Introduction

Psoriasis is a complex chronic autoimmune disease, closely associated with various factors including genetics, immunity, and environmental factors1,2. In recent years, mounting evidence suggests that obesity and inflammation play significant roles in the onset and progression of psoriasis3. Among them, abdominal obesity, characterized by fat accumulation primarily in the abdominal region, has been identified as one of the risk factors for psoriasis4,5,6. However, the exact relationship between abdominal obesity and psoriasis remains contentious, especially with insufficient evidence from large-scale population studies.

Psoriasis is a common chronic autoimmune skin disease characterized by red patches on the skin surface covered with silver or white scales7. As it is an autoimmune disease, the etiology of psoriasis is currently unclear. Studies suggest that abnormal activity of immune cells may lead to excessive proliferation of skin cells, which could be one of the causes of psoriasis8,9. Additionally, genetic factors may play a significant role in the occurrence of psoriasis, as a family history of the condition is a major risk factor10,11. Furthermore, environmental factors such as infections, stress, trauma, and medications can trigger psoriasis12. Recent research has also discovered that obesity may be an important risk factor for the occurrence and development of psoriasis. Dai et al. found similarities in the genetic background of obesity and psoriasis through a Mendelian randomization study13. A retrospective study by Czarnecka et al. found that being overweight or obese was a significant risk factor for the occurrence of psoriasis among 147 patients14. Moreover, a study using the NHANES database found a significantly higher prevalence of obesity among psoriasis patients15. However, further large-scale clinical studies are needed to confirm the relationship between abdominal obesity and the occurrence and development of psoriasis.

This study aims to explore the association between body roundness index (BRI) and the risk of psoriasis occurrence by analyzing data from the National Health and Nutrition Examination Survey (NHANES) database. NHANES, as a representative database for health surveys in the United States, provides rich demographic and health information, serving as an ideal data source for our research. Through this study, we hope to comprehensively understand the relationship between abdominal obesity and psoriasis, providing scientific evidence for the prevention and treatment of psoriasis.

Methods

Study population

NHANES is a large-scale cross-sectional survey conducted nationwide in the United States16. During the NHANES process, researchers used complex stratified sampling to obtain representative sample data nationwide, reflecting nutrition and health data for all residents of the United States, including adults and children17. In this study, we included all participants from five research cycles: 2003–2004, 2005–2006, 2009–2010, 2011–2012, and 2013–2014. These research cycles include health survey questionnaires related to psoriasis. According to the inclusion and exclusion criteria we established, we excluded participants under the age of 18 and over the age of 80. Subsequently, we excluded participants without BRI data, pregnant participants, and those without psoriasis status. Finally, we included 21,242 eligible participants. For detailed inclusion process, refer to Fig. 1.

Fig. 1
figure 1

Study population selection scheme.

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BRI measurement

In this study, we obtained body measurement indices directly from the NHANES database, including data such as body height, body weight, and waist circumference. NHANES conducts measurements of these body indices using standardized instruments and equipment by experienced measurers during their research. In this study, these body measurement indices exhibit high homogeneity. Similar to previous studies, we calculated BRI using the following formula18:

$$BRI = 364.2 - 365.5 \times \sqrt {1 - \left( {\frac{{\frac{WC}{{2\pi }}^{ } }}{0.5 \times BH}} \right)^{2} }$$

Diagnosis of psoriasis

Psoriasis was diagnosed based on affirmative responses to the inquiry, “Have you ever been told by a health care provider that you had psoriasis?” or “Have you ever been told by a doctor or other health care professional that you had psoriasis?”. Individuals who declined to respond or were unsure were omitted from the analysis19.

Covariates

In this study, we also collected baseline demographic and clinical data. All demographic information was obtained through questionnaires, including age, gender, and race. Height and weight measurements were conducted by experienced measurers using standardized instruments and equipment for each participant. We also calculated BMI, based on WHO standards, a BMI between 18.5 and 24.9 kg/m2 was considered normal weight, BMI over 25 kg/m2 and less than 29.9 kg/m2 was considered overweight, and BMI over 30 kg/m2 was considered obese. Educational level was likewise obtained through survey questionnaires. Additionally, we obtained information on smoking and alcohol consumption status of the patients. Relevant data including fasting blood glucose, blood lipid spectrum, and complete blood count were obtained after at least 8 h of fasting. The diagnosis of diabetes included both diagnosed diabetes and undiagnosed diabetes, where individuals had diabetes but were unaware of it. If a participant reported a history of diabetes, we considered them to have diabetes. Furthermore, if a participant met the following criteria, we still considered them to have diabetes: (1) HbA1c level of 6.5 or higher, (2) FPG level of 7.0 mmol/L or higher, (3) plasma glucose level of 11.1 mmol/L or higher during a 2-h oral glucose tolerance test (OGTT)20.

