels < 0.05 ng/mL, low exposure: 0.05 − 2.99 ng/mL, or heavy exposure: serum cotinine levels ≥ 3 ng/mL) [13], and asthma (yes or no).
Statistical analysis
Continuous variables are expressed as median (interquartile range) and categorical variables as count (percent). Differences across dietary carotenoid intake levels were compared using analysis of variance (ANOVA), Kruskal-Wallis test, or χ2 tests, where appropriate.
To account for the complex, multistage probability sampling design used in NHANES to select nationally representative participants, analyses incorporated stratification variables (SDMVSTRA), primary sampling units (SDMVPSU), and the adjusted dietary weights. This study used the two-day dietary sample weights (WTDR2D) for all primary analyses involving dietary carotenoid intake, as these weights are specifically designed to account for the unique characteristics of NHANES 24-hour dietary recall data. For analyses combining data across eight NHANES cycles (2003 − 2018), we implemented the NCHS-recommended weight adjustment procedure using the formula: adjusted weight = (WTDR2D×N_total)/(8×N_cycle), where N_total denotes the total analytic sample size across all cycles and N_cycle denotes the cycle-specific sample size. This adjustment ensures proper representation of population characteristics while maintaining the integrity of the original sampling design. Weighted logistic regression was used to model the association between dietary carotenoids and ARIs in three steps: (1) no adjustment was made; (2) age, sex, race/ethnicity, and PIR were adjusted; (3) BMI, smoke exposure, and asthma were additionally adjusted based on step (2). Risk for ARIs was quantified using odds ratio (OR) and 95% confidence interval (CI). Trends were tested by fitting median scores for quartiles of dietary carotenoid intake as continuous variables. Restricted cubic spline (RCS) analysis was used to illustrate the dose-response association between dietary carotenoids and ARI risk.
Stratified analyses were performed according to sex, race, PIR, BMI, smoke exposure, and asthma, respectively. Interactions between quartiles of dietary carotenoids and stratified factors were performed by adding interaction terms in fully-adjusted models.
To evaluate the robustness of our findings, three sensitivity analyses were conducted: (1) multiple imputation by chained equations (MICE, m = 50) for missing data; (2) direct covariate adjustment for total energy intake; (3) further adjustment for hypertension and diabetes; (4) adoption of energy-adjusted dietary carotenoids (residual method).
All analyses were complete using the STATA version 18.0 (StataCorp, College Station, TX, US) and R coding platform version 4.4.0. Statistical significance was defined as two-sided P values < 0.05.
Results
Characteristics of study participants
The baseline characteristics of 64,560 participants (median age: 28.0 years) according to dietary carotenoids in quartiles are shown in Table 1. Of all participants, 50.3% were men, 38.0% were of non-Hispanic White origin, and median BMI was 25.00 kg/m2. Respiratory infections within the latest 30 days were documented in 3,068 participants. Participants with high dietary carotenoid intake were more likely to be older, male, non-Hispanic White, unexposed to cotinine, overweight or obese, and free of asthma comorbidities (all P < 0.05).
Table 1.
