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Excessive gestational weight gain (GWG) during pregnancy is a major public health concern associated with negative health outcomes for both mother and child. Scalable interventions are needed, and digital interventions have the potential to reach many women and promote healthy GWG. Most previous studies of digital interventions have been small pilot studies or have not included women from all BMI categories. We therefore examined the effectiveness of a smartphone app in a large sample (n=305) covering all BMI categories.
To investigate the effectiveness of a 6-month intervention (the HealthyMoms app) on GWG, body fatness, dietary habits, moderate-to-vigorous physical activity (MVPA), glycemia, and insulin resistance in comparison to standard maternity care.
A 2-arm parallel randomized controlled trial was conducted. Women in early pregnancy at maternity clinics in Östergötland, Sweden, were recruited. Eligible women who provided written informed consent completed baseline measures, before being randomized in a 1:1 ratio to either an intervention (n=152) or control group (n=153). The control group received standard maternity care while the intervention group received the HealthyMoms smartphone app for 6 months (which includes multiple features, eg, information; push notifications; self-monitoring; and feedback features for GWG, diet, and physical activity) in addition to standard care. Outcome measures were assessed at Linköping University Hospital at baseline (mean 13.9 [SD 0.7] gestational weeks) and follow-up (mean 36.4 [SD 0.4] gestational weeks). The primary outcome was GWG and secondary outcomes were body fatness (Bod Pod), dietary habits (Swedish Healthy Eating Index) using the web-based 3-day dietary record Riksmaten FLEX, MVPA using the ActiGraph wGT3x-BT accelerometer, glycemia, and insulin resistance.
Overall, we found no statistically significant effect on GWG (
Although we found no overall effect on GWG, our results demonstrate the potential of a smartphone app (HealthyMoms) to promote healthy dietary behaviors as well as to decrease weight gain during pregnancy in women with overweight and obesity.
ClinicalTrials.gov NCT03298555; https://clinicaltrials.gov/ct2/show/NCT03298555
RR2-10.2196/13011
Excessive gestational weight gain (GWG) is a major public health problem [
Traditional interventions (eg, face-to-face counseling and supervised exercise sessions) to reduce the risk of excessive GWG have been reported to be successful [
In the last decade, the use of digital technologies (eg, mobile Health [mHealth]) to deliver lifestyle interventions has increased. In comparison to traditional interventions, mHealth interventions have the advantages of being more cost-effective and accessible [
The aim of this randomized controlled trial was to investigate the effectiveness of the 6-month intervention (the HealthyMoms app) on GWG (primary outcome), body fatness, dietary habits (Swedish Healthy Eating Index), moderate-to-vigorous physical activity (MVPA), glycemia, and insulin resistance (secondary outcomes) in gestational week 37 among Swedish women.
The HealthyMoms trial (clinicaltrials.gov NCT03298555) was a 2-arm parallel design randomized controlled trial conducted between October 2017 and November 2020 in the county of Östergötland, Sweden. The study received approval from the Regional Ethical Review Board in Linköping, Sweden (reference numbers 2017/112-31 and 2018/262-32) and all women provided written informed consent before entering the trial. Development of the HealthyMoms app and full details of the study design have been described previously [
Between October 2017 and March 2020 participants were recruited in early pregnancy at the first routine visit at maternity clinics in the county of Östergötland, Sweden. During the study period approximately 4000 eligible women attended maternity care. At the maternity clinic, participants received written information about the study, and women interested in participating contacted the research team via email or postal mail. Inclusion criteria were aged 18 years or older, a singleton pregnancy, and the ability to read and speak well-enough Swedish to be able to understand the app content. Women previously diagnosed with an eating disorder, diabetes, or other medical conditions with possible effects on body weight were excluded. Eligible women who agreed to participate were sent an accelerometer to assess physical activity and were instructed to register their diet using a web-based dietary assessment tool prior to the measurement. Baseline measures (13.9 [SD 0.7] gestational weeks) and follow-up measures (36.4 [SD 0.4] gestational weeks) were conducted at Linköping University Hospital. In short, these measures included assessment of body weight and height, body composition, plasma glucose, serum insulin, and sociodemographic variables. These are described in more detail below.
