Total Physical Activity Volume,Physical Activity Intensity,and Metabolic Syndrome: 1999–2004 National Health and Nutrition Examination Survey

Abstract

Background:

This study examined the association of total physical activity volume (TPAV) and physical activity (PA) from three domains [leisure-time physical activity (LTPA), domestic, transportation] with metabolic syndrome. We also investigated the relationship between LTPA intensity and metabolic syndrome risk.

Methods:

Sample included adults who participated in the 1999–2004 National Health and Nutrition Examination Survey. Physical activity measures were created for TPAV, LTPA, domestic PA, and transportational PA. For each, a six-level measure based upon no PA (level 1) and quintiles (levels 2–6) of metabolic equivalents (MET)·min·wk⁻¹ was created. A three-level variable associated with the current Department of Health and Human Services (DHHS) PA recommendation was also created. SAS and SUDAAN were used for the statistical analysis.

Results:

Adults reporting the greatest volume of TPAV and LTPA were found to be 36% [odds ratio (OR) 0.64; 95% confidence interval (CI) 0.49–0.83] and 42% (OR 0.58; 95% CI 0.43–0.77), respectively, less likely to have metabolic syndrome. Domestic and transportational PA provided no specific level of protection from metabolic syndrome. Those reporting a TPAV that met the DHHS PA recommendation were found to be 33% (OR 0.67; 95%; CI 0.55–0.83) less likely to have metabolic syndrome compared to their sedentary counterparts. Adults reporting engaging in only vigorous-intensity LTPA were found to be 37% (OR 0.63; 95 CI 0.42–0.96) to 56% (OR 0.44; 95% CI 0.29–0.67) less likely to have metabolic syndrome.

Conclusions:

Volume, intensity, and domain of PA may all play important roles in reducing the prevalence and risk of metabolic syndrome.

Introduction

T he prevalence of the metabolic syndrome has been reported in worldwide populations¹ and currently is becoming a global epidemic.² Recently, we reported that an estimated one in three to one in five Americans meet metabolic syndrome criteria, depending on the definition used.³ A metabolic syndrome diagnosis carries a two-fold increase in cardiovascular disease mortality,^4,5 and individuals with the syndrome have been found to be 29%–79% more likely to die from all causes.^6
–8 Research usng both cross-sectional^9

–13 and prospective study designs^7,14

–18 illustrates that levels of physical activity (PA), exercise, and cardiorespiratory fitness have been shown to impact metabolic health favorably, thus attenuating morbidity and mortality from metabolic syndrome.

Usng data from the third National Health and Nutrition Examination Survey (NHANES), DuBose et al.¹¹ estimated adults reporting no leisure-time physical activity (LTPA) were 45% more likely to have the metabolic syndrome versus their regularly active counterparts. We estimated U.S. adults reporting between 390 and 1360 metabolic equivalents (MET)·min·wk⁻¹ of LTPA to be 30%–35% less likely to have the metabolic syndrome depending the defining criteria employed.¹³ More recently, Sisson et al.¹⁹ reported that men and women were found to be 94% and 54% more likely to have the metabolic syndrome, respectively, if they reported 4 h or of screen time per day compared to those reporting 1 h or less of screen time per day, illustrating the negative impact sedentary time may have on metabolic health.

Despite there being a plethora of studies examining the relationships between PA, exercise, and cardiorespiratory fitness level with the metabolic syndrome, few studies have examined the association of multiple domains of PA and PA intensity with metabolic syndrome. The primary aim this study was to investigate the association(s) of total physical activity volume (TPAV) and PA from three domains with metabolic syndrome in U.S. adults. A secondary aim was to examine the relationship between LTPA intensity and metabolic syndrome risk.

