Abstract
Purpose:
To determine whether Hispanic residents receiving the Healthy Fit intervention enhanced with Motivational Interviewing (MI) experienced greater improvements in body composition, relative to participants receiving the initial intervention.
Design:
Quasi-experimental evaluation.
Setting:
El Paso, Texas.
Sample:
Among 656 baseline participants, 374 (54%) completed the 12-month assessment.
Intervention:
In Healthy Fit, community health workers (CHWs) promote nutrition and exercise. To strengthen intrinsic motivation and help participants overcome barriers to change, we incorporated a 30-minute motivational interview into the baseline assessment. Follow-up phone calls at 1, 3, and 6 months were identical across conditions.
Measures:
CHWs assessed body mass index (BMI) and body fat percentage (BFP) using a bioelectrical impedance scale.
Analysis:
Regression models estimated differences between intervention conditions on change in BMI and BFP from baseline to the 12-month assessment.
Results:
Participants receiving MI had 2.13 times higher odds of losing weight (OR = 2.14, 95% CI [1.30, 3.53], P = .003) and 2.59 times higher odds of reduced BFP (OR = 2.59, 95% CI [1.51, 4.41], P < .001), relative to initial intervention participants. MI participants lost an average of 1.23 kg (2.71 lbs.) and their BFP declined 2% over 12 months.
Conclusion:
Findings suggest CHW use of MI is a promising approach for promoting incremental changes in diet and exercise, which Healthy Fit integrates into a low-cost intervention.
Keywords: community health workers, motivational interviewing, obesity, hispanic health disparities, health equity
Obesity is a leading cause of preventable death and a prominent health disparity among Hispanics and other minority populations.1,2 Individuals attempting to improve their diet and exercise are met with a complex set of environmental, cultural, and social barriers that interfere with sustainable lifestyle changes.3 Intrapersonal factors also interfere with behavior change initiation and maintenance, such as lack of motivation or ambivalence to change.4
These barriers are disproportionately experienced by underprivileged groups such as Hispanic populations who are more likely to have lower educational attainment, lower income, and be uninsured.1 Acculturation, the process of adopting behaviors and attitudes from a new culture, may also influence risk among immigrants.5 Less acculturated Hispanics are less likely to exhibit correct weight perception, weight loss intention, and weight loss success.6 Common perceived barriers to not engaging in regular physical activity among Hispanic adults include not having enough time due to existing responsibilities, fatigue, lack of interest, and lack of self-discipline.4 Physical activity is often viewed as a waste of time and unnecessary beyond regular daily activities.7
Community Health Workers as Change Agents
Low-income Hispanic communities are often hard-to-reach with few culturally and linguistically appropriate programs available.8 Community health worker (CHW) driven interventions have been successful in reaching Hispanic populations because CHWs are from the focal community and use their shared experiential knowledge to connect with the focal population.9 CHWs link community members to health care by establishing peer-to-peer communication and building trusting relationships.10 CHWs have been used widely in health promotion programs addressing outcomes such as obesity, asthma, hypertension, diabetes, cancer screenings, maternal and child health, and infectious diseases.10-12 As local experts who bring education and services to underserved communities, their involvement in developing and delivering interventions can close health disparities.11
Understood through Diffusion of Innovations theory, CHWs receive training to operate as community change agents, providing both safety and competence credibility when helping people adopt new behaviors.13,14 The cultural competence of CHWs is key to their effectiveness as change agents because it allows for culturally tailored communication and problem solving.15 Research suggests culturally tailored interventions are more effective in promoting physical activity and preventing obesity among immigrants.16
Motivational Interviewing
To address lack of motivation and ambivalence towards health behavior change, motivational interviewing (MI) has been incorporated into several weight loss interventions delivered by highly trained professionals.17 MI increases the chances that individuals make a health behavior change by increasing intrinsic motivation.18 MI also allows for the provision of stage-dependent tailored feedback, which can improve healthy eating and physical activity.19 The client-centered interviews explore and resolve ambivalence toward change while strengthening commitment to change. The spirit of MI emphasizes autonomy by supporting participants as experts about themselves.20 During MI conversations, interviewers seek to engage participants in change talk, where they express willingness to make a behavior change. However, change talk may be accompanied by sustain talk, where participants provide reasons to not make a change.21 Encouraging change talk while shifting away from sustain talk is delicate. Confrontation and persuasion on the part of the interviewer may elicit resistance and soften change talk.21,22
The MI approach is different from advice and information oriented programs because it focuses on building a collaborative relationship to identify and overcome barriers.23 CHWs trained to implement MI with fidelity are ideal change agents because they are well positioned to provide emotional validation due to their shared lived experience, which serves to establish a trusting partnership and helps ignite motivation.24 Research suggests MI adherence by CHWs improves over time and is achievable.22 By using MI skills to resolve resistance, CHWs can support participants in committing to a diet and exercise plan and help them maintain behavior changes.
