樱花视频

Skip to main content
Download PDF
  • Research
  • Published:

Association of sedentary behaviour with gout and the interaction effect of hyperuricemia: a cross-sectional study from 2007 to 2018

樱花视频 volume听24, Article听number:听3428 (2024) Cite this article

Abstract

Background

The increasing prevalence of sedentary lifestyles has raised concerns about its health impacts. This study sought to explore the association between sedentary behaviour and gout, a condition historically linked with affluent lifestyles but now increasingly prevalent in the general population.

Methods

Utilizing data from the National Health and Nutrition Examination Survey database, this cross-sectional study analysed 34,526 participants from 2007 to 2018. The study focused on identifying any potential relationships between sedentary behaviour and the incidence of gout while adjusting for various confounders.

Results

The study found a significant increase in the prevalence of gout from 2017 to 2018 and identified a reversed L-shaped relationship between sedentary behaviour and gout (OR鈥�=鈥�1.03; 95%听CI 1.00, 1.06; P鈥�=鈥�0.0198), especially among individuals without hyperuricemia. Body Mass Index (BMI) may act as a key mediator in the relationship between sedentary behaviour and gout. In those with hyperuricemia, more than 12听h per day of sedentary behaviour substantially increased the prevalence of gout.

Conclusion

Prolonged sedentary behaviour emerged as an independent risk factor for gout. This association was particularly pronounced in individuals without hyperuricemia, suggesting the need for lifestyle modifications in this group. However, further research using prospective cohort studies is necessary to establish causality.

Peer Review reports

Introduction

Gout is a common inflammatory joint disease characterized by elevated serum urate levels, leading to the deposition of monosodium urate (MSU) crystals in joints and non-articular structures (such as bursae, ligaments, and tendons). It presents with intense pain and swelling in the joints, particularly affecting the lower limbs [1]. Globally, the burden of gout is substantial and escalating. The adult prevalence of gout worldwide ranges between 0.68% and 3.90% [1]. As of 2017, the age-standardized prevalence per 100,000 was 790.90 for men and 253.49 for women, with both the prevalence and disability-adjusted life years (DALYs) showing an annual increase [2].

Hyperuricemia, defined as serum urate concentrations exceeding the saturation threshold at physiological temperatures and pH levels, is the most crucial risk factor and primary cause of gout. There is a recognized proportional relationship between higher serum urate levels and the prevalence of gout [3]. However, studies reveal that only a minority of individuals with hyperuricemia ultimately develop gout, with the majority manifesting as asymptomatic hyperuricemia [4]. This indicates that additional risk factors are likely required to precipitate gout onset on top of hyperuricemia. Current understanding implicates poor lifestyle choices as contributing factors to various rheumatic and musculoskeletal diseases [5]. Gout, in particular, is associated with a high-purine diet, sleep disorders, obesity, and excessive alcohol consumption [6,7,8,9]. Among these, the direct correlation between sedentary behaviour and gout has received limited research focus.

Sedentary behaviour is defined as any waking behaviour characterized by an energy expenditure of 鈮も��1.5 METs while sitting, reclining, or lying, encompassing activities like sitting, watching television, and lying down [10]. With the advancement of modern technology, sedentary behaviour has become a significant component of contemporary lifestyle [11]. In the United States, adult sedentary time increased from 5.5听h per day in 2007 to 6.4听h in 2016 [12], accounting for 55% of waking hours. Consequently, the impact of sedentary behaviour on public health is becoming an increasingly researched topic.

Current research on the relationship between sedentary behaviour and gout is limited and remains inconclusive. A study examining the association between sedentary behaviour and the risk of 45 common non-communicable diseases found that participants reporting more than 6听h of sedentary time had a higher risk of gout than those sitting for less than鈥�2听h per day [13]. Moreover, several studies exploring the link between sedentary behaviour and hyperuricemia consistently indicate that sedentary behaviour increases the risk of hyperuricemia [14,15,16]. Sedentary behaviour is a significant risk factor for hyperuricemia, but its direct connection to gout is not well-defined. Therefore, the exact nature of the relationship between sedentary behaviour and gout remains unclear and warrants further investigation.

With the escalating prevalence of sedentary behaviour in populations and the rising incidence of gout [1, 12], there is a notable gap in health recommendations concerning sedentary behaviour for gout prevention. Furthermore, no studies have independently and systematically investigated the association between sedentary behaviour and gout, nor the role of hyperuricemia in this relationship. This study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018 to systematically examine the correlation between sedentary behaviour and gout in the American population. We hypothesized that prolonged sedentary behaviour is associated with an increased incidence of gout. It aims to investigate the association between sedentary behaviour and gout. These findings will contribute to shaping recommendations for preventing gout related to sedentary behaviour in the general population.

Methods

Study population

This cross-sectional study utilized data from NHANES, a nationwide survey of the American population, to collect information on nutrition and health determinants of all non-institutionalized civilians. Employing a complex stratified, multi-stage probability cluster sampling design, the survey is representative of the entire U.S. population through sample weighting. The NHANES study protocol adhered to the ethical standards of the 1975 Helsinki Declaration. Written informed consent was obtained from all survey participants. Participants underwent standardized interviews, health examinations, and laboratory tests under professional medical supervision at Mobile Examination Centers (MECs), providing comprehensive assessments of their health and nutritional status with detailed data collection. This study selected data from six NHANES survey cycles between 2007 and 2018 (i.e., 2007鈥�2008, 2009鈥�2010, 2011鈥�2012, 2013鈥�2014, 2015鈥�2016, and 2017鈥�2018) to investigate the association between sedentary behaviour and gout occurrence, as these cycles included complete variables for gout occurrence and sedentary behaviour. In the survey, we excluded 25,072 participants under 20 years old, 41 without Gout data, and 203 without sedentary activity data from a qualified population of 59,842. The study thus comprised 34,526 individuals. The detailed sample selection process, along with inclusion and exclusion criteria is shown in Fig.听1.