The control group received standard maternity care consisting of regular monitoring of maternal and fetal health (such as measurements of blood pressure, blood glucose and ferritin, weight gain, symphysis fundus, as well as fetal movements and heart rate). Standard care also included an optional lecture in early pregnancy on a healthy lifestyle with some brief and general advice on diet, physical activity, smoking and alcohol, pregnancy-related health (eg, nausea, iron deficiency, pelvic pain), and medical care (eg, midwife visits, information on fetal diagnostics). In addition, standard care included repeated measurements of body weight throughout pregnancy.
In addition to standard maternity care, participants in the intervention group received the HealthyMoms app (Android and iOS compatible), a 6-month program aimed at promoting recommended GWG [
Screenshots from the HealthyMoms app showing examples from the app (ie, an exercise video, the weight gain chart, and diet registration with feedback).
We estimated that 226 women (113 in each group) would provide 80% power (α=.05, 2 sided), assuming a common SD in GWG of 4 kg [
The primary outcome was GWG between baseline (gestational week 14) and the follow-up measurement (gestational week 37). Secondary outcomes included body fatness, dietary habits (Swedish Healthy Eating Index), physical activity (time spent in MVPA), glycemia, and insulin resistance. All outcomes were assessed in gestational weeks 14 and 37.
Body weight was measured after an overnight fast when the participant was wearing underwear using standardized procedures (Bod Pod; COSMED). Subsequently, GWG was calculated as the difference in body weight (in kg) between the baseline measurement (gestational week 14) and the follow-up measurement (gestational week 37). Furthermore, GWG between gestational weeks 14 and 37 was expressed per week (kg/week). Subsequently, we applied the pre-pregnancy BMI-specific GWG recommendations for the second and third trimester proposed by the National Academy of Medicine to categorize GWG for each woman as inadequate, adequate, and excessive (ie, underweight: 0.44-0.58 kg/week; normal weight: 0.35-0.50 kg/week; overweight: 0.23-0.33 kg/week; and obesity: 0.17-0.27 kg/week) [
Body composition was measured using Bod Pod (COSMED) with accompanying software version 5.2.0 as described previously [
The web-based dietary recall method Riksmaten FLEX developed by the Swedish National Food Agency [
The design of Riksmaten FLEX has been described in detail elsewhere [
To assess diet quality, we calculated the Swedish Healthy Eating Index score [
An ActiGraph wGT3x-BT (ActiGraph) accelerometer was used to assess physical activity. Participants were instructed to wear the accelerometer on the wrist for 7 consecutive 24-hour periods and to only remove it when engaging in water activities. The accelerometer was programmed to register accelerations at 100 Hz and participants filled in a diary where they reported sleep time and nonwear time which were used in the analysis to confirm sleep time. Participant data with at least one valid day were included. A valid day was defined as one-third or more of the 24-hour period being wear time, two-thirds or more of the wake time being wear time, and two-thirds or more of the sleep time being wear time. Participants who were not able to wear the accelerometer on the wrist (eg, health care workers due to hygiene restrictions at the workplace) were instructed to wear it on the hip instead, both at baseline and at follow-up (baseline n=23; follow-up n=18). Appropriate thresholds to identify MVPA were used for wrist- (ie, 100 m
Blood samples were drawn after an overnight fast. Concentrations of glucose and insulin were analyzed on a Cobas 602 (Roche Diagnostics Scandinavia AB) at the Department of Clinical Chemistry, Linköping University Hospital. Insulin resistance was assessed by using the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) according to Matthews et al [
All statistical analyses were conducted in accordance with the study protocol [
To contrast differences in primary (GWG in kg) and secondary outcomes (Swedish Healthy Eating Index, MVPA, body fatness, glycemia, and insulin resistance) between the 2 groups (intervention vs control) we estimated linear regression models. More specifically, for the primary outcome GWG, we regressed follow-up weight in gestational week 37 on group allocation and adjusted for baseline weight in gestational week 14 (crude model). This procedure has the advantage of being robust to imbalances at baseline and regression toward the mean [
We conducted the following sensitivity and complementary analyses. First, in accordance with our protocol [
As shown in
Flowchart of the HealthyMoms trial.
