physical activity Reduces the Risk of Metabolic Syndrome and Circadian Syndrome - A Cross- Sectional Study from the NHANES Database 2007-2018

doi:10.21203/rs.3.rs-4840385/v1

Background

Circadian syndrome (CircS) and metabolic syndrome (MetS) are closely associated with cardiovascular disease. physical activity has been proved to ameliorate the MetS, however, its association with CircS, as well as CircS comorbid MetS, is largely obscured.

Objective

To investigate the association between physical activity on MetS, CircS, and their comorbidity.

Methods

The associations and dose-response relationships between physical activity and MetS, CircS, and their comorbidity were analyzed using univariate and multivariate logistic regression, restricted cubic spline (RCS), and subgroup analyses.

Results

After adjusting for confounders, higher levels of physical activity were significantly associated with the risks of MetS, CircS, and the comorbidity (0.87 (0.77 ~ 0.99), p = 0.034; 0.85 (0.74 ~ 0.98), p = 0.027; and 0.87 (0.75 ~ 0.98), p = 0.026).The results of RCS suggested that MetS risk decreases with the increase of physical activity (p for overall < 0.001, p for nonlinear < 0.001), whereas CircS, and its comorbidity of MetS, shown a nonlinear trend from decreasing to increasing (p for overall < 0.001, p for nonlinear < 0.001), with the increasing physical activity. Subgroup analyses showed that increased physical activity was associated with a decreased risk of CircS and comorbidity in middle-aged and older adults, women, higher education population, low-income population, the non-obese, non-smokers, and non-drinkers.

Conclusion

physical activity could ameliorate MetS, CircS, and their comorbidity, especially for the middle-aged and married people as well as those with higher education, which provides a reference for early prevention of metabolism-related diseases in specific populations.

physical activity

Metabolic syndrome

Circadian syndrome

Comorbidity

NHANES database

Cross-sectional study

Metabolic syndrome (MetS) is characterized by the co-existence of a cluster of metabolic disorders, including insulin resistance, atherogenic dyslipidemia, central obesity, and hypertension^[1]. It poses a major health threat to public health by increasing the risk of cardiovascular disease and diabetes, severely burdening the individuals and society^{[2, 3]}. In addition, with the increasing of the aging and Hispanic population, the United States has evidenced an accelerated prevalence of MetS and MetS-related complications^[3], besides, there is a recent report of approximately one-third of Iranian adults suffer from MetS^[4]. Growing evidence demonstrates that the dysregulation of circadian rhythms might contribute to type 2 diabetes mellitus (T2DM), cardiovascular disease and hypertension, as well as some other common complications such as sleep disorders, depression and non-alcoholic fatty liver disease (NAFLD)^[5–7], thus the concept of circadian syndrome (CircS) was proposed. Similar to MetS, CircS a serious chronic disease with no effective treatments of early prevention currently.

The change of lifestyle might be an effective way to early prevent chronic diseases. In a prospective randomized controlled study, volunteers diagnosed with MetS were randomly assigned (1:1) into physical activity or control group, with or without a 6-month lifestyle intervention of regular physical activity. Participants in the physical activity group received personal physical activity advice in face-to-face meetings and on a smartphone app, with a goal of 150 minutes of physical physical activity per week. Participants in the control group continued their current lifestyle. The outcome of this study proved that a 6-month physical activity-targeted intervention effectively reduced the severity of MetS^[8]. There is emerging evidence suggesting that disruption of circadian rhythms exacerbates the development of depression, cardiovascular disease and T2DM. Physical physical activity synchronizes the circadian system and ameliorate depression and anxiety-like syndromes induced by circadian rhythm disruption, both in mouse and gerbil models. This study demonstrates that physical activity improves activity and pathological daily rhythms in blood glucose, glucose tolerance, and depression- and anxiety-like behaviors in a gerbil model, suggesting the crucial role of physical physical activity in regulating circadian rhythms and circadian-related disorders^[9]. There is tons of evidence confirming that regular physical activity provides primary and secondary protection to health, importantly, even a marginal increase in regular physical physical activity can significantly reduce diabetes mellitus and hypertension^[10]. However, most of the current studies have been limited to the analysis of physical activity on MetS or its disease components, and further investigation on CircS and comorbid MetS is still deficient.

