Literature DB >> 19688106

Validation of reported physical activity for cholesterol control using two different physical activity instruments.

Amy Z Fan1, Sandra A Ham, Shravani Reddy Muppidi, Ali H Mokdad.   

Abstract

The National Cholesterol Education Program recommends increasing physical activity to improve cholesterol levels and overall cardiovascular health. We examined whether US adults who reported increasing their physical activity to control or lower blood cholesterol following physician's advice or on their own efforts had higher levels of physical activity than those who reported that they did not. We used data from the National Health and Nutrition Examination Survey 2003-2004, which implemented two physical activity assessment instruments. The physical activity questionnaire (PAQ) assessed self-reported frequency, intensity, and duration of leisure-time, household, and transportation-related physical activity in the past month. Physical movement was objectively monitored using a waist accelerometer that assessed minute-by-minute intensity (counts of movement/minute) during waking time over a 7-day period. We adjusted our analysis for age, gender, race/ethnicity, educational attainment, and body mass index. Participants who reported increasing physical activity to control blood cholesterol had more PAQ-assessed physical activity and more accelerometer-assessed active days per week compared to those who did not. However, there were no significant differences in cholesterol levels between comparison groups. These findings suggest that self-report of exercising more to control or lower cholesterol levels among US adults might be valid.

Entities:  

Keywords:  accelerometer; cardiovascular diseases; hypercholesterolemia; physical activity; risk reduction behavior

Mesh:

Substances:

Year:  2009        PMID: 19688106      PMCID: PMC2725798          DOI: 10.2147/vhrm.s6164

Source DB:  PubMed          Journal:  Vasc Health Risk Manag        ISSN: 1176-6344


Epidemiologic evidence has shown that elevated low-density lipoprotein cholesterol (LDL-C) is a major cause of coronary heart disease (CHD).1,2 Strong evidence also establishes the inverse relationship of high-density lipoprotein cholesterol (HDL-C) with cardiovascular morbidity and mortality.3–6 HDL is protective against cardiovascular disease by inhibiting the oxidative modification of LDL.7 The cardio-protective action of physical activity can be attributed to the elevation of HDL,8–14 and decrease in LDL and triglyceride levels.8–10,12,13 Low to moderate levels of physical activity are sufficient to bring about changes in the lipid profile of hypercholesterolemic patients.8,9,11,13,14 The National Cholesterol Education Program (NCEP) also recommended an increase in physical activity for hypercholesterolemic patients as a method of primary prevention of CHD.1 The US Department of Health and Human Services recommends 150 minutes of moderate-intensity physical activity per week, or 75 minutes of vigorous-intensity activity per week, or an equivalent combination of moderate- and vigorous-intensity physical activity (MVPA).15 Activity can be performed in bouts of 10 minutes or more. However, a large proportion of the population does not meet these recommendations.16,17 Physicians play an important role in promoting physical activity. Patients are more likely to increase their physical activity levels if their physician had advised such measures.18–23 Although a number of studies have been conducted to examine the influence of physician advice on physical activity in normal adults, no studies have been conducted among hypercholesterolemic adults. In this study we examined whether hypercholesterolemic participants who reported increasing their physical activity (compliant group) indeed had higher levels of physical activity than those who reported that they did not exercise more (noncompliant group) with two physical activity assessment instruments – namely, the National Health and Nutrition Examination Survey (NHANES) physical activity questionnaire (PAQ) and the accelerometer. We were interested in validating the self-reported PAQ in the NHANES with accelerometer data in samples defined based on concern about hypercholesterolemia. In addition, we were interested in understanding the type, frequency, intensity, and duration of activities that each group performed. We also did similar comparisons among participants who were not told they had high cholesterol but still increased physical activity to control cholesterol. Finally, we assessed whether the groups that reported increased physical activity possessed better lipid profiles than the low activity groups.