Although the integration of CHWs and MI for obesity is novel, non-CHW weight loss programs with an MI component have promising results.17 For example, there was an average weight loss of up to 8% in the Look AHEAD Lifestyle intervention.25 In another randomized trial, women who received MI counseling lost significantly more weight compared to women who received health education only, with weight loss maintained 18 months after the intervention.26 However, more research is needed on MI effectiveness in Hispanic populations.27
Purpose
This study evaluates Healthy Fit (En Forma Saludable), which uses CHWs to extend public health department infrastructure, in an effort to reduce health disparities related to cardiovascular disease and access to preventive health services in a low-income Hispanic population on the US-Mexico border.28 Following a health screening identifying participants who were overweight, CHWs encouraged participants to complete activities in a fotonovela (a culturally tailored health education comic book) designed to improve physical activity and nutrition. CHWs also encouraged participants to join community-based exercise programs.
After implementing the standard Healthy Fit intervention, we developed an enhanced version of Healthy Fit, which added an MI protocol that CHWs used to promote diet and exercise. The current study is a natural experiment, which compares body composition outcomes at 12-month follow-up among participants who received the standard Healthy Fit intervention to those who received the MI enhanced Healthy Fit intervention. It is the first study to our knowledge to examine CHWs using MI to address obesity. Given other MI interventions’ success with improving health behaviors,23,27 we hypothesized that participants receiving the MI enhanced intervention would have improved body composition (body mass index and body fat percentage) at 12-month follow-up as compared to participants who received the standard intervention.
Method
Design
This longitudinal quasi-experimental evaluation of Healthy Fit examines participants who completed baseline and 12-month follow-up measurements of body composition. A total of 782 participants were recruited between February 2015 and April 2017. Figure 1 provides a CONSORT flow diagram of participant selection and allocation, explaining how we ended with a final sample of 374 participants, of which 97 received MI and 277 completed the standard intervention. The first author’s institutional review board approved all study procedures. There were no adverse events or protocol deviations noted, other than occasional data collection errors that led to missing data.
Figure 1.
Consort flow diagram of participant selection and allocation.
Sample
The program targeted residents of El Paso County, Texas who were 18 years or older and who were uninsured or Medicaid beneficiaries; however, participants with insurance were not excluded. The only exclusion criterion was for pregnant women because of our interest in tracking body composition changes over time. El Paso County is a predominantly Hispanic (83%) population with 20% living in poverty and 23% uninsured, compared to 17% uninsured in Texas and 9% in the US overall.29 El Paso County is also medically underserved and has a high percentage of residents with overweight or obesity (68.2%), putting them at risk of chronic diseases.30 CHWs recruited participants from community events, health fairs, and local agencies that serve low-income, Hispanic populations. CHWs also encouraged participants to refer friends and family members via word-of-mouth, which helped recruit other participants of similar socioeconomic status.
Intervention
After obtaining written informed consent for participation in Healthy Fit, CHWs administered a baseline health screening, which took approximately 20 minutes. Participants who were overweight or had elevated blood pressure, according to American Health Association guidelines, received fotonovelas and physical activity resources.31 The fotonovelas were from the Mi Corazón Mi Comunidad (My Heart My Community) curriculum previously tested as part of Project HEART.32 Written at an elementary literacy level, the fotonovelas contained culturally-tailored information and activities to improve diet and exercise.
CHWs also shared a list of exercise activities that were free or donation-based, including Zumba, yoga classes, aerobics classes and walking groups. After reviewing the participant’s body measurements in relation to their risk of chronic disease onset, CHWs explained how participants could use the resources to improve their body composition measurements and reduce their risk of chronic diseases. Other Healthy Fit referrals that the participant could receive, but are not the focus of this study, included vouchers for free breast, cervical, or colon cancer screening, vaccine vouchers, a list of low-cost primary care providers, a tobacco cessation guide, and a guide to help reduce risky drinking.
