Abstract
Parkinson disease (PD) has become a public health issue. Our aim is to explore the global, regional, and national burden of PD and analyze the association between the neutrophil-to-lymphocyte ratio (NLR) and PD, providing recommendations for PD prevention and control. On the basis of latest Global Burden of Disease Study 2021 data, we estimated the incidence, prevalence, and mortality rates of PD globally and assessed the changing trend of the PD burden using Joint regression analysis. Employing National Health and Nutrition Examination Survey data (2005–2018), we used logistic regression analyses to explore the association between NLR and PD. Global Burden of Disease Study data indicated that the global incidence, prevalence, mortality, and disability-adjusted life year of PD showed an overall upward trend from 1990 to 2021. In 2021, among over 200 countries and regions, the incidence rate, morbidity, mortality, and disability-adjusted life year of PD in the United States were relatively high. On the basis of National Health and Nutrition Examination Survey data, after adjusting for covariates, the PD risk in the Q4 NLR group increased by 1.73 times compared with the Q1 group (odds ratio = 2.73, 95% confidence interval = 1.70–4.37, P < .001). Moreover, there was a significant linear relationship between NLR and PD risk. Over the past 30 years, the global burden of PD has increased, with a higher burden in developed regions. Elevated NLR was significantly correlated with a higher PD risk.
Keywords: Global Burden of Disease Study, neutrophil-to-lymphocyte ratio, NHANES, Parkinson disease
1. Introduction
Parkinson disease (PD) is the second most common chronic neurodegenerative disease behind Alzheimer disease.[1] According to the survey, the global prevalence of PD is 1.51 cases per 1000. In the past few decades, the prevalence of PD has been on the rise.[2] Moreover, as the global aging process accelerates, its prevalence is expected to increase.[3] The prominent clinical features of PD are motor symptoms, such as bradykinesia, resting tremor, and postural disturbances. In addition, there are also nonmotor symptoms, such as sleep disorders, cognitive impairment, and autonomic dysfunction.[4] These clinical symptoms greatly reduce the patient’s quality of life and bring huge social and medical burdens. Therefore, it is particularly necessary to explore the PD burden globally and in different regions.
The main pathological characteristics of PD are loss of nigrostriatal dopaminergic neurons and abnormal accumulation of α-synuclein in residual neurons.[5] Increasing evidence supports that inflammation plays a critical role in the pathophysiology of PD. Research has found that a large number of activated microglia can be observed in the substantia nigra and striatum of both PD patients and PD animal models,[6] and pro-inflammatory cytokines, including interleukin-1 beta, IL-6, and tumor necrosis factor-alpha, are significantly elevated in the serum, cerebrospinal fluid (CSF), and striatum of PD patients.[7,8] Some scholars believe that excessive activation of microglia is a key driving factor for PD.[9] Activated microglia can cause damage to dopaminergic neurons and promote the accumulation of α-synuclein by producing pro-inflammatory cytokines, leading to PD.[9,10] Thus, the crucial association between inflammation and PD has attracted our attention.
The neutrophil-to-lymphocyte ratio (NLR) is a simple and widely used inflammatory biomarker, reflecting the inflammatory state and immune function of the body.[11,12] Currently, an increasing number of studies indicate that NLR is associated with PD. Studies have shown that compared with healthy individuals, the NLR levels in PD patients are significantly elevated, which may have predictive value for PD diagnosis.[13,14] It has been found that NLR is one of the risk factors for PD.[15,16] However, the potential association between NLR and PD has rarely been studied by integrating Global Burden of Disease Study (GBD) and National Health and Nutrition Examination Survey (NHANES) databases.
Therefore, we herein aimed to conduct a comprehensive assessment of the epidemiology and trends of PD worldwide based on the latest GBD data, and the further purpose of our work was to evaluate the potential association between NLR and PD employing the NHANES database. Our data are promising for a deeper understanding of PD risk, meanwhile providing effective recommendations for the prevention and control of PD.
2. Methods
2.1. Study participants from GBD and NHANES databases
First, the publicly available PD data from the GBD (from 1990 to 2021) was downloaded (https://www.healthdata.org/research-analysis/gbd-data). Of these, the records of births and deaths were considered as the predominant data source for PD burden.
Moreover, detailed information about American nutrition and health from 2005 to 2018 (7 cycles, 14 years in total) was downloaded from the NHANES database (http://www.cdc.gov/nchs/nhanes/index.htm). Next, the demographic data (including age, gender, race, marital status, family poverty-to-income ratio [PIR], and education level), examination data (including body mass index [BMI] and blood pressure), questionnaire data (including hypertension status, alcohol use, and smoking status), and laboratory data (including absolute neutrophil count and absolute lymphocyte count) were extracted from the NHANES database. As the data from the above databases were de-identified, publicly available data, our present work was exempt from the approval of the local review board.
2.2. Incidence rate and mortality rate estimates
Basing on data derived from GBD, the incidence rate, prevalence, mortality rate, and disability-adjusted life year (DALY) of PD patients in the world and various regions were analyzed. Incidence rate was defined as the proportion of new PD cases in a specific population within a specific period. Prevalence was defined as the proportion of existing PD cases in a specific population at a specific point or period. Mortality rate referred to the proportion of deaths in a specific population during a certain period. DALY was the sum of years of life lost caused by specific reasons and years lived with disability of people living in poor health conditions because of specific reasons. Annual percent change referred to the percentage change per year, reflecting the dynamic trends and short-term fluctuations between years. Average annual percent change referred to the weighted average of multiple annual percent changes, which was suitable for describing the average annual change at different stages of a long-term trend.