Materials and methods

The NHANES is a household interview and examination survey among the civilian, noninstitutionalized US population selected using a complex, multi-stage probability design. In 2003–2004, data were collected for 10,122 persons of all ages. The participants who were aged 18 years and older, not pregnant, and who answered the cholesterol check-up questions and the PAQ were included in our analysis (n =4,637). The study participants were initially interviewed at their residence to obtain data for demographic and family characteristics. The PAQ section was administered in the household interview. The PAQ section includes an extensive array of questions related to daily activities, leisure time activities, and sedentary activities at home. Participants were invited to a Mobile Examination Center (MEC) for a health examination and an in-person survey interview of health behaviors including cholesterol checkup, physician counseling to increase physical activity to lower blood cholesterol, and physical activity behaviors. Ambulatory participants were asked to wear a uniaxial accelerometer (ActiGraph model 7164; ActiGraph, LLC, Pensacola, FL) for seven consecutive days during waking hours to monitor their physical movement. Accelerometers are small, electronic devices that record acceleration of change of bodily movement and provide an objective estimate of duration and intensity of locomotion.24 Participants were asked to return the accelerometers in an envelope with prepaid postage following the monitoring period. The details on physical activity measures derived from PAQ and accelerometer are shown in Appendix 1. Blood specimens were collected at the MECs. General information on specimen collection and quality control for laboratory data is available at http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/lab_c_generaldoc.pdf. The lab methodology for assessment of total cholesterol and HDL-cholesterol were available at http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/l13_c.pdf. The lab methodology for the assessment of triglycerides is available at http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/l13am_c.pdf. LDL-cholesterol is calculated from measured values of total cholesterol, triglycerides, and HDL-cholesterol according to the Friedewald calculation. About 4,637 eligible participants were asked whether they had their blood cholesterol checked and whether they were told their cholesterol was high. The participants who were told they had high cholesterol (n =1,441) were then asked whether they were told by health professionals to exercise more to control their cholesterol and whether they followed the advice. Among those who were never told they had high blood cholesterol (n =3196), the following questions were asked: “Have you made any major changes on your own to lower your blood cholesterol? Specifically, have you increased your physical activity or exercise in order to lower your blood cholesterol?” We analyzed data from four groups: hypercholesterolemic adults who received advice and self-reported that they were (n =655) or were not compliant (n =293), and adults who were never told to have hypercholesterolemia increased (n =552) or did not increase (n =2,644) physical activity on their own to lower their cholesterol levels. The step-by-step sample distribution is shown in Figure 1.
Figure 1

Sample distribution. National Health and Nutrition Examination survey 2003–2004.

Abbreviation: DK, don’t know.

Covariates

Age and sex were self-explanatory. Four categories of race/ethnicity were created: non-Hispanic white, non-Hispanic black, Mexican American, and others. Years of education is a three-category variable that groups survey participants into one of three educational attainment groups: 1) less than high school education attainment, 2) high school graduate (has a high school diploma or high school equivalency diploma such as a General Educational Development [GED]), or 3) has more than a high school education. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters.

Statistical analysis

The analysis was performed using SAS-callable SUDAAN (Release 9.0.1, Research Triangle Institute, Research Triangle Park, NC, 2007) to account for the complex sampling design of NHANES. We used generalized linear modeling to compare physical activity levels between groups for measures of physical activity based on different domains (ie, exercise, sports, recreation, household physical activity, transportation physical activity, all physical activity), types of physical activity (ie, cardio, strengthening, flexibility), and physical activity based on intensity (ie, moderate-intensity physical activity, vigorous-intensity physical activity). The least-square means of continuous questionnaire-derived variables were obtained with adjustment for age, gender, race/ethnicity, educational attainment, and BMI category. The least-square means of continuous accelerometer-derived variables were obtained with adjustment for age, gender, race/ethnicity, educational attainment, BMI category, and days of valid accelerometer wear. All analyses were weighted. For the latter comparisons, we used sample weights, which reflects the additional “nonresponse” related to not having complete accelerometer data. Serum triglyceride and LDL cholesterol were available only for those who had fasted at least eight hours before their laboratory examination in the morning. Therefore, separate weight for morning fasting sample was used for these variables. Some variables were log-transformed before the analysis because of right skewness and transformed back to original scales for comparison. P values are two-sided.