Methods

Sample and description of NHANES

The NHANES provides national estimates of the health and nutritional status of the noninstitutionalized U.S. civilian population over the age of 2 mo.²⁰ The total population for 1999–2004 NHANES was 31,126. For this study, the final sample consisted of 5,620 U.S. adults ≥20 years of age who met the following conditions: (1) Adult men and women who gave informed consent; (2) participated in a morning medical examination following an overnight fast (minimum of 8 h); (3) if female, not pregnant; and (4) had complete data on all the variables of interest. NHANES uses trained staff to conduct in-home interview-administered questionnaires and standardized medical examinations conducted by physicians and other health-care professionals in mobile examination centers. The questionnaires collected demographic data, as well as data specific to PA, diet, and current medical conditions. Physicians conducted medical examinations and gathered information on anthropometrics, hemodynamics, and complete blood profiles. The NHANES questionnaires and laboratory methodology have been described previously.^21,22 The Institutional Review Board of the University of North Florida approved the use of the 1999–2004 NHANES data.

American Heart Association and National Heart, Lung, and Blood Institute metabolic syndrome definition

The dependent variable in this study was a positive diagnosis of the metabolic syndrome based on the American Heart Association and National Heart, Lung, and Blood Institute (AHA/NHLBI) definition,²³ which has been described previously.¹³ In creating a dependent variable based on a positive diagnosis of the metabolic syndrome using the AHA/NHLBI definition, data on blood pressure, fasting glucose, lipoprotein values, and waist circumference were taken from the morning examination, the health examination component of the NHANES. Each metabolic syndrome component was dichotomized, with the demarcation being the cutoff value or pharmacological treatment for inclusion as a component of the metabolic syndrome (0=no risk; 1=risk). Risk factors were summed, and a total metabolic syndrome risk score (MSRS) was calculated, which ranged from 0 (no risk factors) to 5 (all five risk factors present). Those participants with a score of 0–2 risk factors were determined not to have the metabolic syndrome, and those participants with a score of 3–5 risk factors were determined to have the metabolic syndrome. In this study, the MSRS also served as a secondary dependent measure that was used to examine the relationship of TPAV and accumulating metabolic syndrome risk.

Total PA volume, PA domains, and intensity

Data used to measure TPAV, LTPA, domestic and transportational PA, along with PA intensity, were accessed from two distinct NHANES questionnaire data files— the ‘Physical activity’ data file (PAQ_C) and the ‘physical activities individual activities file’ (PAQIAF).²¹ The PAQ_C asked questions related to the frequency, intensity, and duration specific to transportational and domestic PA performed over the past 30 days (e.g., Over the last 30 days, how often did you walk or cycle as a part of getting to or from work, or school, or to do errands?). The PAQIAF is the second of the two files on PA and includes more detailed information regarding 43 specific types of moderate and vigorous LTPA. We used frequency due to its availability in the 1999–2004 NHANES. However, the recent Department of Health and Human Services (DHHS) PA guidelines are based solely on moderate and vigorous TPAV for which frequency is necessary to calculate. A specific quantified frequency (e.g., 3–5 days per week) is not currently a necessary component for meeting the DHHS guidelines.

The combination of information from the two PA files allowed us to create a broad measure of PA to examine the possible inverse association with metabolic syndrome risk. These measures, which used total PA MET·min·wk⁻¹ over the last 30 days, allowed for the calculation of overall total PA frequency per week. The compendium of PA²⁴ was used to designate an appropriate MET level to each type of activity performed. METs are obtained by dividing oxygen uptake in mL·kg·min⁻¹ by 3.5 mL·kg·min⁻¹ (resting energy expenditure).²⁵ Resting energy expenditure precisely reflecting 1-MET or 3.5 mL·kg·min⁻¹ has not gone without controversy; however, Ainsworth et al.²⁴ clearly convey that the compendium of PA was developed to standardized MET intensities for researchers using survey data. Those reporting actual measured MET intensities that may vary from the compendium would represent expected individual differences, thus correction factors may sometimes be necessary when estimating PA energy expenditure.²⁶ The average duration (minutes per session) was then multiplied by the average frequency (number of sessions per week) and the intensity level (MET-level) to calculate the MET·min·wk⁻¹ specific to each activity. With the sum MET·min·wk⁻¹ completed for all LTPA, transportational, and domestic activities, we created the TPAV, LTPA, domestic PA and transportational PA MET·min·wk⁻¹ variables.