2.3. PD definition
The dependent variable of this study was PD. In the NHANES database, participants who reported using anti-PD medications were identified as PD participants, while those who reported not taking anti-PD medications were identified as non-PD patients. PD patients were defined as individuals who reported using at least 1 of the following seven anti-PD medications: Benztropine, Methyldopa, Carbidopa, Levodopa, Entacapone, Amantadine, and Ropinirole.[17]
2.4. NLR calculation
The NHANES database also recorded the laboratory data of the participants. Herein, the NLR was included as the independent variable, which was calculated using the following formula: NLR = total absolute neutrophil counts/total absolute lymphocyte counts. According to the quartiles of NLR levels, participants were divided into 4 groups: Q1 (NLR < 1.41), Q2 (1.41 ≤ NLR < 1.87), Q3 (1.87 ≤ NLR < 2.47), and Q4 (NLR ≥ 2.47).
2.5. Assessment of various covariables
The covariates of this study included demographic information such as gender, age, race, education level, marital status, PIR, BMI, hypertension status, alcohol use, and smoking status. The specific categorization criteria were as follows: gender was categorized as male and female; age was categorized as 20 to 60 and ≥60 years old; race was categorized as Mexican American, non-Hispanic Black, non-Hispanic White, other Hispanic, and other race, including multi-racial; education level was categorized as less than high school, high school or equivalent, and college or above; marital status was categorized as never married, married/partnered, and separated/divorced/widowed; PIR was categorized as <1.5, 1.5 to 3.5, and >3.5; BMI was categorized as <25, 25 to 30, and ≥30; hypertension was diagnosed based on self-report in the questionnaire. Hypertensive patients were defined as individuals who take antihypertensive drugs or have an average systolic blood pressure of ≥140 mmHg and/or an average diastolic blood pressure of ≥90 mmHg; alcohol use was categorized as mild (never drinking, or <2 drinks per day for females, <3 drinks per day for males), moderate (2 drinks per day for females, 3 drinks per day for males), and heavy (≥3 drinks per day for females, ≥4 drinks per day for males); smoking status was categorized as never (≤100 cigarettes in a lifetime), ever (>100 cigarettes but no longer smoking), and now (>100 cigarettes but occasionally or continuously smoking).[18]
2.6. Statistical analysis
Regarding the GBD data analysis, we conducted Joinpoint regression analysis using Joinpoint trend analysis software (version 5.3.0; National Cancer Institute) to evaluate the changing trend of PD burden. To capture the main trends of the data and avoid overfitting, the maximum number of joint points was set to 5. The uncertain interval (UI) was a series of values that estimate certainty. The 95% UI was determined by the 25th and 975th values sorted from 1000 estimated values. Other analyses were conducted using R (version 4.4.2; R Foundation for Statistical Computing). When P < .05, the difference was considered statistically significant.
Regarding the NHANES data analysis, continuous variables were represented as mean ± standard deviation, and categorical variables were represented as quantity (proportion). The t-test and chi-square test were applied to evaluate the differences in continuous and categorical variables, respectively. Multivariate logistic regression analysis was used to construct a multivariate model. The odds ratio (OR) and 95% confidence interval (CI) were calculated, where the OR was used to reflect the difference in exposure factors between cases and controls. All the above statistical analyses were conducted using R software (version 4.4.2). When P < .05, the difference was considered statistically significant.
3. Results
3.1. Trends in PD burden and epidemiology in various regions
First of all, the GBD data (1990–2021) were used to estimate the general PD burden. The results of the GBD data showed that, from 1990 to 2021, the incidence rate (Fig. 1A), prevalence (Fig. 1B), mortality rate (Fig. 2A), and DALY (Fig. 2B) of PD were all on the rise globally (Average annual percent change was 2.52, 3.03, 1.86, and 1.87, separately).
Figure 1.
Joinpoint regression analysis of the global incidence (A) and prevalence (B) of PD from 1990 to 2021. Joinpoint regression arnalysis was used here to evaluate the changing trend of PD burden. APC = annual percentage change, PD = Parkinson disease.
Figure 2.
Joinpoint regression analysis of the global mortality (A) and DALYs (B) of PD from 1990 to 2021. Joinpoint regression analysis was used here to evaluate the changing trend of PD burden. APC = annual percentage change, DALYs = disability-adjusted life years, PD = Parkinson disease.
In 2021, the incidence rate, prevalence, mortality rate, and DALY of PD were generally high in Western Europe, North America, and other developed regions, but relatively low in Africa and Western Asia, where economic development is lagging (Figs. 3 and 4). The countries with the highest and lowest incidence rates were Germany (53.1, 95% UI = 51–55.3) and Somalia (1.7, 95% UI = 1.5–2), respectively. The countries with the highest and lowest prevalence were Germany (494.2, 95% UI = 474.4–515.2) and Somalia (11.5, 95% UI = 9.3–14.1), respectively. The countries with the highest and lowest mortality rates were Monaco (20.4, 95% UI = 15.5–25.5) and the United Arab Emirates (0.4, 95% UI = 0.3–0.5), respectively. The countries with the highest and lowest DALYs were Monaco (333.1, 95% UI = 267.5–396.2) and Somalia (12.7, 95% UI = 8.9–17), respectively (Table S1, Supplemental Digital Content 1). It was worth noting that among more than 200 countries and regions, the burden of PD in the United States was relatively heavy, and its incidence rate, prevalence, mortality rate, and DALY in 2021 were 26.2 (95% UI = 24–28.7), 208 (95% UI = 191.1–226.1), 11.3 (95% UI = 9.6–12.1), and 184.3 (164.3–197.7), respectively (Table S1, Supplemental Digital Content 1). Briefly, the PD burden had obviously increased worldwide based on the GBD data, exhibiting an urgent need for PD prevention.