Baseline characteristics of the women in the HealthyMoms trial.
Characteristics | All women (n=305) | Intervention (n=152) | Control (n=153) | ||
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0 | 175 (57.4) | 86 (56.6) | 89 (58.2) | ||
≥1 | 130 (42.6) | 66 (43.4) | 64 (41.8) | ||
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Primary school (9 years) | 2 (0.7) | 0 (0.0) | 2 (1.3) | ||
High school (12 years) | 66 (21.6) | 37 (24.3) | 29 (19.0) | ||
University degree | 237 (77.7) | 115 (75.7) | 122 (79.7) | ||
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Underweight (<18.5 kg/m2) | 6 (2.0) | 1 (0.7) | 5 (3.3) | ||
Normal weight (18.5-24.9 kg/m2) | 212 (69.5) | 103 (67.8) | 109 (71.2) | ||
Overweight (25.0-29.9 kg/m2) | 67 (22.0) | 34 (22.4) | 33 (21.6) | ||
Obesity (≥30.0 kg/m2) | 20 (6.6) | 14 (9.2) | 6 (3.9) | ||
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Gestational week | 13.9 (0.7) | 13.8 (0.6) | 14.0 (0.7) | ||
Age (years) | 31.3 (4.1) | 31.4 (4.3) | 31.3 (3.8) | ||
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Weight (kg) | 67.7 (11.5) | 68.3 (12.8) | 67.0 (10.2) | ||
Height (m) | 1.67 (0.06) | 1.66 (0.06) | 1.68 (0.06) | ||
BMI (kg/m2) | 24.2 (3.8) | 24.7 (4.3) | 23.8 (3.2) | ||
Fat mass index (kg/m2) | 8.0 (3.2) | 8.4 (3.6) | 7.6 (2.6) | ||
Fat free mass index (kg/m2) | 16.2 (1.3) | 16.2 (1.4) | 16.2 (1.3) | ||
Swedish Healthy Eating Index Scorec | 6.66 (0.98) | 6.54 (0.98) | 6.79 (0.97) | ||
Moderate-to-vigorous physical activity (min/day)d | 39.2 (24.0) | 38.7 (24.6) | 39.8 (23.5) | ||
Glycemia (mmol/L)e | 4.8 (0.3) | 4.8 (0.3) | 4.8 (0.3) | ||
Homeostatic Model Assessment for Insulin Resistancee | 1.4 (0.7) | 1.4 (0.8) | 1.4 (0.7) |
aAll women (n=305): intervention group (n=152) + control group (n=153).
bBased on self-reported pre-pregnancy weight and height.
cAll women (n=302): intervention group (n=151) + control group (n=151).
dAll women (n=296); intervention group (n=146) + control group (n=150).
eAll women (n=304); intervention group (n=151) + control group (n=153).
Self-reported app satisfaction in the intervention group (n=134) at the follow-up measurement. Participants responded to the following statements with the 6 alternatives shown.