The continuous MET·min·wk⁻¹ variable was used to create categorical variables for TPAV, LTPA, domestic PA, and transportational PA. Each of these categorical PA variables was a six-level variable allowing a potential dose–response association to be examined. The first level for each represented those who reported performing no PA during the past month, the referent groups for this study. This level included all individuals who reported no moderate or vigorous LTPA, transportational PA, or domestic PA. Thus, they received a score of “0” MET·min·wk⁻¹. The following is an example of how the TPAV variable was created. Each of the six-level categorical PA variables in the study was created using the same methodology. In calculating the remaining five levels of TPAV, the MET·min·wk⁻¹ values were divided into quintiles from the MET·min·wk⁻¹ measure: 1^st quintile >0.0 to ≤283.43 MET·min·wk⁻¹; 2^nd quintile >283.43 to ≤675.48 MET·min·wk⁻¹ 3^rd quintile >675.48 to ≤1261.18 MET·min·wk⁻¹; 4^th quintile >1261.18 to ≤2298.66 MET·min·wk⁻¹; 5^th quintile >2298.66 MET·min·wk⁻¹. The creation of quintiles was done to account for the nonnormally distributed and skewed PA measures inherent in national population surveys²⁷ while allowing for the illustration of a potential dose–response.

An additional TPAV measure used to examine the possible inverse association with the metabolic syndrome was a three-level categorical variable based on the recent DHHS PA guidelines.²⁸ Individuals who met the DHHS PA recommendation of at least 150 min of moderate to intense PA, or 75 min of vigorous intense PA per week, or an aggregate of both equating to TPAV (150 min) were classified as meeting the DHHS guidelines. Those reporting engaging in PA at least one time per week at any duration or intensity, but not meeting the DHHS guidelines, were classified as insufficiently active, and those who reported performing no PA were classified as inactive.

Covariates

Other measures included demographic variables of gender, age, and race/ethnicity, and two markers of socioeconomic status, which included education and income. Education was categorized as completing less than 12^th grade, completing 12^th grade, or education beyond 12^th grade. Income was categorized as a percent of the poverty threshold (<100%, 100%–199%, 200%–299%, 300%–399%, >400%). Falling below a poverty threshold of 100% demarcates living in poverty. Alcohol consumption was categorized as above-moderation drinker, moderate drinker, and nondrinker. Smoking status was also coded as a three-level categorical variable: Current smoker, previous smoker, and never smoked. In addition, family history of chronic disease(s), including heart disease and diabetes, were dichotomized.

Data analysis

The data in this study were initially managed using SAS 9.1.²⁹ SAS was used to conduct both complex variable recodes and data coding validation. SAS-callable SUDAAN³⁰ was then used to conduct the analysis, incorporating sampling weights within the context of the correlated multistage complex sampling design inherent to NHANES. Age-adjusted prevalence estimates were calculated using PROC DESCRIPT. For all prevalence estimates, non-overlapping 95% confidence intervals (CI) indicated significance. Also, a CI that included 1.0 indicated there was no statistical significance compared to the referent group. Logistic regression (PROC RLOGIST) analysis was used to estimate odds ratios (OR) and 95% CI for the metabolic syndrome, which is our dependent variable and all three domains of PA and TPAV. In addition, multiple logistic regression (PROC MULTILOG) was used to examine the OR for metabolic syndrome and adding an additional metabolic syndrome risk factor based on TPAV and meeting the DHHS recommendation. Our analysis controlled for gender, age, race, education, income, alcohol, smoking, and family history of diabetes and heart disease within SUDAAN.

Results

Metabolic syndrome prevalence by TPAV and multiple domains

Table 1 illustrates the prevalence of the metabolic syndrome according to the AHA/NHLBI definition by TPAV, LTPA, and domestic and transportational PA in weekly MET·min. When examining TPAV and LTPA, adults reporting the greatest volume of PA were found to have significantly lower prevalence estimates of metabolic syndrome compared to their less active and sedentary counterparts. When examining the remaining two domains of PA, domestic and transportational, the prevalence estimates for metabolic syndrome were similar, independent of weekly PA volume.

Table 1.

