This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.
Hispanic men have disproportionate rates of overweight and obesity compared with other racial and ethnic subpopulations. However, few weight loss interventions have been developed specifically for this high-risk group. Furthermore, the use of mobile health (mHealth) technologies to support lifestyle behavior changes in weight loss interventions for Hispanic men is largely untested.
This single-arm pilot study examined the feasibility and acceptability of integrating mHealth technology into a 12-week gender- and culturally sensitive weight loss intervention (GCSWLI) for Hispanic men with overweight and obesity.
A total of 18 Hispanic men (mean age 38, SD 10.9 years; mean BMI 34.3, SD 5.5 kg/m²; 10/18, 56% Spanish monolingual) received a GCSWLI, including weekly in-person individual sessions, a daily calorie goal, and prescription of ≥225 minutes of moderate-intensity physical activity per week. mHealth technology support included tailored SMS text messaging, behavior self-monitoring support using Fitbit Charge 2, and weight tracking using a Fitbit Aria Wi-Fi Smart Scale. Changes in weight from baseline to 12 weeks were estimated using a paired 2-tailed
Of 18 participants, 16 (89%) completed the 12-week assessments; the overall attrition rate was 11.1%. The mean weight loss at week 12 was −4.7 kg (95% CI 7.1 to −2.4 kg;
Although clinically significant weight loss was achieved by integrating mHealth technology into the GCSWLI, adherence to the prescribed use of technology was modest. Addressing barriers to the use of such technologies identified in our work may help to refine an mHealth intervention approach for Hispanic men.
ClinicalTrials.gov NCT02783521; https://clinicaltrials.gov/ct2/show/NCT02783521
Hispanics, one of the largest and fastest growing racial and ethnic subpopulations in the United States, comprise 17% of the total US population and are projected to reach 28% by 2060 [
Lifestyle interventions have proven to be an effective strategy for implementing chronic disease prevention approaches that are responsive to weight loss [
Hispanics are receptive to using mHealth technologies for preventive care services. In particular, SMS text messages have been used as an effective tool for engaging Hispanic participants in research studies [
Given the rapid growth of the Hispanic population in the United States and the disproportionate burden of preventable chronic diseases faced by this population, effective and sustainable interventions are urgently required. In this context, engaging Hispanic men with mHealth technology that is linguistically and culturally competent, while also meeting their health needs within chronic disease prevention, may be a potential solution. Earlier formative work by our investigative team showed that an mHealth-supported intervention, in combination with face-to-face counseling, may improve engagement and adherence to behavior change recommendations, particularly for physical activity [
Study participants were part of the ANIMO (a Spanish term for motivation or encouragement) pilot study (ClinicalTrials.gov NCT02783521), a 24-week randomized controlled trial that tested the effects of in-person GCSWLI on body weight in Hispanic males (n=25) compared with a waitlist control (WLC) group (n=25) [
Study flow diagram for the mobile health (mHealth)–supported gender- and culturally sensitive weight loss intervention (GCSWLI). WLC: waitlist control.
All study activities were conducted at the University of Arizona Collaboratory for Metabolic Disease Prevention and Treatment in Tucson, Arizona. Eligible participants were invited to the Collaboratory, where complete details of the study were given in the participant’s preferred language (English or Spanish), and informed consent was obtained. This study was approved by the University of Arizona Institutional Review Board (approval 604536275).
Participants met with a trained bilingual, bicultural Hispanic male lifestyle coach in person (one to one) for 30 to 45 minutes once a week for 12 weeks. During these individual counseling sessions, lifestyle coaches assisted participants in setting a daily calorie goal and physical activity goals (progressing to ≥225 minutes of moderate-intensity physical activity per week) and reminded participants to self-monitor in written diaries. The GCSWLI was developed based on the Diabetes Prevention Program lifestyle intervention [
At the conclusion of the 12-week GCSWLI study, specific mHealth components were added to the in-person GCSWLI curriculum used with WLC control participants. Specifically, the use of Fitbit Charge 2, a consumer-wearable physical activity tracker, and a Fitbit Aria Wi-Fi Smart Scale for body weight were included to complement self-monitoring using written diaries. In the first in-person session, all participants were instructed on how to use the Fitbit tools to reduce any barriers related to the introduction of mHealth technology. This included logging into their personal Fitbit dashboard, where the lifestyle coach stored and monitored the data weekly. It was recommended that participants wear the Fitbit Charge 2 during all waking hours and weigh themselves daily using the Aria smart scale. The Fitbit data were downloaded during weekly in-person sessions and discussed with the participants by the lifestyle coach. A total of 2 weekly SMS text messages were sent to participants throughout the following week by a lifestyle coach, tailored to the participants’ needs based on observations from the Fitbit tools and self-reported barriers during the weekly in-person sessions. All intervention strategies from the original GCSWLI curriculum were maintained to ensure that participants had the opportunity to lose weight, independent of mHealth use.