Fig. 1
figure 1

Flowchart of the study population. The flowchart demonstrates the criteria as well as the detailed process for inclusion and exclusion of the study population in this study

Full size image

Exposure variable

Sedentary activity, the exposure variable in this study, was based on self-reported data from the NHANES physical activity questionnaire. Participants were asked, 鈥淗ow much time do you usually spend sitting on a typical day?鈥� The questionnaire also defined sedentary behaviour as time spent at school or home, traveling between places, including sitting at a desk, in a car or bus, reading, playing cards, watching TV, or using a computer, but not including sleeping hours. Referring to previous epidemiological studies on sedentary behaviour [16], sedentary time was divided into four categories: <4听h/day, 4鈥�6听h/day, 6鈥�8听h/day, and 鈮モ��8听h/day.

Outcome variable

Gout, the outcome variable in this study, was assessed based on a self-reported diagnosis consistent with published literature methods [17, 18]. The determination of gout was based on participants鈥� responses to the question, 鈥淗as a doctor or other health professional ever told you that you had gout?鈥� during the NHANES home interviews. Participants affirming this question were categorized as adults with gout and the rest without gout.

Covariates

The selection of covariates in this study was based on results from previous cross-sectional studies on gout, including gender, age, race, education level, income-to-poverty ratio, BMI, diabetes, hypertension, chronic kidney disease, drinking status, smoking status, triglycerides, high-density lipoprotein, low-density lipoprotein, total cholesterol, serum creatinine, serum uric acid and physical activity. Gender, age, and race were based on self-reported demographic information in the questionnaire, with age further categorized into four subgroups (20鈥�39, 40鈥�59, 60鈥�79, 鈮モ��80) [17] and race into Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Other Race. Educational levels were categorized as High school (<鈥�9th grade), High school (9-11th grade), High school graduate/GED, Some college/AA degree, and College graduate or above. Based on BMI, categories were defined as Underweight (<鈥�20), Normal weight (20-24.9), Overweight (25-29.9), and Obese (鈮モ��30) [19]. Diabetes and hypertension statuses were determined by participants鈥� responses to 鈥淗ave you ever been told by a doctor or health professional that you have diabetes/hypertension?鈥� Smoking history (yes/no) depended on whether participants had smoked more than 100 cigarettes in their lifetime [20], and drinking status (yes/no) was based on self-reported alcohol consumption over the past 12 months from the alcohol questionnaire [21]. Chronic kidney disease (yes/no) was defined as eGFR鈥�<鈥�60 mL/min/1.73听m^2 and/or albuminuria [22], with estimated glomerular filtration rate calculated from participants鈥� serum creatinine levels using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula [23]. Albuminuria was considered urinary albumin-to-creatinine ratio (ACR)鈥�>鈥�30听mg/g [22]. Laboratory covariates included triglycerides, high-density lipoprotein, low-density lipoprotein, total cholesterol, serum creatinine, and serum uric acid. Hyperuricemia assessment was based on measured blood uric acid levels, defined as serum uric acid levels鈥�>鈥�7.0听mg/dL for men and >鈥�5.7听mg/dL for women [17]. Blood uric acid levels were determined using patients鈥� refrigerated serum, employing a timed endpoint method. Uric acid is oxidized by uricase to produce urea and hydrogen peroxide. The peroxide produced reacts with peroxidase in the presence of 4-aminophenazone to yield a measurable coloured product. Detailed procedures and quality control information are available at . Physical activity is a key confounding factor in studies examining the relationship between sedentary behaviour and hyperuricemia [14,15,16]. Vigorous and moderate physical activity was assessed using self-reported data from the Global Physical Activity Questionnaire (GPAQ), which includes items covering different domains of physical activity such as transportation, occupation, and leisure-time moderate-to-vigorous physical activity (MVPA), as well as sedentary behaviour. The total PA level was calculated by summing the time participants reported engaging in activities across these domains, measured in h per week.

Statistical analysis

All statistical analyses were conducted following the Centers for Disease Control and Prevention (CDC) guidelines, using appropriate NHANES sampling weights and accounting for the complex multi-stage cluster survey. A total sample 2-year Mobile Examination Centers (MEC) weight was employed to calculate the US non-institutionalized population. Continuous variables were summarized as means with standard errors (SE), and categorical parameters as proportions.

First, the prevalence trend of gout across the six cycles was evaluated using the chi-square test. Weighted student t-tests (for continuous variables) or weighted chi-square tests (for categorical variables) were used to assess differences between participants with and without gout. To assess the independent association of sedentary behaviour with gout, this study specifically considered BMI, physical activity, and serum urate as key confounders, adjusting for them in the various models: Model 1 (Unadjusted), Model 2 (Adjusted for gender, age, and race), Model 3 (Adjusted for all covariates except BMI, serum urate, and physical activity), Model 4 (Added BMI to Model 3 as covariate), Model 5 (Added serum urate to Model 3 as covariate), Model 6 (Added vigorous and moderate physical activity to Model 3 as covariates), Model 7 (Fully adjusted for all covariates, combining BMI, serum urate, vigorous and moderate physical activity).

In addition, sensitivity analyses were conducted by stratifying sedentary behavior into four categories (<鈥�4听h/day, 4鈥�6听h/day, 6鈥�8听h/day, 鈮モ��8听h/day). Stratified multivariate logistic regression models were used to explore the association between sedentary behavior and gout across subgroups, including gender (male/female), age (20鈥�39, 40鈥�59, 60鈥�79, 鈮モ��80), BMI (Underweight, Normal weight, Overweight, Obese), race (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Other Race), hypertension (yes/no), diabetes (yes/no), chronic kidney disease (yes/no),听hyperuricemia (yes/no). These factors were also evaluated as potential effect modifiers.

Based on covariates in Model 7, a generalized additive model and smooth curve fitting were applied to assess potential nonlinear associations between sedentary behaviour and gout. A two-piecewise linear regression model was employed to evaluate threshold effects, with the turning point determined using a recursive algorithm. A log-likelihood ratio test compared one-line and two-piecewise linear regression models.

