Independent and cumulative effects of risk factors associated with stillbirths in 50 low- and middle-income countries: A multi-country cross-sectional study

Abstract

Background: Early identification of high-risk pregnancies could reduce stillbirths, yet remains a challenge in low- and middle-income countries (LMICs). This study aims to estimate the associations between easily observable risk factors and stillbirths, and construct a risk score which could be adopted in LMICs to identify pregnancies with high risk of stillbirths. Methods: Using the most recent Demographic and Health Surveys from 50 low- and middle-income countries (LMICs) with available data between January 1, 2010 and December 31, 2021, we analysed a total of 22 factors associated with stillbirths in a series of single-adjusted and mutually adjusted logistic regression models. Upon identification of the risk factors with the strongest associations, we constructed a risk score on the basis of the magnitude of the β coefficient to examine the cumulative effects of risk factors on stillbirths. To assess whether the associations between risk scores and stillbirths were moderated by protective factors, we added an interaction term between the identified protective factor and risk scores to the regression model. We also conducted two sets of subgroup analyses for previous history of pregnancy and maternal age at pregnancy and four sets of supplementary analyses to test the robustness of the results. Findings: Among the 795,642 women identified for analysis with at least one pregnancy within the five years before the survey, the most recent pregnancy of 8968 (1.13%) ended as stillbirths. Using a mutually adjusted regression model, we found that the top factors showing the strongest associations with stillbirths were short maternal height (odds ratio [OR]: 1.99, 95% confidence interval [CI]: 1.48–2.67, P < 0.001), interpregnancy interval less than six months (OR: 1.84, 95% CI: 1.42–2.38, P < 0.001), previous stillbirth history (OR: 1.55, 95% CI: 1.07–2.26, P < 0.020), low maternal education (OR: 1.50, 95% CI: 1.01–2.24, P = 0.045), and lowest household wealth (OR: 1.32, 95% CI: 1.08–1.61, P = 0.008). A female household head was a protective factor with an OR of 0.71 (95% CI: 0.55–0.90, P = 0.005). Single-adjusted models, subgroup analyses, and sensitivity analyses showed generally consistent results. We also found that the odds of stillbirths increased with a larger risk score with a P trend <0.001. Compared with women without any risk factors, women with a risk score of 5 or more were 4.11 (95% CI: 2.83–5.97, P < 0.001) times more likely to have their pregnancies ending up as stillbirths. However, these associations were weakened if the head of household was female. Interpretation: Our study suggested that short maternal height, low socioeconomic status, previous stillbirth history, low maternal education, and very short interpregnancy interval had the strongest associations with stillbirths. The construction of risk scores using easily observable risk factors could be an effective way to identify high-risk pregnancies in resource-poor settings. Funding: This research was supported by Sanming Project of Medicine in Shenzhen (NO. SZSM202111001) and China National Natural Science Foundation (NO. 72203119). © 2022 The Author(s)