Characteristics of study participants by dietary carotenoids in quartiles in NHANES 2003 − 2018
| Characteristics | Total (n = 64,560) | Quartile 1 (n = 16,138) |
Quartile 2 (n = 16,142) |
Quartile 3 (n = 16,140) |
Quartile 4 (n = 16,140) |
P |
|---|---|---|---|---|---|---|
| Age, median (Q₁, Q₃) | 28.00 (12.00, 54.00) | 20.00 (8.00, 51.00) | 23.00 (10.00, 52.00) | 29.00 (12.00, 54.00) | 35.00 (16.00, 57.00) | < 0.001 |
| BMI, median (Q₁, Q₃) | 25.00 (19.90, 30.20) | 24.30 (18.73, 30.00) | 24.75 (19.21, 30.13) | 25.15 (20.10, 30.12) | 25.68 (21.24, 30.50) | < 0.001 |
| Sex | < 0.001 | |||||
| Female | 32,479 (50.3) | 8563 (53.06) | 8289 (51.35) | 8093 (50.14) | 7534 (46.68) | |
| Male | 32,081 (49.7) | 7575 (46.94) | 7853 (48.65) | 8047 (49.86) | 8606 (53.32) | |
| Race | < 0.001 | |||||
| Non-Hispanic white | 24,544 (38.0) | 5828 (36.11) | 5816 (36.03) | 6223 (38.56) | 6677 (41.37) | |
| Non-Hispanic black | 15,143 (23.5) | 4500 (27.88) | 3888 (24.09) | 3326 (20.61) | 3429 (21.25) | |
| Mexican American | 12,906 (19.99) | 2898 (17.96) | 3509 (21.74) | 3594 (22.27) | 2905 (18.00) | |
| Others | 11,967 (18.54) | 2912 (18.04) | 2929 (18.15) | 2997 (18.57) | 3129 (19.39) | |
| Family poverty-income ratio | < 0.001 | |||||
| < 1.0 | 15,510 (25.93) | 4616 (31.00) | 4015 (26.87) | 3634 (24.26) | 3245 (21.64) | |
| 1.0 − 2.9 | 25,058 (41.90) | 6544 (43.95) | 6389 (42.75) | 6217 (41.51) | 5908 (39.40) | |
| ≥ 3.0 | 19,241 (32.17) | 3731 (25.06) | 4541 (30.38) | 5126 (34.23) | 5843 (38.96) | |
| Smoke exposure | < 0.001 | |||||
| Unexposed | 28,020 (50.92) | 5577 (43.07) | 6829 (50.44) | 7568 (54.06) | 8046 (55.35) | |
| Low exposure | 15,682 (28.50) | 4150 (32.05) | 4060 (29.99) | 3743 (26.74) | 3729 (25.65) | |
| Heavy exposure | 11,322 (20.58) | 3221 (24.88) | 2651 (19.58) | 2689 (19.21) | 2761 (18.99) | |
| Asthma | 0.03 | |||||
| No | 54,808 (85.00) | 13,595 (84.39) | 13,713 (85.05) | 13,704 (85.01) | 13,796 (85.56) | |
| Yes | 9671 (15.00) | 2515 (15.61) | 2411 (14.95) | 2417 (14.99) | 2328 (14.44) |
Data are expressed as median (interquartile range) or n (%). Smoke exposure was classified as unexposed (serum cotinine levels < 0.05 ng/mL), low exposure (serum cotinine levels: 0.05 − 2.99 ng/mL), or heavy exposure (serum cotinine levels ≥ 3 ng/mL)
BMI Body mass index, NHANES National Health and Nutrition Examination Survey, Q Quartile
Dietary carotenoids and ARIs
Figure 1 shows the dose-response relationship between ln-transformed dietary carotenoids and ARI risk, which followed a linear trend (P = 0.038). The association between total carotenoid intake and ARIs is presented in Table 2. After adjusting for multiple confounders, participants in the highest quartile of dietary carotenoid intake exhibited a 15% lower risk of ARIs than those in the lowest quartile (OR: 0.85, 95% CI: 0.72 − 0.99). Per unit increment in natural ln-transformed of dietary carotenoids was significantly associated with 6% lowered risk of ARIs (OR: 0.94; 95% CI: 0.89 − 0.98).
Fig. 1.
Dose-response association between ln-transformed dietary carotenoids and ARI risk. Restricted cubic spline regression model was used after adjusting for adjusted for age, sex, race/ethnicity, family poverty-income ratio, body mass index, smoke exposure, and asthma. Solid blue line represents odds ratio (OR), and light-blue shadow represents its 95% confidence interval (CI). Dotted horizontal grey line represents the reference line (OR: 1)
Table 2.