Finally, the same analysis procedure was replicated for subgroups stratified by hyperuricemia to validate the consistency of results. Missing values were imputed using the median for continuous variables or the mode for categorical variables based on existing cases.

All analyses were performed using R 3.4.3 (, The R Foundation) and EmpowerStats 2.0 (; X&Y Solutions, Inc., Boston, MA), with two-tailed P鈥�<鈥�0.05 considered statistically significant.

Results

Baseline characteristics

In this study, a total of 34,536 participants from the NHANES database, spanning six cycles between 2007 and 2018, were ultimately included. By calculating the weighted prevalence of gout across different cycles, Table听1 indicates a significant change in the prevalence of gout in the United States from 2007 to 2018 (3.87% in 2007鈥�2008 to 5.12% in 2017鈥�2018, P鈥�=鈥�0.0004).

Table 1 The prevalence of gout among adults aged above 20 years in United States adults from 2007 to 2018
Full size table

After weighted calculations, the average age of the included participants was 47.46鈥壜扁��17.01 years, with 48.12% being male and 51.88% female. The majority (65.89%) were non-Hispanic White, followed by non-Hispanic Black, Mexican Americans, other ethnicities, and other Hispanic individuals. Among the participants, 4.78% were diagnosed with gout, 20.28% had hyperuricemia, and 79.72% did not. The overall average duration of sedentary behaviour was 6.19鈥壜扁��3.39听h/day (Table听2).

Table 2 Weighted characteristics of adults aged above 20 years with or without gout in United States among 2007 to 2018
Full size table

Furthermore, baseline data comparison between the two groups (adults with or without gout) revealed that participants with gout had higher ages, triglycerides, blood uric acid levels, and duration of sedentary behavior than those without gout. In contrast, gout participants had lower LDL, HDL, and total cholesterol levels. Additionally, significant statistical differences were observed between the two groups in terms of gender, ethnicity, BMI, smoking status, hypertension, diabetes, chronic kidney disease, and hyperuricemia. Therefore, in this study, adults with gout were more likely to be older, male, non-Hispanic White, obese, smokers, with hypertension, diabetes, chronic kidney disease, and hyperuricemia. They had lower LDL, HDL, and total cholesterol; higher triglyceride and blood uric acid levels, had less time in physical activity and spent more time in prolonged sedentary behaviour each day. (Table听2)

The association of prolonged sedentary behaviour and gout

Our study reaffirmed the association between prolonged sedentary behaviour and the prevalence of gout, although the strength of this relationship varied depending on covariate adjustments. In the crude and partially adjusted models, prolonged sedentary behaviour was positively associated with gout prevalence (P鈥�<鈥�0.0001). In Model 3, which adjusted for major demographic and clinical covariates (excluding BMI, serum uric acid, and physical activity), the association remained statistically significant (OR鈥�=鈥�1.03; 95%听CI 1.00, 1.06; P鈥�=鈥�0.0198), with each additional hour of sedentary behaviour increasing the prevalence of gout by 3%. However, the inclusion of BMI in Model 4 attenuated this association, rendering it statistically non-significant (P鈥�=鈥�0.1037). This suggests that BMI may act as a key mediator in the relationship between sedentary behaviour and gout.

The addition of serum urate (Model 5) and physical activity (Model 6) to the adjustments did not substantially alter the association, indicating that these factors may exert less influence in this specific context. In Model 7, which included all covariates, the association between sedentary behaviour and gout remained non-significant (P鈥�=鈥�0.0840), further emphasizing BMI鈥檚 mediating role.

Sensitivity analyses using a categorical classification of sedentary behaviour (<鈥�4听h/day, 4鈥�6听h/day, 6鈥�8听h/day, 鈮モ��8听h/day) provided additional insights. Severe sedentary behaviour (鈮モ��8听h/day) was significantly associated with an increased prevalence of gout in Model 2 (P鈥�=鈥�0.0004). However, this association also became non-significant in fully adjusted models with more covariates (Table听3).

Table 3 Multivariate logistic regression models of the association between gout and sedentary behaviour
Full size table

Subgroup analysis

To evaluate whether the association between sedentary behaviour and gout is consistent across different populations, this study conducted subgroup analyses and interaction tests stratified by gender, age, ethnicity, BMI, diabetes, hypertension, chronic kidney disease, and hyperuricemia听(Table 4). The subgroup analyses and interaction tests revealed that, except for hypertension and hyperuricemia, no other factors showed significant interaction with the relationship between sedentary behaviour and gout, indicating a high consistency of the study鈥檚 conclusions across different populations. The interaction test also revealed a significant interaction between hyperuricemia and the relationship between sedentary behaviour and gout (P for interaction鈥�=鈥�0.0152), suggesting that the association between sedentary behaviour and gout varies significantly between individuals with and without hyperuricemia. In summary, the association between sedentary behaviour and gout shows a dependency on hyperuricemia status, which is more applicable to individuals without hyperuricemia.

Table 4 Subgroup analysis of the association between gout and sedentary behaviour
Full size table

To further investigate the association between prolonged sedentary behaviour and gout, generalized additive models and smooth curve fitting were utilized, revealing a reversed L-shaped relationship between sedentary behaviour and gout (Fig.听2). Subsequently, a two-piecewise linear regression model was applied to fit each interval and perform a threshold effect analysis (Table听5). The study found a nonlinear relationship between sedentary behaviour and gout, with a turning point at 11听h/day. When sedentary behaviour was less than 11听h/day, there was no significant association with an increased prevalence of gout (OR鈥�=鈥�0.99; 95%CI 0.96, 1.03; P鈥�=鈥�0.7049). However, when sedentary behaviour was equal to or greater than 11听h/day, each additional hour of sedentary behaviour was associated with a 17% increase in the prevalence of gout (OR鈥�=鈥�1.17; 95%CI 1.07, 1.29; P鈥�=鈥�0.0010).