Clinical assessments included anthropometrics, cardiometabolic measures, and self-reported diet and physical activity behaviors at baseline and 12 weeks. Acculturation was measured at baseline, and treatment satisfaction was measured at the completion of the study.
Height (cm) was measured using a wall-mounted stadiometer, and weight (kg) was measured using a calibrated digital scale (Seca 876). Waist circumference (cm) was measured using a Gulick tape measure, and body composition was measured using whole-body dual-energy x-ray absorptiometry (Lunar Prodigy; Lunar). A trained phlebotomist collected fasting blood samples (venipuncture, 25 mL) using an approved protocol for examining the following cardiometabolic measures: (1) a metabolic liver panel (alanine transaminase and aspartate transaminase), (2) a lipid panel (total cholesterol, high-density lipoprotein, low-density lipoprotein, and triglycerides), (3) high-sensitivity C-reactive protein, and (4) fasting glucose and hemoglobin A1c.
Dietary intake was assessed using the Southwestern Food Frequency Questionnaire (SWFFQ) [
Acculturation affects attitudes, perceptions, and behaviors surrounding health-related activities and outcomes [
All participants were invited to participate in individual postintervention interviews. The interview protocol was devised to elicit information about (1) participant satisfaction with the intervention, (2) adequacy of cultural and gender intervention adaptation, (3) strategies for improved intervention engagement, (4) adequacy of physical activity and dietary recommendations, and importantly, (5) perspectives on the integration of mHealth technology as a component in weight management interventions. Written and verbal consent was obtained from each willing participant, and an additional US $25 was offered as compensation. All interviews were conducted by each participant’s respective lifestyle coach in their preferred language and were audio recorded to facilitate data interpretation. To minimize bias, all interviewers carefully explained that the participants were free and under no pressure to express their views and that the focus of the interviews was to learn their perceptions to help inform the future development of similar intervention programs.
Descriptive statistics were calculated for all the variables at baseline. To explore differences in baseline variables between the enrolled group and the group that did not enroll in the mHealth pilot study, we conducted 2-tailed
All individual interviews were digitally recorded, transcribed verbatim in their respective languages (Spanish or English), and coded using NVivo (version 10, QSR International) qualitative analysis software [
On completion of the initial 12-week GCSWLI, WLC participants (n=25) were offered the mHealth-supported intervention. Overall, 2 patients were lost to follow-up for unknown reasons, 4 declined participation, and 1 individual had a measured BMI 25 kg/m2 before the start of the treatment and was deemed ineligible (
Overall, an average of 75% (SD 27%) of the individual sessions were attended throughout the 12-week treatment period. Of the 18 participants, 2 (11%) attended <50% of the sessions, 6 (33%) attended 50% to 75% of the sessions, and 10 (56%) attended >75% of the sessions. Of the 18 participants, 16 (89%) completed the intervention, with an overall attrition rate of 11.1%. Self-monitoring adherence and mHealth technology use at the follow-up are shown in
On average, each person completed 6.2 weekly written diaries; 51.93% (698/1344) of the total diaries were completed. Diet was recorded on average 1.7 days per week, with an average of 1260 kcal reported each day. Participants reported physical activity an average of 1.4 days per week, with a total of 78 minutes of weekly exercise, and they recorded their weight on an average of 1.8 days per week. Activity monitors were used 5.1 days per week, and weight was reported using wireless scales 3.2 days per week. Overall, participants wore the Fitbit 71.6% of the intervention days and weighed themselves using the smart scale for 30.5% of the days they spent in the intervention. The participants were highly satisfied with the weight management program, and 100% (15/15) of the participants indicated that they were likely to recommend the program to others. Satisfaction with overall progress toward weight loss was positive, with progress in changing dietary habits ranking the highest (
The pre- and postweight and cardiometabolic measures are shown in
Demographic and baseline characteristics of participants in a mobile health (mHealth)–supported gender- and culturally sensitive weight loss intervention.