Association between dietary carotenoids in quartiles and ARI risk in the general US population, NHANES 2003 − 2018
| Carotenoids | Model 1 | Model 2 | Model 3 |
|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | |
| Q1 | 1.00 [Ref] | 1.00 [Ref] | 1.00 [Ref] |
| Q2 | 0.83 (0.72 − 0.96) | 0.84 (0.72 − 0.98) | 0.88 (0.74 − 1.05) |
| Q3 | 0.75 (0.65 − 0.87) | 0.79 (0.68 − 0.91) | 0.83 (0.70 − 0.97) |
| Q4 | 0.73 (0.63 − 0.84) | 0.78 (0.68 − 0.90) | 0.85 (0.72 − 0.99) |
| P for trend | < 0.001 | 0.006 | 0.11 |
| (ln-transformed) | 0.89 (0.85 − 0.93) | 0.92 (0.88 − 0.96) | 0.94 (0.89 − 0.98) |
ARI Acute respiratory infection, CI Confidence interval, OR Odds ratio, Q Quartile, Ref reference
Model 1: unadjusted
Model 2: adjusted for age, sex, and race/ethnicity
Model 3: adjusted for age, sex, race/ethnicity, family poverty-income ratio, body mass index, smoke exposure, and asthma
P values for trend were calculated by fitting median scores for quartiles as continuous variables in models
Individually, the association with ARI was consistently significant for β-carotene (OR, 95% CI: 0.82, 0.69 − 0.98), β-cryptoxanthin (0.77, 0.66 − 0.91), lycopene (0.86, 0.75 − 0.99), and lutein plus zeaxanthin (0.84, 0.71 − 0.99) after adjusting for all pre-defined covariates (Table 3).
Table 3.
Association between dietary carotenoid components in quartiles and ARI risk, NHANES 2003 − 2018
| Carotenoid components | Model 1 | Model 2 | Model 3 |
|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | |
| α-carotene | |||
| Q1 | 1.00 [Ref] | 1.00 [Ref] | 1.00 [Ref] |
| Q2 | 0.88 (0.77 − 1.01) | 0.89 (0.77 − 1.02) | 0.91 (0.77 − 1.07) |
| Q3 | 0.78 (0.67 − 0.91) | 0.82 (0.69 − 0.96) | 0.81 (0.67 − 0.97) |
| Q4 | 0.75 (0.65 − 0.86) | 0.82 (0.70 − 0.95) | 0.85 (0.71 − 1.01) |
| β-carotene | |||
| Q1 | 1.00 [Ref] | 1.00 [Ref] | 1.00 [Ref] |
| Q2 | 0.82 (0.71 − 0.96) | 0.86 (0.74 − 1.01) | 0.88 (0.74 − 1.04) |
| Q3 | 0.76 (0.65 − 0.88) | 0.82 (0.70 − 0.96) | 0.83 (0.70 − 0.98) |
| Q4 | 0.66 (0.56 − 0.78) | 0.77 (0.65 − 0.91) | 0.82 (0.69 − 0.98) |
| β-cryptoxanthin | |||
| Q1 | 1.00 [Ref] | 1.00 [Ref] | 1.00 [Ref] |
| Q2 | 0.86 (0.75 − 0.98) | 0.85 (0.73 − 0.98) | 0.87 (0.74 − 1.02) |
| Q3 | 0.83 (0.71 − 0.96) | 0.86 (0.74 − 1.00) | 0.85 (0.72 − 1.01) |
| Q4 | 0.75 (0.65 − 0.87) | 0.76 (0.66 − 0.88) | 0.77 (0.66 − 0.91) |
| Lycopene | |||
| Q1 | 1.00 [Ref] | 1.00 [Ref] | 1.00 [Ref] |
| Q2 | 0.84 (0.73 − 0.97) | 0.82 (0.71 − 0.96) | 0.85 (0.71 − 1.02) |
| Q3 | 0.82 (0.72 − 0.94) | 0.81 (0.70 − 0.93) | 0.87 (0.74 − 1.02) |
| Q4 | 0.81 (0.72 − 0.92) | 0.80 (0.71 − 0.91) | 0.86 (0.75 − 0.99) |
| Lutein + zeaxanthin | |||
| Q1 | 1.00 [Ref] | 1.00 [Ref] | 1.00 [Ref] |
| Q2 | 0.89 (0.78 − 1.03) | 0.92 (0.80 − 1.06) | 0.96 (0.81 − 1.15) |
| Q3 | 0.90 (0.78 − 1.04) | 0.93 (0.80 − 1.07) | 1.00 (0.85 − 1.18) |
| Q4 | 0.67 (0.58 − 0.78) | 0.77 (0.66 − 0.90) | 0.84 (0.71 − 0.99) |
ARI Acute respiratory infection, CI Confidence interval, OR Odds ratio, Q Quartile, Ref reference
Model 1: unadjusted
Model 2: adjusted for age, sex, and race/ethnicity
Model 3: adjusted for age, sex, race/ethnicity, family poverty-income ratio, body mass index, smoke exposure, and asthma
In Table 4, there was a significant inverse relationship between total carotenoid intake and ARIs among children aged 1 − 18 years (multi-adjusted OR, 95% CI: 0.74, 0.57 − 0.97 for the highest quartile, and 0.78, 0.63 − 0.96 for the third quartile compared with lowest quartile).