Results

Our study population (nonpregnant, 18 years or older) consisted of 74% non-Hispanic whites, 11% non-Hispanic blacks, 8% Mexican Americans, and 7% others. The average age was 46 years. About 48% were male and 55% attained high school or higher education. About 35% of this population were overweight and 32% were obese. Among this population, about 70.8% (95% confidence interval [CI]: 67.6%, 73.8%) had their cholesterol checked. Among the adults checked, 42.2% (95% CI: 39.7%, 44.7%) were told they have high blood cholesterol. Among these adults with high blood cholesterol, about 67.0% (95% CI: 62.7%, 71.0%) were told to increase physical activity in order to lower blood cholesterol. Among the adults given advice, 68.1% (95% CI: 64.4%, 71.7%) reported having followed the advice. Among those who had no high blood cholesterol and never received such advice, only 15.3% (95% CI: 13.2%, 17.8%) increased physical activity on their own. Among the hypercholesterolemic adults who were advised by their physician to increase physical activity levels, the compliant adults had a greater number of sessions and more total MET-minutes of all physical activity per month compared to the noncompliant adults (P <0.0001; Table 1). Based on the intensity of physical activity, the compliant adults had greater numbers of sessions and MET-minutes of moderate- and vigorous-intensity physical activity per month compared to the noncompliant adults (P <0.0001). From the accelerometer data during wear periods from all valid days, the compliant adults also had greater mean intensity counts per minute (P =0.0006), mean counts per minute of most intense 10 minutes per week (P =0.001), and mean duration (minutes) of moderate- and vigorous-activity bouts (minimum one minute bouts) per day from all valid days (P =0.0008). Compliant adults also had higher mean duration (minutes) of moderate- and vigorous-activity bouts (eight out of 10 minute bouts) per day from all valid days (P =0.0002) and more days per week of greater than or equal to 10 minutes of MVPA bouts (eight out of 10 minutes) from all valid days (P <0.0001). However, there was no difference in adherence to physical activity recommendations based on Bayesian probability estimates.
Table 1

Physical activity (PA) measures (adjusted mean, [95% CI]) assessed by PAQ and by accelerometer and lipids profile based on whether the hypercholesterolemic participants followed the physician’s advice to increase PA levels

Questionnaire-derived measuresCompliant (n =655)Noncompliant* (n =293)P for difference
1) PA based on different domains (number of sessions per month):
Exercise19.7 (16.6–22.8)4.7 (2.9–6.5)<0.0001
Sports0.9 (0.5–1.3)0.4 (0.2–0.6)0.13
Recreation1.9 (1.3–2.5)0.3 (0.1–0.5)<0.00001
Household PA7.7 (6.5–8.9)5.8 (4.8–6.8)0.02
Transportation PA2.5 (1.3–3.7)2.3 (0.3–4.3)0.8
All PA32.7 (29.2–36.2)13.5 (10.6–16.4)<0.0001
2) PA based on different domains (total MET-minutes):
Exercise2988 (2428–3548)609 (344–873)<0.0001
Sports415 (187–643)207 (82–332)0.2
Recreation674 (392–955)142 (12–263)0.0070
Household PA3470 (2727–4212)2694 (1902–3486)0.22
Transportation PA250 (127–372)156 (26–285)0.23
All PA7796 (7037–8555)3808 (3127–4488)<0.0001
3) Type of PA:
Number of sessions per month
 Cardio29.3 (26.2–32.4)12.8 (10–15.5)<0.0001
 Strengthening1.04 (0.3–1.8)0.3 (0.1–0.5)0.013
 Flexibility2.3 (1.7–2.9)0.5 (0.1–1.0)0.0005
Total MET-minutes
 Cardio7603 (6854–8352)3735 (3056–4415)<0.0001
 Strengthening108 (49–167)50 (0–116)0.20
 Flexibility85 (62–109)23 (0–49)0.0007
4) PA based on intensity
Number of sessions per month
 Moderate intensity PA24.3 (22.0–26.6)12.2 (9.6–14.7)<0.0001
 Vigorous intensity PA5.0 (3.6–6.4)0.5 (0–1.1)<0.0001
Total MET-minutes
 Moderate intensity PA6303 (5563–7043)3534 (2819–4250)<0.0001
 Vigorous intensity PA1299 (916–1683)201 (11–391)<0.0001
Accelerometer-derived measuresN = 557N = 232
Mean intensity counts/minute on wear periods from all valid days264 (254–275)229 (216–243)0.0006
Mean counts/minute of most intense 10 min/week2415 (2277–2,562)2079 (1960–2205)0.001
Mean duration (minutes) of moderate and vigorous activity bouts (minimum 1 minute bouts) per day from all valid days12.1 (10.9–13.4)9.1 (8.0–10.3)0.0008
Mean duration (minutes) of moderate and vigorous activity bouts (8 out of 10 minute bouts) per day from all valid days1.8 (1.5–2.1)0.8 (0.6–1.1)0.0002
Days/week ≥10 min of MVPA bouts (8 out of 10 minutes) from all valid days1.0 (0.9–1.2)0.5 (0.4–0.7)<0.0001
Bayesian probability of ≥5 days/wk ≥30 min/day of 10-minute bouts of at least moderate intensity movement, % of adults at or exceeding threshold2.5 (1.7–3.3)1.1 (0.3–1.9)0.056
Lipids profile
Total serum cholesterol (mmol/L)5.50 (5.39–5.62)5.48 (5.32–5.66)0.89
Serum HDL cholesterol (mmol/L)1.28 (1.25–1.32)1.24 (1.19–1.30)0.30
Serum LDL cholesterol (mmol/L)3.09 (2.96–3.22)3.20 (2.99–3.42)0.45
Plasma triglycerides (mmol/L)1.71 (1.60–1.83)1.85 (1.63–2.09)0.26