|
mHealth participants (n=18) | Did not enroll (n=7) | |||||
Age (years), mean (SD) | 38.0 (10.9) | 48.9 (12.1) | .04 | ||||
BMI (kg/m2), mean (SD) | 34.3 (5.5) | 30.3 (3.6)a | .14 | ||||
Weight (kg), mean (SD) | 104.6 (20.8) | 90.0 (6.3)a | .02 | ||||
Waist circumference (cm), mean (SD) | 114.1 (14.6) | 107.5 (5.7)a | .34 | ||||
Employed, n (%) | 12 (66) | 6 (85) | .63 | ||||
|
.99 | ||||||
|
<30,000 | 13 (72) | 5 (71) |
|
|||
|
30,000-60,000 | 4 (22) | 2 (29) |
|
|||
|
>60,000 | 1 (6) | 0 (0) |
|
|||
|
.99 | ||||||
|
Less than high school | 6 (33) | 2 (29) |
|
|||
|
High school or General Educational Development | 5 (28) | 2 (29) |
|
|||
|
Greater than high school | 7 (39) | 3 (43) |
|
|||
Married or lives with a domestic partner, n (%) | 14 (78) | 7 (100) | .30 | ||||
US born, n (%) | 10 (56) | 1 (14) | .09 | ||||
|
.53 | ||||||
|
Mexican | 10 (56) | 6 (86) |
|
|||
|
Mexican American | 7 (39) | 1 (14) |
|
|||
|
Puerto Rican | 1 (6) | 0 (0) |
|
|||
|
.39 | ||||||
|
Spanish | 10 (56) | 6 (86) |
|
|||
|
English | 6 (33) | 1 (14) |
|
|||
|
Both equally | 2 (11) | 0 (0) |
|
|||
Mexican Orientation Subscale of ARSMA-IIb, mean (SD) | 65.6 (16.7) | 73.6 (8.2) | .24 | ||||
|
.79 | ||||||
|
Very Mexican oriented | 7 (39) | 5 (71) |
|
|||
|
Mexican oriented to approximately balanced to oriented bicultural | 6 (33) | 1 (14) |
|
|||
|
Slightly Anglo bicultural | 3 (17) | 1 (14) |
|
|||
|
Strongly Anglo oriented | 1 (6) | 0 (0) |
|
|||
|
Very assimilated | 1 (6) | 0 (0) |
|
aA total of 2 individuals dropped out owing to their participation in the waitlist control.
bARSMA-II: Acculturation Rating Scale for Mexican Americans-II.
Attendance, self-monitoring adherence, and mobile health (mHealth) technology use in a gender- and culturally sensitive weight loss intervention (N=18).
Characteristics | Values | |||
|
75.0 (27.0) | |||
|
Attended <50% of the sessions, n (%) | 2 (11) | ||
|
Attended 50%-75% of the sessions, n (%) | 6 (33) | ||
|
Attended >75% of the sessions, n (%) | 10 (56) | ||
|
||||
|
Diaries completed, n (%) | 112 (52) | ||
|
Diaries completed per person, mean (SD) | 6.2 (4.2) | ||
|
Diet days recorded (days per week), mean (SD) | 1.7 (2.8) | ||
|
Self-reported calorie intake (kcal per day), mean (SD) | 1260 (566) | ||
|
|
|||
|
|
Days per week | 1.4 (2.0) | |
|
|
Minutes per week | 78.0 (63.1) | |
|
Self-weighed (days per week), mean (SD) | 1.8 (2.9) | ||
|
||||
|
Activity monitor use (days per week) | 5.1 (2.0) | ||
|
Activity monitor use during sleep (days per week) | 2.2 (2.4) | ||
|
Diet days recorded via web (days per week) | 0.4 (1.3) | ||
|
Weight reported using wireless scale (days per week) | 3.2 (3.2) |
aData obtained from paper diary logging.
Participant responses to treatment satisfaction survey (for 15 of 16 completers).
