Previous researches have reported the relationship between uric acid and cardiovascular disease. We aimed to investigate the association of Life’s Essential 8, a recently updated measurement of cardiovascular health, with the prevalence of hyperuricemia (HUA) and gout among US adults. Additionally, we also explored the relationship between LE8 and all-cause mortality among patients with HUA or gout.
Methods
Participants from the National Health and Nutrition Examination Survey in 2007–2016 were involved in this study. LE8 score was categorized into low, moderate, high CVH groups according to American Heart Association definitions. Multivariable logistic regression and cox regression analyses, restricted cubic spline models, subgroup analysis and sensitivity analysis were used to explore the associations.
Results
A total of 23,619 adult participants were included in this study, which included 4,775 hyperuricemia patients and 1,055 gout patients. Among all participants, the overall median LE8 score was 65.62 (21.25) and the prevalence of hyperuricemia and gout of were 20.2% and 4.5%, respectively. After fully adjusted the potential confounders, participants in high CVH group had a lower prevalence of hyperuricemia and gout compared with the low CVH group, with a OR (95%CI) of 0.50 (0.39–0.63) and 0.50 (0.30–0.82), respectively. The restricted cubic spline showed a significantly inverse relationship between LE8 and hyperuricemia and gout. Similar patterns were also identified in the association between LE8 scores and all-cause mortality in HUA and gout patients.
Conclusions
Higher LE8 scores are associated with lower risk and lower all-cause mortality of HUA and gout among US adults. Adherence to optimal CVH metrics may be an appropriate prevention and management strategy for reducing the socioeconomic burden of hyperuricemia and gout.
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Afkortingen
AHA
American Heart Association
BMI
Body mass index
CVH
Cardiovascular health
CVD
Cardiovascular disease
HB
Health behaviors
HEI-2015
Healthy Eating Index 2015
HF
Health factors
HRs
Hazard ratio
HUA
Hyperuricemia
LE8
Life’s Essential 8
LS7
Life’s Simple-7
NHANES
National Health and Nutrition Examination Surveys
OR
Odd ratio
Background
Uric acid is the end-product of purine nucleotide degradation [1]. Hyperuricemia (HUA) is classically defined as an elevation of blood urate concentration beyond the solubility threshold [2]. Today, about 20% of the US population have symptomatic or asymptomatic HUA [3]. HUA is an essential step in the development of gout. Gout is a common crystalline arthritis caused by the deposition of monosodium urate crystals in articular and non-articular structures [1]. The prevalence of gout increased steadily in the twentieth century due to the changing age structure of populations and the growing rate of metabolic syndrome. Population-based studies from Asia, Europe and North America have reported incidence ranges from 0.6 to 2.9 per 1000 person-years, and the prevalence ranged from 0.68% to 3.9% in adults [4‐6]. Previous studies suggested that HUA and gout are associated with systematic metabolic dysfunction such as hypertension, obesity and type 2 diabetes. All of these diseases were well-established independent risk factors of cardiovascular disease (CVD) [7‐9]. Thus, the prevention of HUA and gout is of a significant public health priority.
Back in 2010, the American Heart Association (AHA) published its definition of cardiovascular health (CVH), it was measured on the basis of 7 health behaviors (HB) and factors (Life’s Simple-7, LS7), including diet, physical activity, smoking, BMI, total cholesterol, blood pressure and blood glucose. A greater number of ideal CVH metrics was consistently associated with favorable health outcomes among disease populations [10‐13]. However, researchers found that LS7 cannot accurately define and quantify CVH, and the AHA recently updated the assessment for quantification of CVH, namely “Life’s Essential 8” (LE8) [14]. LE8 added sleep health as the eighth metric for measuring CVH and update the remaining metrics. This update shows a new scoring algorithm, which is more comprehensive and sensitive to inter-individual differences compared with LS7, and it could show the thresholds for the beneficial associations between LE8 and various diseases.
Earlier studies have shown the close association between uric acid and the CVD [15], and HUA & gout share several risks factors with CVD. However, to our knowledge, no study has evaluated the associations between the newly launched LE8 and HUA & gout all over the world. Therefore, using the latest available National Health and Nutrition Examination Surveys (NHANES) data, we sought to examine the correlation between AHA’s developed LE8 and the prevalence of HUA or gout in a nationally representative population of US adults. Additionally, we aimed to explore the relationship between LE8 and all-cause mortality among patients with HUA or gout.