Table 5 Threshold effect analysis of sedentary behaviour on gout using the linear regression model
Full size table
Fig. 2
figure 2

The dose-response relationship between sedentary behaviour and the prevalence of gout. This graph demonstrates the change in gout prevalence as sedentary behaviour increases. Relationship between sedentary behaviour and the risk of gout. The red line represents the estimated association between sedentary behaviour (h/day) and the odds ratio (OR) of gout. The blue dashed lines indicate the 95% confidence interval (CI) for the estimated OR

Full size image

After stratifying the analysis by hyperuricemia, it was found that in the population with hyperuricemia, there was also a reversed L-shaped relationship between sedentary behaviour and the prevalence of gout (Fig.听3). The threshold effect analysis identified the turning point at 12听h/day. This suggested that in the hyperuricemia population when sedentary behaviour was greater than or equal to 12听h/day, each additional hour of sedentary time was associated with a 33% increase in the prevalence of gout (OR鈥�=鈥�1.33; 95%听CI 1.12, 1.58; P鈥�=鈥�0.0013). Conversely, when sedentary behaviour was less than 12听h/day, the increase was associated with a decrease in the prevalence of gout, but this association was not statistically significant (OR鈥�=鈥�0.97; 95%听CI 0.92, 1.02; P鈥�=鈥�0.1831). In the non-hyperuricemia population, the results of a log-likelihood ratio test indicated that the relationship between sedentary behaviour and the risk of gout was not segmented (P鈥�=鈥�0.130), and a significant positive correlation existed between the two groups (OR鈥�=鈥�1.04; 95%听CI 1.01, 1.08; P鈥�=鈥�0.0171).

Fig. 3
figure 3

The dose-response relationship between sedentary behaviour and the prevalence of gout in adults with or without hyperuricemia. The graph demonstrates how the relationship between sedentary behaviour and the prevalence of gout varies among people with or without hyperuricemia, with such an association showing a clear inverse L-shape among those with hyperuricemia

Full size image

Discussion

This study aimed to investigate the relationship between sedentary behaviour and gout in the American population. We found a significant increase in the prevalence of gout during 2017鈥�2018, consistent with the previous study [24]. The analysis of 34,526 participants from 2007 to 2018 revealed the association between sedentary behaviour and gout. The interaction effect of hyperuricemia on this association was also noted. Prolonged sedentary behaviour was significantly and independently associated with a higher prevalence of gout, especially in individuals without hyperuricemia. For patients with hyperuricemia, the prevalence of gout significantly escalates when sedentary behaviour exceeds 12听h per day, showing a reversed L-shaped relationship. These findings support recommendations to prevent gout related to sedentary behaviour, particularly for those with asymptomatic hyperuricemia.

While many studies have linked high-fat and high-sugar diets to gout, few have examined sedentary behaviour directly. A UK Biobank study found that participants reporting鈥�>鈥�6听h/day of sedentary time had a higher risk of gout compared to those with 鈮も��2听h/day [13]. Another study using Mendelian randomization did not find a genetic causal relationship between sedentary behaviour and gout, though it identified accelerometer-assessed physical activity as a risk factor [25]. Our study validated the link between sedentary behaviour and gout using large-scale cross-sectional data, identifying a positive correlation, and highlighting the role of hyperuricemia in this relationship, particularly in individuals with asymptomatic hyperuricemia.

Sedentary behaviour promotes gout by affecting metabolic processes

While the mechanisms behind this relationship are not fully elucidated, several plausible explanations exist. Sedentary behaviour may promote gout through the metabolic processes [26]. Sedentary behaviour has been associated with increased risks of metabolic diseases, including type 2 diabetes [27], hypertension [28], dyslipidaemia [29], obesity [30] and metabolic syndrome [31]. One potential mechanism involves the body鈥檚 and skeletal muscle鈥檚 ability to metabolize glucose. Prolonged sedentary behaviour reduces glucose uptake, increases lipid storage, and ultimately decreases insulin sensitivity, which can lead to metabolic syndrome [32, 33]. Additionally, sedentary behaviour may decrease muscle fibre content [34,35,36] and mitochondrial oxidative capacity [37], further contributing to obesity and related metabolic disturbances.

Our study found that when BMI was added to the model, the association between sedentary behaviour and gout lost statistical significance (P鈥�=鈥�0.1037). This suggests that BMI acts as an important confounder and highlights metabolic dysregulation as a critical pathway linking sedentary behaviour to gout. Previous studies have consistently shown that metabolic syndrome significantly elevates gout risk, with individuals diagnosed with metabolic syndrome having a substantially higher likelihood of developing gout [38]. These findings reinforce the role of metabolic health as a mediating factor in the sedentary behaviour鈥揼out relationship.

Sedentary behaviour enhances the risk of gout by facilitating systemic inflammation

Sedentary behaviour may increase gout risk by promoting systemic inflammation, beyond its metabolic effects. This study found a significant association between sedentary behaviour and gout even after adjusting for hyperuricemia and metabolic factors, suggesting alternative pathways. Sedentary behaviour has been shown to elevate pro-inflammatory cytokines such as IL-6, C-reactive protein, and TNF-伪, and to reduce anti-inflammatory markers like IL-RA [39,40,41]. In skeletal muscle and adipose tissue, sedentary behaviour enhances inflammatory signalling via proteins like JNK and TLR4, and promotes macrophage infiltration [42, 43].

In gout pathogenesis, inflammatory cytokines, particularly IL-1尾, TNF-伪, and IL-6, mediate acute inflammatory responses triggered by MSU crystals. Sedentary behaviour may exacerbate this process by increasing cytokine levels and upregulating pro-inflammatory pathways, potentially enhancing the body鈥檚 recognition of MSU crystals and susceptibility to gout. These findings highlight inflammation as a critical link between sedentary behaviour and gout risk [44,45,46].

