Young women's physical activity from one year to the next: What changes? What stays the same?

ABSTRACT

The Majority of women do not meet recommended physical activity (PA) guidelines. Assessment on changes in PA patterns among young, healthy US women was therefore performed. PA changes were assessed from self-reported PA at baseline (year 1) and follow-up (year 2). Participants [N = 127] aged 18–30 years had completed a randomized controlled aerobics trial. A two-sample test of proportions tested the sample changes in PA; a paired t test assessed the within-person changes. A multivariate logistic regression model assessed the demographic predictors of meeting PA levels in year 2 (6 months post-intervention). Women who met the recommended PA used a combination of leisure and lifestyle PA at both timepoints. In year 2, attaining the recommended PA levels through leisure-time PA increased, while work-related and active transit PA decreased. Leisure-time physical activity at moderate and vigorous levels of intensity is recommended to ensure that young women meet the recommended PA levels and obtain health benefits.

INTRODUCTION

Regular physical activity is an important factor for preventing disease throughout the lifespan [1]. Recommendations for active adults are 150 min per week of moderate intensity activity in bouts that last at least 10 min each and some additional weekly strength training [2]. The proportion of the adult population obtaining insufficient physical activity increases with age, from adolescence onward. According to the 2007 Behavioral Risk Factor Surveillance System data, 39% of young adults in the USA aged 18–24 years reported physical activity levels below the recommended guidelines of physical activity, whereas 46% of adults 25–34 years old reported levels below the recommended guidelines [3]. There are gender disparities in physical activity levels. According to the 2010 National Health Interview Survey, women aged 18–75 years engaged in less leisure-time physical activity than men [4]. Only 32% of US women aged 18–24 years reported recommended levels of leisure-time physical activity, compared to 51% of men aged 18–24 years.

Demographic differences within gender are also of concern. Analysis of the Third National Health and Nutrition Examination Survey (NHANES III) found that non-Hispanic white women reported higher moderate to vigorous physical activity levels than non-Hispanic black women. Mexican-American women reported the lowest levels [5]. A comparison of NHANES I–III found the prevalence of obesity among women aged 20–39 years highest in non-Hispanic black women (about 50%), followed by Mexican-American women (about 36%), and non-Hispanic white women (about 24%) [6]. Women with high body mass index (BMI) are less likely to be physically active [5].

These gender disparities generate interest in research investigating physical activity among young women at a time when patterns of physical activity may be shifting [5,7–11]. It is important to know how young women meet activity recommendations, because the knowledge of the variety of ways in which members of various subgroups of the population succeed in meeting the recommendations for physical activity will allow us to design more effective and feasible physical activity interventions and health promotion messages with options that are appropriate for the targeted population [12].

Some researchers suggest that non-leisure-time physical activities of daily life, including activities conducted during work, for the household, and for active transportation, may be sufficient for adults to meet the recommended levels of moderate physical activity [13]. According to the American Time Use Survey of 2003–2005, walking for a variety of purposes (i.e., transportation, shopping, exercise, and leisure) added up to 45 min per day among more than 45% of adults [14]. Non-leisure-time physical activities have been associated with racially and ethnically diverse populations. In a large 2001 US health survey, leisure-time physical activities were found to be more associated with men than women, with higher levels of education, and with white populations, whereas non-leisure-time activities, especially walking or bicycling for transportation, were associated with African-Americans, Latinos, and Asians [15]. Women's lifestyle physical activities have also not traditionally been well documented in survey questionnaires [16]. It is important to assess both leisure and non-leisure, or lifestyle activities, to better assess whether various subgroups of the population are meeting the recommended levels.

The aim of this study was to assess the changes in physical activity patterns among young, healthy US women over the same six calendar months across two consecutive years. More specifically, we asked the following: Do young US women who are able to meet the recommended levels engage in “lifestyle” activities relating to employment and/or active transit, or do they meet them in leisure-time activities such as walking, sports, and exercise? How do their patterns of physical activity change over time, and what factors, including participation in an exercise intervention, might influence alterations? Based on prior research [17], we hypothesized that to be successful in meeting the recommended levels of physical activity, young women must engage in both leisure-time physical activity and lifestyle physical activity.