Motivational Interviewing in Healthy Fit
After implementing the standard intervention protocol for 1 year, CHWs received training and ongoing supervision on the enhanced MI protocol, which was designed to promote intrinsic motivation for targeted behavior changes. In this program, CHWs used MI to address participant’s ambivalence towards utilizing a specific health referral provided through Healthy Fit. After reviewing the Healthy Fit referrals that the participant qualified for, CHWs explained the purpose of the motivational interview so that they could choose the program referral for which they felt the most ambivalence towards. The CHWs then conducted an MI conversation with the participant focused on that specific health referral, which lasted approximately 30 minutes. Most participants (122 of 148 or 82%) chose the referral to improve their heart health through diet and exercise as the focus of their MI conversation. CHWs were trained by a Motivational Interviewing Network of Trainers (MINT) certified instructor. After receiving two 6-hour MI training sessions, CHWs started recording their MI interviews, which were then coded by MI experts following the Motivational Interviewing Treatment Integrity (MITI) scoring system.33 CHWs received feedback from their coded interviews, both individually and in group meetings focused on improving practice. MITI scores were in the fair to good range, with an average technical global score of 3.9 out of 5 and an average relational global score of 3.6 out of 5.
Follow-Up Protocol
In both the MI and standard intervention conditions, CHWs conducted telephone follow-ups 1-, 3-, and 6-months post-baseline to assess and encourage follow through on the referrals provided. At 12 months, CHWs repeated the in-person interview with health screening to assess changes in body composition. The telephone and in-person follow-up protocols were identical in both study conditions. Among the 656 participants receiving either the MI or the standard intervention for diet and exercise, 395 (60%) completed the 6-month telephone follow-up and 374 (57%) completed the in-person 12-month follow-up, as outlined in Figure 1.
Measures
The baseline screening instrument consisted of demographic and health-related questions used to determine referral eligibility. The demographic portion of the survey included questions about the participants’ age, gender, country or origin, years living in the US, language preference, English proficiency, yearly household income, and level of education. A social economic status variable was computed as the mean of educational attainment and yearly income z-scores. An acculturation variable was computed as an aggregate score of language preference, English proficiency, foreign or US-born, and number of years living in the US.
For the health screening, CHWs used the HM200P Port-Stad portable stadiometer to measure height and the Omron HBF-514C full-body composition scale with bioelectrical impedance analysis to measure weight and body fat percentage. Changes in body composition were calculated using the baseline and 12-month follow-up measurements. The primary outcome measures were change in body mass index and body fat percentage. We also created binary weight loss and fat loss variables by subtracting baseline values from 12-month follow-up values, coding weight loss and fat loss as true (= 1) if the difference was negative and false (= 0) if the difference was positive or zero. For health related measures, the interview followed the NIH funded PhenX Toolkit protocols where applicable.34 When pre-existing Spanish versions of the questions could not be found, researchers and CHWs collaborated to translate instruments into Spanish, with back translation into English, as is recommended to refine accuracy of the Spanish translations.35
The 6-month telephone follow-up assessed participant follow-through on CHW recommendations. Participants reported on which fotonovela recommendations and activities they put into practice. We used this data to create a binary variable (fotonovela use) indicating whether participants put fotonovela recommendations or activities into practice. Participants also reported on which organized exercise activities they participated in, such as Zumba, and other exercises they did on their own, such as walking. For each exercise, participants reported how often they did the activity, recorded as times per week. We used this data to create a binary variable (self-reported exercise) representing whether the participant did any exercise and a continuous variable (exercise frequency) representing the number of exercises completed per week.
Analysis
We used SAS version 9.4 to conduct all analyses and multiple imputation to estimate missing data. Logistic regression models predicted weight loss, fat loss, fotonovela use, and self-reported exercise. Linear regression models predicted the repeated measures of body mass index and body fat percentage at baseline and 12-month follow-up, along with exercise frequency at the 6-month follow-up. We included age, gender, socioeconomic status, and acculturation as covariates in all regression models based on evidence of their impact on body composition.36 To test for moderation effects, each covariate was multiplied with the focal predictor, intervention condition (MI or standard intervention), to create an interaction term, none of which were significant and thus dropped from the models.
Results
Table 1 presents the sociodemographic characteristics of the participants, who were predominantly Hispanic, low-income, female, foreign-born, and Spanish speaking. There were no significant differences between the MI condition and the standard intervention on most sociodemographic characteristics. However, participants in the MI condition were less acculturated, as they were more likely to be foreign-born (92% vs 77%, P = .012) and to have spent less than 10 years in the U.S. (41% vs 24%, P = .002). Participants in the MI condition also had higher body mass index (32.7 vs 31.6, P = .095) and higher body fat percentage (45.8% vs 43.1%, P = .003).
Table 1.
Frequency of key sample characteristics by exposure group (n = 374 overall, n = 97 for motivational interview, n = 277 for standard intervention).