Statement | Strongly disagree, n (%) | Agree to a small extent, n (%) | Agree to some extent, n (%) | Strongly agree, n (%) | Fully agree, n (%) | Do not know, n (%) |
I am satisfied with the app | 2 (1.5) | 5 (3.7) | 18 (13.4) | 66 (49.3) | 38 (28.4) | 5 (3.7) |
The app has been a good support for a healthy weight gain during pregnancy | 9 (6.7) | 18 (13.4) | 39 (29.1) | 32 (23.9) | 20 (14.9) | 16 (11.9) |
The app has been a good support for healthy food habits | 12 (9.0) | 16 (11.9) | 42 (31.3) | 41 (30.6) | 11 (8.2) | 12 (9.0) |
The app has been a good support for exercise habits | 15 (11.2) | 16 (11.9) | 29 (21.6) | 44 (32.8) | 20 (14.9) | 10 (7.5) |
The app has given me insight regarding my food habits | 26 (19.4) | 16 (11.9) | 39 (29.1) | 31 (23.1) | 9 (6.7) | 13 (9.7) |
The app has given me insight regarding how physically active I am | 28 (20.9) | 16 (11.9) | 32 (23.9) | 36 (26.9) | 13 (9.7) | 9 (6.7) |
I think that the HealthyMoms app is better than other similar apps | 3 (2.2) | 10 (7.5) | 31 (23.1) | 24 (17.9) | 9 (6.7) | 57 (42.5) |
I would recommend other pregnant women to use the HealthyMoms app | 3 (2.2) | 7 (5.2) | 16 (11.9) | 45 (33.6) | 57 (42.5) | 6 (4.5) |
Intervention effect on gestational weight gain (primary outcome) assessed using regression analysisa,b,c.
Model | Imputed data analysis (n=305) | Complete cases analysis (n=271) | ||
Coefficient (95% CI) | Coefficient (95% CI) | |||
Crude | –0.20 (–0.98 to 0.59) | .62 | –0.22 (–1.00 to 0.56) | .58 |
Adjusted | –0.20 (–1.00 to 0.60) | .62 | –0.24 (–1.01 to 0.54) | .55 |
aRegression analysis of follow-up measure of weight on group allocation. The coefficient is interpreted as the estimated effect of the intervention compared with the control adjusted for baseline weight (crude model), BMI category (underweight and normal weight vs overweight and obesity), parity (0 vs 1 or more), and educational attainment (university degree vs no university degree) (adjusted model).
bBaseline, n=305 (152 intervention and 153 control); Follow-up, n=271 (134 intervention and 137 control).
cAt baseline, the mean bodyweight (kg) for the intervention and control group was 68.3 (SD 12.8) and 67.0 (SD 10.2), respectively, whereas at follow-up the corresponding values were 78.7 (SD 13.1) and 77.3 (SD 10.6).
Intervention effect on gestational weight gain according to National Academy of Medicine’s recommendations.
Outcome | Descriptive data, n (%) | Intervention effect using regression analysisa | ||||
Group | Imputed data analysis (n=305) | Complete cases analysis (n=271) | ||||
Intervention (n=134) | Control (n=137) | Odds ratioa (95% CI) | Odds ratioa (95% CI) | |||
Excessive GWGb,c | 67 (50.0) | 68 (49.6) | 0.75 (0.43-1.32) | .31 | 0.75 (0.43-1.32) | .32 |
Adequate GWGb | 52 (38.8) | 48 (35.0) | Reference | Reference | ||
Inadequate GWGb | 15 (11.2) | 21 (15.3) | 0.66 (0.30-1.43) | .29 | 0.66 (0.30-1.44) | .29 |
aRegression analysis of gestational weight gain on group allocation. The coefficient is interpreted as the estimated effect of the intervention compared with the control adjusted for baseline body weight, BMI category (underweight and normal weight vs overweight and obesity), parity (0 vs 1 or more), and educational attainment (university degree vs no university degree).
bGWG was calculated as the difference between weight at follow-up and baseline, which then was divided by gestational weeks to obtain GWG expressed as kg/week. This GWG (kg/week) was compared to the weekly GWG recommendations by the National Academy of Medicine for the second and third trimesters to classify GWG as excessive, adequate, or inadequate.
cGWG: gestational weight gain.
