| Literature DB >> 31215516 |
Na Wang1,2,3, Zequn Deng1,3, Li Ming Wen4,5, Yan Ding2, Gengsheng He1,3.
Abstract
BACKGROUND: Hospital-based health promotion resources to assist pregnant women in adopting a healthy lifestyle and optimizing gestational weight gain are important, but with limited effects. Increasingly, women are using mobile apps to access health information during the antenatal period.Entities:
Keywords: consumer health information; health promotion; mobile applications; pregnancy
Mesh:
Year: 2019 PMID: 31215516 PMCID: PMC6604500 DOI: 10.2196/12631
Source DB: PubMed Journal: JMIR Mhealth Uhealth ISSN: 2291-5222 Impact factor: 4.773
Characteristics of study participants in the survey, Shanghai, China, 2018 (N=535).
| Characteristics | Values | |
| ≤25 | 30 (5.6) | |
| 26-34 | 436 (81.5) | |
| ≥35 | 69 (12.9) | |
| ≤Senior high school | 35 (6.5) | |
| College degree | 398 (74.4) | |
| Postgraduate degree or above | 102 (19.1) | |
| Single/divorced/separated/widowed | 6 (1.1) | |
| Married | 529 (98.9) | |
| <¥10,000 | 115 (21.8) | |
| ¥10,000-¥30,000 | 302 (57.2) | |
| >¥30,000 | 111 (21.0) | |
| First degree family history of diabetes mellitus | 73 (13.6) | |
| Anemia before or during pregnancy | 127 (23.7) | |
| Smoking before pregnancy | 20 (3.7) | |
| Smoking during pregnancy | 0 (0) | |
| Physical activity (moderate level <30 min) | 417 (77.9) | |
| Parity (primipara) | 478 (89.3) | |
| Underweight | 85 (15.9) | |
| Normal weight | 346 (64.7) | |
| Overweight | 75 (14.0) | |
| Obese | 29 (5.4) | |
| Gestational week (week), median (interquartile range) | 32 (17-33) | |
| Inadequate GWGc | 172 (32.1) | |
| Adequate GWG | 234 (43.7) | |
| Excessive GWG | 129 (24.1) | |
aN=528.
bOne Chinese Yuan (¥)=US $0.1437.
cGWG: gestational weight gain.
Sources of health information by trimester of pregnancy of Chinese women in Shanghai, China, 2018.
| Sources of health information | All women (N=535), n (%) | First trimester (n=50), n (%) | Second trimester (n=139), n (%) | Third trimester (n=346), n (%) | ||
| iOS | 438 (81.9) | 39 (78) | 111 (79.9) | 288 (83.2) | .52 | |
| Android | 97 (18.1) | 11 (22) | 28 (20.1) | 58 (16.8) | .52 | |
| Pregnancy apps | 261 (48.8) | 35 (70) | 75 (54.0) | 151 (43.6) | .001a | |
| Other Web-based media | 366 (68.4) | 37 (74) | 96 (69.1) | 233 (67.3) | .63 | |
| Television | 36 (6.7) | 6 (12) | 17 (12.2) | 13 (3.8) | .001a | |
| Paper materials | 84 (15.7) | 14 (28) | 33 (23.7) | 37 (10.7) | <.001a | |
| Face-to-face with health professionals | 184 (34.4) | 23(46) | 57(41.0) | 104(30.1) | .01a | |
| Family/friends | 59 (11.0) | 4 (8) | 4 (2.9) | 51 (14.7) | .001a | |
| Pregnancy apps | 263 (49.2) | 35 (70) | 85 (61.2) | 143 (41.3) | <.001a | |
| Other Web-based media | 392 (73.3) | 40 (80) | 120 (86.3) | 232 (67.1) | <.001a | |
| Television | 39 (7.3) | 8 (16) | 17 (12.2) | 14 (4.0) | <.001a | |
| Paper materials | 83 (15.5) | 15 (30) | 35 (25.2) | 33 (9.5) | <.001a | |
| Face-to-face consultations with health professionalsb | 109 (20.4) | 6 (12) | 27 (19.4) | 76 (22.0) | .25 | |
| Family/friendsb | 97 (18.1) | 3 (6) | 5 (3.6) | 89 (25.7) | <.001a | |
aRepresents a significant difference between the 3 groups.
bThere were significant differences between current sources of information and expected sources of information from face-to-face consultations with health professionals (P<.001) and family/friends (P=.001) for health promotion.