Characteristic | Motivational Interview n (%) | Standard Intervention n (%) | P-Value |
---|---|---|---|
Gender | .773 | ||
Male | 13 (13.4) | 34 (12.3) | |
Female | 84 (86.6) | 243 (87.7) | |
Hispanic ethnicity | .377 | ||
Yes | 95 (97.9) | 266 (96.0) | |
No | 2 (2.1) | 11 (4.0) | |
Income | .975 | ||
< $20,000 | 70 (71.1) | 193 (69.9) | |
$20,000–$29,999 | 16 (16.5) | 51 (18.4) | |
$30,000–$39,999 | 6 (6.2) | 17 (6.1) | |
$40,000+ | 5 (5.2) | 15 (5.4) | |
Missing | 0 (0) | 1 (.4) | |
Educational attainment | .842 | ||
< High school diploma | 50 (51.6) | 135 (48.7) | |
High school grad or GED | 20 (20.6) | 69 (24.9) | |
Some college | 18 (18.6) | 50 (18.1) | |
Bachelors or higher | 9 (9.3) | 22 (7.9) | |
Missing | 0 (0) | 1 (.4) | |
U.S. born | .012 | ||
Yes | 8 (8.3) | 51 (18.4) | |
No | 89 (91.8) | 214 (77.3) | |
Missing | 0 | 12 (4.3) | |
Years in U.S. | .002 | ||
<10 | 40 (41.2) | 65 (23.5) | |
10+ | 57 (58.8) | 197 (71.1) | |
Missing | 0 | 15 (5.4) | |
English fluency | .187 | ||
Poor or fair | 79 (81.4) | 196 (70.8) | |
Good or excellent | 18 (18.6) | 66 (23.8) | |
Missing | 0 (0) | 15 (5.4) | |
Spanish language preference | .391 | ||
Yes | 85 (87.6) | 241 (87.0) | |
No | 12 (12.4) | 22 (7.9) | |
Missing | 0 (0) | 14 (5.1) | |
Mean (SD) | Mean (SD) | ||
Age | 48.8 (11.6) | 47.6 (13.0) | .388 |
Body mass index | 32.7 (5.7) | 31.6 (5.6) | .095 |
Body fat percentage | 45.8 (7.0) | 43.1 (8.4) | .003 |
Participants lost to follow-up at 12 months (n = 282) were largely similar to participants included in the analysis (n = 374). However, participants lost to follow-up were more often men (24% vs 13%, P < .001) and had a lower body fat percentage at baseline (41.6% vs 43.9%, P = .003). Among participants lost to follow-up, there were no significant differences at baseline by intervention condition.
In analyses of participant follow-through on CHW recommendations at the 6-month telephone follow-up adjusted for covariates (n = 395), participants receiving MI had 4.78 times higher odds of any self-reported exercise, relative to participants receiving the standard intervention protocol (OR = 4.78, 95% CI [1.99, 11.47], P < .001). In the adjusted model, 92.4% of participants receiving MI reported exercising, whereas 71.2% of participants receiving the standard intervention reported exercising. In terms of exercise frequency, MI participants reported exercising an average of 4.54 times per week, whereas standard intervention participants exercised 3.54 times per week (B = .99, 95% CI [.32, 1.66], P = .004). With regard to fotonovela use, MI participants had 3.71 times higher odds of putting the fotonovela activities and recommendations into practice (OR = 3.71, 95% CI [1.95, 7.07], P < .001), with 82.6% of MI participants and 56.1% of standard intervention participants putting fotonovela activities into practice.
For outcome analyses using the in-person 12-month follow-up data (n = 374), participants who received MI had 2.14 times higher odds of losing weight, relative to participants who received the standard intervention protocol (OR = 2.14, 95% CI [1.30, 3.53], P = .003). In the adjusted model, 72.6% of participants who received MI lost weight, relative to 55.3% of participants who received the standard intervention. Similarly, the odds of a reduction in body fat percentage were 2.59 times higher among participants who received MI, relative to participants who received the standard intervention, after adjusting for covariates (OR = 2.59, 95% CI [1.51, 4.41], P < .001). Among MI participants, 78.4% experienced a reduction in body fat percentage compared to 58.4% in the standard intervention group.
To estimate the magnitude of changes in body composition, we modeled body mass index and body fat percentage over time, adjusting for acculturation, age, gender, and socioeconomic status (Figure 2). Table 2 presents results from these regression models. The time*MI interaction term estimates the difference in change over time between the MI condition and the standard practice condition. Being in the MI condition predicted a reduction in body mass index of .49 (B = −.49, 95% CI [−.93, −.04], P = .03) and a decrease in body fat percentage of 1.62% (B = −1.62, 95% CI [−2.66, −.58], P = .002). As illustrated in Figure 2, participants who received MI decreased their body mass index from 33.08 to 32.63, losing an average of 1.23 kg or 2.71 lbs. Body fat percentage also declined 2%, from 41.6% to 39.6% among participants who received MI.
Figure 2.