Metabolic Syndrome Prevalence According to the AHA/NHLBI Definition by TPAV, LTPA, Domestic PA, and Transportational PA in Weekly MET ċ Min from All Three Domains ^a Among U.S. Adults ≥20 Years: 1999–2004 NHANES

TPAV weekly MET min	%	95% CI	LTPA weekly MET min	%	95% CI	Dom-PA weekly MET min	%	95% CI	Trans-PA weekly MET min	%	95% CI
0.0^b	41.1	37.6, 44.6	0.0^b	40.0	37.5, 42.6	0.0^b	37.1	34.5, 39.7	0.0^b	36.7	34.7, 38.8
>0.0 to ≤283.43	41.4	37.3, 45.5	>0.0 to ≤156.24	41.2	36.8, 45.7	>0.0 to ≤126.00	41.6	36.8, 46.4	>0.0 to ≤80.07	35.6	27.8, 43.4
>283.43 to ≤675.48	36.2	32.6, 39.8	>156.24 to ≤393.10	37.2	32.9, 41.4	>126.00 to ≤250.05	36.9	29.4, 44.4	> 80.07 to ≤201.71	33.9	28.1, 39.8
>675.48 to ≤1261.18	35.3	31.3, 39.3	>393.10 to ≤736.55	36.3	31.8, 40.8	>250.05 to ≤547.10	34.8	31.4, 38.3	>201.71 to ≤399.57	38.9	31.7, 46.2
>1,261.18 to ≤2298.66	34.3	30.5, 38.1	>736.55 to ≤1360.15	29.5	24.5, 34.6	>547.10 to ≤1119.14	31.7	26.9, 36.4	>399.57 to ≤909.38	32.1	26.7, 37.5
>2298.66	31.0	27.1, 35.0	>1,360.15	27.2	22.7, 31.7	>1,119.14	36.4	31.7, 41.1	>909.38	33.4	27.4, 39.5

PA from LTPA, domestic PA, and transportational PA.

Referent groups.

AHA/NHBLI, American Heart Association and National Heart, Lung, and Blood Institute; TPAV, total physical activity volume; LTPA, leisure-time physical activity; PA, physical activity; MET, metabolic equivalent (1 MET=3.5 mL/kg/min⁻¹); NHANES, National Health and Nutrition Examination Survey; CI, confidence interval; Dom, domestic; Trans, transportational; %, prevalence; Dom-PA, domestic physical activity; Trans-PA, transportational physical activity.

Metabolic syndrome risk by TPAV and multiple domains

Table 2 depicts the OR of a metabolic syndrome diagnosis by TPAV, LTPA, and domestic and transportational PA in weekly MET·min. When examining TPAV and LTPA, significant protection was seen beginning in the fourth quintiles of PA. Interestingly, when examining TPAV, we found a significant inverse association (OR 0.76; 95% CI 0.58–0.98) beginning at a volume of 1,261.18 weekly MET·min, a much greater level of PA than that found when examining the results of our earlier study that focused solely on LTPA (OR 0.65; 95% CI 0.48–0.88) (736.55 weekly MET·min).¹³ No volume of PA specific to the domestic and transportational domains provided significant protection from metabolic syndrome; however, there was a significant trend toward protection for domestic PA (P=0.02) (Table 2).

Table 2.

Odds Ratios of Metabolic Syndrome Diagnosis by TPAV, LTPA, Domestic PA, and Transportational PA in Weekly MET ċ Min from All Three Domains ^a: 1999–2004 NHANES

TPAV weekly MET min	OR	95% CI	LTPA weekly MET min	OR	95% CI	Dom-PA weekly MET min	OR	95% CI	Trans-PA weekly MET min	OR	95% CI
0.0^b	1.00		0.0^b	1.00		0.0^b	1.00		0.0^b	1.00
>0.0 to ≤283.43	1.15	0.88, 1.51	>0.0 to ≤156.24	1.16	0.94, 1.43	>0.0 to ≤126.00	1.29	0.98, 1.68	>0.0 to ≤80.07	1.08	0.69, 1.67
>283.43 to ≤675.48	0.84	0.66, 1.08	>156.24 to ≤393.10	1.02	0.82, 1.27	>126.00 to ≤250.05	0.97	0.67, 1.41	>80.07 to ≤201.71	0.89	0.65, 1.21
>675.48 to ≤1,261.18	0.85	0.66, 1.10	>393.10 to ≤736.55	0.89	0.69, 1.15	>250.05 to ≤547.10	0.93	0.77, 1.12	>201.71 to ≤399.57	1.33	0.94, 1.89
>1,261.18 to ≤2,298.66	0.76	0.58, 0.98	>736.55 to ≤1,360.15	0.67	0.49, 0.90	>547.10 to ≤1,119.14	0.76	0.53, 1.08	>399.57 to ≤909.38	0.77	0.55, 1.08
>2,298.66	0.64	0.49, 0.83	>1,360.15	0.58	0.43, 0.77	>1,119.14	0.86	0.65, 1.14	>909.38	0.78	0.55, 1.08
P value for trend		<0.01			<0.01			0.02			0.06