There was no statistically significant interaction effect for parity or educational attainment (results not shown); however, data indicated that there was a marked interaction between pre-pregnancy BMI and group allocation with the intervention being more effective in women with overweight and obesity compared with those who were underweight and normal weight. Thus, for women with overweight and obesity, GWG in the intervention group was 1.33 kg (95% CI –2.92 to 0.26,
The interaction effect was furthermore supported by the results from a Bayesian estimation of the same interaction model (
Bayesian analysis (with imputation, n=305) of the intervention effect on gestational weight gain according to prepregnancy BMI.
Intervention effect on the secondary outcomes.
Outcome | Descriptive data, mean (SD) | Intervention effect using regression analysisa | |||||
Group | Imputed data analysis | Complete cases analysis | |||||
Intervention | Control | Coefficienta (95% CI) | Coefficienta (95% CI) | ||||
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Baseline (n=302)b | 6.54 (0.98) | 6.79 (0.97) | 0.27 (0.05 to 0.50) | .017 | 0.27 (0.05 to 0.50) | .018 | |
Follow-up (n=269)b | 6.53 (0.94) | 6.38 (1.07) | |||||
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Baseline (n=296)c | 38.7 (24.6) | 39.8 (23.5) | –0.76 (–5.34 to 3.80) | .74 | –1.01 (–5.66 to 3.62) | .67 | |
Follow-up (n=267)c | 26.3 (19.0) | 27.8 (24.7) | |||||
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Baseline (n=305)d | 23.4 (10.1) | 21.5 (7.6) | 0.05 (–0.65 to 0.76) | .88 | –0.03 (–0.71 to 0.64) | .92 | |
Follow-up (n=268)d | 26.8 (9.7) | 24.7 (7.5) | |||||
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Baseline (n=305)d | 45.0 (4.8) | 45.6 (4.8) | –0.09 (–0.46 to 0.28) | .64 | –0.07 (–0.45 to 0.30) | .70 | |
Follow-up (n=268)d | 51.9 (5.4) | 52.5 (5.4) | |||||
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Baseline (n=304)e | 4.8 (0.3) | 4.8 (0.3) | 0.06 (–0.03 to 0.15) | .21 | 0.06 (–0.03 to 0.14) | .18 | |
Follow-up (n=263)e | 4.7 (0.5) | 4.6 (0.3) | |||||
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Baseline (n=304)e | 1.41 (0.76) | 1.36 (0.65) | 0.10 (–0.13 to 0.34) | .39 | 0.12 (–0.11 to 0.36) | .31 | |
Follow-up (n=263)e | 2.41 (1.36) | 2.19 (0.98) |
aRegression analysis of follow-up measure of secondary outcome on group allocation. The coefficient is interpreted as the estimated effect of the intervention compared with the control adjusted for baseline value of the secondary outcome, BMI category (underweight and normal weight vs overweight and obesity), parity (0 vs 1 or more), and educational attainment (university degree vs no university degree). Imputed data analysis included data for all 305 women and the complete cases analysis included data for 263-269 women.
bBaseline, n=302 (151 intervention and 151 control); follow-up, n=269 (135 intervention and 134 control).
cBaseline, n=296 (146 intervention and 150 control); follow-up, n=267 (132 intervention and 135 control). Number of valid days for accelerometry: intervention group (baseline: 6.5 [SD 1.1] days; follow-up: 6.7 [SD 0.8] days); control group (baseline: 6.7 [SD 0.9] days; follow-up: 6.7 [SD 1.1] days). Average wear time for valid days: intervention group (baseline: 99.0%; follow-up: 97.5%); control group (baseline: 98.7%; follow-up: 98.4%).
dBaseline, n=305 (152 intervention and 153 control); follow-up, n=268 (133 intervention and 135 control).
eBaseline, n=304 (151 intervention and 153 control); follow-up, n=263 (130 intervention and 133 control).
