We showed that higher depression scores were associated with higher physical activity barriers when adjusting for sociodemographic and clinical variables. There was a quadratic effect of depression on physical activity barriers, so that as CES-D scores increased, the positive relationship with physical activity barriers tapered off. These results indicate that depression level is a particularly important factor to consider when designing physical activity interventions for physically inactive women.
Our study shows that physical activity interventions for inactive women with depression diagnoses or symptoms may benefit from taking into account their greater perceived barriers to engaging in exercise. Many physical activity interventions still use a ‘one size fits all’ approach. For instance, a review paper illustrated that unique barriers to physical activity in mental health are usually not accounted for within behavior change theories used to design physical activity interventions(27). This may be one of the reasons that individuals with depression are less likely to engage in exercise programs, especially when they have a low baseline level of fitness(10). Previous work shows that physical activity interventions are more effective when they are tailored to subgroups like women and ethnic minorities(28). These findings suggest interventions may further increase their potential by tailoring depression levels as well.
Most important barriers for physical activity
For the sample as a whole, we identified that willpower, lack of time and lack of energy were the most significant barriers whereas injury and lack of skill were less often reported. This is consistent with previous research in physically inactive pregnant women and a community sample of Brazilian women, also using the same barriers scale(29, 30).
The Barriers to Being Physically Active Quiz subscales that were most associated with depression in a posthoc analysis were the Social Influence and Lack of Energy subscales. Although we assessed these relationships in an exploratory analysis, these barriers may be the driving factors behind the differences in total subscale scores.
The Social Influence subscale included statements such as: “None of my family members or friends like to do anything active, so I don’t have a chance to exercise.” and “I’m embarrassed about how I will look when I exercise with others”. A lack of social support has been suggested as a risk factor for physical inactivity before(31), and our results show that this may be even more important in women with high depression scores. A review on physical activity barriers in depression (not specific to women) also identified other people’s behaviors and a lack of social encouragement as important barriers, and social support as a facilitator(14). Other research found that having a family member who exercises, or who encourages exercise, motivates engaging in healthy behaviors(32). Our findings also suggest that self-consciousness in social exercise-related situations (e.g. appearance towards others when exercising) may be an important factor discouraging women with higher depressive symptoms from physical activity.
The Lack of Energy subscale includes statements like: “I’m too tired after work to catch up on exercise”, and “I need the weekend to catch up on sleep”. A lack of energy and increased fatigue are symptoms of depression. Low energy was also identified before as one of the most important barriers in men and women with depression(14). Of note, changes in physical activity may improve energy, and reduce the magnitude of perceived energy as a barrier(29).
Our posthoc results, though they need to be confirmed in future work, suggests the need for an emphasis on social influence and boosting energy to increase the effectiveness of physical activity promotion. Physical activity interventions could, for instance, integrate social support from family or friends, utilize peer-support or use community-based structures. Furthermore, exercise interventions can build-in graded exercise, personalized to a women’s individual fitness levels to help slowly overcome feelings of fatigue(33). Future work should also quantify and integrate facilitators to exercise in women with high depressive symptoms. In mixed gender populations with depression, facilitators included having a reason for exercising, being able to identify the psychological benefits of exercise, having positive social support and integrating cognitive behavior change strategies(34).
Physical activity interventions are increasingly delivered in digital formats and via smartphones, using apps, and text-messaging and conversational agents. There is a growing interest in adaptive interventions, which alter their content based on the day-to-day behavior of individuals(35). We argue that physical activity interventions should both adapt to individuals’ daily changing circumstances, and tailor their content to overcoming barriers of user subgroups.
The quadratic effect of depression
After a depression score (CES-D) of around 20, past the clinical cut-off for identifying individuals at risk for clinical depression (≥ 16), physical activity barriers no longer increased with higher scores. We can’t make finite conclusions about why this effect tapers off but there are multiple possible explanations. First, for participants with higher depression scores, physical activity may not be a priority and therefore they are less aware of their physical activity barriers. Another potential explanation is that the Barriers to Being Physically Active Quiz scale doesn’t capture all barriers that are relevant when women reach more severe levels of depression. For instance, previous research(36) showed that in severe mental illness, low mood and stress are perceived as the most significant barriers for physical activity, followed by social support. In addition, in outpatients with depression, physical exertion was the most common reported PA barrier(37). The Barriers to Being Physically Active Quiz scale used in this study assess lack of energy, but it does not capture whether low mood, high stress or physical exhaustion prevent women from exercising. We recommend these questions be included in future versions.
One caveat here is that our data were sparse for very high depression scores, making these estimates less precise. Further, when we retained influential observations in the model the quadratic effect lost significance. Future work should assess differences in barriers between women with slightly elevated symptoms and clinically diagnosed depression.
Age, employment and physical activity
Another interesting finding was the inverse relationship between age and perceived physical activity barriers. In our posthoc analyses higher age was associated with lower barrier subscale scores, except for the injury and skills scales. These findings complement previous work in community samples showing that younger adults, both men and women, (25–44 years) report most physical activity barriers, and older adults (> 65 years) least(38). In line with our findings, earlier work has also identified lack of time and energy due to family and household responsibilities among the top barriers to physical activity for women(39). Older women may be less impacted by these responsibilities.
Finally, full-time or part-time employment was associated with higher barriers opposed to unemployment. Past work revealed that working women perceived lack of time and energy as most frequently reported barriers to physical activity(26). Future interventions may want to incorporate strategies for promoting physical activity into working hours to overcome these barriers for working women.
Strengths & Limitations
We included a relatively large sample of diverse women. To our knowledge, this is one of the first studies to systematically examine the relationship between physical activity barriers and depressive symptoms in women using the instrument that was developed and validated by the CDC(14).
A limitation is that findings may be specific to our sample of female adults aged 25–65 years with relatively high levels of education from the San Francisco Bay Area. Our sample included fewer women with high depression scores, i.e. CESD > 20, therefore the estimate of the relationship may be less reliable after these higher scores. In addition, our analyses are cross-sectional, thus don’t allow us to understand the causal relationship between perceived barriers and depression. This should be explored in future work. Another limitation may be selection bias. Since we included women who signed up to participate in a physical activity intervention, the study participants might be more motivated to engage in physical activity. Further, women with higher depressive symptoms are less likely to participate in the study. This may in part explain the tapering off effects we observe for high depression scores.