99% of low birth weight babies were either small for gestational age or preterm. Just 23% of babies were born either small for gestational age or preterm but they contributed 52% of the neonatal deaths. The 4% of babies who were born preterm were at highest likelihood of death, accounting for 30% of the neonatal deaths, with over 90% of their mortality risk being attributed to being preterm. However this analysis of data from East Africa revealed that weight for gestational age played an important role for moderately preterm babies. The odds of neonatal mortality of babies born 34–36 wk gestation and appropriate weight for gestational age was just three times higher than term babies of appropriate weight, but was 20 times higher amongst babies born 34–36 wk gestation and small for gestational age.
Preterm birth is a direct cause of mortality but also aggravates the effect of other risk factors; small for gestational age may arise because of intra-uterine growth retardation which has been shown to increase the risk of mortality and morbidity 
. Therefore being small for gestational age (especially if that was due to intra-uterine growth retardation) and preterm (even if only moderately so) may synergistically lead to the increased odds observed here. These findings have public health importance when thinking about the potential of interventions that focus on reducing intra-uterine growth retardation, or on reducing prematurity in this setting. Malaria in pregnancy interventions, for example, may have a marked impact to reduce the occurrence of severe neonatal outcomes but push a larger number of newborns into moderate categories of risk.
Previous studies have reported the mortality risk associated with separate measures of birth outcome in East Africa 
, but to our knowledge, this analysis of preterm births stratified by weight for gestational age has not been presented before for an African population and thus provides much needed evidence relevant to priority setting in a high mortality setting 
. One limitation was that the search for studies was not systematic because early discussions and searches of the literature did not reveal any studies that had addressed this problem in the African setting. The analysis does not attempt to present population level estimates of low birth weight, small for gestational age, preterm, or neonatal mortality, but rather to disentangle the relationship between them when they occur. A particular strength has been the access to detailed newborn datasets from a relatively homogenous geographical spread, and the rigorous definitions applied to measures of birth weight and gestational age.
Nonetheless, there are three inter-related limitations in this study, each a reflection of the difficulty of obtaining high quality individual level birth outcome data in this setting. First, there was selection bias in that 70% of the included babies were born in a health facility, compared to only 24% of excluded babies, and an expected 50% at the population level for East Africa; thus the included mothers may be better health seekers than those excluded. These study findings may be an underestimate of the true population level effects.
The second limitation, consistent with the first, was the exclusion of around 15% of live births because of missing data for birth weight or gestational age information, or survival to 28 d of life. In our sensitivity analysis there was evidence of bias in that, for three of the four studies, neonatal mortality of those excluded was far higher than of those included, as was the prevalence of preterm birth. The most likely explanation for this finding is that some very early deaths were excluded or classified as lost to follow-up because babies died before birth weight or gestational age could be estimated (32% of those excluded [285/884] had missing birth weight and gestational age data, 17% [149/884] had missing gestational age, and 16% [144/884] had missing birth weight). Again, this limitation may have led to underestimation of the mortality risks, especially in the first days of life, associated with low birth weight, preterm, and small for gestational age. Imputation was considered as an approach to address the problem of missing data, a key factor being to have gestational age where birth weight was missing. However, given the quantity of missing gestational age data we did not feel confident that there were enough good covariates with which to make a sensible prediction model.
Finally, there may be measurement error for gestational age (and therefore classification of size for gestational age) because of the methods used to determine gestational age, and there may also be misclassification of size for gestational age because of the use of US-based reference population for standardised birth weight by gestational age values 
. On the later point, currently there is a lack of standardised birth weight by gestational age values for sub-Saharan Africa: one multi-country study (www.intergrowth21.org.uk
) that aims to address this is on-going and results are expected to be available in 2014. Some data from individual studies exist, for example in 2011 a study in Botswana developed standard values there and found that Botswana-born preterm infants had higher average birth weights than US-born infants 
. Similar conclusions were also reported from Congo 
, and it has previously been suggested that such findings may be due to different growth velocity at the end of pregnancy for some groups 
. If the findings from the Botswana and Congo studies are generalisable for Tanzania, Kenya, and Uganda, then using the US standard could have led us to underestimate small for gestational age amongst preterm babies. However, the authors of those studies noted that the accurate dating of gestation was problematic, 
or may have represented an atypically healthy population. 
Indeed, gestational age data across Africa are scarce, and what data exist are prone to bias—most markedly for preterm newborns who are at highest mortality risk 
. Of the three available gestation dating methods, neonatal assessments have consistently been shown to underestimate very preterm infants by as much as 2 wk compared to ultrasound, date of last monthly period has been shown to overestimate prematurity and to be susceptible to serious reporting errors, while ultrasound is generally considered to be the most precise dating method but is rarely available in sub-Saharan Africa 
. In our study, only 4% of the newborns included in the analysis were defined as preterm. A previous meta-analysis had estimated preterm births in East Africa to be amongst the highest in the world at 14% 
, but over half the included studies in that analysis did not report the method of estimation and the findings should be interpreted with caution.
Reflecting on the implications of these uncertainties for the principal findings, we observed an increase in odds of neonatal mortality to be consistently larger when gestational age was assessed by ultrasound compared to neonatal assessment, but both methods show results in the same direction, and the lower limit of confidence around the estimates was very close for both (). We also observed a consistent pattern across countries. As such, we have confidence that the finding of an increased odds of neonatal mortality amongst those born moderately premature and small for gestational age (SGA) in comparison to those born moderately premature and appropriate for gestational age (AGA) in East Africa is secure. However, because of the challenges of gathering high quality population-level newborn data in the East African setting, especially gestational age and classification of size for gestational age, we cannot be certain about the true magnitude of that increase. Given the growing emphasis on the prevention of newborn deaths across sub-Saharan Africa, the measurement and reporting of individual newborn outcomes should be given greater emphasis.
Three issues particularly exacerbate interventions to prevent preterm and small births in the East African setting: (1) the aetiology of small for gestational age and preterm birth is multi-factorial 
; (2) around half of babies are born at home and experience higher mortality risks than those born in facilities 
; and (3) small for gestational age and preterm babies born at home are frequently not identified as needing extra care 
. As the deadline for achieving Millennium Development Goals grows near, implementing newborn interventions that target small for gestational age as well as preterm birth, and are adaptable to poorly resourced health facility or community settings is vital 
Preterm or small for gestation births accounted for 52% of newborn deaths in this analysis of data from East Africa. Preterm birth had the strongest association with death, but there was also an additional risk for moderately preterm babies born small for gestational age compared to those born moderately preterm and appropriate for gestational age. 8% of babies who died were born moderately preterm and small for gestational age: if this was extrapolated to the estimated 1.2 million neonatal deaths in sub-Saharan Africa in 2008 this finding would translate to 96,000 African newborns lost.