Covariates adjusted for in the model include gender, age, race/ethnicity, education, income, smoking status, alcohol intake, family history of heart disease, and family history of diabetes.

PA from LTPA, domestic, and transportation.

Referent groups.

TPAV, total physical activity volume; LTPA, leisure-time physical activity; PA, physical activity; NHANES, National Health and Nutrition Examination Survey; MET, metabolic equivalent (1 MET=3.5 mL/kg/min⁻¹); TPAV, total physical activity volume; OR, odds ratio; CI, confidence interval; Dom-PA, domestic physical activity; Trans-PA, transportational physical activity.

Metabolic syndrome risk and prevalence estimates by DHHS PA guidelines

Table 3 depicts the OR of a metabolic syndrome diagnosis and the increasing MSRS by the DHHS PA guidelines when focusing on TPAV represented as inactive, insufficiently active, and meeting the DHHS PA guidelines. Those meeting the current PA guidelines were found to be 33% (OR 0.67; 95% CI .055–0.83) less likely to have the metabolic syndrome and 32% less likely (OR 0.68; 95% CI 0.58–0.80) to add an additional risk factor to the MSRS compared to those reporting no PA (inactive) from any of the three domains.

Table 3.

Odds Ratios of Metabolic Syndrome Diagnosis and Increasing Metabolic Syndrome Risk Score (MSRS) by DHHS PA Guidelines ^a and TPAV from All Three Domains ^b: 1999–2004 NHANES

	Metabolic syndrome risk by TPAV ^b			Odds of increasing MSRS
Total weekly PA level	OR	95% CI	P value for trend	OR	95% CI	P value for trend
Inactive^d	1.00		<0.01	1.00		<0.001
Insufficiently active^c	1.01	0.86, 1.18		0.96	0.81, 1.12
Meets DHHS PA guidelines^a	0.67	0.55, 0.83		0.68	0.58, 0.80

Covariates adjusted for in the model include gender, age, race/ethnicity, education, income, smoking status, alcohol intake, family history of heart disease, and family history of diabetes.

All Americans should engage in at least 150 min of moderate to intense physical activity, or 75 min of vigorous intense physical activity per week, or an aggregate of both equating to a total physical activity duration sufficient to meet the DHHS guidelines²⁸

PA from LTPA, domestic PA, and transportational PA.

Physically active but insufficient to meet DHHS guidelines.²⁸

Referent group.

DHHS, Department of Health and Human Services; PA, physical activity; TPAV, total physical activity volume; OR, odds ratio; CI, confidence interval; NHANES, National Health and Nutrition Examination Survey.

The prevalence of the metabolic syndrome among those reporting engaging in a level of PA that would meet the current DHHS PA recommendation was 30.4% (95% CI 27.0–33.7). The prevalence among those reporting being insufficiently active and inactive from any of the three domains was 38.4% (95% CI 35.5, 41.4) and 40% (95% CI 37.5–42.6), respectively, both significantly greater than those reporting a level of PA meeting the current DHHS guidelines. Additionally, as illustrated by overlapping 95% CI, the OR for having metabolic syndrome was found to be similar between those reporting insufficient levels of PA and those reporting being inactive, suggesting that the risk of metabolic syndrome among insufficiently active adults parallels that of sedentary adults.