Notes: The comparison on questionnaire-derived measures and lipid profile variables was adjusted for age, gender, race/ethnicity, education attainment, and BMI category. The comparison on accelerometer-derived measures was adjusted for age, gender, race/ethnicity, education attainment, BMI category and days of valid accelerometer wear.

This group included participants who responded “no”, “do not know” and refusal.

The variables are log-transformed before the analysis due to right skewness; the values shown have been transformed back to original scales.

Abbreviations: BMI, body mass index; Cts, counts; HDL, high-density lipoprotein; LDL, low-density lipoprotein; MET, metabolic equivalent; MVPA, moderate to vigorous physical activity; PAQ, physical activity questionnaire.

Among nonhypercholesterolemic adults who were never told to increase physical activity to lower cholesterol, adults who increased their physical activity on their own had a greater number of sessions and total MET-minutes of all physical activity per month compared to the adults who did not increase physical activity on their own (P <0.001; Table 2). They also had more MET-minutes of exercise (P <0.0001) per month. Based on the type of physical activity, the adults that increased physical activity on their own had a larger number of sessions and more total MET-minutes of cardio and strengthening exercises per month compared to those who did not increase physical activity. Based on the intensity of physical activity, the adults who increased physical activity on their own had more sessions of moderate- (P =0.0003) and vigorous- (P < 0.0001) intensity physical activity per month and more MET-minutes of vigorous-intensity physical activity (P <0.0001) than those who did not increase physical activity. The accelerometer data showed that the adults who increased physical activity on their own had greater mean counts per minute of most intense 10 minutes per week of physical activity (P =0.044), mean duration (minutes) of moderate- and vigorous-activity bouts (minimum one minute bouts) per day from all valid days (P =0.03), mean duration (minutes) of moderate- and vigorous-activity bouts (eight out of 10 minute bouts) per day from all valid days (P =0.046), and more days per week of greater than or equal to 10 min of MVPA bouts (eight out of 10 minutes) from all valid days (P =0.026). However, there was no difference in adherence to recommendations for physical activity based on Bayesian probability estimates.
Table 2

Differences in physical activity (PA) measures (adjusted mean [95% CI]) assessed by PAQ and by accelerometer and lipids profile in nonhypercholesterolemic adults between categories of efforts to increase PA to lower their blood cholesterol