Body mass index and body fat percentage from baseline to 12-month follow-up among Healthy Fit participants who received a motivational interview for diet and exercise, as compared to participants receiving the standard intervention, adjusted for covariates (n = 374).
Table 2.
Regression models predicting repeated measures of body mass index and body fat percentage at baseline and 12 months after the initial Healthy Fit assessment (n = 374).
Body Mass Index |
Body Fat Percentage |
|||||
---|---|---|---|---|---|---|
Independent Variables | B | 95% CI | P-value | B | 95% CI | P-value |
Intercept | 32.55 | (30.20, 34.89) | <.001 | 46.80 | (43.95, 49.66) | <.001 |
Time | .03 | (−.22, .28) | .817 | −.35 | (−.91, .20) | .213 |
Motivational interview | 1.12 | (−.20, 2.44) | .096 | 2.78 | (1.13, 4.44) | .001 |
Time*motivational interview | −.49 | (−.93, −.04) | .034 | −1.62 | (−2.66, −.58) | .002 |
Acculturation | .25 | (−.87, 1.37) | .657 | .64 | (−.58, 1.87) | .30 |
Socioeconomic status | −.80 | (−1.73, .13) | .093 | −1.19 | (−2.31, −.07) | .037 |
Age | −.02 | (−.07, .02) | .319 | −.50 | (−.11, .01) | .089 |
Gender | .95 | (−.80, 2.69) | .287 | −11.41 | (−13.53, −9.30) | <.001 |
Discussion
Consistent with our hypotheses, participants receiving the intervention enhanced with MI lost more weight and body fat relative to participants who received the standard intervention. Although weight loss was modest (1.23 kg or 2.71 lbs.), the intervention was of limited intensity, with an initial MI conversation of approximately 30 minutes, followed by 10-20 minute phone calls at 1, 3, and 6 months post baseline. Furthermore, the participants receiving MI had more than twice the odds of losing weight, with 73% losing some weight. Even though weight loss was often not clinically significant, not gaining weight may be considered meaningful, as many adults gradually gain weight over their lives.37 Small and incremental changes in diet and physical activity can have important health benefits over time beyond weight loss, including improved mental health.38-40 A longer-term intervention, with ongoing motivational support from a CHW, may produce more substantial changes in body composition over time.
It is important to note that the standard intervention was not inconsequential and intervention effect sizes may have been larger if the comparison group received no treatment. Previous research suggests the standard intervention was effective in helping people make health behavior changes and increase physical activity.28 Specifically, an earlier evaluation of the standard intervention found that 70% of participants read the fotonovelas and completed 1 or more of the recommended activities for improved heart health.28 Some example fotonovela recommendations are meal planning and strategies to reduce saturated fat consumption. Additionally, 79% of participants took up an exercise activity, such as walking, running, or going to the gym, going an average of 4 times per week.28 Research also suggests the standard intervention led to improvements in body composition at the 12-month follow-up, especially among less acculturated individuals.41
This study’s findings are consistent with previous research on MI, which suggests it is a helpful strategy for supporting behavior changes related to diet and exercise.23,42 Findings not only bolster the evidence for using MI to address obesity but also suggest CHWs can effectively deliver interventions in an MI compliant manner when provided ongoing feedback and coaching. CHWs are sometimes exposed to MI concepts but are not offered ongoing practice with feedback and coaching. Our experience suggests feedback and coaching are essential for CHWs to integrate MI techniques into their practice. It represents a major shift in approach, as CHWs often default to giving advice and offering didactic health education.23 However, when successfully integrated into practice, building the MI skills of CHWs may substantially improve their ability to promote the adoption of health behaviors in the communities they serve.23
Unlike the standard Healthy Fit intervention, MI allowed the CHWs to address several factors influencing participants’ motivations and abilities to make lifestyle changes, such as mental health issues and personal family dynamics. CHWs using MI were able to guide participants in identifying relevant issues and strategies to address barriers, helping them visualize the process involved in changing behavior. Future studies can analyze MI conversations to identify core barriers and motivating factors expressed by participants, estimating the magnitude of their relation to behavior change. With core barriers and motivating factors identified, interventions may then be able to offer resources that address barriers while strengthening the most salient motivating factors.
Study Strengths and Weaknesses
This study has several strengths and some important limitations. The use of the biometric outcomes of body mass index and body fat percentage are important study strengths that avoid problems with self-report bias. The examination of body composition changes over 12 months also helps to ensure the body composition improvements are sustainable. The presence of a control group is another important strength of the study design that enhances causal inference. However, the use of a quasi-experimental design rather than random assignment is an important weakness that limits causal inference. One potential consequence of the non-random assignment is that participants in the MI condition were less acculturated to the United States and had higher body fat percentage. Over time, our recruitment strategies were refined to focus more exclusively on high-risk immigrant communities, which were always the focal population despite an absence of exclusion criteria related to income or immigration status. Our success reaching such a vulnerable population facing obesity disparities is an important study strength. However, it is unclear how generalizable the findings are to other communities.