Figure 3.
Global distribution of PD in 2021. The descriptive and spatial analysis of global incidence (A) and prevalence (B) of PD. PD = Parkinson disease.
Figure 4.
Global distribution of PD in 2021. The descriptive and spatial analysis of global mortality (A) and DALYs (B) of PD. DALYs = disability-adjusted life years, PD = Parkinson disease.
3.2. Characteristics of PD participants
GBD data indicated that the PD burden in the United States was relatively heavy. Hence, we then analyzed the baseline information of PD patients and explored the potential risk of NLR for developing PD, incorporating NHANES data. From 2005 to 2018, a total of 156,015 participants participated in NHANES. First, 53,031 participants younger than 20 years old were excluded. Then, 9126 participants with incomplete NLR data and 78,212 participants with incomplete PD data were excluded, leaving 15,646 participants included in this study. Among them, there were 322 PD participants and 15,324 non-PD participants (Fig. 5).
Figure 5.
Flowchart of study inclusion: flowchart of the participants’ selection from NHANES (2005–2018). NHANES = National Health and Nutrition Examination Survey, NLR = neutrophil-to-lymphocyte ratio, PD = Parkinson disease.
We then analyzed the general characteristics between PD and non-PD groups (Table 1). In terms of demographic factors, the proportion of females in the PD group was significantly higher than that in the non-PD group (59.9% vs 44.3%, P < .001), and the proportion of non-Hispanic Whites was significantly higher than that in the non-PD group (81.9% vs 56.8%, P < .001). Compared with the non-PD group, the average age of participants in the PD group was older (60.87 ± 15.44 years vs 39.12 ± 13.56 years, P < .001), and the proportion of participants aged ≥60 years was significantly higher (49.7% vs 8.4%, P < .001). In terms of lifestyle and health conditions, compared with the non-PD group, the PD group had a larger number of participants with higher BMI, hypertension, lower alcohol use, and a smoking history (P < .05). Regarding inflammation-related parameters, the proportion of the NLR Q4 population in the PD group was significantly higher than that of the non-PD group (50.4% vs 24.8%, P < .001). Moreover, compared with the non-PD group, the lymphocyte number of participants was significantly increased, while the segmented neutrophil number was significantly decreased in the PD group (P < .05). In terms of socioeconomic factors, there was a significant difference in marital status between the 2 groups (P < .001), while there was no significant difference in education level and PIR (P > .05).
Table 1.
Characteristics of the participants, stratified by PD status.
| Variable | Level | Overall | Non-PD | PD | P value |
|---|---|---|---|---|---|
| N | 15646 | 15324 | 322 | ||
| Gender (%) | <.001 | ||||
| Female | 6978 (44.6) | 6789 (44.3) | 193 (59.9) | ||
| Male | 8668 (55.4) | 8535 (55.7) | 129 (40.1) | ||
| Age | <.001 | ||||
| 39.53 ± 13.91 | 39.12 ± 13.56 | 60.87 ± 15.44 | |||
| 20–60 | 14,222 (90.9) | 14,037 (91.6) | 162 (50.3) | ||
| ≥60 | 1424 (9.1) | 1287 (8.4) | 160 (49.7) | ||
| Race (%) | <.001 | ||||
| Mexican American | 2050 (13.1) | 2038 (13.3) | 13 (4) | ||
| Non-Hispanic Black | 1940 (12.4) | 1916 (12.5) | 26 (8) | ||
| Non-Hispanic White | 8965 (57.3) | 8704 (56.8) | 264 (81.9) | ||
| Other Hispanic | 1189 (7.6) | 1180 (7.7) | 10 (3.2) | ||
| Other Race – including Multi-Racial | 1502 (9.6) | 1486 (9.7) | 9 (2.8) | ||
| Education level (%) | .702 | ||||
| Less than high school | 954 (6.1) | 935 (6.1) | 22 (6.9) | ||
| High school or equivalent | 5867 (37.5) | 5747 (37.5) | 113 (35.2) | ||
| College or above | 9779 (62.5) | 9578 (62.5) | 209 (64.8) | ||
| Marital status (%) | <.001 | ||||
| Never married | 3739 (23.9) | 3693 (24.1) | 40 (12.3) | ||
| Married | 9888 (63.2) | 9715 (63.4) | 183 (56.8) | ||
| Separated | 2003 (12.8) | 1916 (12.5) | 100 (31) | ||
| PIR (%) | .361 | ||||
| <1.5 | 4616 (29.5) | 4505 (29.4) | 107 (33.1) | ||
| 1.5–3.5 | 5069 (32.4) | 4950 (32.3) | 113 (35.2) | ||
| >3.5 | 5961 (38.1) | 5854 (38.2) | 102 (31.7) | ||
| BMI (%) | .008 | ||||
| <25 | 5507 (35.2) | 5409 (35.3) | 88 (27.4) | ||
| 25–30 | 5257 (33.6) | 5164 (33.7) | 91 (28.4) | ||
| ≥30 | 4882 (31.2) | 4750 (31) | 142 (44.2) | ||
| Hypertension (%) | <.001 | ||||
| No | 12,751 (81.5) | 12,627 (82.4) | 111 (34.4) | ||
| Yes | 2895 (18.5) | 2697 (17.6) | 211 (65.6) | ||
| Alcohol using (%) | <.001 | ||||
| Mild | 7698 (49.2) | 7463 (48.7) | 237 (73.6) | ||
| Moderate | 3207 (20.5) | 3157 (20.6) | 53 (16.5) | ||
| Heavy | 4741 (30.3) | 4704 (30.7) | 32 (9.9) | ||
| Smoking status (%) | .027 | ||||
| Never | 9184 (58.7) | 9011 (58.8) | 167 (51.9) | ||
| Ever | 2801 (17.9) | 2728 (17.8) | 84 (26.1) | ||
| Now | 3661 (23.4) | 3586 (23.4) | 71 (22) | ||
| NLR | <.001 | ||||
| 2.10 ± 1.02 | 2.08 ± 0.97 | 2.96 ± 2.38 | |||
| Q1 | 3489 (22.3) | 3448 (22.5) | 33 (10.2) | ||
| Q2 | 4052 (25.9) | 4000 (26.1) | 57 (17.8) | ||
| Q3 | 4146 (26.5) | 4076 (26.6) | 69 (21.5) | ||
| Q4 | 3958 (25.3) | 3800 (24.8) | 162 (50.4) | ||
| Lymphocyte number (mean ± SD) | 4.28 ± 1.73 | 4.27 ± 1.72 | 4.79 ± 2.12 | .005 | |
| Segmented neutrophil number (mean ± SD) | 2.18 ± 0.86 | 2.19 ± 0.85 | 1.97 ± 1.14 | .004 |
Data are presented as N (%) (t-test) or mean ± SD (chi-square test).