Methods
Data source and study population
The NHANES, which collects the nutritional and health information of the United States population every 2 years, is a periodic, cross-sectional health survey program using multistage, stratified sampling and probability-cluster design to collect a nationally representative sample of non-institutionalized United States civilians [16].
The population for the present analysis consisted of five consecutive cycles of NHANES from 2007 to 2016. Finally, 23,619 adult participants were included in this study (figure s1), which included 4,775 hyperuricemia patients and 1,055 gout patients.
Measurement of LE8
LE8 scoring algorithm consists of 4 health behaviors (physical activity, diet, sleep duration and nicotine exposure) and 4 health factors (HF) (non-high-density-lipoprotein cholesterol, blood glucose, blood pressure and body mass index [BMI]). Detailed algorithms for calculating LE8 scores for each of the metrics to NHANES data have been previously published and can be found in Table S1 [14,17]. The overall LE8 score was calculated as the average of all 8 CVH metrics. American Heart Association recommends that participants with overall CVH scores of 80 to 100 be considered high CVH; 50–79, moderate CVH; and 0–49 points, low CVH [14].
Diet metric was evaluated by the Healthy Eating Index (HEI) 2015 [18]. The components and scoring standards HEI-2015 were summarized in Table S2 [19]. The simple HEI scoring algorithm method (by person) was used to compute the HEI-2015 score using an official SAS code provided by National Cancer Institute [20].
Self-report questionnaires collected information about nicotine exposure, physical activity, sleeping information, diabetes history, and medication history. Height, weight and blood pressure were measured, and BMI was calculated in regards to weight and height. Data on blood lipids, plasma glucose, hemoglobin A1c and serum creatinine were also collected.
Covariates
Potential confounding factors in this study include age, gender, race/ethnicity, education levels, marital status, poverty ratio, obesity status, and serum creatinine.
Definition of hyperuricemia and gout
Hyperuricemia is defined as serum uric acid level ≥ 420 μmol/L (7 mg/dL) and ≥ 360 μmol/L (6 mg/dL) in males and females, respectively [15]. Gout was defined as participants who answered “Yes” to the question “Doctor ever told you that you had gout?”.
Mortality ascertainment
National Center for Health Statistics has linked data from various surveys with death certificate records from the National Death Index with follow-up through NHANES 1999–2018. The Linked Mortality Files have been updated with mortality follow-up data through December 31, 2019 [21]. The underlying cause of death was determined by the ICD-10. The duration of follow-up was defined as the interval from the interview date to the date of death or through December 31, 2019, for participants without event.
Statistical analysis
To account for the complex sampling design and ensure nationally representative estimates, all analyses were adjusted for survey design and weighting variables. New sample weight (the original 2-year sample weight divided by 5) was constructed according to the analytical guidelines of the NHANES [22]. The continuous variables were described with median (interquartile range) and categorical variables were reported as numbers (percentage). The median values among different CVH groups (Low CVH: 0–49; Moderate CVH: 50–79; High CVH: 80–100) were compared with the Kruskal Wallis test. The Chi-square test was adopted to compare the percentages of categorical variables among three CVH groups. We used the same definition and cut-off points to categorize HB and HF scores to further investigate above association.
Multivariable binary logistic regression analyses were used to calculate the odds ratios (ORs) and 95% CIs for the association of LE8 with the prevalence of hyperuricemia and gout. In model 1, we adjusted for age, gender, race, and obesity status. In model 2, poverty status, education levels, marital status and creatinine were additionally adjusted. Restricted cubic spline analysis was applied to characterize the dose–response relationship between the LE8 and its subscale scores with prevalence of hyperuricemia and gout in the logistic regression Model 2. Nonlinearity was tested using the likelihood ratio test.
Stratified analyses were conducted by age groups (20–44, 45–64, 65 and over), gender, education levels, poverty ratio levels, race/ethnicity and marital status. The P values for the production terms between LE8 scores and the stratified factors were used to estimate the significance of interactions. And sensitivity analysis was used to assess the robustness of our findings. We divided LE8 scores, HB and HF scores into 4 groups according to the quartiles, with the first quartile (Q1 group) as the reference group. We then performed the logistic regression to test the robustness of our findings.