This study is the first to examine the effectiveness of a comprehensive intervention delivered solely via an app on GWG, body fatness, dietary habits, physical activity, glycemia, and insulin resistance in pregnant women from all BMI categories. We did not observe any statistically significant effect on GWG; however, there was some evidence that women with overweight and obesity before pregnancy gained less weight in the intervention group as compared with the control group in the imputed analyses (–1.33 kg; 95% CI –2.92 to 0.26;
Previous studies of apps promoting healthy GWG have been pilot studies [
Another main finding is that we observed a statistically significant higher Swedish Healthy Eating Index score in the intervention group compared with the control group. As shown in
In contrast to the positive findings for dietary behaviors, we observed no effect on MVPA in this study. A few pilot mHealth studies in pregnant women have shown a beneficial effect on physical activity [
The HealthyMoms trial has several strengths. These include the randomized control design, high compliance (88.8% completion rate, 271/305) which provided adequate power to assess our outcomes, and the use of accurate and objective methods to assess primary and secondary outcomes (ie, measurements of body weight and body fatness using Bod Pod and objective measures of physical activity). Furthermore, another strength is that the intervention is theory-informed and uses key behavioral change techniques [
The HealthyMoms trial provides several important findings. Although we did not observe a statistically significant overall effect on the primary outcome (GWG), our findings indicate a meaningful effect in pregnant women with overweight or obesity compared with standard care, with a similar effect as seen in traditional face-to-face interventions [
Although we found no overall effect on GWG, our results demonstrate the potential of a smartphone app (HealthyMoms) to promote healthy dietary behaviors as well as to decrease weight gain during pregnancy in women with overweight and obesity, and with a similar effect as in traditional interventions. Thus, this intervention, solely delivered through an app, has potential to be useful for promoting a healthy lifestyle during pregnancy in many women while using less resources from health care.
CONSORT eHealth checklist.
Additional self-reported data on app usage and satisfaction in the intervention group (n=134) at the follow-up measurement. Participants responded to the following statements with the 6 alternatives shown.
Intervention effect on the components in the Swedish Healthy Eating Index.
gestational weight gain
Homeostatic Model Assessment for Insulin Resistance
mobile health
moderate-to-vigorous physical activity
This study was funded by the Swedish Research Council (2016-01147 to ML) and additionally supported by the Swedish Research Council for Health, Working Life and Welfare (Forte, 2017-00088 to PH; 2018-01410 to ML); Bo and Vera Ax:son Johnsons’ Foundation (to ML); the Strategic Research Area Health Care Science, Karolinska Institutet/Umeå University (to PH); the Swedish Society of Medicine (to PH); Karolinska Institutet (to PH); Lions Forskningsfond (to PH); and ALF Grants, Region Östergötland (ML). MHL was supported by a grant from Yrjö Jahnsson Foundation. The funders had no role in study design, conduct, or reporting of the trial. The authors thank all the participants in the trial as well as Eva Flinke and Ellinor Nilsson for invaluable help with data collection, the midwives in Region Östergötland for help with the recruitment, Hanna Henriksson and Christina Alexandrou for valuable help developing the content of the app, Jan Fjellström and Nils Lidström at ScientificMed for development of the app and technical support, and Anna Karin Lindroos and Eva Warensjö Lemming for support with the Riksmaten FLEX method (adaptations, data processing, and interpretation of results).
ML is the principal investigator of this randomized controlled trial. The study was conceptualized and designed together with PH, MBL, and RM. JS was responsible for developing the intervention content with support from PH and ML. JS and ES were responsible for the recruitment and data collection. JHM and MH contributed to processing of accelerometer and dietary data, respectively. MB contributed to data analysis with statistical expertise. ML, JS, PH, MBL, and MHL contributed to the development of the HealthyMoms app. JS, ES, PH, and ML drafted the manuscript and all authors have approved the final draft and submitted manuscript.
The authors declare no conflict of interest. MB owns a private company (Alexit AB) that works with development and dissemination of eHealth apps to health organizations and professionals (both private and public sector). Alexit AB was not involved in this study.