We found a positive association between increasing pre pregnancy body mass index and the risk of developing preeclampsia, amounting to an adjusted odds ratio of 1.8 for obese women with BMI above 30 as compared to normal weight women with BMI between 20 and 24.9. Among the maternal characteristics included in our analysis, only maternal age above 35 years of age showed a higher odds ratio. Our findings are in line with previous studies based on populations of pregnant women in high income countries [8,9,10,11,12].
Using the WHO definition of overweight and obesity, the prevalence of pre pregnancy overweight and obesity in our study population of ethnic African women was 24.0% and 7.3%, respectively. This compares with a study from Dar Es Salaam, where prevalence of obesity among females of reproductive age increased from 3.6% in 1995 to 9.1% in 2004 [13]. Our results, with nearly one third of the women were overweight or obese, correspond with global numbers of obesity, showing that obesity has now become a significant health challenge also in many low income countries [19].
We had no information on severity of preeclampsia or time of onset, but used preterm birth as a proxy for severity. The association between increasing BMI and preeclampsia was strongest for preeclampsia in connection with a term delivery, although the interaction between gestational age at delivery and preeclampsia was not statistically significant. These results are consistent with a study from the Swedish birth registry where the association between increasing BMI was stronger for term preeclampsia than for preeclampsia before term [20]. A possible explanation for these findings is that early and severe preeclampsia more often originates in placenta, whereas late and mild preeclampsia is more related to metabolic disease and hence more often associated with high BMI [21].
In our data, being overweight and obese was associated with higher maternal age, being married, high education, and being from the Chagga tribe, the majority tribe in the area. This indicates that overweight and obesity in this population are associated with higher socioeconomic status rather than low socioeconomic status which is the case in resource rich countries. In our study, adjustment for socioeconomic factors had, however, little influence on the effect of BMI. Socioeconomic factors are not among major risk factors of preeclampsia [7], and, although associated with BMI, are therefore not likely important confounders.
Our study was based on women of African origin in a low income setting, but we found an association between BMI and preeclampsia that was similar both in direction and magnitude to those from resource rich countries. However, the course and outcome of a preeclamptic pregnancy may vary not only by race or ethnicity but also by available resources. It is therefore important that African women, who bear a disproportionate burden of global maternal morbidity and mortality due to preeclampsia and other pregnancy complications, are included in studies on preeclampsia.
Strengths and limitations
A strength of our study is that we used data from a registry with a systematic collection of data based on a structured interview during the 13 years study period. It is also a strength that we had information on several possible confounding factors such as socio-demography and maternal disease both before and during pregnancy.
Because the study is hospital based we cannot rule out selection bias if women who deliver at KCMC differ from women in the area who deliver at home or in other hospitals. In the Kilimanjaro region, 13% of all deliveries take place outside a health facility, and nearly all women receive antenatal care from a skilled provider [22]. In general, selection will mostly influence prevalence estimates of exposure and outcome and to a lesser extent effect estimates. As a result of possible selection to giving birth at KCMC and also of how we selected our study population (exclusion of multifetal deliveries and women from rural areas who were referred to KCMC for medical reasons), the preeclampsia rate of 3.3% may not reflect the rate in the population. Furthermore, poor ascertainment of the mildest forms of preeclampsia may influence the observed preeclampsia rate. Among women in Northern Tanzania who had attended ANC for their most recent birth in the last five years, 79.9% had their blood pressure measured and 65.4% had their urine tested [22].
The mother’s weight was retrieved from her antenatal record if her first antenatal visit took place before week 16 of pregnancy, otherwise self-reported weight was recorded if reasonable. Most studies report that women tend to underreport their body weight [23], but this might vary from population to population depending on how socially acceptable or desirable it is to be underweight or overweight. However, since body weight was reported before the onset of preeclampsia, reporting error in any direction most likely represents a non-differential misclassification and therefore will tend to change the odds ratios towards 1, i.e. give conservative effect estimates. Furthermore, unmeasured factors such as nutrition and diet might represent residual confounding and affect our results if associated with both body mass index and preeclampsia.
Our main aim was to assess the association between BMI and preeclampsia, but we also report associations between the covariates and preeclampsia. We acknowledge that multiple comparisons are a concern and that the additional tests should be regarded as exploratory.