Another potential generalizability limitation is related to gender. Most participants were women (87%), which reflects greater interest in Healthy Fit participation among women. This may in part be due to our reliance on female CHWs and also offering vouchers for free breast and cervical cancer screenings, which helped attract participants. Although interaction analyses testing for gender differences on the effect of MI on body composition produced null findings, MI effect sizes on body composition were larger among men than women (findings not shown). Thus, the approach appears promising for men to the extent they can be successfully recruited.
The differential rates of study attrition between MI and standard intervention participants are another study limitation (20% vs 48%). The more successful follow-up in the MI condition may be indicative of superior participant engagement. Disinterested participants may have been less engaged in efforts to improve diet and exercise, which would bias findings to underestimate the impact of MI on body composition.
Implications for Practice
CHWs trained in MI may be able to reach a large percentage of the population with a low-cost intervention like Healthy Fit.43 The combination of CHWs and MI allows for seamless cultural tailoring of the intervention, given that CHWs are from the community they are trying to reach.9 MI treats the interviewee as the expert, thereby responding to their own unique situation and culture.44 To reach other cultures, however, the health education materials would need to be modified to resonate with a different focal population.
Anecdotally, CHWs reported that they and their participants found the intervention more rewarding with the integration of MI. Thus, both efficacy and satisfaction appear to be enhanced, which is important for sustainability. Further, CHW implementation of Healthy Fit can be integrated into clinical practice, bolstering behavior change efforts around healthy eating and exercise.45 Future cost effectiveness studies of Healthy Fit are needed, but the cost savings could be substantial, given the tremendous health care costs associated with obesity.46
Conclusion
By integrating MI into a CHW-led intervention, Healthy Fit provides an innovative and low-cost strategy to promote healthy eating and physical activity. Although study findings are promising, more rigorous evaluation research using a randomized design is necessary to estimate unbiased intervention effects. Longer term follow-up is also necessary to ensure the weight loss is sustainable, given that many interventions promote short-term weight loss followed by weight gain.47 Nevertheless, the intervention is a promising approach for promoting small and incremental changes in diet and physical activity that can help to address obesity disparities without medications or surgical intervention.
So What?
What is already known on this topic?
Low-income and minority communities face substantial obesity disparities. Motivational interviewing and community health workers are two promising approaches for promoting sustainable behavior changes related to diet and exercise. Healthy Fit integrates these approaches into a low-cost intervention designed to address Hispanic obesity disparities.
What does this article add?
Community health workers demonstrated an ability to successfully employ motivational interviewing techniques when ongoing feedback and coaching was available. Findings suggest the use of motivational interviewing by community health workers helped participants lose weight and body fat.
What are the implications for health promotion practice or research?
The integration of community health workers and motivational interviewing is a promising low-cost approach to reach vulnerable populations and address obesity disparities. A randomized clinical trial is needed to more rigorously establish the efficacy of this approach.
Acknowledgments
Research reported in this paper was supported by the Border Public Health Interest Group of the City of El Paso, with funding from the Centers for Medicare and Medicaid Services and by the National Institute of General Medical Sciences of the National Institutes of Health under linked Award Numbers RL5GM118969, TL4GM118971, and UL1GM118970. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, the City of El Paso, or the Centers for Medicare and Medicaid Services.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Ethical Approval
The Committee for the Protection of Human Subjects at the University of Texas Health Science Center at Houston approved all study procedures (HSC-SPH-14-0688). All participants provided informed consent.
