Dataset: Internet use for pregnancy-related information among antenatal care attendees in Mogadishu, Somalia
# Internet Use for Pregnancy-Related Information — Mogadishu, Somalia
## Background and Objective
Somalia faces persistent maternal health gaps alongside expanding digital connectivity. This dataset accompanies the study *"Internet use for pregnancy-related information and its correlates among women attending antenatal care in Mogadishu, Somalia,"* which assessed the prevalence, patterns, and sociodemographic correlates of internet use for pregnancy-related information among antenatal clinic attendees.
## Dataset Description
| Item | Detail |
|---|---|
| **Setting** | Six antenatal clinics (public and private), Banaadir region, Mogadishu, Somalia |
| **Period** | February – May 2025 |
| **Design** | Analytical cross-sectional study |
| **Sample size** | 422 pregnant women (18–49 years, literate, attending ANC) |
| **Data collection** | Structured, self-administered questionnaire |
## Outcome Variable
The primary outcome is **internet use for pregnancy-related information during the current pregnancy** (`internet`: Yes/No). Among the 422 participants, 78.2 % reported using the internet for this purpose, predominantly via social media, with daily use being the most common frequency.
## Variables Overview
The dataset contains 34 variables covering:
- **Sociodemographics** — age, education, employment, income, state of origin
- **Obstetric characteristics** — gravida, number of living children, trimester, reported fetal gender
- **Information sources** — internet, healthcare providers, family, friends, books/magazines, television
- **Educational activity** — participation and venue
- **Internet-use patterns** (among users) — frequency, access method, purpose, topic searched
- **Self-reported health problems** — anemia, gestational diabetes, heartburn, low back pain, morning sickness, vomiting, others
See `data_dictionary.csv` for a complete variable-level description.
## File Structure
```
├── data/
│ └── internet use data.csv # De-identified dataset (N …