Multivariable Cox proportional hazards regression models were used to calculate hazard ratios (HRs) and 95%CIs for the associations of LE8 scores with prevalence of all-cause mortality after the adjustment of the same potential confounders among patients with HUA or gout. Restricted cubic spline analysis was applied to characterize the dose–response relationship between the LE8 and its subscale scores with all-cause mortality in patients with hyperuricemia or gout.
Statistical tests were 2-sided, and statistical significance was set at P < 0.05. All analyses were performed with SPSS 23.0 (IBM Corporation, Chicago, USA) SAS version 9.4 (SAS institute, Cary, NC) and R software, version 4.1.0. (Core Team, Vienna, Austria).
Results
Baseline characteristics
The clinical characteristics of the study population (n = 23,619) were summarized by the CVH status in Table 1. The median age of the study participants was 49 (29) years, and 12,082 (51.2%) were females. The overall median LE8 score was 65.62 (21.25). The prevalence of hyperuricemia and gout were 20.2% and 4.5%, respectively. Compared to those with low or moderate CVH, participants with high CVH were younger and had lower serum creatinine and higher education levels. Furthermore, with the increase of CVH status, the proportion of obesity participants and people living under poverty line declined gradually (Table 1).
Table 1
Clinical characteristic of the study population by cardiovascular health (CVH) status
Overall
(n = 23,619)
Low CVH
(n = 3,581)
Moderate CVH
(n = 15,860)
High CVH
(n = 4,178)
P Value
Age (year)†
49 (34–63)
57 (46–68)
50 (36–64)
36 (26–49)
< 0.01
Female (%)‡
12,082 (51.2)
1,865 (52.1)
7,669 (48.4)
2,548 (61.0)
< 0.01
Race (%)‡
< 0.01
Mexican American
3,715 (15.7)
550 (15.4)
2,563 (16.2)
602 (14.4)
Other Hispanic
2,542 (10.8)
362 (10.1)
1,713 (10.8)
467 (11.2)
NH White
10,240 (43.4)
1,532 (42.8)
6,874 (43.3)
1,834 (43.9)
NH Black
4,738 (20.1)
945 (26.4)
3,249 (20.5)
544 (13.0)
Other Race
2,384 (10.1)
192 (5.4)
1,461 (9.2)
731 (17.5)
Education level (%)‡
< 0.01
High school or less
11,223 (47.5)
2,239 (62.5)
7,823 (49.3)
1,161 (27.8)
Some college or AA
6,910 (29.3)
985 (27.5)
4,741 (29.9)
1,184 (28.3)
College graduate or above
5,486 (23.2)
357 (10.0)
3,296 (20.8)
1,833 (43.9)
Marital status (%)‡
< 0.01
Coupled
14,150 (59.9)
1,968 (55.0)
9,648 (60.8)
2,534 (60.7)
Single or separated
9,469 (40.1)
1,613 (45.0)
6,212 (39.2)
1,644 (39.3)
Poverty ratio (%)‡
< 0.01
< 1.0
4,691 (21.6)
995 (30.3)
3,049 (20.9)
647 (16.9)
≥ 1.0
16,991 (78.4)
2290 (69.7)
11,519 (79.1)
3,182 (83.1)
Obesity status (%)‡
< 0.01
Normal
6,772 (28.7)
279 (7.8)
3,872 (24.4)
2,621 (62.7)
Overweight
7,841 (33.2)
756 (21.1)
5,814 (36.7)
1,271 (30.4)
Obesity
9,006 (38.1)
2,546 (71.1)
6,174 (38.9)
286 (6.8)
Creatinine (mg/dL)†
0.84 (0.71–1.00)
0.87 (0.73–1.05)
0.85 (0.72–1.01)
0.80 (0.67–0.93)
< 0.01
LE8 scores (out of 100 possible points)†
65.62 (55.00- 76.25)
43.75 (38.12–46.88)
65.00 (58.12–71.88)
85.62 (82.50–90.00)