National Health and Nutrition Examination Survey (NHANES) composes of series of comprehensive studies conducted in the United States with the aim to evaluate the health and nutritional status of adults and children^[11]. By accessing the NHANES 2007–2018 data, we purposed to investigate the association between physical activity on MetS, CircS, and their comorbidity, with a combination of logistic regression, restricted cubic spline (RCS), and subgroup analyses, thus to provide advice on early prevention for specific populations.

The NHANES cross-sectional survey has been conducted annually since 1999 and the data are released for public every two years. Data are collected using a variety of methods, such as questionnaires, interviews (face-to-face or telephone), laboratory tests, or physical examinations. The Institutional Ethics Review Board of the National Center for Health Statistics (NCHS) approved the study and written consent was obtained from all participants.

Definition of activity

Physical activity data was retrieved from the NHANES Physical Activity Questionnaire (PAQ), which is obtained by trained interviewers using a computer-assisted personal interview (CAPI) system. NHANES has assigned recommended MET values for different types of physical activity. The PAQ survey included vigorous work-related activity (MET = 8), moderate work-related activity (MET = 4), walking or bicycling for transportation (MET = 4), vigorous leisure time physical activity (MET = 8), and moderate leisure time physical activity (MET = 4). PA value is calculated based on the MET value, type of activity, weekly frequency, and duration: PA (MET-h/wk) = MET× weekly frequency of each physical activity × duration^{[12, 13]}.

Definition of MetS and CircS

Definition of MetS: A person will be categorized as MetS if he or she had ≥ 3 of the following components. (1) elevated waistline (≥ 102 cm in men and ≥ 88 cm in women); (2) hypertension (systolic blood pressure ≥ 130 mm Hg and/or diastolic blood pressure ≥ 85 mm Hg) or take medications for hypertension; (3) high-density lipoprotein (HDL) cholesterol (< 40 mg/dL in men and < 50 mg/dL in women) or take medications for dyslipidemia; (4) high triglycerides (TG) (≥ 150 mg/dL) or take dyslipidemia medication; and (5) elevated fasting glucose (≥ 100 mg/dL, with hyperglycemia medication taking as a surrogate indicator).

Assessment of CircS was based on 7 components, including the 5 components of MetS and self-reported sleep deprivation (< 6 hours per day) and depressive symptoms. The presence of ≥ 4 of these metabolic disorder components was categorized as the CircS.

Covariant

The following variables were considered as covariates: gender, age (20–44, 45–64, ≥ 65), race (Mexican American, White, Black, Other Hispanic, and other races), education level (recorded as less than high school, high school, college, or college graduated or higher), marital status (married, unmarried, cohabiting, divorced, separated, widowed), poverty-to-income ratio (PIR) was calculated by dividing household income by the household's poverty threshold and is categorized into three levels (< 1.3, 1.3–3.5, and > 3.5)^[14], BMI (< 25, 25–30, > 30), smoking status (nonsmoker, quitter, and current smoker), alcohol use (drinker or nondrinker), and health insurance related.

Statistical analysis

Continuous variables were presented as mean with standard deviation, while categorical variables were presented in specific value and percentage. For between-group comparisons, the t-test was used for continuous variables with normal distribution, the Mann-Whitney test for continuous variables without normal distribution, and the chi-square test for categorical variables. When analyzing the relationship between physical activity and disease using logistic regression, the physical activity was grouped into tertiles, with the first tertile as the reference group. The robustness of the models was analyzed using three logistic regression models: specifically Model 1 was analyzed without variable adjustment, Model 2 was adjusted for age, gender, race, and BMI, and Model 3 was further adjusted for additional variables based on Model II, including education attainment, marital status, PIR, smoking, alcohol consumption, and health insurance. RCS were used to plot dose-response curves for physical activity and risk of disease onset. Subgroup analysis was used to find specific populations that benefit from physical activity. Data were processed and statistically analyzed using R software (version 4.2.1). p value less than 0.05 was considered statistically significant.