Questionnaire-derived measuresIncreased PA on own effort (n =552)Did not increase* PA (n =2644)P for difference
1) PA based on different domains (number of sessions per month)
Exercise25.9 (22.4–29.4)12.9 (11.3–14.5)<0.0001
Sports2.6 (1.6–3.6)1.5 (1.3–1.7)0.02
Recreation1.9 (1.3–2.5)1.4 (1.2–1.6)0.05
Household PA7.4 (6.2–8.6)6.8 (6.0–7.6)0.33
Transportation PA4.6 (1.5–7.7)3.5 (2.3–4.7)0.37
All PA42.5 (36.5–48.2)26.0 (23.6–28.3)<0.0001
2) PA based on different domains (total MET-minutes)
Exercise4389 (3657–5121)2276 (1974–2577)<0.0001
Sports1261 (876–1,646)882 (716–1,049)0.04
Recreation657 (419–895)680 (529–830)0.86
Household PA2594 (2101–3086)2584 (2449–2718)0.38
Transportation PA503 (297–708)401 (267–536)0.38
All PA9440 (8170–10710)6822 (6179–7465)0.0004
3) Type of PA:
Number of sessions per month
 Cardio37.9 (32.4–43.4)23.9 (21.7–26.0)<0.0001
 Strengthening2.2 (1.6–2.8)0.9 (0.7–1.1)0.0003
 Flexibility2.5 (1.3–3.7)1.3 (0.9–1.7)0.046
Total MET-minutes
 Cardio9038 (7769–10307)6634 (6012–7255)0.0008
 Strengthening288 (191–385)122 (91–153)0.003
 Flexibility114 (67–160)67 (47–86)0.09
4) PA based on intensity
Number of sessions per month
 Moderate intensity PA26.7 (22.4–31.0)19.2 (17.2–21.2)0.0003
 Vigorous intensity11.1 (9.1–13.1)4.7 (3.9–5.5)<0.0001
Total MET-minutes
 Moderate intensity PA5453 (4630–6246)4851 (4338–5363)0.13
 Vigorous intensity3585 (2890–4280)1783 (1639–2075)<0.0001
Accelerometer-derived measuresN =460N =2,009
Mean intensity counts/minute on wear periods from all valid days286 (270–304)272 (262–283)0.07
Mean counts/minute of most intense10 min/week2751 (2543–2975)2489 (2393–2588)0.044
Mean duration (minutes) of moderate and vigorous activity bouts (minimum 1 minute bouts) per day from all valid days13.4 (11.6–15.6)11.7 (10.5–13.0)0.03
Mean duration (minutes) of moderate and vigorous activity bouts (8 out of 10 minute bouts) per day from all valid days2.0 (1.5–2.7)1.5 (1.2–1.8)0.046
Days/week ≥10 min of MVPA bouts (8 out of 10 minutes) from all valid days1.1 (0.9–1.3)0.9 (0.8–1.0)0.026
Bayesian probability of ≥5 days/wk ≥ 30 min/day of 10-minute bouts of at least moderate intensity movement, % of adults at or exceeding threshold4.0 (2.7–5.2)3.1 (2.5–3.7)0.21
Lipids profile
Total serum cholesterol (mmol/L)4.93 (4.85–5.01)4.95 (4.91–4.99)0.73
Serum HDL cholesterol (mmol/L)1.35 (1.31–1.38)1.35 (1.33–1.38)0.81
Serum LDL cholesterol (mmol/L)2.78 (2.67–2.89)2.79 (2.73–2.85)0.85
Plasma triglycerides (mmol/L)1.24 (1.12–1.37)1.26 (1.20–1.32)0.82

Notes: The comparison on questionnaire-derived measures was adjusted for age, gender, race/ethnicity, education attainment and BMI category. The comparison on accelerometer-derived measures was adjusted for age, gender, race/ethnicity, education attainment, BMI category and days of valid accelerometer wear.

This group included participants who responded “no”, “do not know” and refusal.

The variables are log-transformed before the analysis due to right skewness; the values shown have been transformed back to original scales.

Abbreviations: BMI, body mass index; Cts, counts; HDL, high-density lipoprotein; LDL, low-density lipoprotein; MET, metabolic equivalent; MVPA, moderate to vigorous physical activity; PAQ, physical activity questionnaire.

The sample used in the accelerometer data analysis had at least one valid day of accelerometer data. Alternatively, we restricted our analysis to the sample that had four or more valid days of accelerometer data and obtained similar results. No significant difference in blood lipid profiles (total cholesterol, LDL-C, HDL-C, triglycerides) were found between hypercholesterolemic adults who increased physical activity levels and those who did not and between nonhypercholesterolemic adults who increased physical activity levels on their own and those who did not (Tables 1 and 2). The analysis was adjusted for age, gender, race/ethnicity, educational attainment, and BMI category. Controlling for cholesterol-lowering medication did not change the results significantly.