< 0.01
Health behaviors score†
67.50
(50.00–81.25)
42.50 (30.00–50.00)
67.50 (55.00–76.25)
87.50 (78.75–92.50)
< 0.01
Health factors score†
66.25 (51.25–81.25)
42.50 (32.50–51.25)
63.75 (53.75–76.25)
90.00(81.25–100.00)
< 0.01
Hyperuricemia (%)‡
4,775 (20.2)
1,155 (32.3)
3,299 (20.8)
321 (7.7)
< 0.01
Gout (%)‡
1,055 (4.5)
322 (9.0)
689 (4.3)
44 (1.1)
< 0.01
Data are number of subjects (percentage) or medians (interquartile ranges)
†Kruskal–Wallis test was used to compare the median values among participants in different groups
‡Chi-square test was used to compare the percentage among participants in different groups
LE8 score and the prevalence of HUA/gout
The associations between LE8 and prevalence of HUA and gout are displayed in Table 2 and Table 3. In the multivariable model 2, compared with the low CVH group, the ORs (95% CI) of HUA were 0.77 (0.67–0.89) in the moderate CVH group, and 0.50 (0.39–0.63) in the high CVH group, respectively (Table 2). And the ORs of gout were 0.64 (0.52–0.81) in the moderate CVH group and 0.50 (0.30–0.82) in the high CVH group, respectively (Table 3). The ORs with per 10 scores increase in LE8 were 0.84 (0.80–0.88) (Table 2) and 0.82 (0.75–0.88) (Table 3) in association with HUA and gout, respectively. LE8 score was inversely associated with the prevalence of HUA (P < 0.01) and gout (P < 0.01) (Fig. 1A, 1B). Nonlinear association was observed between the LE8 score and HUA (P < 0.01 for nonlinearity) (Fig. 1A). The minimal threshold for the beneficial association was 65.6 scores (estimate OR = 1.0).
Table 2
Association of the Life’s Essential 8 scores with hyperuricemia
Crude model
Multivariable model 1
Multivariable model 2
OR (95% CI)
P value
OR (95% CI)
P value
OR (95% CI)
P value
LE8 score
Low (0–49)
1 (Reference)
/
1 (Reference)
/
1 (Reference)
/
Moderate (50–79)
0.55 (0.48–0.63)
< 0.01
0.76 (0.66–0.87)
< 0.01
0.77 (0.67–0.89)
< 0.01
High (80–100)
0.19 (0.15–0.23)
< 0.01
0.48 (0.39–0.60)
< 0.01
0.50 (0.39–0.63)
< 0.01
Per 10 points increase
0.70 (0.67–0.72)
< 0.01
0.84 (0.80–0.87)
< 0.01
0.84 (0.80–0.88)
< 0.01
Health behaviors score
Low (0–49)
1 (Reference)
/
1 (Reference)
/
1 (Reference)
/
Moderate (50–79)
0.93 (0.83–1.03)
0.16
0.96 (0.85–1.08)
0.46
0.96 (0.85–1.09)
0.57
High (80–100)
0.72 (0.63–0.82)
< 0.01
0.85 (0.74–0.98)
0.03
0.93 (0.79–1.08)
0.31
Per 10 points increase
0.95 (0.92–0.97)
< 0.01
0.98 (0.95–1.00)
0.07
0.99 (0.96–1.02)
0.53
Health factors score
Low (0–49)
1 (Reference)
/
1 (Reference)
/
1 (Reference)
/
Moderate (50–79)
0.48 (0.43–0.53)
< 0.01
0.63 (0.56–0.71)
< 0.01
0.63 (0.56–0.71)
< 0.01
High (80–100)
0.16 (0.14–0.19)
< 0.01
0.37 (0.30–0.45)
< 0.01
0.36 (0.29–0.45)
< 0.01
Per 10 points increase
0.70 (0.69–0.72)
< 0.01
0.78 (0.76–0.81)
< 0.01
0.78 (0.75–0.82)
< 0.01
OR odds ratio, CI confidence interval, LE8 life’s essential 8.
Model 1 adjusted for age, sex, race, and obesity status.
Model 2 additionally adjusted for poverty status, education levels, marital status and creatinine.
