A majority of the existing research on attrition has been conducted in strictly controlled clinical trials, and may not be generalizable to the general population seeking weight management. In the general population seeking weight management, we observe that younger age and certain health conditions were associated with both early attrition and lower WL success in both sexes. In addition, lower educational attainment in males and smoking status in females predicted only early attrition whereas, females of ethnic minorities only had lower WL success. As none of the characteristics were associated with WL success after adjusting for treatment time, these results suggest that greater time in treatment may be beneficial for WL success.
We observe that the duration of treatment was an independent predictor of weight loss, which is in accordance with previous literature [13, 14]. Longer treatment times may be important as it may allow for continued support [13], and provide patients with a greater opportunity to practice the behaviors necessary for long term WL success [14], which may aid in reducing attrition and improve weight loss success. Conversely, greater weight loss may be the motivating factor leading to longer treatment length, however, we and others [13, 14] observe that those with longer treatment time had a lower rate of weight loss. Thus, as the rate of weight loss is lower, it is unlikely that the weight loss is the motivating factor for patients to remain in treatment. Given the low success of independent weight management after formal weight loss programs cease [13, 15], it may be important to reframe obesity as a chronic condition and provide chronic clinical care.
Our study reports that older age is associated with lower early attrition and greater weight loss success, which is in accordance with some studies [6, 9] but in contrast with others that report no influence of age on attrition [16–18]. The studies that did not observe associations between age and attrition had smaller age ranges consisting of mainly younger or middle-aged participants [16–18], as opposed to our study that also included younger, middle-aged and older adults. These age-related differences in attrition may be explained by several factors. Younger individuals may not be able to attend treatment as frequently as older individuals as they may have the extra burden of childcare [6], have less financial stability [6], may not be able to take time off work [6], or may be less motivated to improve their health [19]. In some settings, patients seeking medical treatment from weight management clinics may also be faced with additional barriers such as long wait times or distance to the clinic. As attrition and weight loss are related, the lower weight loss success in younger patients as compared to older individuals may also be due to their greater early attrition. Therefore, there may be a need to adopt specific strategies that cater to younger individuals, in order to improve treatment attendance and weight loss success.
Previous literature on attrition and weight loss often excludes participants who have existing obesity-related health conditions [16, 20, 21] such as T2D [22], depression, or a history of cancer [23] while others make no mention of participant health conditions [7, 17, 24]. In our study, having certain baseline comorbidities such as depression or hypertension is associated with both greater early attrition and lower WL success depending on sex. Our findings are consistent with previous studies [19, 22, 25], but contradict several others that do not observe comorbidities to be associated with differential attrition or weight loss [18, 26]. For example, having depression may interfere with weight management as it is often associated with symptoms such as lethargy and lack of motivation [25], or uncontrolled eating and substance abuse [25], which may make weight loss or attendance more difficult. The remaining health conditions such as hypertension or cancer may be related to attrition as they may reduce quality of life [27] which may in turn increase attrition and reduce weight loss success. However, the relationship between hypertension, cancer and their effect on WL and early attrition is less clear and warrants future investigation. Other factors such as the use of medications are also important to consider as they can be associated with weight gain [28]. Therefore, participants may require more flexible treatment options and a more tailored approach in order to improve WL success and reduce early attrition depending on their comorbid conditions.
Lower educational attainment was related to greater early attrition in only males, and was not related with weight loss success in either sex. Our findings are consistent with some previous research studies [21, 29] which report an association between education and attrition, but differ from others which report no relationship between education and attrition [10, 16]. Education may be related to greater early attrition as education is often a marker of SES [21]. SES may be associated with lower weight loss success in patients of ethnic minorities, however, income was poorly completed in our study because of which we could not include SES information in our study. As the clinic is publically funded, patients often questioned the importance of completing questions related to income as the program is offered at no cost to the patients. As a result, our study used education as it is often related to health literacy and income [1, 21, 30]. Therefore, patients with lower education or SES may have greater attrition due to inflexible work hours [21, 29], transportation or parking costs, or reliance on public transportation which may make it more difficult to attend treatment. Although education was associated with greater early attrition, education level did not influence weight loss success in our study. The program at WMC is purposefully designed so that it will be understandable and accessible to those with more modest English language facility and health literacy. Patients are also in regular contact with their physician, which is important in building a trusting and collaborative physician-patient relationship which has been reported to help overcome obstacles to weight loss [24]. Thus, while low educational attainment does not appear to limit weight loss success, it may still be associated with greater early attrition in males. Additional accommodations may therefore be necessary to reduce early attrition in patients with lower education.