Discussion

Physician advice has been shown to be effective in changing people’s lifestyle behaviors including physical activity,18–23,25,26 whereas other studies showed that physician advice on increasing physical activity does not seem to be effective in changing behavior.27,28 Nonetheless, physician advice, counseling, and follow-up are important components of the social-environmental supports needed to increase population physical activity levels. In this study, about two thirds of the individuals with elevated blood cholesterol recalled being given the advice from health professionals to increase physical activity to control their condition. Among these individuals, our analyses suggest that members of this group tended to heed this advice. Our findings showed that people who reported to have increased their physical activity levels either by following physician’s advice or on their own might have done so as reflected in physical activity levels measured by both questionnaire and accelerometer. Group differences were observed in the majority of measures of physical activity type (ie, cardio, strengthening, flexibility, moderate-intensity physical activity, vigorous-intensity physical activity) assessed by PAQ. The relevant group differences determined by PAQ were corroborated by the accelerometer findings. The compliance groups differed by all of the accelerometer-assessed measures of intensity, duration, and frequency, but not the measure of compliance with physical activity recommendations. The findings in this report are subject to some limitations. First, the health condition screening, physician’s counseling, change in exercise, and physical activity questionnaire data were self-reported, and therefore, subject to biases from misunderstanding the questions, recall, and social desirability. Moreover, self-reported duration of physical activity may include minutes of activity and rest periods.29 However, the accelerometer data were not subject to these biases.30 Second, although seven days of monitoring has been shown to provide a reasonable representation of usual physical activity,31 only one quarter of the NHANES sample wore the instruments for ≥10 hours/day for seven days.30 Participants who were excluded because of missing accelerometer data are somewhat different in categorical distributions of age, education, the poverty index and race/ethnicity.17 Third, the persons who said they followed their physician’s advice to increase physical activity actually had more valid wear days and more wear minutes in valid days; this might partially contribute to the detected difference although valid days of accelerometer wear was controlled in the comparison. Fourth, although gardening and yard work are among the most common leisure-time physical activities,29 they were reported as “other” and recoded in the NHANES 2003–2004, introducing the potential for underreporting. Fifth, the waist-mounted, uniaxial accelerometers miss some physical activity that involves upper-body movement (eg, weightlifting, cycling) and load carrying, and all waterborne activity.30 However, only 2% of US adults engage in weightlifting and 1% engage in cycling or water sports on any given day.29 Sixth, accelerometer data analyses are sensitive to the cut-off points that are used to classify minutes as light or moderate-to-vigorous intensity.30 We selected cut off-points based on walking and treadmill studies that have been published for other analyses of this NHANES data17,30 in an attempt to discriminate volitional exercise from other activities. Finally, this is a cross-sectional study. Whether a person actually increased their activity level over time is not certain because we did not perform any baseline physical activity measurement. For the same reason, we are uncertain whether the finding of virtually no significant difference in lipid profiles between participants who increased physical activity levels and those who did not is because the increased physical activity is not significant enough to produce any beneficial effects in changing lipid profiles. Despite low activity levels in hypercholesterolemic adults, there has been a drop in the percentage of people with high cholesterol and the levels of the average blood cholesterol over the last few decades.32 This trend might be largely attributed to the increase in the use of cholesterol-lowering medication.33–35 The decrease in the prevalence of hypercholesterolemia and average cholesterol levels would be presumably deepened if hypercholesterolemic or nonhypercholesterolemic persons adopt or maintain healthy lifestyles. Nonetheless, this population-based study showed that individuals who reported having increased their physical activity levels to control blood cholesterol do not possess more favorable lipid profiles than their counterparts, no matter whether they were told to have high cholesterol or not. Obviously, given the prevalent use of cholesterol-lowering medication, the “dosage” of increased physical activity may not be sufficient enough to bring out any significant difference in the outcome at the population level. There are very few studies that co-relate self-reported measures with direct measurement of physical activity using an accelerometer.19 More such studies are needed to examine the effect of lifestyle modification such as increasing physical activity on improving blood cholesterol or other subclinical conditions. In conclusion, our results suggest that persons who reported following physician advice to increase physical activity to increase physical activity are likely to have done so. Moreover, self report of physical activity to control cholesterol appears to be valid. Results suggest that self reports might be valid to track progress in lifestyle modifications towards cholesterol control. However, more intensive interventions are called for to increase physical activity in the communities in order to achieve significant health benefits including lower cholesterol levels in US adults.
Table S1

Classifications of physical activities into sets of indicators using NHANES 2003–2004 data

Indicators
Domains and subdomains
Type
Intensity
ExerciseSportsRecreationHousehold PATransportation PACardioStrengtheningFlexibilityModerateVigorous
Aerobics****

Baseball***

Basketball****

Bicycling****

Bowling***

Boxing***

Cheerleading, gymnastics**

Children’s games(eg, dodgeball, kickball)**

Dance***

Fishing***

Football****

Frisbee***

Gardening**

Golf***

Hiking****

Hockey****

Horseback riding***

Household tasks***

Hunting***

Jogging****

Kayaking****

Martial arts****

Other activity during leisure time****

Push-ups**

Racquetball***

Rollerblading****

Rope jumping**

Rowing****

Running**

Sit-ups**

Skateboarding**

Skating****

Skiing – cross-country***

Skiing – downhill****

Soccer****

Softball***

Stair climbing****

Stretching***

Surfing**

Swimming****

Tennis****

Trampoline jumping*

Treadmill****

Volleyball****

Walking during leisure time***

Walk and bicycle for transportation***

Weightlifting***

Wrestling***

Yard work**

Yoga****

Abbreviation: PA, physical activity.