Table 3
Association of the Life’s Essential 8 scores with gout
Crude model
Multivariable model 1
Multivariable model 2
OR (95% CI)
P value
OR (95% CI)
P value
OR (95% CI)
P value
LE8 score
Low (0–49)
1 (Reference)
/
1 (Reference)
/
1 (Reference)
/
Moderate (50–79)
0.44 (0.37–0.53)
< 0.01
0.63 (0.51–0.77)
< 0.01
0.64 (0.52–0.81)
< 0.01
High (80–100)
0.15 (0.10–0.22)
< 0.01
0.52 (0.34–0.81)
< 0.01
0.50 (0.30–0.82)
< 0.01
Per 10 points increase
0.67 (0.64–0.71)
< 0.01
0.82 (0.77–0.88)
< 0.01
0.82 (0.75–0.88)
< 0.01
Health behaviors score
Low (0–49)
1 (Reference)
/
1 (Reference)
/
1 (Reference)
/
Moderate (50–79)
0.74 (0.62–0.88)
< 0.01
0.77 (0.65–0.91)
< 0.01
0.79 (0.65–0.95)
0.01
High (80–100)
0.55 (0.42–0.71)
< 0.01
0.63 (0.48–0.84)
< 0.01
0.64 (0.47–0.85)
< 0.01
Per 10 points increase
0.91 (0.88–0.95)
< 0.01
0.93 (0.89–0.98)
< 0.01
0.94 (0.89–0.99)
0.01
Health factors score
Low (0–49)
1 (Reference)
/
1 (Reference)
/
1 (Reference)
/
Moderate (50–79)
0.40 (0.33–0.49)
< 0.01
0.60 (0.49–0.73)
< 0.01
0.59 (0.47–0.72)
< 0.01
High (80–100)
0.14 (0.10–0.18)
< 0.01
0.59 (0.42–0.84)
< 0.01
0.58 (0.40–0.86)
< 0.01
Per 10 points increase
0.70 (0.67–0.73)
< 0.01
0.84 (0.79–0.89)
< 0.01
0.83 (0.78–0.90)
< 0.01
OR odds ratio, CI confidence interval, LE8 life’s essential 8.
Model 1 adjusted for age, sex, race, and obesity status.
Model 2 additionally adjusted for poverty status, education levels, marital status and creatinine.
Fig. 1
Dose–response relationships between Life’s Essential 8 scores (A), Health Behavior score (C), Health Factors Score (E), and risk of hyperuricemia. Dose–response relationships between Life’s Essential 8 scores (B), Health Behavior score (D), Health Factors Score (F), and risk of gout. ORs (solid lines) and 95% confidence levels (shaded areas) were adjusted for age, sex, race/ethnicity, obesity status, poverty ratio (as a binary variable), education level, marital status, and creatinine. Vertical dotted lines indicate the minimal threshold for the beneficial association with estimated OR = 1. OR odds ratio, LE8 Life’s Essential 8
×
Health behavior score and the prevalence of HUA/gout
In model 2, HB scores were not significant associated with HUA (Table 2). HB scores were inversely associated with gout, compared with the low HB group, the ORs (95% CI) of gout were 0.79 (0.65–0.92) in the moderate HB group and 0.64 (0.47–0.85) in the high HB group, respectively (Table 3). The OR for every 10 scores increase was 0.94 (0.84–0.99) in association with gout (Table 3). An inverted U-shaped association was observed between HB score and prevalence of HUA (P < 0.01, P for nonlinearity < 0.01) (Fig. 1C). HB score was inversely associated with the prevalence of gout (P < 0.01, P for nonlinearity = 0.09) (Fig. 1D). The minimal thresholds for the beneficial association in HUA and gout were both 67.5 scores (estimate OR = 1.0).
Health factors score and prevalence of HUA/gout
After multivariable adjustment, compared with the low HF group, the ORs (95% CI) of HUA were 0.63 (0.56–0.71) in the moderate HF group and 0.36 (0.29–0.45) in the high HF group, respectively (Table 2). And the ORs (95%CI) of gout were 0.59 (0.47–0.72) in the moderate HF group and 0.58 (0.40–0.86) in the high HF group, respectively (Table 3). The ORs with per 10 scores increase in HF scores were 0.78 (0.75–0.82) (Table 2) and 0.83 (0.78–0.90) (Table 3) in association with HUA and gout, respectively. HF scores were inversely associated with the prevalence of HUA (P < 0.01) and gout (P < 0.01) (Fig. 1e, f). Nonlinear association was observed between the HF score and HUA (P < 0.01 for nonlinearity) (Fig. 1E). The minimal thresholds for the beneficial association with HUA and gout were both 66.3 scores (estimate OR = 1.0).