Baseline characteristics of participants

A total of 12,061 individuals were included in this study, including 3,188 (26.43%) with MetS and 8,873 (73.57%) with non-MetS. Overall, there was a significant difference in the demographic characteristics of both MetS and non-MetS groups (p < 0.05). Out of the 3,188 MetS, 22.65% were male and 77.35% were female. Among non-MetS, 59.54% were male and 40.46% were female. The highest percentage of age groups in MetS is 45–64 years, reached 42.88%, and 20–44 years in non-MetS reached 47.26%. Compared to the non-MetS group, the MetS population had a far higher percentage of females and obese people, and a significantly lower percentage of young adults (20–44 years). Never smokers had the highest percentage in both MetS and non-MetS, 53.75% and 55.03%, respectively. Non-drinkers had the highest percentage in both MetS and non-MetS, 75.14% and 66.61%, respectively, and comparisons of the remaining relevant variables are shown in Table 1.

Table 1

Comparison of the baseline characteristics of participants with metabolic syndrome (MetS) and non-metabolic syndrome (non-MetS).
Variables	Total (n = 12061)	Non-MetS (n = 8873)	MetS (n = 3188)	p
PA all, M (Q₁, Q₃)	20.00 (0.00, 69.00)	24.00 (4.00, 80.00)	9.00 (0.00, 40.00)	< .001
Gender, n(%)				< .001
Men	6005 (49.79)	5283 (59.54)	722 (22.65)
Women	6056 (50.21)	3590 (40.46)	2466 (77.35)
Age group, n(%)				< .001
20–44	4943 (40.98)	4193 (47.26)	750 (23.53)
45–64	4252 (35.25)	2885 (32.51)	1367 (42.88)
≥ 65	2866 (23.76)	1795 (20.23)	1071 (33.59)
Race, n(%)				< .001
Mexican American	1787 (14.82)	1276 (14.38)	511 (16.03)
Non-Hispanic Black	2359 (19.56)	1771 (19.96)	588 (18.44)
Non-Hispanic White	5329 (44.18)	3874 (43.66)	1455 (45.64)
Other Hispanic	1228 (10.18)	874 (9.85)	354 (11.10)
Other Race - Including Multi-Racial	1358 (11.26)	1078 (12.15)	280 (8.78)
Education level, n(%)				< .001
<High school	2786 (23.10)	1876 (21.14)	910 (28.54)
High school graduate	2758 (22.87)	1956 (22.04)	802 (25.16)
Some college	3580 (29.68)	2623 (29.56)	957 (30.02)
College graduate or above	2937 (24.35)	2418 (27.25)	519 (16.28)
Marital status, n(%)				< .001
Married	6259 (51.89)	4635 (52.24)	1624 (50.94)
Never married	2144 (17.78)	1804 (20.33)	340 (10.66)
Living with partner	999 (8.28)	793 (8.94)	206 (6.46)
Divorced	1364 (11.31)	897 (10.11)	467 (14.65)
Separated	405 (3.36)	285 (3.21)	120 (3.76)
Widowed	890 (7.38)	459 (5.17)	431 (13.52)
PIR group, n(%)				< .001
< 1.35	3959 (32.82)	2746 (30.95)	1213 (38.05)
1.35-3.00	3703 (30.70)	2674 (30.14)	1029 (32.28)
≥ 3.00	4399 (36.47)	3453 (38.92)	946 (29.67)
BMI group, n(%)				< .001
Under 25	3507 (29.08)	3228 (36.38)	279 (8.75)
25–30.0	4028 (33.40)	3076 (34.67)	952 (29.86)
30.0 and over	4526 (37.53)	2569 (28.95)	1957 (61.39)
Smoking, n(%)				0.016
Never smoker	6591 (54.69)	4878 (55.03)	1713 (53.75)
Ex-smoker	3031 (25.15)	2171 (24.49)	860 (26.98)
Current smoker	2430 (20.16)	1816 (20.49)	614 (19.27)
Drinking, n(%)				< .001
Non-drinker	8300 (68.87)	5906 (66.61)	2394 (75.14)
Drinker	3752 (31.13)	2960 (33.39)	792 (24.86)
Covered by health insurance, n(%)				< .001
No	2554 (21.18)	1991 (22.44)	563 (17.66)
Yes	9507 (78.82)	6882 (77.56)	2625 (82.34)