METHODS

Study design and sample

We conducted a longitudinal analysis with baseline data (year 1) and follow-up data 1 year later from a sub-sample of participants drawn from the Women in Steady Exercise Intervention (WISER). The WISER study was a randomized controlled trial (2006–2009) testing the hypothesis that regular aerobic exercise among young, healthy women will result in beneficial physiological changes associated with reduction of risk for breast cancer. Details of the trial (NCT00393172) are reported elsewhere [18]. Briefly, the participants in the WISER trial (N = 391) were women aged 18–30 years; healthy but insufficiently active (exercising fewer than three times per week during the prior 6 months according to a brief pre-screening); and had a BMI between 18 and 40 kg/m [2]. The main recruitment method for the WISER trial was an email sent to female students and staff at the University of Minnesota. This recruitment source was complemented by emails sent to county employees, fliers posted at other universities, colleges and community colleges in the area, and newspaper ads. Randomization was balanced by baseline BMI and age (18–24 years old vs. 25–30 years old). Women randomized into the exercise groups were asked to complete a 30-min weight-bearing aerobic exercise five times weekly for 4 months. The intervention protocol was supervised by certified fitness professionals and were based on recommended minutes per week of physical activity [2].

The sub-study reported here, WISER-PS, consisted of a survey interview asking participants about their physical activity in the 6 months after completing the WISER intervention (see Fig. 1). A written invitation to be interviewed 6 months after the WISER trial was sent to the 234 participants who completed the WISER trial in 2 years of the 4-year trial (2007–2008). These women constituted 59.8% of all WISER participants. Of these 234, 127 completed the sub-study survey (i.e., approximately 54.3% of all those invited participated). Fifty-nine of the recruited WISER-PS participants (46.5%) were in the WISER intervention group, and 68 (53.5%) were in the WISER control group.

Fig. 1.

Flowchart of WISER-PS study

Measures

Demographic characteristics

All participants completed a baseline survey which included demographic questions on age, educational attainment, residence, which was recoded as urban vs. suburban or rural, marital status, and race/ethnicity. Race/ethnicity was recoded as white, black, Asian, and other (which included 7 Latinas and some participants declaring multiple race/ethnicity). Additional survey items included the number of children, hours of paid employment per week, and hours of school per week. Paid employment and student-related work were compiled together as occupational work hours.

Self-reported physical activity

All participants completed the Modifiable Physical Activity Questionnaire (MAQ) at two timepoints: baseline (pre-intervention) in face-to-face interviews and 1 year later, 6 months after completing the intervention, in phone-based interviews. The MAQ is a self-reported physical activity survey measuring leisure time, occupational, and sedentary activity [19]. The MAQ asks how many of 33 leisure-time activities the respondent participated in over the prior year (or other time frame), the specific months, times per month, and number of minutes or hours of practice. The leisure-time physical activity section concludes with an “other” category to capture activities not listed. The survey questions differentiate between jogging/running, hiking, mountain climbing, bicycling, walking for exercise (outdoors or on a treadmill), and other walking (i.e., for leisure). In data analysis, questionnaire data on leisure-time and occupational physical activity were then transformed into metabolic equivalents per hour per week (MET hours/week) using commonly accepted MET values for each activity [20]. Activities of moderate intensity are considered to be from 3 to 6 METs, while more vigorous activities are rated at ≥7 METs [21]. Thus skating and basketball receive 7 METs, jogging and hiking receive 6 METs, walking for exercise receives 4 METs, and other walking receives 2.5 METs. A separate section of the MAQ elicits information on all non-seated occupational activities and categorizes these as light, moderate, and vigorous. These data were similarly transformed into METs. (The section on sedentary activity was not used in this study.) The baseline survey asked participants about their physical activity over the 12 months prior to starting WISER. The post-intervention survey asked participants about their physical activity in the 6 months after completing the intervention. Because seasonal effects can be significant, we matched the calendar months of the two surveys: the same 6 months reported on in the 6-month post-intervention survey were selected from the 12-month baseline survey for comparison. As a result, we were able to compare 6 months of physical activity from 1 year to the next.