Table 4.
Association between dietary carotenoids in quartiles and ARI risk by age, NHANES 2003 − 2018
| Age category | Model 1 | Model 2 | Model 3 |
|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | |
| < 18 years | |||
| Q1 | 1.00 [Ref] | 1.00 [Ref] | 1.00 [Ref] |
| Q2 | 0.94 (0.79 − 1.12) | 0.97 (0.81 − 1.16) | 1.05 (0.82 − 1.35) |
| Q3 | 0.89 (0.74 − 1.07) | 0.93 (0.77 − 1.12) | 1.10 (0.86 − 1.41) |
| Q4 | 0.68 (0.56 − 0.84) | 0.77 (0.62 − 0.95) | 0.74 (0.57 − 0.97) |
| ≥ 18 years | |||
| Q1 | 1.00 [Ref] | 1.00 [Ref] | 1.00 [Ref] |
| Q2 | 0.80 (0.65 − 0.98) | 0.80 (0.64 − 0.99) | 0.83 (0.66 − 1.05) |
| Q3 | 0.73 (0.60 − 0.88) | 0.76 (0.62 − 0.93) | 0.78 (0.63 − 0.96) |
| Q4 | 0.79 (0.65 − 0.95) | 0.82 (0.67 − 0.99) | 0.89 (0.73 − 1.09) |
ARI Acute respiratory infection, OR Odds ratio, CI Confidence interval, Q Quartile, Ref reference
Model 1: unadjusted
Model 2: adjusted for age, sex, and race/ethnicity
Model 3: adjusted for age, sex, race/ethnicity, family poverty-income ratio, body mass index, smoke exposure, and asthma
Subgroup analyses
The association between total carotenoid intake and ARIs were explored upon stratification by sex, race/ethnicity, PIR, BMI, smoke exposure, and asthma, respectively (Table 5). There was no hint of significance for the interaction between total carotenoid intake and these stratified factors (all Pinteraction >0.05).
Table 5.
Stratified analyses on the association between dietary carotenoids in quartiles and ARI risk
| Characteristics | OR (95% CI) by quartiles of dietary carotenoids |
P value for interaction |
|||
|---|---|---|---|---|---|
| Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | ||
| Sex | 0.06 | ||||
| Female | 1.00 [Ref] | 0.79 (0.64 − 0.99) | 0.74 (0.60 − 0.91) | 0.74 (0.59 − 0.93) | |
| Male | 1.00 [Ref] | 1.03 (0.79 − 1.34) | 0.98 (0.75 − 1.26) | 1.02 (0.80 − 1.30) | |
| Race/ethnicity | 0.12 | ||||
| Non-Hispanic white | 1.00 [Ref] | 0.86 (0.67 − 1.11) | 0.81 (0.63 − 1.04) | 0.80 (0.62 − 1.02) | |
| Other | 1.00 [Ref] | 0.95 (0.79 − 1.15) | 0.91 (0.75 − 1.11) | 0.98 (0.80 − 1.19) | |
| Family poverty-income ratio | 0.32 | ||||
| < 1.0 | 1.00 [Ref] | 0.96 (0.72 − 1.27) | 1.05 (0.76 − 1.44) | 0.84 (0.61 − 1.15) | |
| 1.0 − 2.9 | 1.00 [Ref] | 1.04 (0.82 − 1.33) | 0.91 (0.73 − 1.14) | 0.99 (0.78 − 1.27) | |
| ≥ 3.0 | 1.00 [Ref] | 0.69 (0.50 − 0.95) | 0.65 (0.47 − 0.91) | 0.71 (0.52 − 0.95) | |
| BMI (kg/m2) | 0.15 | ||||
| ≤ 25 | 1.00 [Ref] | 0.88 (0.71 − 1.10) | 0.90 (0.72 − 1.13) | 0.72 (0.57 − 0.91) | |
| > 25 | 1.00 [Ref] | 0.89 (0.70 − 1.14) | 0.80 (0.64 − 1.00) | 0.94 (0.76 − 1.17) | |
| Smoke exposure | 0.36 | ||||
| Unexposed | 1.00 [Ref] | 0.83 (0.64 − 1.09) | 0.83 (0.65 − 1.06) | 0.72 (0.55 − 0.93) | |
| Low exposure | 1.00 [Ref] | 0.96 (0.73 − 1.26) | 1.01 (0.77 − 1.33) | 1.10 (0.84 − 1.45) | |
| Heavy exposure | 1.00 [Ref] | 0.92 (0.63 − 1.35) | 0.70 (0.49 − 1.00) | 0.94 (0.67 − 1.34) | |