PA intensity

One possible explanation for these conflicting results between TPAV and LTPA may reside with the intensity of PA. Table 4 illustrates the odds of metabolic syndrome by LTPA intensity. LTPA was chosen because the domestic and transportational domains of PA reside predominantly in the moderate intensity classification (data not shown). When examining the OR of metabolic syndrome by moderate-intensity LTPA, only the third quintile of LTPA was found to be protective, and a dose–response was not observed (P=0.15). However, when examining vigorous-intensity LTPA, significant protection from metabolic syndrome was seen beginning in the third quintile of LTPA (OR 0.63; 95% CI 0.42–0.96). In addition, a significant inverse dose–response was also observed (P<0.01). Table 4 also illustrates the proportion of vigorous MET·min among those who reported strictly LTPA and those reporting PA from up to all three domains (TPAV) of PA. When examining the first two levels of PA, approximately 10%–15% of the weekly MET·min come from vigorous activities for LTPA and TPAV. However, as the volume of LTPA MET·min increases, the proportion of those MET·min coming from vigorous PA also increases. Those accumulating the greatest volume of LTPA (>1360.15 MET·min) acquired 45.7% of their MET·min from vigorous PA. Those accumulating the greatest TPAV (>2298.66 MET·min) only acquired 27.6% of their MET·min from vigorous PA.

Table 4.

Odds of Metabolic Syndrome by LTPA Intensity and Proportion of Vigorous Intensity TPAV from All Three Domains ^a and PA from Those Reporting Only LTPA:1999–2004 NHANES

Moderate-intensity LTPA	OR	95% CI	Vigorous-intensity LTPA	OR	95% CI	LTPA weekly MET min	% from VPA	% from VPA	TPAV weekly MET min
0.0	1.00		0.0	1.00		0.0	—	—	0.0
>0.0–≤93.01	1.01	0.80, 1.27	>0<–≤195.02	0.77	0.58, 1.03	>0.0–≤156.24	10.0	9.4	>0.0–≤283.43
>93.01<–≤210.64	1.06	0.83, 1.35	>195.02<–≤430.64	0.86	0.65, 1.13	>156.24–≤393.10	15.8	15.7	>283.43–≤675.48
>210.64<–≤376.11	0.70	0.52, 0.95	>430.64<–≤776.33	0.63	0.42, 0.96	>393.10–≤736.55	24.8	21.4	>675.48–≤1261.18
>376.11<–≤709.66	0.94	0.68, 1.29	>776.33<–≤1382.82	0.56	0.39, 0.81	>736.55–≤1360.15	34.5	25.9	>1261.18–≤2298.66
>709.66	0.79	0.61, 1.03	>1,382.82	0.44	0.29, 0.67	>1, 360.15	45.7	27.6	>2,298.66
P value for trend	0.15			<0.01

PA from LTPA, domestic PA, and transportational PA.

LTPA, leisure-time physical activity; TPAV, total physical activity volume; PA, physical activity; VPA, vigorous physical activity; OR, odds ratio; CI, confidence interval; MET, metabolic equivalent (1 MET=3.5 mL/kg/min⁻¹).

Discussion

The level and appearance of protection associated with PA and the metabolic syndrome in this study clearly differs when examining multiple domains (LTPA, domestic and transportational), versus one domain, in this case LTPA. Perhaps the reason Ford et al.³¹ in an earlier NHANES metabolic syndrome and PA study did not find protection associated with PA was because they used multiple domains (LTPA and domestic). Our findings suggest that intensity, one of the parameters of PA volume, may play an important role in the relationship between PA and metabolic syndrome. Approximately half of all reported LTPA was vigorous PA, whereas only a quarter of TPAV was reported as vigorous. With significant protection beginning in the third quintile of LTPA when examining only vigorous PA and protection from metabolic syndrome beginning at a much lower level of LTPA when compared to TPAV, PA intensity may be a mediating factor when examining protection from metabolic syndrome. Findings from several studies and reviews suggest that PA or exercise intensity may moderate CVD^32
–34 and metabolic syndrome^35
–37 risk.