P < .05 indicates statistical significance (highlighted in bold font).
BMI = body mass index, NLR = neutrophil-to-lymphocyte ratio, PD = Parkinson disease, PIR = poverty-to-income ratio, SD = standard deviation.
Next, detailed baseline information was also analyzed among Q1, Q2, Q3, and Q4 PD patients to further illustrate the characteristics of PD patients with differential NLR. It was found that the proportion of non-Hispanic Whites in the Q4 group was significantly higher than that in the Q1 group (76.5% vs 45.7%, P < .001). Compared with the Q1 group, the proportion of participants with a smoking history in the Q4 group was significantly higher (47.5% vs 22.2%, P < .001). In addition, there were no significant differences in gender, age, education level, marital status, PIR, BMI, hypertension status, and alcohol use (P > .05; Table 2).
Table 2.
Characteristics of the participants, stratified by NLR levels.
| Variable | Level | Overall | Q1 | Q2 | Q3 | Q4 | P value |
|---|---|---|---|---|---|---|---|
| NLR | <1.75 | 1.75–2.35 | 2.35–3.15 | >3.15 | |||
| N | 322 | 81 | 80 | 80 | 81 | ||
| Gender (%) | .033 | ||||||
| Female | 166 (51.6) | 47 (58.0) | 47 (58.8) | 41 (51.2) | 31 (38.3) | ||
| Male | 156 (48.4) | 34 (42.0) | 33 (41.2) | 39 (48.8) | 50 (61.7) | ||
| Age | .565 | ||||||
| 63.13 (15.73) | 60.62 (14.76) | 61.70 (16.38) | 64.75 (15.50) | 65.44 (16.03) | |||
| 20–60 | 192 (59.6) | 44 (54.3) | 46 (57.5) | 51 (63.7) | 51 (63.0) | ||
| ≥60 | 130 (40.4) | 37 (45.7) | 34 (42.5) | 29 (36.2) | 30 (37.0) | ||
| Race (%) | <.001 | ||||||
| Mexican American | 32 (9.9) | 6 (7.4) | 9 (11.2) | 11 (13.8) | 6 (7.4) | ||
| Non-Hispanic Black | 45 (14.0) | 24 (29.6) | 7 (8.8) | 10 (12.5) | 4 (4.9) | ||
| Non-Hispanic White | 201 (62.4) | 37 (45.7) | 47 (58.8) | 55 (68.8) | 62 (76.5) | ||
| Other Hispanic | 25 (7.8) | 11 (13.6) | 5 (6.2) | 2 (2.5) | 7 (8.6) | ||
| Other Race - Including Multi-Racial | 19 (5.9) | 3 (3.7) | 12 (15.0) | 2 (2.5) | 2 (2.5) | ||
| Education level (%) | .689 | ||||||
| Less than high school | 161 (50.0) | 34 (42.0) | 39 (48.8) | 44 (55.0) | 44 (54.3) | ||
| High school or equivalent | 125 (38.8) | 36 (44.4) | 31 (38.8) | 28 (35.0) | 30 (37.0) | ||
| College or above | 36 (11.2) | 11 (13.6) | 10 (12.5) | 8 (10.0) | 7 (8.6) | ||
| Marital status (%) | .285 | ||||||
| Never married | 175 (54.3) | 44 (54.3) | 44 (55.0) | 39 (48.8) | 48 (59.3) | ||
| Married | 43 (13.4) | 10 (12.3) | 16 (20.0) | 9 (11.2) | 8 (9.9) | ||
| Separated | 104 (32.3) | 27 (33.3) | 20 (25.0) | 32 (40.0) | 25 (30.9) | ||
| PIR (%) | .56 | ||||||
| <1.5 | 129 (43.6) | 36 (46.8) | 33 (44.6) | 24 (33.8) | 36 (48.6) | ||
| 1.5–3.5 | 70 (23.6) | 15 (19.5) | 17 (23.0) | 22 (31.0) | 16 (21.6) | ||
| >3.5 | 97 (32.8) | 26 (33.8) | 24 (32.4) | 25 (35.2) | 22 (29.7) | ||
| BMI (%) | .419 | ||||||
| <25 | 82 (27.5) | 15 (19.2) | 25 (34.2) | 20 (27.0) | 22 (30.1) | ||
| 25–30 | 130 (43.6) | 39 (50.0) | 30 (41.1) | 34 (45.9) | 27 (37.0) | ||
| ≥30 | 86 (28.9) | 24 (30.8) | 18 (24.7) | 20 (27.0) | 24 (32.9) | ||
| Hypertension (%) | .178 | ||||||
| No | 110 (34.5) | 29 (36.2) | 24 (30.0) | 22 (28.2) | 35 (43.2) | ||
| Yes | 209 (65.5) | 51 (63.7) | 56 (70.0) | 56 (71.8) | 46 (56.8) | ||
| Alcohol using (%) | .056 | ||||||
| Never | 23 (9.7) | 8 (15.4) | 8 (12.3) | 3 (5.3) | 4 (6.3) | ||
| Moderate | 25 (10.5) | 10 (19.2) | 3 (4.6) | 7 (12.3) | 5 (7.9) | ||
| Heavy | 189 (79.7) | 34 (65.4) | 54 (83.1) | 47 (82.5) | 54 (85.7) | ||
| Smoking status (%) | <.001 | ||||||