| Asthma | 0.26 | ||||
| No | 1.00 [Ref] | 0.84 (0.68 − 1.02) | 0.85 (0.70 − 1.03) | 0.87 (0.73 − 1.03) | |
| Yes | 1.00 [Ref] | 1.03 (0.74 − 1.43) | 0.74 (0.52 − 1.04) | 0.77 (0.55 − 1.09) | |
OR and 95% CI were calculated after adjusting for age, sex, race/ethnicity, family poverty-income ratio, body mass index, smoke exposure, and asthma
ARI Acute respiratory infection, CI Confidence interval, OR Odds ratio, Ref reference
Sensitivity analyses
All sensitivity analyses yielded results consistent with primary models, indicating the stability of our observations (Supplementary Tables 1 and Supplementary Table 2).
Discussion
In this US nationally representative cohort, we aimed to investigate the association between dietary carotenoids and ARI risk. Notably, we found that higher dietary carotenoid intake was associated with lower likelihood of having ARIs, highlighting the “upstream” driving importance of carotenoids in the primary prevention of respiratory disorders. This association is independent of a wide panel of potential confounders and dose-dependent, indicating the robustness of our findings.
Carotenoids have emerged as a hot topic in nutrition research. A growing body of evidence has suggested that dietary carotenoids are beneficial for respiratory health [8, 14], with no consensus on their implications. Two studies among male smokers reported no significant association between β-carotene supplementation and pneumonia risk [15, 16]. Another study conducted in 652 elderly individuals from Netherlands indicated that higher intake of β-carotene, instead of α-carotene, β-cryptoxanthin, lycopene, lutein, and zeaxanthin was associated with a lower risk of ARIs, but not for higher intake of α-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin [17]. Most prior studies have investigated the association between carotenoids and respiratory diseases in specific cohorts, mainly due to the difficulties to acquire detailed nutrition data in a large-scale population. Additionally, less attention has been paid to ARIs in the medical literature. Hence, a note of caution should be sounded when generalizing the findings of these studies to the national populations. In this study, we analyzed data from the US NHANES 2003 − 2018, and provided nation-based evidence by using appropriate sampling weights. Besides dietary carotenoids as a whole, we also explored the association of individual carotenoids with ARI risk, and differing from the results of prior studies [17, 18], we observed an obvious dose-dependent relationship between carotenoids and ARIs, with higher carotenoid intake corresponding to lower likelihood of having ARIs. Besides the difference in study power and population representativeness, the reasons behind the inconsistent observations might be related to the diversity in the bio-accessibility and bio-availability of carotenoids [19].