Participant responses | Values | |
|
||
|
Somewhat satisfied | 1 (7) |
|
Very satisfied | 13 (87) |
|
Missing response | 1 (7) |
Would you recommend the weight management program you received to others?b (definitely would), n (%) | 15 (100) | |
Given the effort you put into following the weight management program, how satisfied are you with your overall progress over the past 12 weeks?c median (IQR) | 3.0 (2.5-4.0) | |
|
||
|
Changing your weight | 3.0 (3.0-4.0) |
|
Changing your dietary habits | 3.0 (2.5-4.0) |
|
Changing your physical activity habits | 3.0 (2.0-4.0) |
a1=very dissatisfied and 4=very satisfied.
b1=definitely not and 4=definitely would.
c4=very dissatisfied and 4=very satisfied.
Outcomes before and after the mobile health intervention and estimated mean change from baseline.
|
Baseline (n=18), mean (SD) | Week 12 (n=16), mean (SD) | Change from baseline, mean (95% CI) | ||||||
Weight (kg) | 104.6 (20.8) | 100.3 (21.6) | −4.7 (−7.1 to −2.4) | <.001 | |||||
BMI (kg/m2) | 34.3 (5.5) | 32.7 (5.9) | −1.6 (−2.4 to −0.8) | <.001 | |||||
Percentage weight change | —a | −4.8 (4.5) | −4.8 (−7.0 to −2.0) | <.001 | |||||
Percentage body fat | 37.3 (3.6) | 35.3 (4.8) | −1.97 (−2.98 to −0.96) | <.001 | |||||
Waist circumference (cm) | 114.1 (14.6) | 109.5 (14.3) | −5.1 (−6.8 to −3.4) | <.001 | |||||
Leisure-time physical activity (min/week) | 87.2 (100.6) | 139.4 (170.8) | 60.0 (−44.6 to 164.6) | .24 | |||||
Average caloric intake (kcal/day) | 3102 (3745) | 1754 (1329) | −1196 (−2647 to 254) | .11 | |||||
|
|||||||||
|
Hemoglobin A1c (%) | 5.6 (0.8) | 5.5 (0.6) | −0.22 (−0.41 to −0.03) | .02 | ||||
|
Glucose (mg/100 mL) | 105.3 (28.4) | 105.4 (32.8) | −2.31 (−9.26 to 4.64) | .49 | ||||
|
Alanine transaminase (U/L) | 53.6 (52.7) | 39.6 (28.1) | −16.9 (−32.5 to −1.23) | .04 | ||||
|
Aspartate transaminase (U/L) | 28.9 (19.3) | 24.9 (9.6) | −5.3 (−11.7 to 1.04) | .10 | ||||
|
Total cholesterol (mg/100 mL) | 185.7 (40.4) | 171.4 (37.5) | −11.8 (−19.9 to −3.7) | .007 | ||||
|
High-density lipoprotein cholesterol (mg/100 mL) | 40.2 (5.6) | 39.3 (6.9) | −1.0 (−4.2 to 2.2) | .51 | ||||
|
Low-density lipoprotein cholesterol (mg/100 mL) | 113.7 (34.3) | 104.8 (31.8) | −5.6 (−12.0 to 0.80) | .08 | ||||
|
Triglycerides (mg/100 mL) | 158.8 (82.2) | 136.4 (71.5) | −25.6 (−52.0 to 0.9) | .06 | ||||
|
High-sensitivity C-reactive protein (mg/100 mL) | 3.4 (2.9) | 2.5 (2.5) | −0.83 (−2.37 to 0.70) | .26 |
aNot available.
Of the 16 participants who completed the intervention, 14 (88%) agreed to participate in an individual interview after the completion of the 12-week intervention. A total of 4 overarching themes emerged during these interviews regarding participants’ perceptions of the integration of mHealth technology into a weight management intervention.
When asked to reflect on their use of Fitbit activity and weight trackers, participants expressed positive feedback and no concerns about the security or privacy of the e-supported data were reported. The participants explained that mHealth technology was at times easier to use than the written diary self-monitoring method. This, in turn, facilitated the seamless integration of self-monitoring into daily lifestyle behavior changes. For example, a participant commented the following:
And of course the best part that I really enjoyed were the technological tools, the Fitbit the scale things like that the Fitbit app that made a huge world of difference. You know it became part of my life and now I use it all the time to count my steps look at information look at data look at how I sleep and how much exercise I got that day it’s great it’s a great thing to have.
Participants also expressed that using the Fitbit wearable tracking device facilitated accountability to daily goals. Specifically, the participants expressed that it was easy to see when daily goals were not being met and that they enjoyed the positive feedback they received when goals were met. A participant stated the following:
[I liked the Fitbit] because I can have a record of whether or not I walk, you understand me? Instead of forgetting...and when I do wrap up a night, it will tell me, “hey great job! You walked like 10, 20, 25 minutes” and I pay attention to that. So that helps.