References
- 1.Wheeler SM, Bryant AS. Racial and ethnic disparities in health and health care. Obstet Gynecol Clin North Am. 2017;44(1):1–11. [DOI] [PubMed] [Google Scholar]
- 2.Borrell LN, Samuel L. Body mass index categories and mortality risk in US adults: The effect of overweight and obesity on advancing death. Am J Publ Health. 2014;104(3):512–519. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Chan RSM, Woo J. Prevention of overweight and obesity: how effective is the current public health approach. Int J Environ Res Public Health. 2010;7:765–783. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Bautista L, Reininger B, Gay JL, Barroso CS, McCormick JB. Perceived barriers to exercise in Hispanic adults by level of activity. J Phys Activ Health. 2011;8:916–925. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Alidu L, Grunfeld EA. A systematic review of acculturation, obesity and health behaviours among migrants to high-income countries. Psychol Health. 2018;33:724–745. [DOI] [PubMed] [Google Scholar]
- 6.New C, Xiao L, Ma J. Acculturation and overweight-related attitudes and behavior among obese hispanic adults in the United States: acculturation and obesity in US Hispanics. Obesity. 2013;21:2396–2404. [DOI] [PubMed] [Google Scholar]
- 7.Im E-O, Lee B, Hwang H, et al. “A waste of time”: Hispanic women’s attitudes toward physical activity. Women Health. 2010;50:563. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Shedlin MG, Decena CU, Mangadu T, Martinez A. Research participant recruitment in Hispanic communities: lessons learned. J Immigr Minor Health. 2011;13:352–360. [DOI] [PubMed] [Google Scholar]
- 9.Balcazar H, Rosenthal EL, Brownstein JN, Rush CH, Matos S, Hernandez L. Community health workers can be a public health force for change in the United States: three actions for a new paradigm. Am J Publ Health. 2011;101:2199–2203. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Rosenthal EL, Brownstein JN, Rush CH, et al. Community health workers: part of the solution. Health Aff. 2010;29(7):1338. [DOI] [PubMed] [Google Scholar]
- 11.Perry HB, Zulliger R, Rogers MM. Community health workers in low-, middle-, and high-income countries: an overview of their history, recent evolution, and current effectiveness. Annu Rev Public Health. 2014;35:399–421. [DOI] [PubMed] [Google Scholar]
- 12.Kangovi S, Mitra N, Grande D, Huo H, Smith RA, Long JA. Community health worker support for disadvantaged patients with multiple chronic diseases: a randomized clinical trial. Am J Publ Health. 2017;107:1660–1667. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Dearing JW. Applying diffusion of innovation theory to intervention development. Res Soc Work Pract. 2009;19:503–518. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Mack M, Uken R, Powers J. People improving the community’s health: community health workers as agents of change. J Health Care Poor Under. 2006;17:16–25. [DOI] [PubMed] [Google Scholar]
- 15.Mobula LM, Okoye MT, Boulware LE, Carson KA, Marsteller JA, Cooper LA. Cultural competence and perceptions of community health workers’ effectiveness for reducing health care disparities. J Prim Care Comm Health. 2015;6:10–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Tovar A, Renzaho AM, Guerrero AD, Mena N, Ayala GX. A systematic review of obesity prevention intervention studies among immigrant populations in the US. Curr Obes Rep. 2014;3:206–222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Armstrong MJ, Mottershead TA, Ronksley PE, Sigal RJ, Campbell TS, Hemmelgarn BR. Motivational interviewing to improve weight loss in overweight and/or obese patients: a systematic review and meta-analysis of randomized controlled trials. Obes Rev. 2011;12:709–723. [DOI] [PubMed] [Google Scholar]
- 18.McNeil DW, Addicks SH, Randall CL. Motivational Interviewing and Motivational Interactions for Health Behavior Change and Maintenance. New York: Oxford University Press; 2017. [Google Scholar]
- 19.Mastellos N, Gunn LH, Felix LM, Car J, Majeed A. Trans-theoretical model stages of change for dietary and physical exercise modification in weight loss management for overweight and obese adults. Cochrane Database Syst Rev. 2014;5:Cd008066. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Miller WR, Moyers TB. Eight stages in learning motivational interviewing. J Teach Addict. 2006;5:3–17. [Google Scholar]
- 21.Resnicow K, McMaster F. Motivational interviewing: moving from why to how with autonomy support. Int J Behav Nutr Phys Activ. 2012;9:19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Brandford A, Adegboyega A, Combs B, Hatcher J. Training community health workers in motivational interviewing to promote cancer screening. Health Promot Pract. 2019;20:239–250. [DOI] [PubMed] [Google Scholar]
- 23.Dilillo V, West DS. Motivational interviewing for weight loss. Psychiatr Clin. 2011;34:861–869. [DOI] [PubMed] [Google Scholar]
- 24.Reinschmidt K, Hunter J, Lacy-Martínez C. Understanding the success of promotoras in increasing chronic disease screening. J Health Care Poor Under. 2006;17:256–264. [DOI] [PubMed] [Google Scholar]
- 25.Group TLAR. Long-term effects of a lifestyle intervention on weight and cardiovascular risk factors in individuals with type 2 diabetes mellitus: four-year results of the look ahead trial. Arch Intern Med. 2010;170:1566–1575. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.West DS, Dilillo V, Bursac Z, Gore SA, Greene PG. Motivational interviewing improves weight loss in women with type 2 diabetes. Diabetes Care. 2007;30:1081–1087. [DOI] [PubMed] [Google Scholar]
- 27.Frost H, Campbell P, Maxwell M, et al. Effectiveness of motivational interviewing on adult behaviour change in health and social care settings: A systematic review of reviews. PLoS One. 2018;13(10):e0204890. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Brown LD, Vasquez D, Salinas JJ, Tang X, Balcazar H. Evaluation of healthy fit: A community health worker model to address Hispanic health disparities. Prev Chronic Dis. 2018;15:170347. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Barnett JC, Berchick E. Health Insurance Coverage in the United States: 2016. Washington, DC: US Census Bureau; 2017. [Google Scholar]
- 30.Paso del Norte Health Foundation. Healthy Paso del Norte: Disparities Dashboard [Internet]; 2020. http://www.healthypasodelnorte.org/index.php?module=indicators&controller=index&action=dashboard&id=83017179230228502&card=0&localeId=2645. Accessed May 27, 2020.