The study was approved by the Institutional Review Board of the University of Minnesota.

Analysis

Questionnaire data on leisure-time and occupational physical activity were transformed into metabolic equivalents per hour per week (hours/week) [20]. Descriptive statistics were calculated for METs. As a check on group differences between WISER-PS participants compared to the full sample of WISER participants, we compared the baseline characteristics of those who completed the year 2 follow-up survey to those who did not using independent t tests. No statistical differences (p > 0.05) were found in race, BMI, marital status, parenting status, or number of hours worked. However, compared to the full WISER sample, WISER-PS participants had higher baseline levels of total MET hours per week (WISER-PS = 24.8 vs. WISER 21.1, t = 2.05, p = 0.04), driven by higher levels of leisure MET hours per week (analytic = 14.0 vs. lost to follow-up = 10.9, t = 2.30, p = 0.02).

Physical activity levels of WISER-PS participants were assessed by Student t test for continuous variables and χ² tests for categorical variables. There were no differences found in physical activity between the WISER-PS and full sample at baseline and year 2, at the 6-month post-intervention. There was no intervention effect of physical activity. Therefore, “condition” was added as a covariate for adjustment.

Variables of physical activity were dichotomized to reflect those meeting or not meeting physical activity recommendations of at least 7.5 MET hours/week at baseline and 1 year later [22]. Descriptive statistics were used to describe physical activity by type using a two-sample test of proportions. Mean MET hours/week for each type of physical activity were calculated for all those participants who met the recommended levels of total physical activity at either or both timepoints (i.e., a non-paired sample). The sample was then reduced to include only those who met physical activity guidelines at both baseline and follow-up; a paired t test assessed the within-person change (i.e., a paired sample).Finally, baseline demographic predictors of meeting the recommendations for total physical activity, leisure-time, and work-related physical activity were assessed using a multivariate logistic regression model.

RESULTS

Table 1 presents selected sociodemographics of the WISER-PS sample (N = 127). The sample was 75% white, and the majority was college-educated. Nearly 20% were married or had a domestic partner, and nearly 10% were parents. The average work schedule was about 30 h per week. Table 1 also presents physical activity characteristics of the sample at baseline, when they reported on activities during the previous year, and 1 year later both as categorical (% meeting the recommended levels) and continuous variables. At baseline (year 1), more than two-thirds of the sample, 69.1%, met the recommended levels of total physical activity. Thirty-five percent did so through a combination of total leisure-time activities. Others met them through one activity: 24.4% did so on the job; 14.2% did so through leisure activities other than walking/cycling; and 11.0% did so through leisure-time walking/cycling. No participant met the criteria through transit-related physical activity alone. In year 2, the proportion who met the recommeded levels decreased to 66.9%. Among those who met the recommended levels, a higher percent met them through total leisure, through leisure other than walking and through walking/cycling. A smaller percent met the recommended guidelines through work-related physical activity alone.

Table 1.