Sedentary behaviour contributes to gout by affecting the intra-articular microenvironment

Sedentary behaviour may also promote gout by altering the joint microenvironment. As shown in Table听5听and Fig.听3, individuals with hyperuricemia exhibit a higher baseline gout risk, which increases markedly when sedentary behaviour exceeds 11听h per day. This suggests that sedentary behaviour, particularly under conditions of hyperuricemia, more significantly contributes to the transition from asymptomatic hyperuricemia to the onset of gout. This novel finding implies that sedentary behaviour might play a critical role in this transition, warranting further investigation. Sodium urate crystal deposition, essential for gout development, is influenced by joint microenvironment factors such as temperature, pH, mechanical stress, and tissue composition [47, 48]. Sedentary behaviour could lower joint temperature by reducing blood flow, shear stress, and metabolic heat production in the lower limbs through prolonged sitting, which impairs vascular function and decreases skeletal muscle activity [32, 49, 50]. A reduction in joint temperature diminishes the solubility of sodium urate, promoting crystal deposition.

Additionally, sedentary behaviour may contribute to joint injury, a known factor in gout development [47]. Reduced joint movement associated with prolonged sitting can impair synovial fluid distribution, reducing cartilage nourishment and lubrication. This may accelerate cartilage degeneration, compromise joint integrity, and diminish protective lubricin and hyaluronic acid levels [51,52,53,54]. Evidence linking sedentary behaviour to osteoarthritis further supports this mechanism, as prolonged inactivity has been associated with poorer joint function and an increased risk of degenerative changes [55,56,57]. These processes collectively create a pro-inflammatory and injury-prone joint environment, facilitating the onset and progression of gout.

The dual role of sedentary behaviour and physical activity in gout

In this study, a specific inverse L-shaped curve was observed between sedentary behaviour and gout risk, particularly among individuals with hyperuricemia. This observation aligns with our subgroup analysis, which found that hyperuricemia modifies the relationship between sedentary behaviour and gout. In people with hyperuricemia, prolonged sedentary behaviour was significantly positively associated with gout, while mild sedentary behaviour seemed to show a slight protective effect. One plausible explanation is that sedentary behaviour may reflect reduced PA levels. However, when PA was included in our model, the association between sedentary behaviour and gout remained robust, suggesting that the impact of sedentary behaviour extends beyond the mere lack of PA.

This finding emphasizes the independent effect of sedentary behaviour. While PA is generally considered beneficial for reducing hyperuricemia risk, its direct association with gout remains complex. Epidemiological studies have failed to establish a consistently negative correlation between PA and gout [13, 58], and some have even suggested a potential positive association between high PA levels and gout risk due to factors like joint injury or inflammation triggered by intense exercise [25]. Our results indicate that mild sedentary behaviour might substitute for high-intensity exercise, thereby mitigating some potential harms and appearing slightly protective in individuals with hyperuricemia. Thus, while sedentary behaviour and PA are intertwined, our findings underscore that sedentary behaviour鈥檚 influence on gout operates through mechanisms beyond PA deficiency, such as metabolic dysfunction, systemic inflammation, or joint-specific microenvironmental changes. This highlights the need to address sedentary behaviour directly in gout prevention strategies, regardless of PA levels.

This study possesses specific strengths. First, it features a large sample size and spans a considerable time range, lending it a degree of representativeness. Additionally, many confounding factors were adjusted in the study to arrive at more reliable conclusions, including numerous factors closely associated with gout as demonstrated in other studies. However, there are also limitations to this study. As a cross-sectional study, it cannot definitively establish causal relationships between exposure factors and outcome variables, but only their correlation. Patients with gout may also have increased sedentary behaviour due to joint pain, which is a condition considered in the study. However, our discussion of the mechanisms by which sedentary behaviour leads to gout suggests that the causal relationship constructed in this study is plausible. Furthermore, since the data was obtained from a public database, the cross-sectional study design could not be altered. More accurate conclusions would require further exploration using prospective cohort studies. Additionally, although many covariates have been included in the study, the influence of other confounding factors cannot be entirely ruled out, and the conclusions may be affected by these factors and become less precise. Lastly, the NHANES data used in this study is from the US population, so the conclusions need to be further validated in populations from more countries.

There are areas for improvement in this study.听Verification from prospective cohort studies is needed to ascertain whether sedentary behaviour increases the risk of gout. Regarding the exposure and outcome variables in the database, since the information on gout and sedentary behaviour of participants was obtained through questionnaires and self-reports, which are less accurate than objective indicators, subsequent prospective cohort studies could consider using accelerometers to further measure sedentary behaviour time, reducing subjective errors. Additionally, in the database used for this study, the data on sedentary behaviour only captured total duration, without distinguishing between leisurely and work-related sedentary behaviour. Leisure- and work-related sedentary behaviours might differ in their impact on participants鈥� psychological states and sitting postures, which could be a point of deeper exploration in future studies.

Conclusion

This study found that prolonged sedentary behaviour is independently associated with an increased prevalence of gout, particularly among individuals without hyperuricemia. For those with hyperuricemia, avoiding sedentary behaviour exceeding 12听h per day may serve as a health recommendation for the prevention of gout. However, further research is required to validate these conclusions.

Data availability

In-depth details regarding the study鈥檚 population and methodologies are accessible on the NHANES website (). The National Health and Nutrition Examination Survey (NHANES), an initiative by the National Center for Disease Control (CDC) in collaboration with the Center for Preventive National Health Statistics, is meticulously designed to evaluate the health and nutritional conditions of adults and children across the United States.