Statistical analysis

In this study, all data analyses were conducted according to the guidelines provided by the NHANES officials. We employed t-tests and chi-square tests to compare clinical and demographic characteristics between participants with and without psoriasis. Furthermore, we utilized weighted multivariable logistic regression analysis to explore the relationship between BRI and psoriasis occurrence. We established three models: Model 1 was unadjusted, Model 2 adjusted for age, gender, and race, and Model 3 adjusted for age, gender, race, education level, household income, smoking, alcohol consumption, and other relevant indicators. We also employed RCS curves to observe the relationship between BRI and psoriasis occurrence. Subgroup analyses were conducted based on gender, age, race, BMI, smoking, and alcohol consumption. In sensitivity analysis, as some researchers suggest that weighted analysis may yield different conclusions from the actual scenario, we further analyzed the odds of psoriasis occurrence using unweighted regression analysis for BRI. All data analysis was based on R, with statistical significance set at a two-tailed P-value < 0.05.

Results

Baseline characteristics

In this study, 21,242 participants were included, with 562 having psoriasis. The age distribution was 43.9% for 18–40 years, 41.6% for 40–60 years, and 13.3% for 60–80 years. Gender distribution was nearly equal. We compared the demographic and some clinical data between participants with psoriasis and those without psoriasis (Table 1). A comparison between participants with and without psoriasis revealed that those with psoriasis were significantly older, with a higher proportion of Caucasians, and a higher prevalence of obesity and overweight. Educational attainment and alcohol consumption were also significantly higher among participants with psoriasis. Detailed comparisons based on BRI are presented in Table S1.

Table 1 Baseline characteristic of study population.
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Associations between BRI and psoriasis odds

In this study, we divided all study participants into four equal groups based on the values of BRI. We utilized weighted multivariable logistic regression to explore the relationship between BRI and the occurrence of psoriasis. In the unadjusted model without controlling for confounding factors, we found that for every one-unit increase in BRI, the odds of psoriasis occurrence increased by 9%, with a 95% confidence interval (CI) ranging from 5 to 13%. After adjusting for age, gender, and race, we observed that for every one-unit increase in BRI, the odds of psoriasis occurrence increased by 7%, with a 95% CI ranging from 3 to 11%. Furthermore, after adjusting for age, gender, race, education level, household income, smoking status, and alcohol consumption, we found that for every one-unit increase in BRI, the odds of psoriasis occurrence increased by 9%, with a 95% CI ranging from 4 to 13%. Moreover, treating BRI as a categorical variable also confirmed the positive association between BRI and the odds of psoriasis occurrence. In model 2, adjusted for all confounding factors, compared to the BRI-Q1 group, the odds ratios for psoriasis occurrence in the BRI-Q2, BRI-Q3, and BRI-Q4 groups were 1.43 (95% CI: 0.96, 2.12), 1.69 (95% CI: 1.23, 2.30), and 1.95 (95% CI: 1.36, 2.78), respectively (Table 2). Additionally, the results of the RCS curve also demonstrated that as BRI increased, the odds of psoriasis occurrence increased. Furthermore, we found that before the median BRI of 4.86 in all study participants, the odds of psoriasis occurrence increased rapidly with increasing BRI. Conversely, after the BRI median of 4.86, the rate of increase in the odds of psoriasis occurrence slowed down with increasing BRI (Fig. 2).

Table 2 Analysis on the association between BRI and psoriasis using weighted multivariate logistic regression.
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Fig. 2
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RCS analysis of the relationship between BRI and psoriasis.