Selected demographic and physical activity characteristics of the WISER-PS sample, US Midwest, 2007–2008

Characteristics				Frequency (%)
Participants randomized into
Exercise group				46.5
Control group				53.5
Race
White				69.3
Black				6.3
Asian				11.8
Other				12.6
Education
Not attending college/university				35.4
Attending college/university full time				42.5
Attending college/university part time				22.1
Decreased school attendance between baseline and follow-up				29.1
Marital status
Married				18.9
Domestic partner				0.79
Divorced/separated				1.6
Never married				78.7
Parent				9.5
Participants meeting recommended PA:
Year 1 (baseline)				69.1
Year 2 (follow-up)				66.9
Participants meeting recommended PA by total leisure activity
Year 1 (baseline)				35.4
Year 2 (follow-up)				45.7
Participants meeting recommended PA at work
Year 1 (baseline)				24.4
Year 2 (follow-up)				20.5
Participants meeting recommended PA by leisure other than walking/cycling
Year 1 (baseline)				14.2
Year 2 (follow-up)				26.8
Participants meeting recommended PA by leisure walking/cycling
Year 1 (baseline)				11.0
Year 2 (follow-up)				14.2
	Mean	SD	Min	Max
Age at baseline	25.3	3.3	18.1	30.8
Body mass index at baseline	24.7	4.7	17.7	40.5
Baseline
Total PA Mets	14.0	11.7	0.7	80.3
Leisure PA Mets	7.3	8.4	0	49.7
Transit-related Mets	0.8	1.2	0	6.6
Work-related Mets	5.9	8.8	0	75.1
Year 2 follow-up
Total PA Mets	14.8	14.2	0.8	114.5
Leisure PA Mets	9.4	9.0	0	57.6
Transit-related Mets	0.5	0.7	0	3.5
Work-related Mets	4.9	8.3	0	73.1

Table 1 also provides the mean MET hours/week in the WISER-PS sample at each timepoint, as well as a breakdown of the contribution of mean leisure time, transit and work-related METs to total physical activity. The mean MET hours/week in the WISER-PS sample at baseline were 14.0 ± 11.7. Among the participants who met the recommended physical activity levels at baseline, the mean MET hours/week were 18.4 ± 11.5. Among the participants who did not meet the recommended levels, the mean MET hours/week were 4.1 ± 2.0. One year later, the mean MET hours/week in the WISER-PS sample were 14.8 ± 14.2. Among the participants who met the recommended physical activity levels in year 2, the mean MET hours/week were 19.8 ± 14.9. Among the participants who did not meet the recommended levels, the mean MET hours/week were 4.7 ± 2.0.

Figure 2 presents the mean MET hours/week and the proportion of total physical activity per type of physical activity among those who met physical activity recommendations at both timepoints. At baseline, the largest portion of physical activity was work-related, followed by leisure activity other than walking/cycling (i.e., sports and exercise). One year later, the proportions nearly reversed: the largest portion of physical activity was leisure activity other than walking/cycling, followed by work-related physical activity. Leisure-time walking/cycling remained fairly stable, while transit-related walking/cycling declined. Stated in terms of the percent each form of activity contributed to the totals among those who met physical activity recommendations, at baseline, 41% of physical activity was work-related, 29.9% was leisure activity other than walking/cycling, 23.2% was leisure-time walking/cycling, and 5.9% transit-related walking/cycling. In year 2, among those who met the recommendations, 40.8% of physical activity was leisure activity other than walking/cycling, 32% was work-related, 23.4% was leisure-time walking/cycling, and 3.8% was transit-related walking/cycling. A two-sample test of proportions did not, however, indicate significant differences in the proportional distribution by activity type at the two timepoints.

Fig. 2.

Mean MET values at baseline (year 1) and year 2 by type of physical activity, WISER-PS study (2007–2008)

The results of analysis of the 63 participants who met the physical activity recommendations both in year 1 and year 2 (the paired sample), show a similar pattern to those who met them at one or both timepoints (the non-paired sample). At baseline in the paired sample, 42% of total physical activity was work-related, 31% derived from leisure activity other than walking/cycling, 21% came from leisure walking/cycling, and 6% was transit-related. One year later, the same changes occurred, with one exception: in the reduced paired sample compared to the non-paired sample, there was a greater increase in the proportion of the total physical activity related to exercise (t test = −2.16, p = 0.03; data not shown).