Abbreviations

NHANES:

National Health and Nutrition Examination Survey

MSU:

Monosodium Urate

DALYs:

Disability-Adjusted Life Years

MECs:

Mobile Examination Centers

CKD-EPI:

Chronic Kidney Disease Epidemiology Collaboration

ACR:

Albumin-to-Creatinine Ratio

SE:

Standard Errors

BMI:

Body Mass Index

CKD:

Chronic Kidney Disease

HUA:

Hyperuricemia

LDL:

Low-Density Lipoprotein

HDL:

High-Density Lipoprotein

MetS:

Metabolic Syndrome

MPA:

Moderate Physical Activity

VPA:

Vigorous Physical Activity

OR:

Odds Ratio

CI:

Confidence Interval

IL-6:

Interleukin 6

罢狈贵-伪:

Tumour Necrosis Factor Alpha

IL-RA:

Interleukin Receptor Alpha

JNK:

C-Jun Kinase enzyme

NF-kB:

Nuclear Factorkappa-B

TLR4:

Toll-like receptor 4

NLRP3:

NLR Family Pyrin Domain Containing 3

References

  1. Dalbeth N, Gosling AL, Gaffo A, Abhishek A. Gout. Lancet. 2021;397(10287):1843鈥�55.

    听 CAS听 听 听

  2. Xia Y, Wu Q, Wang H, Zhang S, Jiang Y, Gong T, Xu X, Chang Q, Niu K, Zhao Y. Global, regional and national burden of gout, 1990鈥�2017: a systematic analysis of the global burden of Disease Study. Rheumatology (Oxford). 2020;59(7):1529鈥�38.

    听 CAS听 听 听

  3. Campion EW, Glynn RJ, DeLabry LO. Asymptomatic hyperuricemia. Risks and consequences in the normative aging study. Am J Med. 1987;82(3):421鈥�6.

    听 CAS听 听 听

  4. Dalbeth N, Phipps-Green A, Frampton C, Neogi T, Taylor WJ, Merriman TR. Relationship between serum urate concentration and clinically evident incident gout: an individual participant data analysis. Ann Rheum Dis. 2018;77(7):1048鈥�52. .

  5. Gwinnutt JM, Wieczorek M, Balanescu A, Bischoff-Ferrari HA, Boonen A, Cavalli G, de Souza S, de Thurah A, Dorner TE, Moe RH, et al. 2021 EULAR recommendations regarding lifestyle behaviours and work participation to prevent progression of rheumatic and musculoskeletal diseases. Ann Rheum Dis. 2023;82(1):48鈥�56.

    听 听 听

  6. FitzGerald JD, Dalbeth N, Mikuls T, Brignardello-Petersen R, Guyatt G, Abeles AM, Gelber AC, Harrold LR, Khanna D, King C, et al. 2020 American College of Rheumatology Guideline for the management of gout. Arthritis Care Res (Hoboken). 2020;72(6):744鈥�60.

    听 听 听

  7. Choi HK, Curhan G. Gout: epidemiology and lifestyle choices. Curr Opin Rheumatol. 2005;17(3):341鈥�5.

    听 听

  8. Yokose C, McCormick N, Choi HK. Dietary and lifestyle-centered Approach in gout care and Prevention. Curr Rheumatol Rep. 2021;23(7):51.

    听 CAS听 听 听 听

  9. New-Tolley J, Reynolds AC, Appleton SL, Gill TK, Lester S, Adams RJ, Hill CL. Sleep disorders and gout in Australian adults. 樱花视频 Rheumatol. 2021;5(1):30.

    听 听 听 听

  10. Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, Chastin SFM, Altenburg TM, Chinapaw MJM. Sedentary Behavior Research Network (SBRN) - terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act. 2017;14(1):75.

    听 听 听 听

  11. Henson J, De Craemer M, Yates T. Sedentary behaviour and disease risk. 樱花视频. 2023;23(1):2048.

    听 听 听 听

  12. Yang L, Cao C, Kantor ED, Nguyen LH, Zheng X, Park Y, Giovannucci EL, Matthews CE, Colditz GA, Cao Y. Trends in Sedentary Behavior among the US Population, 2001鈥�2016. JAMA. 2019;321(16):1587鈥�97.

    听 听 听 听

  13. Cao Z, Xu C, Zhang P, Wang Y. Associations of sedentary time and physical activity with adverse health conditions: outcome-wide analyses using isotemporal substitution model. EClinicalMedicine. 2022;48:101424.

    听 听 听 听

  14. Hong R, Huang J, Xu C, Zhang X, Mi F, Xu F, Wang Y, Feng Y, Yin J. Association of Sedentary Behavior and Physical Activity with Hyperuricemia and Sex differences: results from the China multi-ethnic cohort study. J Rheumatol. 2022;49(5):513鈥�22.

    听 听 听

  15. Park DY, Kim YS, Ryu SH, Jin YS. The association between sedentary behavior, physical activity and hyperuricemia. Vasc Health Risk Manag. 2019;15:291鈥�9.

    听 CAS听 听 听 听

  16. Dong X, Li Y, Zhang L, Liu X, Tu R, Wang Y, Li R, Li L, Hou J, Mao Z, et al. Independent and interactive effect of sitting time and physical activity on prevalence of hyperuricemia: the Henan Rural Cohort Study. Arthritis Res Ther. 2021;23(1):7.

    听 CAS听 听 听 听

  17. Chen-Xu M, Yokose C, Rai SK, Pillinger MH, Choi HK. Contemporary prevalence of gout and Hyperuricemia in the United States and Decadal trends: the National Health and Nutrition Examination Survey, 2007鈥�2016. Arthritis Rheumatol. 2019;71(6):991鈥�9.

    听 听 听 听

  18. Nie J, Deng MG, Wang K, Liu F, Xu H, Feng Q, Li X, Yang Y, Zhang R, Wang S. Higher HEI-2015 scores are associated with lower risk of gout and hyperuricemia: results from the national health and nutrition examination survey 2007鈥�2016. Front Nutr. 2022;9:921550.

    听 听 听 听

  19. Seidell JC, Deurenberg P, Hautvast JG. Obesity and fat distribution in relation to health鈥揷urrent insights and recommendations. World Rev Nutr Diet. 1987;50:57鈥�91.

    听 CAS听 听 听

  20. Natto SSYAL, Midle ZS, Gyurko JB, O鈥橬eill R, Steffensen R. Association between time since quitting smoking and periodontitis in former smokers in the National Health and Nutrition Examination Surveys (NHANES) 2009 to 2012. J Periodontol. 2019;90(1):16鈥�25.

    听 听 听

  21. Xu J, Zhu X, Hui R, Xing Y, Wang J, Shi S, Zhang Y, Zhu L. Associations of metal exposure with hyperuricemia and gout in general adults. Front Endocrinol (Lausanne). 2022;13:1052784.