Out of 12,061 participants, 2,162 (17.92%) were CircS and 9,899 (82.08%) were non-CircS. Overall, the demographic characteristics of the CircS and non-CircS groups were significantly different except for health insurance (P < 0.05). In CircS 17.07% were male and 82.93% were female. Non-CircS was 56.9% male and 43.06% female. The highest percentage of age group in CircS was 45–64 years reaching 44.82%, and 20–44 years in non-CircS reaching 44.65%. Compared to the non-CircS group, the CircS population had a far higher proportion of female, obese people, and a lower proportion of young adults (20–44 years). Never smokers had the highest percentage in both CircS and non-CircS, 51.64% and 55.35%, respectively. Non-drinkers had the highest percentage in both CircS and non-CircS, 75.93% and 67.33%, respectively, and comparisons of the remaining relevant variables are shown in Table 2.

Table 2

Comparison of the baseline characteristics of participants with circadian syndrome (CircS) and non-circadian syndrome (non-CircS).
Variables	Total (n = 12061)	Non-CircS (n = 9899)	CircS (n = 2162)	p
PA all, M (Q₁, Q₃)	20.00 (0.00, 69.00)	24.00 (2.67, 76.00)	8.00 (0.00, 37.25)	< .001
Gender, n(%)				< .001
Men	6005 (49.79)	5636 (56.94)	369 (17.07)
Women	6056 (50.21)	4263 (43.06)	1793 (82.93)
Age group, n(%)				< .001
20–44	4943 (40.98)	4420 (44.65)	523 (24.19)
45–64	4252 (35.25)	3283 (33.16)	969 (44.82)
≥ 65	2866 (23.76)	2196 (22.18)	670 (30.99)
Race, n(%)				< .001
Mexican American	1787 (14.82)	1438 (14.53)	349 (16.14)
Non-Hispanic Black	2359 (19.56)	1914 (19.34)	445 (20.58)
Non-Hispanic White	5329 (44.18)	4385 (44.30)	944 (43.66)
Other Hispanic	1228 (10.18)	978 (9.88)	250 (11.56)
Other Race - Including Multi-Racial	1358 (11.26)	1184 (11.96)	174 (8.05)
Education level, n(%)				< .001
<High school	2786 (23.10)	2098 (21.19)	688 (31.82)
High school graduate	2758 (22.87)	2204 (22.26)	554 (25.62)
Some college	3580 (29.68)	2950 (29.80)	630 (29.14)
College graduate or above	2937 (24.35)	2647 (26.74)	290 (13.41)
Marital status, n(%)				< .001
Married	6259 (51.89)	5263 (53.17)	996 (46.07)
Never married	2144 (17.78)	1876 (18.95)	268 (12.40)
Living with partner	999 (8.28)	869 (8.78)	130 (6.01)
Divorced	1364 (11.31)	1023 (10.33)	341 (15.77)
Separated	405 (3.36)	304 (3.07)	101 (4.67)
Widowed	890 (7.38)	564 (5.70)	326 (15.08)
PIR group, n(%)				< .001
< 1.35	3959 (32.82)	3013 (30.44)	946 (43.76)
1.35-3.00	3703 (30.70)	3030 (30.61)	673 (31.13)
≥ 3.00	4399 (36.47)	3856 (38.95)	543 (25.12)
BMI group, n(%)				< .001
Under 25	3507 (29.08)	3328 (33.62)	179 (8.28)
25–30.0	4028 (33.40)	3419 (34.54)	609 (28.17)
30.0 and over	4526 (37.53)	3152 (31.84)	1374 (63.55)
Smoking, n(%)				< .001
Never smoker	6591 (54.69)	5475 (55.35)	1116 (51.64)
Ex-smoker	3031 (25.15)	2494 (25.21)	537 (24.85)
Current smoker	2430 (20.16)	1922 (19.43)	508 (23.51)
Drinking, n(%)				< .001
Non-drinker	8300 (68.87)	6660 (67.33)	1640 (75.93)
Drinker	3752 (31.13)	3232 (32.67)	520 (24.07)
Covered by health insurance, n(%)				0.008
No	2554 (21.18)	2142 (21.64)	412 (19.06)
Yes	9507 (78.82)	7757 (78.36)	1750 (80.94)

