Demographic and Social Patterns of the Mean Values of Inflammatory Markers in U.S. Adults: A 2009–2016 NHANES Analysis

Abstract

Several studies have reported on the negative implications of elevated neutrophil-to-lymphocyte ratio (NLR) and elevated platelet-to-lymphocyte ratio (PLR) levels associated with outcomes in many surgical and medical conditions, including cancer. In order to use the inflammatory markers NLR and PLR as prognostic factors in disease, a normal value in disease-free individuals must be identified first. This study aims (1) to establish mean values of various inflammatory markers using a healthy and nationally representative U.S. adult population and (2) to explore heterogeneity in the mean values by sociodemographic and behavioral risk factors to better specify cutoff points accordingly. The National Health and Nutrition Examination Survey (NHANES) of aggregated cross-sectional data collected from 2009 to 2016 was analyzed; data extracted included markers of systemic inflammation and demographic variables. We excluded participants who were under 20 years old or had a history of an inflammatory disease such as arthritis or gout. Adjusted linear regression models were used to examine the associations between demographic/behavioral characteristics and neutrophil counts, platelet counts, lymphocyte counts, as well as NLR and PLR values. The national weighted average NLR value is 2.16 and the national weighted average PLR value is 121.31. The national weighted average PLR value for non-Hispanic Whites is 123.12 (121.13–125.11), for non-Hispanic Blacks it is 119.77 (117.49–122.06), for Hispanic people it is 116.33 (114.69–117.97), and for participants of other races it is 119.84 (116.88–122.81). Non-Hispanic Blacks and Blacks have significantly lower mean NLR values (1.78, 95% CI 1.74–1.83 and 2.10, 95% CI 2.04–2.16, respectively) as compared with that of non-Hispanic Whites (2.27, 95% CI 2.22–2.30, p < 0.0001). Subjects who reported a non-smoking history had significantly lower NLR values than subjects who reported any smoking history and higher PLR values than current smokers. This study provides preliminary data for demographic and behavioral effects on markers of inflammation, i.e., NLR and PLR, that have been associated with several chronic disease outcomes, suggesting that different cutoff points should be set according to social factors.

Assessment of the systemic immune‐inflammation index in type 2 diabetic patients with and without dry eye disease: A case‐control study

“…This outcome is consistent with a study that Meng et al published, which indicated that the NLR, but not the PLR, of DED patients was reportedly higher than that of healthy subjects 25 . Also, NLR and PLR value are dependent on population characteristics such as race 38,57 …”

“…25 Also, NLR and PLR value are dependent on population characteristics such as race. 38,57 The DM2-DED had increased levels of SII as well as HbA1c. In addition, SII values were found to be considerably higher in patients with DM2-DED and DM2 than healthy and DED only.…”

Clinical value of the Systemic Inflammatory Response Index for predicting acute pancreatitis severity in Vietnamese setting

“…For example, men often have a higher NLR and monocyte count than females. 16,17 In our study, the percentage of men was 63.3%, surpassing the figures of Silva-Vaz, Biyik, and Yildiz, where the male percentages were 31.0%, 45.5% and 52.8%, respectively. Furthermore, diabetic patients typically exhibit a higher NLR than the general population.…”

“…There are many factors that can affect the NLR and monocyte beyond AP. For example, men often have a higher NLR and monocyte count than females 16,17 . In our study, the percentage of men was 63.3%, surpassing the figures of Silva‐Vaz, Biyik, and Yildiz, where the male percentages were 31.0%, 45.5% and 52.8%, respectively.…”

The associations between dietary fibers intake and systemic immune and inflammatory biomarkers, a multi-cycle study of NHANES 2015–2020

“…Sensitivity analysis was conducted by excluding the participants with incomplete data in covariates. Taking the biochemical markers between human races into consideration ( 37 ), a subgroup analyses between races were performed using a stratified logistic regression model and a interaction test for effect modification for different races were followed by the likelihood-ratio test. Data analysis was performed with the statistical software packages R 2 and EmpowerStats ( http://www.empowerstats.com , X&Y Solutions, Inc., Boston, MA).…”