Measurement of symphysis fundal height for gestational age estimation in low-to-middle-income countries: A systematic review and meta-analysis

In low- and middle-income countries (LMIC), measurement of symphysis fundal height (SFH) is often the only available method of estimating gestational age (GA) in pregnancy. This systematic review aims to summarize methods of SFH measurement and assess the accuracy of SFH for the purpose of GA estimation. We searched PubMed, EMBASE, Cochrane, Web of Science, POPLINE, and WHO Global Health Libraries from January 1980 through November 2021. For SFH accuracy, we pooled the variance of the mean difference between GA confirmed by ultrasound versus SFH. Of 1,003 studies identified, 37 studies were included. Nineteen different SFH measurement techniques and 13 SFH-to-GA conversion methods were identified. In pooled analysis of five studies (n = 5838 pregnancies), 71% (95% CI: 66–77%) of pregnancies dated by SFH were within ±14 days of ultrasound confirmed dating. Using the 1 cm SFH = 1wk assumption, SFH underestimated GA compared with ultrasound-confirmed GA (mean bias: -14.0 days) with poor accuracy (95% limits of agreement [LOA]: ±42.8 days; n = 3 studies, 2447 pregnancies). Statistical modeling of three serial SFH measurements performed better, but accuracy was still poor (95% LOA ±33 days; n = 4 studies, 4391 pregnancies). In conclusion, there is wide variation in SFH measurement and SFH-to-GA conversion techniques. SFH is inaccurate for estimating GA and should not be used for GA dating. Increasing access to quality ultrasonography early in pregnancy should be prioritized to improve gestational age assessment in LMIC

Healthy Workforce, Healthy Baby? Quantitative and Political Analyses of Health Workers in Mexico

Each year, almost five million babies die within their first year of life, from largely preventable causes. Insufficient availability of health workers has been identified as one of the most common barriers to delivering effective newborn healthcare. This dissertation focuses on the allocation and effectiveness of health workers at improving child health in Mexico. The first two chapters of this dissertation use municipality-level fixed effects analyses to assess the relationship between health workers and child health, specifically infant mortality rate (IMR) and two key risk factors for infant mortality: preterm birth prevalence and low birth weight prevalence. In the first chapter, we find that increasing physician density and nurse density both significantly decrease IMR but the effect of adding one physician (4.6 fewer deaths per 1,000 live births, p<0.001) is substantially larger than the effect of adding one nurse (2.5 fewer deaths per 1,000 live births, p<0.001) to a municipality with baseline physician and nurse densities of zero. In the second chapter, we did not find any significant effect of any health worker density on preterm birth or low birth weight prevalence. The findings from chapters one and two suggest that while health workers may have a protective effect on IMR, they may not be effective at preventing preterm/low birth weight births The third chapter of this dissertation uses municipality-level fixed effects analysis to examine the relationship between the state electoral cycle and allocation of health workers. We find that in election years, physician density increased by 0.01 physicians (p<0.001) and nurse density increased by 0.02 nurses (p<0.001) per 1,000 population, leading to an average increase of 33 new physicians and 77 new nurses per state compared to non-election years. This finding suggests the presence of an electoral budget cycle in allocation of health workers during the study period in Mexico. Considering the significant contribution that health workers can have at reducing IMR, understanding the decisions governing their allocation is an important area of study that could improve allocative efficiencies and child health outcomes

Validity of Newborn Clinical Assessment to Determine Gestational Age in Bangladesh

BackgroundGestational age (GA) is frequently unknown or inaccurate in pregnancies in low-income countries. Early identification of preterm infants may help link them to potentially life-saving interventions.MethodsWe conducted a validation study in a community-based birth cohort in rural Bangladesh. GA was determined by pregnancy ultrasound (&lt;20 weeks). Community health workers conducted home visits (&lt;72 hours) to assess physical/neuromuscular signs and measure anthropometrics. The distribution, agreement, and diagnostic accuracy of different clinical methods of GA assessment were determined compared with early ultrasound dating.ResultsIn the live-born cohort (n = 1066), the mean ultrasound GA was 39.1 weeks (SD 2.0) and prevalence of preterm birth (&lt;37 weeks) was 11.4%. Among assessed newborns (n = 710), the mean ultrasound GA was 39.3 weeks (SD 1.6) (8.3% preterm) and by Ballard scoring the mean GA was 38.9 weeks (SD 1.7) (12.9% preterm). The average bias of the Ballard was -0.4 weeks; however, 95% limits of agreement were wide (-4.7 to 4.0 weeks) and the accuracy for identifying preterm infants was low (sensitivity 16%, specificity 87%). Simplified methods for GA assessment had poor diagnostic accuracy for identifying preterm births (community health worker prematurity scorecard [sensitivity/specificity: 70%/27%]; Capurro [5%/96%]; Eregie [75%/58%]; Bhagwat [18%/87%], foot length &lt;75 mm [64%/35%]; birth weight &lt;2500 g [54%/82%]). Neonatal anthropometrics had poor to fair performance for classifying preterm infants (areas under the receiver operating curve 0.52-0.80).ConclusionsNewborn clinical assessment of GA is challenging at the community level in low-resource settings. Anthropometrics are also inaccurate surrogate markers for GA in settings with high rates of fetal growth restriction