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. 2022 Mar 26:12:04024.
doi: 10.7189/jogh.12.04024. eCollection 2022.

A systematic review on estimating population attributable fraction for risk factors for small-for-gestational-age births in 81 low- and middle-income countries

Sabi Gurung  1 , Hannah Hanzi Tong  1 , Emily Bryce  1 , Joanne Katz  1 , Anne Cc Lee  2 , Robert E Black  1 , Neff Walker  1
Affiliations

A systematic review on estimating population attributable fraction for risk factors for small-for-gestational-age births in 81 low- and middle-income countries

Sabi Gurung et al. J Glob Health. .

Abstract

Background: Small for gestational age (SGA) is a public health concern since it is associated with mortality in neonatal and post-neonatal period. Despite the large magnitude of the problem, little is known about the population-attributable risk (PAR) of various risk factors for SGA. This study estimated the relative contribution of risk factors for SGA, as a basis for identifying priority areas for developing and/or implementing interventions to reduce the incidence of SGA births and related mortality and morbidity.

Methods: We conducted a literature review on 63 potential risk factors for SGA to quantify the risk relationship and estimate the prevalence of risk factors (RFs). We calculated the population-attributable fraction for each of the identified RF for 81 Countdown countries and calculated regional estimates. Twenty-five RFs were included in the final model while extended model included all the 25 RFs from the final model and two additional RFs.

Results: In the final and extended models, the RFs included in each model have a total PAF equal to 63.97% and 69.66%, respectively of SGA across the 81 LMICs. In the extended model, maternal nutritional status has the greatest PAF (28.15%), followed by environmental and other exposures during pregnancy (15.82%), pregnancy history (11.01%), and general health issues or morbidity (10.34%). The RFs included in the final and extended model for Sub-Saharan African (SSA) region have a total PAF of 63.28% and 65.72% of SGA, respectively. In SSA, the top three RF categories in the extended model are nutrition (25.05%), environment and other exposure (13.01%), and general health issues or morbidity (10.72%), while in South-Asia's it was nutrition (30.56%), environment and other exposure (15.27%) and pregnancy history (11.68%).

Conclusions: The various types of RFs that play a role in SGA births highlight the importance of a multifaceted approach to tackle SGA. Depending on the types of RFs, intervention should be strategically targeted at either individual or household and/or community or policy level. There is also a need to research the mechanisms by which some of the RFs might hinder fetal growth.

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Conflict of interest statement

Conflict of interest: The authors completed the ICMJE Unified Competing Interest Form (available upon request from the corresponding author), and declare no conflicts of interest.

Figures

Figure 1
Figure 1
Methods for identifying risk factors (RF) for small-for-gestational age babies. Note: The categories with an asterisk sign have an additional RF included only in the extended model (anemia in the maternal nutritional status category and indoor air pollution in the environmental and other exposures during pregnancy category).
Figure 2
Figure 2
Population attributable fractions of risk factors for small-for-gestational age infants in 81 countries in the final and extended models.
Figure 3
Figure 3
Sub-Saharan African region’s population attributable fractions for small-for-gestational age infants in the final and extended models.
Figure 4
Figure 4
South-Asian Region’s population attributable fractions for small-for-gestational age infants in the final and extended models.
See this image and copyright information in PMC

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