| Never | 89 (27.7) | 18 (22.2) | 17 (21.2) | 16 (20.0) | 38 (47.5) | ||
| Ever | 167 (52.0) | 40 (49.4) | 42 (52.5) | 49 (61.3) | 36 (45.0) | ||
| Now | 65 (20.2) | 23 (28.4) | 21 (26.2) | 15 (18.8) | 6 (7.5) | ||
| NLR (mean ± SD) | 2.77 ± 1.83 | 1.29 ± 0.33 | 2.06 ± 0.17 | 2.75 ± 0.23 | 4.97 ± 2.38 | <.001 | |
| Lymphocyte number (mean ± SD) | 4.60 ± 1.85 | 3.40 ± 1.13 | 4.28 ± 1.54 | 4.80 ± 1.57 | 5.94 ± 2.05 | <.001 | |
| Segmented neutrophil number (mean ± SD) | 2.01 ± 1.33 | 2.89 ± 2.15 | 2.08 ± 0.73 | 1.75 ± 0.56 | 1.33 ± 0.56 | <.001 |
Data are presented as N (%) (t-test) or mean ± SD (chi-square test).
P < .05 indicates statistical significance (highlighted in bold font).
BMI = body mass index, NLR = neutrophil-to-lymphocyte ratio, PD = Parkinson disease, PIR = poverty-to-income ratio, SD = standard deviation.
3.3. Association between NLR and PD
We then constructed 3 models to explore the association between NLR and PD. Model 1 was not adjusted with any covariate. Model 2 was adjusted for age, gender, race, marital status, education level, and PIR. Model 3 was adjusted for age, gender, race, marital status, education level, hypertension status, alcohol use, and smoking status.
The results showed that continuous NLR was significantly positively correlated with PD risk in all models (OR of 1.43, 1.36, and 1.34 for models 1, 2, and 3, respectively; all P < .001, Table 3). These data indicated that incorporating the above covariates, continuous NLR was still correlated with the risk of PD.
Table 3.
Association between NLR and PD risk.
| Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|
| OR (95% CI) | P value | OR (95% CI) | P value | OR (95% CI) | P value | |
| Continuous NLR | 1.43 (1.34–1.52) | <.001 | 1.36 (1.26–1.47) | <.001 | 1.34 (1.23–1.47) | <.001 |
| Q1 | ||||||
| Q2 | 1.09 (0.73–1.64) | .675 | 1.00 (0.65–1.55) | .988 | 1.20 (0.70–2.06) | .517 |
| Q3 | 1.74 (1.20–2.52) | .003 | 1.40 (0.94–2.09) | .101 | 1.99 (1.21–3.27) | .006 |
| Q4 | 3.44 (2.46–4.82) | <.001 | 2.45 (1.70–3.54) | <.001 | 2.73 (1.70–4.37) | <.001 |
| P for trend | 2.04 (1.74–2.38) | <.001 | 1.71 (1.44–2.03) | <.001 | 1.70 (1.38–2.09) | <.001 |
Multivariate logistic regression analysis was used to construct a multivariate model.
Model 1: unadjusted.
Model 2: adjusted with gender, race, marital status, education level, and PIR.
Model 3: adjusted with age, gender, race, marital status, and education level, hypertension status, alcohol using, and smoking status.
P < .05 indicates statistical significance (highlighted in bold font).
CI = confidence interval, NLR = neutrophil-to-lymphocyte ratio, OR = odds ratio, PD = Parkinson disease, PIR = poverty-to-income ratio.
When NLR was used as a categorical variable, participants in the higher NLR group had an increased risk of PD compared with those in the lower NLR group. As NLR increased, the PD risk also showed an upward trend (Table 3). Specifically, in model 1, compared with the Q1 group, participants in the Q4 group had a 2.44-fold increase in PD risk (OR = 3.44, 95% CI = 2.46–4.82, P < .001). In model 3, after adjusting for demographic, socioeconomic, and health factors, the PD risk of participants in the Q4 group was 1.73 times higher than that in the Q1 group (OR = 2.73, 95% CI = 1.70–4.37, P < .001). The above results suggested that, as a categorical variable, high NLR was associated with an increased risk of PD. In addition, there was a significant linear relationship between NLR and PD risk in the 3 models (P for trend < .001).