- 31.American Heart Association. Understanding Blood Pressure Readings [Internet]. WVavKIjyvRZ; 2020. http://www.heart.org/HEARTORG/Conditions/HighBloodPressure/KnowYourNumbers/Understanding-Blood-Pressure-Readings_UCM_301764_Article.jsp#. Accessed May 27, 2020.
- 32.Balcázar HG, Heer HD, Thomas SW, et al. Promotoras can facilitate use of recreational community resources: The Mi Corazón Mi Comunidad cohort study. Health Promot Pract. 2016;17:343–352. [DOI] [PubMed] [Google Scholar]
- 33.Moyers TB, Rowell LN, Manuel JK, Ernst D, Houck JM. The motivational interviewing treatment integrity code (MITI 4): Rationale, preliminary reliability and validity. J Subst Abuse Treat. 2016;65:36–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Hamilton CM, Strader LC, PJ G, et al. The PhenX toolkit: get the most from your measures. Am J Epidemiol. 2011;174:253–260. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Cantor SB, Byrd TL, Groff JY, Reyes Y, Tortolero-Luna G, Mullen PD. The language translation process in survey research: a cost analysis. Hisp J Behav Sci. 2005;27:364–370. [Google Scholar]
- 36.Masterson Creber RM, Fleck E, Liu J, Rothenberg G, Ryan B, Bakken S. Identifying the complexity of multiple risk factors for obesity among urban Latinas. J Immigr Minor Health. 2017;19:275–284. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Zheng R, Du M, Zhang B, et al. Body mass index (BMI) trajectories and risk of colorectal cancer in the PLCO cohort. Br J Cancer. 2018;119(1):130–132. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Hills AP, Byrne NM, Lindstrom R, Hill JO. Small changes’ to diet and physical activity behaviors for weight management. Obes Facts. 2013;6(3):228–238. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Lasikiewicz N, Myrissa K, Hoyland A, Lawton CL. Psychological benefits of weight loss following behavioural and/or dietary weight loss interventions. A systematic research review. Appetite. 2014;72:123–137. [DOI] [PubMed] [Google Scholar]
- 40.Ryan DH, Yockey SR. Weight loss and improvement in co-morbidity: Differences at 5%, 10%, 15%, and over. Current Obesity Reports. 2017;6(2):187–194. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Lopez DI, Chacon L, Vasquez D, Brown LD. Body composition outcomes of Healthy Fit and the role of acculturation among low-income Hispanics on the US-Mexico border. BMC Publ Health. 2021;21(1):976. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Eakin EG, Winkler EA, Dunstan DW, et al. Living well with diabetes: 24-month outcomes from a randomized trial of telephone-delivered weight loss and physical activity intervention to improve glycemic control. Diabetes Care. 2014;37:2177. [DOI] [PubMed] [Google Scholar]
- 43.Portillo EM, Vasquez D, Brown LD. Promoting hispanic immigrant health via community health workers and motivational interviewing. Int Q Community Health Educ. 2020;41:3–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Resnicow K, Diiorio C, Soet JE, Borrelli B, Hecht J, Ernst D. Motivational interviewing in health promotion: it sounds like something is changing. Health Psychol. 2002;21:444–451. [PubMed] [Google Scholar]
- 45.Ingram M, Doubleday K, Bell ML, et al. Community health worker impact on chronic disease outcomes within primary care examined using electronic health records. Am J Publ Health. 2017;107:1668–1674. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Kim DD, Basu A. Estimating the medical care costs of obesity in the United States: systematic review, meta-analysis, and empirical analysis. Value Health. 2016;19(5):602–613. [DOI] [PubMed] [Google Scholar]
- 47.Tseng E, Zhang A, Shogbesan O, et al. Effectiveness of policies and programs to combat adult obesity: a systematic review. J Intern Med. 2018;33:1990–2001. [DOI] [PMC free article] [PubMed] [Google Scholar]