Table 2 presents the multivariate logistic regression model exploring the demographic characteristics associated with meeting the recommended levels of physical activity for the total physical activity, leisure-time physical activity, and work-related physical activity. Transit-related physical activity is not included, given that no participant met the recommended levels of physical activity through active transit alone. After adjusting for baseline activity level, the only demographic characteristic that was significantly predictive of participants meeting the recommendations through total physical activity was parenthood. Participants with children were 87% less likely to meet the recommendations in year 2 (OR = 0.13, 95% CI = 0.03–0.59), although the confidence interval is large, reflecting a small proportion of participants with children. A predictor of meeting the recommendations through leisure-time physical activity in year 2 was meeting the recommended levels at baseline (OR = 3.10, 95% CI = 1.37–7.36). There were no significant demographic predictors of meeting physical activity recommendations through work-related activities (data not shown).

Table 2.

Multivariate logistic regression model of demographic characteristics predicting participants meeting total physical activity (PA) recommendations and meeting PA recommendations through total leisure-time activity, WISER-PS 2007–2008

	Total PA: Meets recommendations		Leisure PA: Meets recommendations
	Odds ratio	95% CI	Odds Ratio	95% CI
Intervention	0.80	0.35, 1.82	1.51	0.68, 3.34
Baseline value	2.61	0.99, 6.86	3.10	1.30, 7.36
White	0.56	0.20, 1.57	0.85	0.34, 2.12
College-educated	1.18	0.43, 3.23	0.92	0.36, 2.36
Married	0.72	0.25, 2.05	0.64	0.22, 1.88
Parent	0.13	0.03, 0.59	0.35	0.07, 1.78
Student at baseline
Full-time	1.0		1.0
Part-time	3.14	0.95, 10.41	2.33	0.81, 6.68
Non-student	1.60	0.52, 4.97	0.76	0.25, 2.28
Work hours	0.98	0.96, 1.01	1.02	1.00, 1.05

DISCUSSION

Our longitudinal data of the same 6 calendar months over two consecutive years indicated that young women who met the recommended guidelines of physical activity showed an increase in the proportion of their physical activity from leisure-time activities. At baseline (year 1), the proportion of leisure time, compared to lifestyle activities, was 53.1%; whereas one year later, the proportion of leisure-time activities was 64.2%. We therefore found some support for our hypothesis that, to be successful in meeting the recommended levels of physical activity, young women engaged in leisure-time physical activity; lifestyle physical activity alone did not provide sufficient physical activity.

We found at both timepoints that young women who were successful in meeting the recommended levels of physical activity used a combination of leisure time and lifestyle physical activities. In year 1, work-related physical activity provided the highest portion of total physical activity, followed by leisure-time exercise/sports, walking/cycling for leisure, and finally transit-related walking/cycling. In year 2, leisure-time exercise/sports provided the highest proportion of physical activity, followed by work-related physical activity. Leisure-time walking/cycling remained constant. The changes in proportions were not, however, statistically significant. The shift in some types of physical activity, however, suggests participants may have made a point of being more physically active in their leisure time, possibly compensating for declines in work-related physical activity. The finding that both work- and transit-related physical activities declined in year 2 may reflect occupational shifts away from campus.

In year 2, we found a decline in the proportion of women who met the recommended levels of physical activity, from 69.1% at baseline to 66.9%. There were no significant differences between exercisers and controls in the amount of physical activity 6 months after completing the intervention. Instead, physical activity at baseline predicted on meeting the recommended levels the following year, suggesting the importance of prior socialization [23]. Our WISER-PS sample of young women (aged 18–30 years at baseline) was drawn from participants in an exercise trial in which the intervention group completed, five times weekly, aerobic exercise for approximately 4 months. Although the study goal was to recruit insufficiently active women, we learned from the self-report survey administered subsequent to their enrollment in the study (compared to the brief screen used in recruitment) that many were already meeting the recommended levels of activity. Women who used active transport were allowed not to include that form of activity in their eligibility screening survey, given that that form of activity is highly seasonal in the US Midwest, where the study took place, and not likely to change as a result of the intervention we had planned. The finding that the WISER trial did not lead to a sustained behavior change may have in part been related to the somewhat brief time frame of the intervention, resulting in a lack of change, and in part related to the sample, which was comprised by many already active women among the controls as well as exercisers. Quite possibly, those who joined the WISER trial were already interested in increasing their exercise. In our observational study examining participants' physical activity prior to and after the exercise trial, the decline in physical activity over time across the sample suggests the greater importance of individual factors, factors relating to life transitions (parenting), and factors structuring lifestyle (i.e., occupational activities) compared to the short term intervention.