3.4. Association between NLR and PD among different subgroups
To evaluate whether different demographic and health factors (including gender, age, race, alcohol use, smoking status, and hypertension status) affect the relationship between NLR and PD, we conducted subgroup analysis. The results showed that in all 3 models, regardless of gender, age, and hypertension status, participants in the Q4 group had a significantly higher risk of PD compared to the Q1 group (OR > 1 and P < .05; Table 4). In non-Hispanic Whites (Q4 vs Q1: OR > 1 and P < .05 in 3 models), light drinkers (Q4 vs Q1: OR > 1 and P < .05 in models 2 and 3), nonsmokers, and former smokers (Q4 vs Q1: OR > 1 and P < .05 in 3 models), NLR was significantly positively correlated with PD risk (Table 4). This indicated that the correlation between NLR level and PD risk was statistically significant among race, alcohol use, and smoking status subgroups.
Table 4.
Associations between NLR and PD risk among different subgroups.
| Variable | Level | Model 1 | P value | Model 2 | P value | Model 3 | P value | |
|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | ||||||
| Gender | Male | |||||||
| Q1 | ||||||||
| Q2 | 0.98 (0.52–1.85) | .958 | 0.78 (0.38–1.59) | .487 | 1.18 (0.51–2.77) | .697 | ||
| Q3 | 1.61 (0.91–2.84) | .102 | 1.19 (0.63–2.27) | .591 | 1.82 (0.84–3.97) | .131 | ||
| Q4 | 5.05 (3.10–8.25) | <.001 | 2.79 (1.58–4.93) | <.001 | 3.08 (1.47–6.43) | .003 | ||
| Female | ||||||||
| Q1 | ||||||||
| Q2 | 1.15 (0.68–1.97) | .6 | 1.17 (0.67–2.06) | .573 | 1.10 (0.54–2.24) | .799 | ||
| Q3 | 1.79 (1.10–2.91) | .02 | 1.73 (1.03–2.90) | .037 | 1.98 (1.03–3.81) | .039 | ||
| Q4 | 2.27 (1.42–3.62) | <.001 | 2.15 (1.30–3.55) | .003 | 1.93 (1.02–3.66) | .045 | ||
| Age | 20–60 | |||||||
| Q1 | ||||||||
| Q2 | 0.83 (0.46–1.50) | .53 | 0.73 (0.39–1.39) | .337 | 1.27 (0.58–2.78) | .542 | ||
| Q3 | 1.21 (0.70–2.08) | .495 | 1.12 (0.63–2.00) | .692 | 1.77 (0.86–3.64) | .12 | ||
| Q4 | 2.50 (1.55–4.04) | <.001 | 2.06 (1.23–3.46) | .006 | 2.70 (1.36–5.36) | .004 | ||
| ≥60 | ||||||||
| Q1 | ||||||||
| Q2 | 1.50 (0.84–2.67) | .171 | 1.06 (0.54–2.07) | .864 | 0.87 (0.37–2.02) | .739 | ||
| Q3 | 2.46 (1.45–4.18) | <.001 | 1.62 (0.88–3.00) | .122 | 2.01 (0.95–4.24) | .068 | ||
| Q4 | 3.97 (2.43–6.49) | <.001 | 2.84 (1.60–5.03) | <.001 | 2.46 (1.20–5.08) | .015 | ||
| Race | Mexican American | |||||||
| Q1 | ||||||||
| Q2 | 0.56 (0.13–2.52) | .453 | 0.29 (0.05–1.69) | .171 | 0.16 (0.01–1.70) | .128 | ||
| Q3 | 1.90 (0.59–6.08) | .281 | 1.34 (0.37–4.85) | .657 | 1.63 (0.36–7.46) | .53 | ||
| Q4 | 2.88 (0.95–8.73) | .061 | 1.15 (0.32–4.17) | .832 | 1.27 (0.27–5.89) | .758 | ||
| Non-Hispanic Black | ||||||||
| Q1 | ||||||||
| Q2 | 0.78 (0.33–1.87) | .584 | 0.81 (0.31–2.09) | .662 | 2.23 (0.73–6.82) | .162 | ||
| Q3 | 0.81 (0.32–2.03) | .647 | 0.83 (0.30–2.27) | .71 | 1.42 (0.41–5.00) | .581 | ||
| Q4 | 1.85 (0.91–3.77) | .091 | 1.93 (0.89–4.21) | .097 | 2.21 (0.68–7.24) | .189 | ||
| Non-Hispanic White | ||||||||
| Q1 | ||||||||
| Q2 | 1.33 (0.71–2.48) | .375 | 1.24 (0.64–2.39) | .518 | 1.01 (0.45–2.29) | .983 | ||
| Q3 | 1.79 (0.99–3.22) | .054 | 1.42 (0.76–2.64) | .271 | 1.81 (0.86–3.81) | .12 | ||
| Q4 | 4.00 (2.32–6.91) | <.001 | 2.99 (1.69–5.29) | <.001 | 2.91 (1.44–5.91) | .003 | ||
| Other Hispanic | ||||||||
| Q1 | ||||||||
| Q2 | 0.57 (0.18–1.80) | .336 | 0.54 (0.12–2.57) | .443 | 0.29 (0.04–2.13) | .226 | ||
| Q3 | 0.62 (0.20–1.98) | .423 | 0.60 (0.13–2.79) | .512 | 0.50 (0.07–3.36) | .472 | ||
| Q4 | 1.09 (0.39–3.03) | .872 | 1.57 (0.44–5.63) | .492 | 1.98 (0.43–9.15) | .381 | ||