    听 听 听

  22. Webster AC, Nagler EV, Morton RL, Masson P. Chronic kidney disease. Lancet. 2017;389(10075):1238鈥�52.

    听 听 听

  23. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604鈥�12.

    听 听 听 听

  24. Yokose C, McCormick N, Lu N, Tanikella S, Lin K, Joshi AD, Raffield LM, Warner E, Merriman T, Hsu J, et al. Trends in prevalence of gout among US Asian adults, 2011鈥�2018. JAMA Netw Open. 2023;6(4):e239501.

    听 听 听 听

  25. Chen J, Feng Q, Liu Z, Yu Q, He P, LI X, Zhang S. POS0515 THE POTENTIAL CAUSAL RELATIONSHIP BETWEEN PHYSICAL ACTIVITY, LEISURE SEDENTARY BEHAVIORS, AND GOUT. In.: BMJ Publishing Group Ltd; 2023.

  26. Bolzetta F, Veronese N, Manzato E, Sergi G. Tophaceous gout in the elderly: a clinical case review. Clin Rheumatol. 2012;31(7):1127鈥�32.

    听 听 听

  27. Patterson R, McNamara E, Tainio M, de S谩 TH, Smith AD, Sharp SJ, Edwards P, Woodcock J, Brage S, Wijndaele K. Sedentary behaviour and risk of all-cause, cardiovascular and cancer mortality, and incident type 2 diabetes: a systematic review and dose response meta-analysis. Eur J Epidemiol. 2018;33(9):811鈥�29.

    听 听 听 听

  28. Beunza JJ, Mart铆nez-Gonz谩lez MA, Ebrahim S, Bes-Rastrollo M, N煤帽ez J, Mart铆nez JA, Alonso A. Sedentary behaviors and the risk of incident hypertension: the SUN Cohort. Am J Hypertens. 2007;20(11):1156鈥�62.

    听 听

  29. Zheng W, Chen Y, Zhao A, Xue Y, Zheng Y, Mu Z, Wang P, Zhang Y. Associations of sedentary behavior and physical activity with physical measurements and dyslipidemia in school-age children: a cross-sectional study. 樱花视频. 2016;16(1):1186.

    听 听 听 听

  30. Ohlsson C, Gidestrand E, Bellman J, Larsson C, Palsdottir V, H盲gg D, Jansson PA, Jansson JO. Increased weight loading reduces body weight and body fat in obese subjects - A proof of concept randomized clinical trial. EClinicalMedicine. 2020;22:100338.

    听 听 听 听

  31. Wu J, Zhang H, Yang L, Shao J, Chen D, Cui N, Tang L, Fu Y, Xue E, Lai C, et al. Sedentary time and the risk of metabolic syndrome: a systematic review and dose-response meta-analysis. Obes Rev. 2022;23(12):e13510.

    听 听 听

  32. Pinto AJ, Bergouignan A, Dempsey PC, Roschel H, Owen N, Gualano B, Dunstan DW. Physiology of sedentary behavior. Physiol Rev. 2023;103(4):2561鈥�622.

    听 CAS听 听 听 听

  33. Bergouignan A, Rudwill F, Simon C, Blanc S. Physical inactivity as the culprit of metabolic inflexibility: evidence from bed-rest studies. J Appl Physiol (1985). 2011;111(4):1201鈥�10.

    听 CAS听 听 听

  34. Trappe S, Creer A, Slivka D, Minchev K, Trappe T. Single muscle fiber function with concurrent exercise or nutrition countermeasures during 60 days of bed rest in women. J Appl Physiol (1985). 2007;103(4):1242鈥�50.

    听 听 听

  35. Trappe S, Creer A, Minchev K, Slivka D, Louis E, Luden N, Trappe T. Human soleus single muscle fiber function with exercise or nutrition countermeasures during 60 days of bed rest. Am J Physiol Regul Integr Comp Physiol. 2008;294(3):R939鈥�947.

    听 CAS听 听 听

  36. Salanova M, Schiffl G, P眉ttmann B, Schoser BG, Blottner D. Molecular biomarkers monitoring human skeletal muscle fibres and microvasculature following long-term bed rest with and without countermeasures. J Anat. 2008;212(3):306鈥�18.

    听 CAS听 听 听 听

  37. Kenny HC, Rudwill F, Breen L, Salanova M, Blottner D, Heise T, Heer M, Blanc S, O鈥橤orman DJ. Bed rest and resistive vibration exercise unveil novel links between skeletal muscle mitochondrial function and insulin resistance. Diabetologia. 2017;60(8):1491鈥�501.

    听 CAS听 听 听

  38. Eun Y, Han K, Lee SW, Kim K, Kang S, Lee S, Cha HS, Koh EM, Kim H, Lee J. Altered risk of incident gout according to changes in metabolic syndrome status: a Nationwide, Population-based Cohort Study of 1.29 million Young men. Arthritis Rheumatol. 2023;75(5):806鈥�15.

    听 CAS听 听 听

  39. Nelson MC, Casanova MP, Ball JR, Midence RD, Johnson TR, Martin B, Fehrenkamp BD, Baker RT, Drum SN, Vella CA. Effects of Uninterrupted sitting: are there differences across sex in vascular and inflammatory biomarkers? 262. Med Sci Sports Exerc. 2021;53(8S):81.

    听 听

  40. Breen L, Stokes KA, Churchward-Venne TA, Moore DR, Baker SK, Smith K, Atherton PJ, Phillips SM. Two weeks of reduced activity decreases leg lean mass and induces anabolic resistance of myofibrillar protein synthesis in healthy elderly. J Clin Endocrinol Metab. 2013;98(6):2604鈥�12.

    听 CAS听 听 听

  41. McGlory C, von Allmen MT, Stokes T, Morton RW, Hector AJ, Lago BA, Raphenya AR, Smith BK, McArthur AG, Steinberg GR, et al. Failed recovery of Glycemic Control and Myofibrillar protein synthesis with 2 wk of physical inactivity in overweight, prediabetic older adults. J Gerontol Biol Sci Med Sci. 2018;73(8):1070鈥�7.