Subgroup analysis and sensitivity analysis
The results of subgroup analyses are presented in Table 4. LE8 score was negatively associated with the prevalence of HUA in all subgroups. The inverse association between LE8 score and HUA appeared stronger in female (0.78(0.73–0.82)), younger participants (aged 20–44 years; 0.82 (0.76–0.88)) and participants with college graduate or above education background (0.78(0.70–0.87)) (Table 4). The results were generally robust in sensitivity analyses (Table 5). The associations of LE8 score and HF score with HUA remained significant in the sensitivity analysis (P < 0.05), and the association between HB score and HUA remained insignificant in the sensitivity analysis (P > 0.05).
Table 4
Subgroup analysis of the association between Life’s Essential 8 scores and the presence of hyperuricemia or gout
Hyperuricemia
Gout
Subgroups
ORs (95% CIs)
P for interaction
ORs (95% CIs)
P for interaction
Overall
0.84 (0.80–0.88)
0.82 (0.75–0.88)
Sex
< 0.01
< 0.01
Male
0.91 (0.86–0.97)
0.85 (0.76–0.94)
Female
0.78 (0.73–0.82)
0.76 (0.66–0.87)
Age Strata
0.04
0.01
20–44
0.82 (0.76–0.88)
0.63 (0.52–0.78)
45–64
0.86 (0.81–0.92)
0.86 (0.76–0.98)
≥ 65
0.87 (0.80–0.95)
0.81 (0.72–0.91)
Education
0.04
0.06
High school or less
0.88 (0.83–0.94)
0.88 (0.79–0.98)
Some college or AA
0.83 (0.76–0.89)
0.71 (0.61–0.83)
College graduate or above
0.78 (0.70–0.87)
0.84 (0.73–0.97)
Poverty ratio
0.44
0.75
< 1.0
0.87 (0.81–0.94)
0.91 (0.77–1.06)
≥ 1.0
0.83 (0.79–0.88)
0.80 (0.73–0.87)
Race/ethnicity
0.06
0.09
Mexican American
0.84 (0.74–0.94)
0.68 (0.49–0.92)
Hispanic
0.79 (0.70–0.89)
0.81 (0.63–1.03)
NH White
0.85 (0.79–0.90)
0.82 (0.75–0.91)
NH Black
0.80 (0.75–0.85)
0.79 (0.69–0.91)
Other Race
0.86 (0.76–0.97)
0.87 (0.68–1.11)
Marital status
0.66
0.74
Coupled
0.83 (0.78–0.88)
0.81 (0.74–0.89)
Single or Divorce
0.85 (0.79–0.91)
0.82 (0.73–0.92)
OR odds ratio, CI confidence interval
ORs were calculated as per 10 scores increase in LE8 score
Each stratification was adjusted for age, sex, race/ethnicity, obesity status, poverty ratio, education level, marital status, and creatinine
Table 5
Sensitivity analysis for the association of Life’s Essential 8 score with hyperuricemia and gout according to quartiles of Life’s Essential 8 score
Multivariable model 2 (Hyperuricemia)
Multivariable model 2 (Gout)
OR (95% CI)
P value
OR (95% CI)
P value
LE8 score
Q1
1 (Reference)
/
1 (Reference)
/
Q2
0.86 (0.75–0.99)
0.04
0.60 (0.47–0.76)
< 0.01
Q3
0.69 (0.59–0.82)
< 0.01
0.58 (0.46–0.73)
< 0.01
Q4
0.51 (0.42–0.62)
< 0.01
0.49 (0.34–0.70)
< 0.01
Health behaviors score
Q1
1 (Reference)
/
1 (Reference)
/
Q2
0.97 (0.85–1.11)
0.67
0.70 (0.56–0.86)
< 0.01
Q3
1.02 (0.89–1.18)
0.77
0.79 (0.61–1.01)
0.06
Q4
0.91 (0.77–1.07)
0.27
0.67 (0.48–0.95)
0.03
Health factors score
Q1
1 (Reference)
/
1 (Reference)
/
Q2
0.71 (0.63–0.81)
< 0.01
0.63 (0.49–0.82)
< 0.01
Q3
0.46 (0.40–0.54)
< 0.01
0.64 (0.49–0.84)
< 0.01
Q4
0.32 (0.25–0.40)
< 0.01
0.53 (0.33–0.83)
< 0.01
OR odds ratio, CI confidence interval, LE8 life’s essential 8
Model 2 additionally adjusted for poverty status, education levels, marital status and creatinine
LE8 score was negatively associated with the prevalence of gout in almost all subgroup. The inverse association between LE8 score and gout appeared stronger in female (0.76(0.66–0.87)) and younger participants (aged 20–44 years; 0.63 (0.52–0.78) (Table 4). The results were generally robust in sensitivity analyses (Table 5). The association of LE8 score, HF score and HB score with gout remained significant in the sensitivity analysis (P < 0.05).