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Subgroup analysis

Furthermore, to further validate the reliability of our conclusions, we stratified participants by different demographic characteristics and conducted detailed subgroup analyses to explore the relationship between BRI and the occurrence of psoriasis in different populations. We found a significant positive correlation between BRI and the odds of psoriasis occurrence in participants of different ages, genders, and races. It is noteworthy that in obese patients, the relationship between BRI and the odds of psoriasis occurrence was more obvious than in normal-weight and overweight individuals. Additionally, we observed that the relationship between BRI and the occurrence of psoriasis was more pronounced in patients who drank alcohol compared to non-drinkers (Fig. 3). The effect of alcohol can be described as an 'effect modifier,' as it may alter the strength or direction of the association between abdominal obesity (as measured by BRI) and the odds of developing psoriasis. We also plotted RCS curves to illustrate the relationship between BRI and the occurrence of psoriasis in different populations. We found a significant positive correlation between BRI and the odds of psoriasis occurrence in various populations, with the odds of psoriasis increasing gradually with higher BRI values. It is worth noting that we found the impact of BRI on the odds of psoriasis occurrence might be more obvious in female patients compared to male patients (Fig. 4).

Fig. 3
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Subgroup logistic regression analysis of the relationship between BRI and psoriasis in individuals with different characteristics.

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Fig. 4
figure 4

Subgroup RCS analysis of the relationship between BRI and psoriasis in individuals with different characteristics, stratified by age (A), gender (B), smoking (C), and drinking (D).

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Sensitive analysis

We also employed unweighted logistic regression to analyze the relationship between BRI and the odds of psoriasis occurrence. Although weighted analyses can greatly extend the generalizability of results, recent studies have indicated that weighted analyses of NHANES data may sometimes yield inaccurate conclusions. To address this potential issue, we performed a sensitivity analysis using unweighted data to ensure the consistency and reliability of our findings. Therefore, in the sensitivity analysis of this study, we also used a unweighted approach to analyze the relationship between BRI and the odds of psoriasis occurrence. We found that after adjusting for psoriasis-related odds factors, for every one-unit increase in BRI, the odds of psoriasis occurrence increased by 8%, with a 95% confidence interval ranging from 4 to 12%. This result is consistent with the main conclusion drawn from the primary analysis. Furthermore, treating BRI as a categorical variable still yielded the conclusion that there is a positive correlation between BRI and the odds of psoriasis occurrence. Participants with higher BRI had a higher odds of psoriasis occurrence, further increasing the reliability of our study conclusions (Table 3).

Table 3 Sensitive Analysis on the Association between BRI and Psoriasis Using Unweighted Multivariate Logistic Regression.
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Discussion

In this study, we conducted a large-scale cross-sectional analysis using NHANES data to investigate the relationship between body roundness index, which reflects abdominal obesity, and psoriasis. We found that abdominal obesity may increase the odds of psoriasis, which could provide some assistance in the prevention and treatment of psoriasis in clinical practice.

Obesity is a global public health issue. With the improvement of economy worldwide, obesity has become an important risk factor for various health problems21. Obesity is closely associated with the occurrence of cardiovascular and cerebrovascular diseases22,23. Studies have shown that obesity, especially abdominal obesity, can increase the risk of overall mortality and various adverse outcomes24,25. Waist circumference is a traditional measure of abdominal obesity26. However, in recent years, more and more studies have suggested that a more reasonable and scientific approach should be used to measure abdominal obesity to reflect the body’s fat distribution. Body roundness index (BRI) is a new body measurement index discovered by researchers in recent years27,28,29. It measures abdominal obesity based on height and waist circumference30. The higher the BRI, the more severe the abdominal obesity, and the more prominent the body’s fat distribution in the abdomen. The body roundness index has been widely used in numerous studies and is an independent risk factor and effective predictor for many diseases31. In fact, in the NHANES database, many researchers have studied the relationship between BRI and the occurrence of different diseases. Some studies have shown that an increase in BRI is associated with an increased odds of urinary incontinence in women. By including 10,317 adult female participants from the NHANES database from 2005 to 2018, logistic regression analysis found that BRI is an independent risk factor for the occurrence of urinary incontinence in women. In addition, through ROC curve analysis, it was demonstrated that BRI has a certain predictive effect on female urinary incontinence32. Furthermore, other studies have shown a positive correlation between abdominal obesity and the risk of kidney stones. BRI can serve as a good predictive indicator for predicting kidney stones33. However, the relationship between abdominal obesity and psoriasis remains unclear to date, and whether BRI is positively correlated with psoriasis is still uncertain. Therefore, in this study, we also investigated the relationship between BRI and the occurrence of psoriasis by including participants from the NHANES database in a large-scale, multi-ethnic population.