| Alcohol using | Mild | |||||||
| Q1 | ||||||||
| Q2 | 1.05 (0.25–4.48) | .942 | 1.57 (0.84–2.91) | .157 | 1.10 (0.55–2.18) | .786 | ||
| Q3 | 0.76 (0.16–3.60) | .73 | 3.30 (1.91–5.71) | <.001 | 2.34 (1.28–4.28) | .006 | ||
| Q4 | 2.17 (0.60–7.90) | .239 | 5.93 (3.52–10.01) | <.001 | 3.15 (1.76–5.63) | <.001 | ||
| Moderate | ||||||||
| Q1 | ||||||||
| Q2 | 0.63 (0.18–2.24) | .476 | 1.05 (0.25–4.48) | .942 | 1.02 (0.23–4.48) | .978 | ||
| Q3 | 0.66 (0.19–2.36) | .526 | 0.76 (0.16–3.60) | .73 | 0.92 (0.19–4.42) | .914 | ||
| Q4 | 1.85 (0.68–5.04) | .229 | 2.17 (0.60–7.90) | .239 | 2.27 (0.60–8.60) | .228 | ||
| Heavy | ||||||||
| Q1 | ||||||||
| Q2 | 2.15 (0.55–8.34) | .268 | 0.78 (0.15–4.04) | .762 | 0.77 (0.14–4.13) | .76 | ||
| Q3 | 1.78 (0.44–7.14) | .416 | 0.96 (0.21–4.26) | .953 | 0.91 (0.20–4.12) | .903 | ||
| Q4 | 1.94 (0.50–7.54) | .336 | 0.66 (0.14–3.14) | .601 | 0.59 (0.12–2.84) | .507 | ||
| Smoking status | Never | |||||||
| Q1 | ||||||||
| Q2 | 1.54 (0.85–2.81) | .155 | 1.51 (0.75–3.02) | .25 | 1.86 (0.69–4.99) | .217 | ||
| Q3 | 2.56 (1.48–4.44) | <.001 | 2.32 (1.21–4.43) | .011 | 3.90 (1.56–9.72) | .004 | ||
| Q4 | 5.06 (3.02–8.48) | <0.001 | 3.88 (2.09–7.19) | <.001 | 5.65 (2.31–13.80) | <.001 | ||
| Ever | ||||||||
| Q1 | ||||||||
| Q2 | 1.06 (0.46–2.48) | .886 | 0.70 (0.27–1.85) | .473 | 0.75 (0.25–2.23) | .604 | ||
| Q3 | 1.38 (0.62–3.11) | .429 | 0.93 (0.38–2.31) | .88 | 1.00 (0.36–2.80) | .995 | ||
| Q4 | 4.74 (2.39–9.41) | <.001 | 3.02 (1.42–6.45) | .004 | 2.58 (1.05–6.30) | .038 | ||
| Now | ||||||||
| Q1 | ||||||||
| Q2 | 0.60 (0.27–1.31) | .198 | 0.51 (0.21–1.25) | .142 | 0.81 (0.27–2.39) | .702 | ||
| Q3 | 1.07 (0.55–2.07) | .847 | 0.77 (0.36–1.67) | .511 | 1.41 (0.57–3.51) | .455 | ||
| Q4 | 0.93 (0.48–1.80) | .824 | 0.70 (0.32–1.50) | .353 | 0.72 (0.27–1.93) | .519 | ||
| Hypertension | No | |||||||
| Q1 | ||||||||
| Q2 | 0.98 (0.51–1.88) | .943 | 0.93 (0.46–1.87) | .838 | 1.18 (0.52–2.66) | .693 | ||
| Q3 | 1.16 (0.62–2.18) | .647 | 0.99 (0.50–1.95) | .975 | 1.34 (0.62–2.90) | .463 | ||
| Q4 | 3.09 (1.81–5.30) | <.001 | 2.36 (1.30–4.27) | .004 | 2.64 (1.29–5.41) | .008 | ||
| Yes | ||||||||
| Q1 | ||||||||
| Q2 | 1.33 (0.78–2.27) | .287 | 0.80 (0.42–1.52) | .493 | 0.90 (0.39–2.07) | .811 | ||
| Q3 | 2.32 (1.44–3.73) | <.001 | 1.58 (0.90–2.78) | .113 | 2.54 (1.25–5.17) | .01 | ||
| Q4 | 3.51 (2.25–5.48) | <.001 | 2.12 (1.25–3.61) | .005 | 2.73 (1.38–5.43) | .004 |
Multivariate logistic regression analysis was used to construct a multivariate model.
Model 1: unadjusted.
Model 2: adjusted with gender, race, marital status, education level, and poverty-to-income ratio.
Model 3: adjusted with age, gender, race, marital status, and education level, hypertension status, alcohol using, and smoking status.
P < .05 indicates statistical significance (highlighted in bold font).
CI = confidence interval, NLR = neutrophil-to-lymphocyte ratio, OR = odds ratio, PD = Parkinson disease.
4. Discussion
PD is the fastest-growing neurological disease in recent years.[19] With the aging population and increasing life expectancy, it is expected that the number of PD patients worldwide will continue to increase.[20,21] Thus, it is particularly important to determine the latest global burden of PD and identify potential risk factors for PD. On the basis the latest GBD data and NHANES large-sample data, this study found that the global burden of PD has been increasing over the past 30 years. Moreover, elevated NLR was significantly correlated with an increased risk of PD.