LE8 and its subscale scores with all-cause mortality of HUA/gout
In the full-adjusted model 2, the HRs of HUA all-cause mortality for every 10-point increment in LE8, HB and HF scores were 0.70 (0.64–0.77), 0.80 (0.76–0.84) and 0.91 (0.84–0.98), respectively (Table 6). LE8 and HB scores were inversely associated with the prevalence of HUA all-cause mortality (P < 0.01) (Fig. 2a, c), while a U-shaped association was observed between HF score and HUA all-cause mortality (P = 0.01 for nonlinearity) (Fig. 2E).
Table 6
Association of the Life’s Essential 8 and its subscale scores with all-cause mortality of hyperuricemia and gout patients
Crude model
Multivariable model 1
Multivariable model 2
HR (95% CI)
P value
HR (95% CI)
P value
HR (95% CI)
P value
Hyperuricemia (n = 4,775)
LE8 score
Per 10 points increase
0.67 (0.62–0.72)
< 0.01
0.66 (0.60–0.71)
< 0.01
0.70 (0.64–0.77)
< 0.01
Health behaviors score
Per 10 points increase
0.78 (0.75–0.82)
< 0.01
0.76 (0.73–0.80)
< 0.01
0.80 (0.76–0.84)
< 0.01
Health factors score
Per 10 points increase
0.82 (0.78–0.87)
< 0.01
0.89 (0.83–0.96)
< 0.01
0.91 (0.84–0.98)
0.01
Gout (n = 1,055)
LE8 score
Per 10 points increase
0.77 (0.68–0.87)
< 0.01
0.66 (0.58–0.76)
< 0.01
0.67 (0.57–0.80)
< 0.01
Health behaviors score
Per 10 points increase
0.83 (0.78–0.88)
< 0.01
0.79 (0.74–0.85)
< 0.01
0.82 (0.74–0.90)
< 0.01
Health factors score
Per 10 points increase
0.91 (0.82–1.01)
0.07
0.87 (0.74–1.02)
0.08
0.85 (0.73–1.01)
0.06
OR odds ratio, CI confidence interval, LE8 life’s essential 8
Model 1 adjusted for age, sex, race, and obesity status
Model 2 additionally adjusted for poverty status, education levels, marital status and creatinine
Fig. 2
Dose–response relationships between Life’s Essential 8 scores (A), Health Behavior score (C), Health Factors Score (E) and hyperuricemia all-cause mortality. Dose–response relationships between Life’s Essential 8 scores (B), Health Behavior score (D), Health Factors Score (F) and gout all-cause mortality. HRs (solid lines) and 95% confidence levels (shaded areas) were adjusted for age, sex, race/ethnicity, obesity status, poverty ratio (as a binary variable), education level, marital status, and creatinine. Vertical dotted lines indicate the minimal threshold for the beneficial association with estimated HR = 1. HR Hazrd ratio, LE8 Life’s Essential 8
×
In model 2, the HRs for every 10-point increment in LE8, HB and HF scores were 0.67 (0.57–0.80), 0.82 (0.74–0.90) and 0.85 (0.73–1.01) in association with gout all-cause mortality (Table 6). LE8 and HB scores were inversely associated with the prevalence of gout all-cause mortality (P < 0.01) (Fig. 2b, d), while no significant association was observed between HF score and prevalence of gout all-cause mortality (P = 0.09) (Fig. 2F).
Discussion
In this study, we observed an inverse dose–response relationship between the LE8 score and HF with HUA in US adults. We also found an inverse dose–response relationship between the LE8 score and its sub-scales of HB and HF with gout in US adults. Subgroup analysis suggested that the negative association between LE8 score and HUA or gout was stronger among female and younger participants. Above associations remained significant in sensitivity analyses. Moreover, LE8 and HB scores were also inversely associated with all-cause mortality in HUA or gout patients.