Among 12,061 participants, 1,953 (16.19%) were MetS and CircS comorbidity, and the number of CircS not comorbid with MetS was 10,108 (83.81%). In comorbidity, males were 13.26% and females were 86.74%. Out of 10,108 participants of CircS not comorbid with MetS, males were 56.85% and females were 43.15%. The percentage of comorbidity reached a maximum of 44.55% in the age group 45–64 years and 44.38% in the age group 20–44 years in CircS not comorbid with MetS. BMI ≥ 30 in comorbidity accounted for 66.15% (Table 3).

Table 3

Comparison of the baseline characteristics of participants with MetS and CircS comorbidity.
Variables	Total (n = 12061)	No (n = 10108)	Yes (n = 1953)	Statistic	p
PA all, M (Q₁, Q₃)	20.00 (0.00, 69.00)	23.50 (2.67, 76.00)	8.00 (0.00, 34.00)	Z=-16.41	< .001
Gender, n(%)				χ²=1243.70	< .001
Men	6005 (49.79)	5746 (56.85)	259 (13.26)
Women	6056 (50.21)	4362 (43.15)	1694 (86.74)
Age group, n(%)				χ²=300.29	< .001
20–44	4943 (40.98)	4486 (44.38)	457 (23.40)
45–64	4252 (35.25)	3382 (33.46)	870 (44.55)
≥ 65	2866 (23.76)	2240 (22.16)	626 (32.05)
Race, n(%)				χ²=33.74	< .001
Mexican American	1787 (14.82)	1466 (14.50)	321 (16.44)
Non-Hispanic Black	2359 (19.56)	1983 (19.62)	376 (19.25)
Non-Hispanic White	5329 (44.18)	4460 (44.12)	869 (44.50)
Other Hispanic	1228 (10.18)	996 (9.85)	232 (11.88)
Other Race - Including Multi-Racial	1358 (11.26)	1203 (11.90)	155 (7.94)
Education level, n(%)				χ²=204.36	< .001
<High school	2786 (23.10)	2165 (21.42)	621 (31.80)
High school graduate	2758 (22.87)	2260 (22.36)	498 (25.50)
Some college	3580 (29.68)	3002 (29.70)	578 (29.60)
College graduate or above	2937 (24.35)	2681 (26.52)	256 (13.11)
Marital status, n(%)				χ²=344.98	< .001
Married	6259 (51.89)	5351 (52.94)	908 (46.49)
Never married	2144 (17.78)	1917 (18.97)	227 (11.62)
Living with partner	999 (8.28)	881 (8.72)	118 (6.04)
Divorced	1364 (11.31)	1054 (10.43)	310 (15.87)
Separated	405 (3.36)	322 (3.19)	83 (4.25)
Widowed	890 (7.38)	583 (5.77)	307 (15.72)
PIR group, n(%)				χ²=157.50	< .001
< 1.35	3959 (32.82)	3111 (30.78)	848 (43.42)
1.35-3.00	3703 (30.70)	3095 (30.62)	608 (31.13)
≥ 3.00	4399 (36.47)	3902 (38.60)	497 (25.45)
BMI group, n(%)				χ²=931.85	< .001
Under 25	3507 (29.08)	3372 (33.36)	135 (6.91)
25–30.0	4028 (33.40)	3502 (34.65)	526 (26.93)
30.0 and over	4526 (37.53)	3234 (31.99)	1292 (66.15)
Smoking, n(%)				χ²=8.53	0.014
Never smoker	6591 (54.69)	5571 (55.16)	1020 (52.25)
Ex-smoker	3031 (25.15)	2537 (25.12)	494 (25.31)
Current smoker	2430 (20.16)	1992 (19.72)	438 (22.44)
Drinking, n(%)				χ²=56.21	< .001
Non-drinker	8300 (68.87)	6816 (67.48)	1484 (76.06)
Drinker	3752 (31.13)	3285 (32.52)	467 (23.94)
Covered by health insurance, n(%)				χ²=9.73	0.002
No	2554 (21.18)	2192 (21.69)	362 (18.54)
Yes	9507 (78.82)	7916 (78.31)	1591 (81.46)
Z: Mann-Whitney test, χ²: Chi-square test
M: Median, Q₁: 1st Quartile, Q₃: 3rd Quartile