It is also worth noting that, in this study, the most beneficial role in the prediction of ARIs played by dietary carotenoids was seen in the third quartile group, rather than in the fourth quartile, in line with the studies exploring carotenoid intake and mortality from influenza and pneumonia in US adults [20]. The reason for this counterintuitive phenomenon may be explained, at least in part, by the possible intake of supplements by participants in the highest quartile of carotenoids due to the disease(s) unaccounted for in the present study [21, 22]. Another explanation is that excessive intake of carotenoids could lead to exposure to toxic substances [23], which may counterbalance the beneficial effect of dietary carotenoids. Whether carotene supplementation can improve respiratory health is still subject to an ongoing debate [7, 24]. We agree that more studies are warranted to confirm the beneficial effects of carotene supplementation against ARIs.
The contribution of dietary carotenoids to respiratory heath is biologically plausible. Carotenoids have potent antioxidant properties, and they can protect cellular structures from oxidative damage by scavenging reactive oxygen species (ROS) and quenching free radicals [25, 26], a critical component of the immune response during respiratory infections [27]. Moreover, carotenoids are known to modulate immune function by interacting with various immune cell populations; carotenoids like β-carotene and lycopene have been shown to enhance the activity of B cells, which are responsible for producing antibodies that neutralize pathogens [28]. The immunomodulatory role of carotenoids contributes to a robust and effective immune response against respiratory infections. Further, carotenoids may help to mitigate the severity and duration of respiratory infections by modulating the production of pro-inflammatory cytokines [19, 29]. The potential mechanisms by which carotenoids, if involved, influence respiratory infections involve their antioxidant and immunomodulatory activities, which can collectively enhance immune defense against respiratory pathogens and promote respiratory health.
Strengths and limitations
Strengths of this study included a large sample size and adjustment for a wide range of covariates. However, several limitations should be acknowledged. Firstly, this is a cross-sectional observational study, precluding the establishment of the causal relation between dietary carotenoids and ARIs. Secondly, although a broad spectrum of potential covariates were controlled, some unmeasured or residual confounders may still exist. Thirdly, two non-consecutive 24-hour dietary recalls as a means to comprehensively assess total food intake were adopted, which cannot reflect the long-term intake of covariates. Additionally, ARIs were defined based on self-reported data, which may introduce misclassification bias due to under-reporting of mild cases or subjective symptom interpretation.
Conclusions
In this US national general population, our findings indicated that higher dietary carotenoid intake was inversely associated with ARI risk. Our findings indicate a protective effect of carotenoid-rich dietary components against ARIs and underscore the importance of maintaining optimal carotenoid levels. Further studies are warranted to elucidate the underlying mechanisms and confirm this association across diverse populations.
Supplementary Information
Acknowledgements
We thank all the staff in the NHANES for sharing data publicly.
Abbreviations
- ARI
Acute respiratory infection
- BMI
Body mass index
- CI
Confidence interval
- NHANES
National Health and Nutrition Examination Survey
- OR
Odds ratio
- PIR
Family poverty-income ratio
- Q
Quartile
Authors’ contributions
WJ, DWH: writing original draft, methodology, data curation, formal analysis, validation, visualization, and data interpretation. ZFJY, CKN: methodology, and writing-review and editing. KYH and NWQ: supervision, funding acquisition, conceptualization, interpretation, and writing review and editing. All authors contributed to the final version of the manuscript.
Funding
This work was supported by the Public Service Development and Reform Pilot Project of Beijing Medical Research Institute (W. Niu). The work was supported by Beijing Municipal Public Welfare Development and Reform Pilot Project for Medical Research Institutes-Rapid and precise diagnosis of children respiratory infection (KYH, JYY2023-19); Capital’s Funds for Health Improvement and Research (2024-1-1132).
Data availability
The data in our study are publicly available online from the NHANES https://wwwn.cdc.gov/nchs/nhanes/Default.aspx.
Declarations
Ethics approval and concent to participate
All study participants gave informed consent following the Institutional Review Board and study ethics guidelines at the Centers for Disease Control and Prevention.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
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Jing Wu and Wenhong Dong are shared first author.
Contributor Information
Yuehua Ke, Email: yuehuakebj@163.com.
Wenquan Niu, Email: niuwenquan_shcn@163.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data in our study are publicly available online from the NHANES https://wwwn.cdc.gov/nchs/nhanes/Default.aspx.