Our study found that from 1990 to 2021, the global incidence rate, prevalence, mortality rate, and DALY of PD showed an overall upward trend. According to literature reports, the main reason for the increased burden of PD is the accumulation of multiple pathogenic factors. In addition to immutable factors such as genetics, an aging population, and increasing life expectancy, there are also variable environmental factors, such as exposure to agricultural and industrial toxins.[22] Studies have shown that individuals exposed to pesticides, solvents, and heavy metals had a significantly increased risk of developing PD.[23–25] We also found that in 2021, the incidence rate, prevalence, mortality rate, and DALY of PD were generally high in Western Europe, North America, and other developed regions, but relatively low in Africa and Western Asia, where economic development is lagging. Similarly, a previous study found that the number of PD patients in high socio-demographic index (SDI) countries was more than twice that of low SDI countries, and the age-standardized DALY rates of PD increased with the increase of SDI,[26] which was consistent with our findings. This may be because of the more common exposure to industrialized environments in high SDI countries.[26]
As mentioned above, the pathogenic factors of PD included genetic susceptibility and environmental factors. Almost all pathogenic factors of PD are closely related to inflammatory response.[27] Peripheral and central inflammation mediated by peripheral white blood cell components (including neutrophils, lymphocytes, and monocytes) has a significant impact on the occurrence and development of PD.[28,29] NLR encompasses information on 2 subtypes of white blood cells, reflecting the balance of neutrophil and lymphocyte counts and the degree of systemic inflammatory response. It is considered an important biomarker of peripheral inflammatory response.[11,12]
So far, many studies have shown a close relationship between NLR and PD. In this study, we analyzed the association between NLR and PD based on a large sample from the NHANES database. We noticed that NLR was significantly positively correlated with PD risk. Previously, clinical evidence showed that, compared with healthy individuals, the NLR level in PD patients was significantly elevated.[13,14,30] Moreover, the neutrophil count increased and the lymphocyte count decreased in PD patients, which was consistent with the changing trend of NLR in PD patients in our work. In addition, NLR was also related to the duration and severity of PD.[31,32] Specifically, NLR was positively correlated with motor severity,[33] and negatively correlated with cognitive ability in PD patients.[34,35] In terms of pathophysiology, peripheral inflammation is believed to potentially trigger neuroinflammation, leading to dopaminergic degeneration in PD.[36] Studies have reported that higher NLR and lower lymphocyte count were significantly correlated with lower striatal dopamine transporter density in the caudate and putamen of PD patients, which was a parameter for evaluating degeneration of nigrostriatal dopaminergic neurons.[37,38] Grillo et al[32] also found that in PD patients, lymphocyte count was positively correlated with α-synuclein level in CSF, while NLR was negatively correlated with CSF amyloid-β42 level, both of which were central neurodegeneration-associated biomarkers. This evidence suggested that NLR can reflect the degree of dopaminergic degeneration caused by peripheral immune changes in PD, thereby serving as a marker relating to PD risk. Furthermore, our stratification analysis, involving gender, age, race, alcohol use, smoking status, and hypertension status, indicated that the association between NLR and PD existed no matter the clinical factors. In addition, we also found a significant linear relationship between NLR and PD risk. Our above findings suggested that higher NLR indicated an increased risk of developing PD in the future, which should be paid special attention to in vulnerable populations.
Although our study provided the first large-scale exploration of the potential association between NLR and PD risk using the NHANES database, several limitations should be acknowledged. First, despite integrating GBD data and NHANES data, the inherent feature of cross-sectional and observational design limited the causal inference. Moreover, some data gaps in the NHANES database partly limited the comprehensiveness of our study. For instance, the definition of PD cases relied primarily on self-reported use of anti-Parkinsonian medications, with no available information on disease severity, duration, and comorbid inflammatory conditions. On the other hand, potential confounding factors of NLR values involving concomitant inflammatory or infectious conditions were largely unavailable in the NHANES database. Therefore, in our future work, a prospective study based on a larger cohort with more comprehensive clinical data is warranted to further explore the potential predictive value of NLR in PD, while accounting for a broader range of confounding factors.
5. Conclusion
In short, the global burden of PD has been increasing over the past 30 years. Moreover, in some developed regions such as Western Europe and North America, the PD burden is generally high. Incorporating NHANES data, a higher NLR has been indicated to significantly correlate with an elevated risk of PD. Our findings outline the potential clinical utility of NLR, which is a promising, inexpensive, and easily available marker for PD, thereby indirectly contributing to the risk stratification and prognostication of PD patients.
Author contributions
Conceptualization: Huaiqing Gao.
Data curation: Huaiqing Gao, Guangjun Nie.
Formal analysis: Huaiqing Gao, Guangjun Nie.
Investigation: Huaiqing Gao.
Methodology: Huaiqing Gao.
Software: Huaiqing Gao, Guangjun Nie.
Validation: Huaiqing Gao, Guangjun Nie.
Visualization: Huaiqing Gao, Guangjun Nie.
Writing – original draft: Huaiqing Gao.
Project administration: Kun Yu.
Resources: Kun Yu.
Supervision: Kun Yu.
Writing – review & editing: Kun Yu.
Abbreviations:
- BMI
- body mass index
- CI
- confidence interval
- DALY
- disability-adjusted life year
- GBD
- Global Burden of Disease Study
- NHANES
- National Health and Nutrition Examination Survey
- NLR
- neutrophil-to-lymphocyte ratio
- OR
- odds ratio
- PD
- Parkinson disease
- PIR
- poverty-to-income ratio,
- UI
- = uncertain interval
The authors have no funding and conflicts of interest to declare.
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
Supplemental Digital Content is available in the online version of this article (http://dx.doi.org/10.1097/MD.0000000000049574).
How to cite this article: Gao H, Nie G, Yu K. The association between neutrophil-to-lymphocyte ratio and Parkinson disease, integrating data from global burden of disease study and NHANES databases. Medicine 2026;105:27(e49574).
Contributor Information
Huaiqing Gao, Email: gao.huaiqing@163.com.
Guangjun Nie, Email: nieguangjun2023@163.com.
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