  33 in total

1.  Physical activity assessment with accelerometers.

Authors:  K R Westerterp
Journal:  Int J Obes Relat Metab Disord       Date:  1999-04

2.  Physician advice about being overweight: association with self-reported weight loss, dietary, and physical activity behaviors of US adolescents in the National Health and Nutrition Examination Survey, 1999-2002.

Authors:  Ashima K Kant; Patricia Miner
Journal:  Pediatrics       Date:  2007-01       Impact factor: 7.124

3.  Participation by US adults in sports, exercise, and recreational physical activities.

Authors:  Sandra A Ham; Judy Kruger; Catrine Tudor-Locke
Journal:  J Phys Act Health       Date:  2009-01

4.  Twenty-year trends in serum cholesterol, hypercholesterolemia, and cholesterol medication use: the Minnesota Heart Survey, 1980-1982 to 2000-2002.

Authors:  Donna K Arnett; David R Jacobs; Russell V Luepker; Henry Blackburn; Christopher Armstrong; Steven A Claas
Journal:  Circulation       Date:  2005-12-12       Impact factor: 29.690

5.  Time trends in the use of cholesterol-lowering agents in older adults: the Cardiovascular Health Study.

Authors:  R N Lemaitre; C D Furberg; A B Newman; S B Hulley; D J Gordon; J S Gottdiener; R H McDonald; B M Psaty
Journal:  Arch Intern Med       Date:  1998-09-14

6.  Advice on exercise from a family physician can help sedentary patients to become active.

Authors:  F C Bull; K Jamrozik
Journal:  Am J Prev Med       Date:  1998-08       Impact factor: 5.043

7.  Prevalence of self-reported physically active adults--United States, 2007.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2008-12-05       Impact factor: 17.586

8.  Physical activity in the United States measured by accelerometer.

Authors:  Richard P Troiano; David Berrigan; Kevin W Dodd; Louise C Mâsse; Timothy Tilert; Margaret McDowell
Journal:  Med Sci Sports Exerc       Date:  2008-01       Impact factor: 5.411

9.  Diet and physical activity of U.S. adults with heart disease following preventive advice.

Authors:  Taylor S Wofford; Kurt J Greenlund; Janet B Croft; Darwin R Labarthe
Journal:  Prev Med       Date:  2007-06-27       Impact factor: 4.018

10.  Patterns of objectively measured physical activity in the United States.

Authors:  Jesse S Metzger; Diane J Catellier; Kelly R Evenson; Margarita S Treuth; Wayne D Rosamond; Anna Maria Siega-Riz
Journal:  Med Sci Sports Exerc       Date:  2008-04       Impact factor: 5.411

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  4 in total

1.  Validity of ActiGraph 2-regression model, Matthews cut-points, and NHANES cut-points for assessing free-living physical activity.

Authors:  Scott E Crouter; Diane M DellaValle; Jere D Haas; Edward A Frongillo; David R Bassett
Journal:  J Phys Act Health       Date:  2012-09-11

2.  A catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003-2006.

Authors:  Catrine Tudor-Locke; Sarah M Camhi; Richard P Troiano
Journal:  Prev Chronic Dis       Date:  2012-06-14       Impact factor: 2.830

3.  Objective vs. self-reported physical activity and sedentary time: effects of measurement method on relationships with risk biomarkers.

Authors:  Carlos A Celis-Morales; Francisco Perez-Bravo; Luis Ibañez; Carlos Salas; Mark E S Bailey; Jason M R Gill
Journal:  PLoS One       Date:  2012-05-09       Impact factor: 3.240

4.  Adherence to physical activity in adults with chronic diseases: ELSA-Brasil.

Authors:  Ludimila Forechi; José Geraldo Mill; Rosane Härter Griep; Itamar Santos; Francisco Pitanga; Maria Del Carmen Bisi Molina
Journal:  Rev Saude Publica       Date:  2018-04-09       Impact factor: 2.106

  4 in total

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