Regarding factors structuring lifestyle, studies of physical activity among students and among employed young adults show conflicting results. Yang found that those young adults who were studying were more active than young working adults [23]. Some studies have found that being employed, rather than unemployed, has been associated with higher levels of physical activity [24,25], while others have found paid work associated with inactivity [5,8]. The association between more work hours and meeting the recommended levels suggests that having available time may be less important to young women's ability to incorporate physical activity into their lives than having a structured lifestyle, whether as students or not. A research based on social cognitive theory similarly suggests that self-regulation (i.e., planning and organization skills) influences physical activity and may mediate self-efficacy [26,27]. Control over one's work schedule and environmental influences on physical activity may also be factors influencing such variance. The findings of this study contribute to efforts to identify the most feasible and effective means by which subgroups of the population can meet the recommended levels of physical activity, taking into account the structure of their other activities of their lives. In our study, a possible trend was observed where working more hours predicted meeting the recommendations through leisure-time activities.

The findings of this study on the importance of walking to achieving the recommended levels of physical activity can be related to larger data sets. Between 1987 and 2000, nearly half (45.6%) of US women met the recommended levels of physical activity by walking alone; nearly one third (32.2%) met them by means other than walking [28]. Surveillance data (from NHANES 1999–2004) found that adults who are physically active beyond walking are more likely to meet the recommended guidelines [29]. From our study of physical activity over 2 years, we found that 11% of participants in year 1 and 14% in year 2 met the recommended levels by walking/cycling alone, and that 14% and 27%, respectively, met them by leisure-time activities other than walking. For most participants in our study, walking/cycling for transit was not by itself sufficient to meet the recommended levels, but it did offer a worthwhile complement to other forms of physical activity. A larger study with adults 18 years old and above in California found that active transit was significantly associated with achieving the recommended physical activity guidelines [15].

Finally, we found that the demographic factors predicted changes in physical activity. Not surprisingly, we found that parenting did not favor meeting the recommended guidelines of physical activity. A meta-analysis of 25 studies has found that parenting is associated in lower levels of physical activity, especially among women [30]. Parenting may translate to a sheer lack of time for parents' own health practices. However, it is important to note a limitation in the self-reported questionnaire used in this study, which did not inquire into household or caregiving activities. The 2003–2004 American Time Use Survey shows that childcare and home production add up to about 90 min of additional work hours per day among mother; mothers of young children have only 75 min of discretionary leisure time per day [31]. It is possible that participants with children were meeting the recommended levels through family and household activities, but these were not reported [32].

This study had limitations. There was no objective measurement of physical activity, but rather, one self-reported physical activity survey was used. Self-reports of physical activity are subject to recall bias. The survey included physical activity in relation to occupational and leisure activity but not household and caregiving. A trend observed of meeting the recommended levels of physical activity in association with hours of work may not have reached a statistical significance owing to the small sample size. The sample largely comprised students. We were unable to examine the changes specific to those graduating, and we did not collect information on other life changes, such as marriage, birth of a child, or other factors that may explain some of the findings. Strengths of this study include the longitudinal data set, allowing us to track changes in several types of physical activity over time.

CONCLUSION

Over 2 years, the young women who met the recommended physical activity levels used a combination of leisure and lifestyle physical activity, and they increasingly engaged in leisure time compared to lifestyle physical activity.