The mechanisms by which obesity increases the risk of psoriasis occurrence are complex, with inflammation playing crucial roles in both conditions34. Obesity-related inflammation mediated by leptin has been demonstrated, as leptin induces the production of inflammatory mediators such as IL-6 and TNF-α35,36. Under the stimulation of inflammatory mediators like TNF-α and IL-1, leptin expression levels in adipose tissue increase. Therefore, in the presence of obesity-associated inflammation, chronic inflammatory stimuli in psoriasis may interact with leptin-mediated obesity-related inflammation, forming a loop that mutually influences inflammation promotion37. Studies have identified genes associated with both conditions, psoriasis patients carrying the rs9939609 allele of the FTO gene tend to have more severe disease progression and an increased risk of developing obesity38. High-fat diets are considered a major factor leading to obesity, with saturated fatty acids or polyunsaturated fatty acids being abundant in such diets. Saturated fatty acids in high-fat diets can promote T cell differentiation into Th1/Th17 cells by activating dendritic cells, thereby exacerbating psoriasis39.

Abdominal obesity may contribute to the occurrence of psoriasis through multiple mechanisms. Inflammation plays a crucial role in the occurrence and development of psoriasis, and there is a close association between abdominal obesity and inflammation. Fat cells in adipose tissue can secrete many bioactive substances, including various inflammatory mediators such as tumor necrosis factor-alpha, interleukin-6, and C-reactive protein40. These inflammatory factors can exacerbate the severity of psoriasis. Additionally, abdominal obesity can lead to infiltration of immune cells within adipose tissue, further exacerbating the inflammatory response41,42. In this study, we found a significant positive association between BRI and the odds of psoriasis. Our research included a total of 21,242 participants from the NHANES database. The population in our study is ethnically diverse, thus providing good representativeness nationwide. We observed that as BRI increased, the odds of psoriasis occurrence also increased. This effect was more pronounced before the median BRI of the entire population. After the median, the rate of increase in the odds of psoriasis with increasing BRI slowed down. Subgroup analyses conducted in different populations showed that our conclusions were highly representative. It is noteworthy that in the male population, before the median, there was an increasing trend in the odds of psoriasis occurrence with increasing BRI. However, after the median BRI, the increase in the odds of psoriasis occurrence with increasing BRI slowed down, and even showed a certain downward trend. This may suggest that the influence of abdominal obesity on the odds of psoriasis occurrence is more obvious in females. In our study, all analyses were weighted analyses conducted according to the complex stratified sampling design in the NHANES database. It is worth noting that some researchers believe that weighted analysis may affect the conclusions of the study, leading to discrepancies between the conclusions and the actual situation. Therefore, we also conducted a sensitivity analysis by analyzing all participants included in this study in an unweighted manner. We found that weighted and unweighted analyses did not affect the conclusions of this study, there is a significant positive correlation between BRI, a measure of abdominal obesity, and the odds of psoriasis occurrence.

This study has several strengths that need to be noted. Firstly, all relevant data of participants were directly obtained from the NHANES database. Due to the sampling design adopted by the NHANES database, this study is representative. Secondly, we included a large number of participants, thus providing robust data support. Thirdly, in this study, measurements of height and weight were conducted by experienced personnel using standardized equipment, ensuring strong consistency. However, there are several limitations in this study that need to be addressed. Firstly, this study is a cross-sectional study, therefore, it cannot establish a causal relationship between BRI and psoriasis. Secondly, since the outcome measure of psoriasis in this study was assessed through questionnaire surveys, there may be some reporting bias. Thirdly, although we have adjusted for potential confounding factors that may affect the occurrence of psoriasis as much as possible, psoriasis is a complex chronic autoimmune disease, and there may be many factors influencing it. We cannot exclude all confounding factors.

Conclusion

Our findings demonstrate that higher BRI, an indicator of abdominal obesity, is consistently linked to an increased odds of psoriasis across diverse demographic groups. The use of multivariable weighted logistic regression, supported by sensitivity and subgroup analyses, reinforces the reliability and generalizability of these results. These findings suggest that BRI may serve as an important marker for identifying individuals at higher risk of psoriasis, offering potential insights for prevention and management strategies targeting abdominal obesity.