The relationship between physical activity and three diseases

The groupings were made in tertiles according to the amount of physical activity, with the first tertile as the reference group. The second and third tertiles in model 1 exhibited significant protection against MetS compared to the reference group (0.59 (0.54 ~ 0.65, p < 0.001; 0.40 (0.36 ~ 0.44), p < 0.001). This protection was further verified after adjusting for age, sex, race, and BMI (0.82 (0.73 ~ 0.92), p < 0.001; 0.85 (0.75 ~ 0.96, p < 0.009). After further adjusting for all covariates, only the protection of third tertile subgroup was ascertained (0.87 (0.77 ~ 0.99), p < 0.034).

Similarly, the significant protection against CircS in Model 1 was observed in the second and third tertile subgroups compared to the reference, with a reduced risk of CircS (OR (95% CI),0.57 (0.51 ~ 0.64), p < 0.001; 0.40 (0.36 ~ 0.45), p < 0.001). After adjusting for age, sex, race and BMI, the second and third tertile subgroups remained protective compared with the reference group, (OR (95% CI), 0.77 (0.68 ~ 0.87), p < 0.001; 0.81 (0.71 ~ 0.94), p < 0.004). The protective effect was only observed in the third tertile subgroup after adjusting for all covariates, (OR (95% CI), 0.85 (0.74 ~ 0.98), p < 0.027).

The second and third tertile subgroups in model 1 shown a significant protection against MetS and CircS comorbidity (OR (95% CI),0.58 (0.51 ~ 0.64), p < 0.001; 0.39 (0.34 ~ 0.44), p < 0.001). After adjusting for age, sex, race and BMI, the protection still existed (OR (95% CI), 0.80 (0.70 ~ 0.91, p < 0.001; 0.84 (0.72 ~ 0.97), p = 0.018). The protection in the third tertile subgroup was noticed (OR (95% CI), 0.87 (0.75 ~ 1.01), p = 0.026) (Table 4).