    听 CAS听 听

  42. Reidy PT, McKenzie AI, Mahmassani Z, Morrow VR, Yonemura NM, Hopkins PN, Marcus RL, Rondina MT, Lin YK, Drummond MJ. Skeletal muscle ceramides and relationship with insulin sensitivity after 2 weeks of simulated sedentary behaviour and recovery in healthy older adults. J Physiol. 2018;596(21):5217鈥�36.

    听 CAS听 听 听 听

  43. Chen YC, Betts JA, Walhin JP, Thompson D. Adipose tissue responses to breaking sitting in men and women with Central Adiposity. Med Sci Sports Exerc. 2018;50(10):2049鈥�57.

    听 听 听

  44. Pinto AJ, Meireles K, Pe莽anha T, Mazzolani BC, Smaira FI, Rezende D, Benatti FB, Ribeiro ACM, Pinto ALS, Lima FR, et al. Acute cardiometabolic effects of brief active breaks in sitting for patients with rheumatoid arthritis. Am J Physiol Endocrinol Metab. 2021;321(6):E782鈥�94.

    听 CAS听 听 听

  45. So AK, Martinon F. Inflammation in gout: mechanisms and therapeutic targets. Nat Rev Rheumatol. 2017;13(11):639鈥�47.

    听 CAS听 听 听

  46. Wu M, Tian Y, Wang Q, Guo C. Gout: a disease involved with complicated immunoinflammatory responses: a narrative review. Clin Rheumatol. 2020;39(10):2849鈥�59.

    听 听 听

  47. Xu H, Qin H, Hua Y, Dalbeth N. Contributions of joint damage-related events to gout pathogenesis: new insights from laboratory research. Ann Rheum Dis. 2023;82(12):1511鈥�5.

    听 CAS听 听 听

  48. Martillo MA, Nazzal L, Crittenden DB. The crystallization of monosodium urate. Curr Rheumatol Rep. 2014;16(2):400.

    听 听 听 听

  49. Restaino RM, Holwerda SW, Credeur DP, Fadel PJ, Padilla J. Impact of prolonged sitting on lower and upper limb micro- and macrovascular dilator function. Exp Physiol. 2015;100(7):829鈥�38.

    听 听 听

  50. Dunstan DW, Dogra S, Carter SE, Owen N. Sit less and move more for cardiovascular health: emerging insights and opportunities. Nat Rev Cardiol. 2021;18(9):637鈥�48.

    听 听 听

  51. Carballo CB, Nakagawa Y, Sekiya I, Rodeo SA. Basic Science of articular cartilage. Clin Sports Med. 2017;36(3):413鈥�25.

    听 听 听

  52. Musumeci G, Castrogiovanni P, Trovato FM, Imbesi R, Giunta S, Szychlinska MA, Loreto C, Castorina S, Mobasheri A. Physical activity ameliorates cartilage degeneration in a rat model of aging: a study on lubricin expression. Scand J Med Sci Sports. 2015;25(2):e222鈥�230.

    听 CAS听 听 听

  53. Roggio F, Petrigna L, Trovato B, Di Rosa M, Musumeci G. The role of Lubricin, Irisin and Exercise in the Prevention and Treatment of Osteoarthritis. Int J Mol Sci 2023, 24(6).

  54. Pitsillides AA, Skerry TM, Edwards JC. Joint immobilization reduces synovial fluid hyaluronan concentration and is accompanied by changes in the synovial intimal cell populations. Rheumatology (Oxford). 1999;38(11):1108鈥�12.

    听 CAS听 听 听

  55. Li X, Wang S, Liu W, Wu H, Zhu Y. Causal effect of physical activity and sedentary behaviors on the risk of osteoarthritis: a univariate and multivariate mendelian randomization study. Sci Rep. 2023;13(1):19410.

    听 CAS听 听 听 听

  56. Wang Y, Zhang Y, Zhao C, Cai W, Wang Z, Zhao W. Physical activity, sedentary behavior, and Osteoarthritis: a two-sample mendelian randomization analysis. Iran J Public Health. 2023;52(10):2099鈥�108.

    听 听 听

  57. Lee J, Chang RW, Ehrlich-Jones L, Kwoh CK, Nevitt M, Semanik PA, Sharma L, Sohn MW, Song J, Dunlop DD. Sedentary behavior and physical function: objective evidence from the Osteoarthritis Initiative. Arthritis Care Res (Hoboken). 2015;67(3):366鈥�73.

    听 听 听

  58. Williams PT. Effects of diet, physical activity and performance, and body weight on incident gout in ostensibly healthy, vigorously active men. Am J Clin Nutr. 2008;87(5):1480鈥�7.

    听 CAS听 听 听

Acknowledgements

The authors express their sincere gratitude to the researchers and participants involved in the original study for their dedicated efforts in data collection and management.

Funding

The work was supported by the National Key R&D Program of China (2020YFA0803800), Shanghai Science and Technology Committee (22dz1204702).

Author information

Authors and Affiliations

  1. Department of Sports Medicine, Huashan Hospital, Fudan University, Shanghai, China

    Hengwei Qin听&听Yinghui Hua

Authors
  1. Hengwei Qin

    You can also search for this author in 听

  2. Yinghui Hua

    You can also search for this author in 听

Contributions

HQ and YH designed the study. HQ wrote the manuscript. HQ collected, analyzed and interpreted the data. YH critically reviewed, edited and approved the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yinghui Hua.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher鈥檚 note

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article鈥檚 Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article鈥檚 Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit .

About this article

Cite this article

Qin, H., Hua, Y. Association of sedentary behaviour with gout and the interaction effect of hyperuricemia: a cross-sectional study from 2007 to 2018. 樱花视频 24, 3428 (2024). https://doi.org/10.1186/s12889-024-20937-4

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-024-20937-4

Keywords

樱花视频

ISSN: 1471-2458

Contact us