Results of a multivariable logistic regression analysis of factors associated with app usage of pregnant women in Shanghai, China (N=528; after exclusion of 7 cases for missing data on household income).
| Factorsa | Beta | SE | Wald | Odds ratio | 95% CI | ||
| —b | — | 0.286 | — | — | .87 | ||
| ≤25 | — | — | — | 1.000 (reference) | — | — | |
| 26-34 | .041 | 0.400 | 0.010 | 1.042 | 0.475-2.282 | .92 | |
| ≥35 | −.113 | 0.474 | 0.057 | 0.893 | 0.352-2.263 | .81 | |
| Education (1= Postgraduate degree or above, 0=≤College degree) | .036 | 0.238 | 0.024 | 1.037 | 0.651-1.653 | .88 | |
| — | — | 3.787 | — | — | .15 | ||
| <¥10,000 | — | — | — | 1.000 (reference) | — | — | |
| ¥10,000-30,000 | .222 | 0.233 | 0.910 | 1.249 | 0.791-1.970 | .34 | |
| >¥30,000 | .559 | 0.290 | 3.722 | 1.749 | 0.991-3.087 | .05 | |
| Parity (1=multipara, 0=primipara) | .681 | 0.326 | 4.361 | 1.975 | 1.043-3.742 | .04d | |
| — | — | 6.994 | — | — | .07 | ||
| Underweight | .197 | 0.256 | 0.594 | 1.218 | 0.738-2.010 | .44 | |
| Normal weight | — | — | — | 1.000 (reference) | — | — | |
| Overweight | −.396 | 0.264 | 2.248 | 0.673 | 0.401-1.129 | .13 | |
| Obese | −.952 | 0.486 | 3.843 | 0.386 | 0.149-1.000 | .05 | |
| — | — | 20.736 | — | — | <.001d | ||
| First | 1.117 | 0.338 | 10.91 | 3.057 | 1.575-5.932 | .001d | |
| Second | .791 | 0.213 | 13.802 | 2.206 | 1.453-3.349 | <.001d | |
| Third | — | — | — | 1.000 (reference) | — | — | |
aRegression models included maternal age, education, household income, parity, pre-pregnancy body mass index category and trimester.
bNot applicable.
cOne Chinese Yuan (¥)=US $0.1437.
dRepresents the variable is significant in the logistic regression model.
Reasons for using pregnancy apps by the trimester of pregnancy.
| Reasons for using pregnancy apps | All women (N=535), n (%) | First trimester (n=50), n (%) | Second trimester (n=139), n (%) | Third trimester (n=346), n (%) | |
| Monitoring fetal development | 436 (81.5) | 36 (72) | 89 (64.0) | 311 (89.9) | <.001a |
| Tracking own body | 101 (18.9) | 16 (32) | 37 (26.6) | 48 (13.9) | <.001a |
| Learning information regarding nutrition during pregnancy and recording diet | 140 (26.2) | 16 (32) | 48 (34.5) | 76 (22.0) | .01a |
| Learning information regarding physical activity during pregnancy and recording exercise | 91 (17.0) | 14 (28) | 25 (18.0) | 52 (15.0) | .07 |
| Understanding the content of antenatal care | 128 (23.9) | 15 (30) | 40 (28.8) | 73 (21.1) | .12 |
| Storing photos of themselves | 52 (9.7) | 4 (8) | 8 (5.8) | 40 (11.6) | .14 |
| Storing fetal ultrasound images | 27 (5.0) | 3 (6) | 6 (4.3) | 18 (5.2) | .88 |
| Recording antenatal examination | 87 (16.3) | 7 (14) | 18 (12.9) | 62 (17.9) | .37 |
| Web-based discussions with other pregnant women | 83 (15.5) | 7 (14) | 21 (15.1) | 55 (15.9) | .93 |
aRepresents a significant difference between the 3 groups.
Demographic characteristics of focus group participants in Shanghai, China.
| Characteristics | Group 1 (n=5) | Group 2 (n=8) | Group 3 (n=7) | Group 4 (n=8) | Total (n=28) | |
| Age (years), mean (SD) | 29.8 (3.5) | 29.3 (3.4) | 30.1 (1.7) | 29.3 (3.8) | 29.6 (3.1) | |
| <¥10,000 | 2 (40) | 4 (50) | 2 (29) | 3 (38) | 11 (39) | |
| ¥10,000-30,000 | 1 (20) | 4 (50) | 4 (57) | 5 (63) | 14 (50) | |
| >¥30,000 | 2 (40) | 0 (0) | 1 (14) | 0 (0) | 3 (11) | |
| ≤Senior high school | 1 (20) | 0 (0) | 0 (0) | 2 (25) | 3 (11) | |
| College degree | 3 (60) | 6 (75) | 5 (71) | 6 (75) | 20 (71) | |
| Postgraduate degree or above | 1 (20) | 2 (25) | 2 (29) | 0 (0) | 5 (18) | |
| Parity (primipara), n (%) | 4 (80) | 8 (100) | 6 (86) | 8 (100) | 26 (93) | |
| Prepregnancy body mass index (kg/m2), median (IQRb) | 18.6 (16.9-18.9) | 21.8 (20.4-27.4) | 22.6 (20.8-22.4) | 20.6 (18.5-22.3) | 21.0 (18.9-23.5) | |
| Gestational age (week), median (IQR) | 32 (13-36) | 33 (15-40) | 30 (18-37) | 34 (17-39) | 32 (15-38) | |
aOne Chinese Yuan (¥)=US $0.1437.
bIQR: interquartile range.