Table 4

Logistic regression analysis of the association between physical activity and indicated diseases.
Variables	Model1		Model2		Model3
Variables	OR (95%CI)	P	OR (95%CI)	P	OR (95%CI)	P
MetS
Tertile 1	1.00 (Reference)		1.00 (Reference)		1.00 (Reference)
Tertile 2	0.59 (0.54 ~ 0.65)	< .001	0.82 (0.73 ~ 0.92)	< .001	0.90 (0.80 ~ 1.01)	0.085
Tertile 3	0.40 (0.36 ~ 0.44)	< .001	0.85 (0.75 ~ 0.96)	0.009	0.87 (0.77 ~ 0.99)	0.034
CircS
Tertile 1	1.00 (Reference)		1.00 (Reference)		1.00 (Reference)
Tertile 2	0.57 (0.51 ~ 0.64)	< .001	0.77 (0.68 ~ 0.87)	< .001	0.89 (0.78 ~ 1.01)	0.064
Tertile 3	0.40 (0.36 ~ 0.45)	< .001	0.81 (0.71 ~ 0.94)	0.004	0.85 (0.74 ~ 0.98)	0.027
With CircS and MetS
Tertile 1	1.00 (Reference)		1.00 (Reference)		1.00 (Reference)
Tertile 2	0.58 (0.51 ~ 0.64)	< .001	0.80 (0.70 ~ 0.91)	< .001	0.91 (0.80 ~ 1.04)	0.168
Tertile 3	0.39 (0.34 ~ 0.44)	< .001	0.84 (0.72 ~ 0.97)	0.018	0.87 (0.75 ~ 0.98)	0.026
OR: Odds Ratio,CI: Confidence Interval
Model1: Crude
Model2: Adjust: Gender, Age, Race, BMI
Model3: Adjust: Gender, Age, Race, Education_level, Marital_status, PIR_group, BMI, Smoking, Drinking, Covered_by_health_insurance

Dose-response relationship between physical activity and three diseases

RCS was employed to analyze the dose-response relationship between physical activity and the three diseases. After adjusting for all confounders, we noticed that the risk of MetS declined with the increasing physical activity (p for overall < 0.001, p for nonlinear < 0.001), whereas the risk of CircS and its comorbidity with MetS, showed a U-shaped trend (p for overall < 0.001, p for nonlinear < 0.001), decreasing followed by increasing (p for overall < 0.001, p for nonlinear < 0.001). Interestingly, the recommended physical activity range for CircS was 0-590 MET/week, whereas the recommended physical activity range for MetS and CircS comorbidity was 0-595 MET/week (Fig. 2).

Subgroup analysis of the association between physical activity and three diseases

We further analyzed the relationship between physical activity and the risk of three diseases by subgroup analysis. The results suggested that physical activity may reduce the risk of MetS in middle-aged adults, other races, college and above, married, PIR > 1.35, and alcohol drinkers (Table 5).

Table 5. Subgroup analysis of the association between physical activity and MetS

There was an interaction between physical activity and age on the risk of CircS (p = 0.035), as indicated by the no protection in the young population (p > 0.05), but significant protection in the middle-aged or the elderly (p < 0.01). In addition, physical activity was more protective against CircS in men (0.78 (0.62,0.98), p = 0.035) than in women (0.84 (0.74,0.96), p = 0.012). Other Hispanics, college or higher, married, PIR < 1.35, BMI < 25 or ≥ 30, non-smokers or ex-smokers, and non-drinkers, all had a significantly lower risk of CircS with increased physical activity (p < 0.05) (Table 6).

Table 6. Subgroup analysis of the association between physical activity and CircS.

Finally, women, 45–64 years old, > 65 years old, college or higher, married, BMI < 25, never smoked or ex-smoked, and non-drinkers may benefit from the physical activity on CircS and MetS comorbidity (Table 7).

Table 7. Subgroup analysis of the association between physical activity and CircS and MetS comorbidity.

physical activity Reduces the Risk of Metabolic Syndrome and Circadian Syndrome - A Cross- Sectional Study from the NHANES Database 2007-2018

Status:

Version 1

Abstract

Background

Objective

Methods

Results

Conclusion

Figures

Introduction

Methods

Definition of activity

Definition of MetS and CircS

Covariant

Statistical analysis

Results

Baseline characteristics of participants

The relationship between physical activity and three diseases

Dose-response relationship between physical activity and three diseases

Subgroup analysis of the association between physical activity and three diseases