In the Atherosclerosis Risk in Communities (ARIC) study, Folsom et al.³² showed that women who reported ever exercising or participating in sports were 46% less likely [relative risk (RR) 0.54; 95% CI 0.35, 0.82] to develop coronary heart disease (CHD). Also in the ARIC study, men who reported participating in any high-intensity sport or exercise activities (RR 0.40; 95% CI 0.23, 0.68) as well as engaging in these activities more frequently (RR 0.43; 95% CI 0.20, 0.91) were found be approximately 60% less likely to develop CHD. One note, in the fully adjusted models, no protection was found for black men or women who reported any level of PA.

In a cross-sectional study examining almost 12,000 men and women age 25–69 years, Mensink et al.³³ investigated the association of various LTPA components with many CHD risk factors. The investigators classified PA into three intensity categories: Low (3.5–4.5 METs), moderate (5.0–7.0 METs), and high (7.5–9.0 METs). Following adjustment for potential confounders, reporting low-intensity activities was found to be associated with favorable changes in body mass index (BMI) and high-density lipoprotein cholesterol (HDL-C) in men and reductions in BMI, diastolic blood pressure (DBP), and triglycerides in women. Reported moderate intensity activities were found to be favorably associated with recovery heart rate in men and improvements in HDL-C, HDL-C/total cholesterol ratio, triglycerides, and BMI in women. The greatest level of protection for CHD risk was found among those who reported high-intensity (7.5–9.0 METs) activities. Favorable changes were found for all examined CHD risk factors, with the exception of systolic blood (SBP) pressure in men, thus suggesting that PA or exercise intensity may moderate CHD risk.

The results of a recent randomized controlled trial (RCT) suggest that exercise intensity influences changes in CHD risk profiles. O'Donovan et al.³⁴ examined changes in cardiorespiratory fitness and CHD risk factors in 42 previously sedentary men using a moderate- or high-intensity exercise intervention with analogous energy costs. There was a nonexercising control group and two exercise groups. The moderate-intensity exercise intervention required the completion of three 400-kcal exercise sessions at 60% of VO_2max and the high-intensity exercise intervention required the completion of three 400-kcal sessions at 80% VO_2max. Following the intervention, there were significant reductions in body fat in both exercise groups; however, waist circumference was significantly reduced in the high-intensity group only. Furthermore, total cholesterol and non-HDL-C in the high-intensity group were found to be significantly different (lower) than the controls, whereas the moderate-intensity exercise group did not differ from the controls, indicating that in this study, higher exercise intensity influenced changes in CHD risk.

More recently, Johnson et al.³⁶ presented data from the Studies of a Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE). The investigators examined associations between three different volumes and intensities of exercise and their impact on metabolic syndrome risk. Individuals in the low-volume, moderate-intensity group and the high-volume, vigorous-intensity group both significantly reduced their metabolic syndrome risk compared to inactive control. Interestingly, the low-volume, vigorous-intensity group did not experience a reduction in metabolic syndrome risk compared to the inactive controls, suggesting that frequency of exercise may play an important role when prescribing exercise to address metabolic health, a component that is not specifically quantified in the recent DHHS PA recommendation.²⁸ Furthermore, our findings also suggest that engaging in a level of PA that meets the DHHS PA recommendation provides significant protection from metabolic syndrome and increasing metabolic risk; however, those reporting some PA, but at a level insufficient to meet the recommendation, had similar risk profiles of those who reported being sedentary, suggesting that the current PA guidelines²⁸ may be the minimal threshold for reducing cardiovascular risk factor aggregation (Table 2).

Our study is not without limitations. First, the cross-sectional nature of our study design prevents the inference of causality. Second, potential recall bias for responses regarding PA patterns over the previous 30 days may result in over or underestimation of LTPA and TPAV. Third, many of the potential confounding variable responses may have been subjected to the social desirability effect (i.e., providing answers to impress or please the interviewer). Last, dietary factors were not controlled in any models due to the complex nature of this data inherent to NHANES (i.e., 1- and 2-day dietary recalls poorly represent day-to-day variation in individual dietary patterns).

Conclusions

Future studies are needed to examine all parameters of PA and exercise to elucidate which components may be related reducing metabolic syndrome prevalence and risk. This type of information may assist health-care professionals to better understand how to recommend PA and prescribe exercise for prevention and disease control specific to the metabolic syndrome and overall metabolic health.

Author Disclosure Statement

No competing financial interests exist.

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