With regard to smoking status and attrition, the current literature has reported mixed findings [9, 10, 18, 19, 21, 25]. Two studies [9, 19] demonstrated no relationship between smoking status and attrition in patients in a randomized weight loss trial [19] and a clinical weight management program [9]. However, these studies frequently contacted patients who missed program visits [9] or had a long run-in period prior to study inclusion [19], which may have improved treatment compliance and made it harder to discern differences in attrition by smoking status. In our study, we observe greater early attrition in patients who smoke. Patients who smoke might have been discouraged from attending weight management treatment after physician consultations regarding the negative effects of smoking. Additionally, as smoking cessation is often associated with weight gain [31], it may be particularly discouraging for patients seeking weight management treatment. However, although smoking status was related with greater attrition, it was not related with differences in weight loss in our study. Taken together, these findings suggest that these individuals may not be attempting to stop smoking or that the treatment provided may be adequate in combatting post-cessation weight gain. As early attrition continues to be a challenge, particular attention should be focused on reducing early attrition in patients who smoke.
Currently, relatively few studies have been adequately powered to examine differences in attrition by ethnicity as most studies have often reported small samples of ethnic minorities [n = 57 to 78] [6, 19, 22]. For example, the only study to report greater attrition in Black patients compared to White individuals attending a clinic based weight loss program had the largest sample of ethnic minority patients [n = 78] [6]. In contrast, two studies [19, 22] reported no association between ethnicity and attrition but had comparable sample sizes of Black [n = 61] [22] and Other [n = 76] [19] ethnic patients to the above study [6]. Although we had a significantly greater number of non-White patients [n = 1229] from a more diverse ethnic background as compared to the mentioned studies, we also did not observe differences in attrition between patients who were White, Black, Asian or Other ethnic background. This may be due to the ethnic diversity of the staff at WMC, which may make the patients feel more comfortable and remain in the program longer. Although ethnicity did not influence attrition, females of ethnic minorities had lower weight loss success compared to White females. Our findings are similar to the findings of Fabricatore et al. [19] who reported lower WL success in Black individuals when compared to White individuals. Individuals of ethnic minorities may have lower WL success, as the majority of the staff at the clinic are trained in providing dietary advice using predominantly North American foods. This may make the WMC dietary intervention less effective for those who normally consume their own ethnic foods. In addition, differences in weight management outcomes may also be due to physiological differences such as resting metabolic rate [19] or language barriers [32]. Given the differences in weight loss success amongst ethnic groups, it may be important to provide strategies tailored to these ethnic differences as it may improve WL success, particularly as many of these ethnicities are reported to be more likely to have obesity related comorbidities at lower levels of obesity.
Therefore, we observe that patients that are in treatment for longer than 6 months tend to see greater weight loss compared to those in treatment for less than 6 months. As weight loss is quite variable in our study ranging from 3 months to 20 months, the differences in the length of treatment between individual patients may account for and impact the overall weight loss reported in our study. Our results demonstrate that both weight loss and treatment time are related, as those who have longer treatment time observe larger weight loss success [13, 15]. Although majority of the patients discontinue treatment before 6 months, WMC makes an attempt to reduce attrition by encouraging more frequent visits (once every 4-6 weeks) in order to continue assisting with weight loss with the eventual goal of weight maintenance. In addition, more frequent visits have also been related to less abandonment of treatment and greater weight maintenance. As previous research [33] indicates a diminishing of weight loss around 6 months, our program tries to focus towards behaviours of weight maintenance. Currently, our program mirrors the real life obstacles faced by patients who are in weight management programs and thus we suggest that patients attend clinic regularly in order to improve treatment success, maximize their weight loss and practice behaviours necessary for weight maintenance.
Our analysis has several strengths and limitations. To our knowledge, this is the first study with such a large ethnically diverse clinical sample. This large sample allowed us to stratify our findings by sex as opposed to statistical adjustment, which is important given the clear sex differences that are commonly observed in health and obesity research. Our sample also consisted of patients that are often excluded from clinical trials. Despite these strengths, our study also has several limitations. Due to the observational study design, our findings cannot imply causation. Furthermore, there are many other factors that we did not assess which may have an effect on attrition and weight loss, such as eating behaviors (weight cycling, binge eating), logistics (travel distance, income, environment), personality and physical health.