Another participant commented on the utility of activity trackers to standardize step count goals, explaining as follows:
I like [the Fitbit] because, how do I explain? I can at least say that 10,000 steps is like the bottom line, right?...So, when I realize that I have not reached 3,000 steps for two or three days I really start paying attention.
Conversely, some participants expressed concerns about the use of technology. For some, reliable internet connectivity was a barrier to the use of supplemental technology. The Fitbit scale requires a reliable internet connection to sync and upload data, which some participants did not have access to. A few men also explained that an additional technology-centered component was an added burden instead of a supplemental benefit of the intervention. This was particularly the case with older participants, who reported less technology literacy because technology was not already integrated into their daily lives. A participant described the following:
I think that was helpful. I don’t know that the Fitbit thing would have been very helpful to me I’m not a real tech-oriented guy I don’t want to sync up this and that enter info, yeah so I’m not, I’m not into that so I don’t know if that would have helped me, but other things did that’s for sure.
Hispanic men are part of the largest racial and ethnic subpopulation in the United States and are disproportionally affected by obesity-related chronic diseases [
The findings of this study yielded promising improvements in body composition, including changes in body weight, body fat percentage, and waist circumference. Recent literature assessing body composition outcomes has yielded only modest results in other Hispanic subpopulations and has been largely limited to enrollment of women [
Regarding feasibility and acceptability, our mHealth intervention was well received and produced a retention rate of 88.9%. In general, weight loss interventions in Hispanic adults have previously reported lower retention rates; however, they did not include mHealth components [
Hispanic men experienced high levels of overall satisfaction with this intervention modality expressing that they would recommend participation to other Hispanic men. This is in agreement with the findings of Wang et al [
Although this study has many strengths, we must acknowledge some limitations, including a small study sample, a short time frame, and a 1-group pre-post design that did not allow direct comparison with a control group. Therefore, we cannot disentangle which mHealth components were most supportive of weight loss, and the results must be interpreted with caution. Furthermore, although most individuals achieved weight loss, we did not observe statistically significant changes in diet or physical activity. Recall bias should be considered as a hindering factor when self-reporting techniques are involved. However, the investigative team attempted to minimize recall bias by reviewing the questionnaires in person for each participant. Furthermore, given that all study participants came from Tucson, Arizona, and were largely of Mexican-origin descent apart from one individual, this decreases the generalizability of findings and adaptability to Hispanic men in other areas. There is also a possibility that increased adherence to mHealth technology could have been due to the novelty of using the Fitbit wearable technology and gaining access to high-level health care tools such as dual-energy x-ray absorptiometry scan and cardiometabolic measures. Future research in this area should explore the impact of this intervention modality beyond 12 weeks to explore the progression of healthy behavior continuity and adherence levels to wearable technology in the long term. In addition, interventions should focus on underrepresented and underresourced subpopulations that are disproportionately affected by health inequalities and have unequal access to high-quality health services and information.
The integration of mHealth technology into our 12-week GCSWLI appeared to be feasible and widely accepted by study participants. Although the use of wearable technology was modest, Hispanic men achieved clinically meaningful weight loss at the end of the intervention. This pilot study contributes to the growing literature on health promotion and mHealth technologies to aid the adoption of healthy lifestyle behavior changes implemented through weight loss interventions for Hispanic men. Research efforts centered on weight management, and mHealth should consider culturally adapted frameworks that address barriers hindering the awareness and maintenance of healthy lifestyles. The use of mHealth holds promise in lifestyle interventions for Hispanic men, making healthy living opportunities more practical and achievable for communities that have historically lacked the benefits of this type of technology.
gender- and culturally sensitive weight loss intervention
mobile health
Southwestern Food Frequency Questionnaire
waitlist control
This work was supported by the University of Arizona Cancer Center Disparities Pilot Project Award, the University of Arizona Foundation, and Dean’s Canyon Rach Center for Prevention and Health Promotion Fund.
DOG, LAV, MLB, and SPH designed the research. DOG, LAV, and BA conducted the research. MLB, BAR, LAV, and DOG analyzed the data. All authors were involved in writing the paper and provided final approval of the submitted and published versions.
None declared.