To our knowledge, this is the first study to report the association between LE8 and HUA and gout in the US population simultaneously. Our findings reveal and confirm the importance of optimal cardiovascular health to lower the prevalence and the all-cause mortality of HUA and gout by using LE8 as the definition of CVH. Based on our findings, a more rigorous standard of health behaviors might be more preferable for gout, because there was no saturation effect in the association of health behaviors with the prevalence of gout, and the HRs in the association of health behaviors with gout-all-cause mortality decreased more sharply than health factors. Intriguingly, the association between LE8 score and HUA and gout was found to be stronger among younger and female participants. Above results highlight the differences in the potential beneficial value of CVH components and that population-level approaches should be implemented to promote CVH.
Previous studies have demonstrated that uric acid is significantly associated with cardiovascular diseases [23]. Uric acid is correlated closely with almost all known cardiovascular risk factors [24], insulin resistance [25,26], metabolic syndrome [27], obesity [28], non-alcoholic fatty liver disease [29] and chronic kidney disease [30]. Elevated uric acid level may be a marker of increased oxidative stress, and pyroptosis induced by reactive oxygen species played a key role in CVD [31,32]. Moreover, extensive UA exerts deleterious effects in many tissues and cells, especially in vascular endothelial cells. Thus, UA may be directly involved in the pathophysiology of CVD [33]. Inflammation also plays an important role both in gout and CVD. Many studies have suggested the association between NLRP3 inflammasome with gout and CVD [1,34]. Furthermore, a previous study showed that men with gout had a higher risk of death from all causes, which was primarily due to an elevated risk of CVD death [35]. These findings would provide support for the importance of the management of cardiovascular risk factors in men with gout. Considering these close relationships between uric acid and CVD, it is not surprisingly to find that all the LE8 metrics are negatively correlated with gout and HUA.
In general, life-style modification is essential for the management of HUA and gout [1]. LE8 is a comprehensive and easily applicable assessment tool in clinical settings to promote adherence to healthy behaviors and ideal health factors. Although the LE8 score in the whole population in our study approximated to the different minimal thresholds for beneficial association between LE8 scores and HUA and gout (52.7–67.5), only 17.69% of participants had a high CVH status in US adults. Adherence to ideal CVH metrics may be an appropriate prevention and management strategy for reducing the burden and mortality of HUA and gout.
The major strength of this study is the use of LE8 for evaluating CVH. Although LS7 was also proved to be correlated with many risks of diseases, LE8 had a better performance. This may be explained by the following reason: each factor in the LS7 score system ranged from 0 to 2 (with an ideal factor assigned a maximum score of 2; intermediate factor = 1; and poor factor = 0), whereas the new LE8 scoring system for each factor ranges from 0 to 100 points14, having more coverage than the original score. We used a large nationally representative sample of US adults, which enables the findings to be generalized to a broader population. We also illustrated the dose–response relationship between CVH and HUA, gout and identified the minimal threshold for the beneficial association. To increase the statistical strength and reliability of our studies, we performed sensitivity analyses to assess the robustness of our findings, and we fully adjusted for the potential covariates to investigate the independent effect of LE8 on HUA and gout.
However, several potential limitations deserve mentioning. We are unable to dynamically evaluate longitudinal changes in participants' CVH status due to NHANES not providing follow-up examination. Some of LE8 metrics assessments were based on self-report questionnaires which are subject to measurement errors. In addition, it was hard to include all potential confounding factors due to the limitations of the data. Finally, as a cross-sectional study, although we fully adjusted for the confounding factors, it was hard to determine causal associations. Further large-scale longitudinal cohort studies are required to confirm the causality.
In our study, higher LE8 score was strongly associated with lower prevalence of HUA and gout. We also found an inversely correlation between LE8 and all-cause mortality among patients with HUA or gout. The strength of the association among LE8 scores and HUA and gout differed within the study population. Our study results indicate a potential beneficial role of LE8 to reduce the disease burden of HUA and gout. Further longitudinal cohort research on the causality association of LE8 and prevalence of HUA and gout is needed.
Acknowledgements
We are grateful to all study participants for their cooperation.
Declarations
Competing interests
The authors declare that they have no competing interests.
Ethical approval and consent to participate
The National Center for Health Statistics’ Research Ethics Review Board reviewed and approved all data collection protocols. Written informed consent was obtained from all participants prior to completing the NHANES, and all data was de-identified by the NCHS before being made publicly available.
Consent for publication
Written informed consent was obtained from the individuals for the publication of any potentially identifiable images or data included in this article.
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