Abstract
Infant morbidity and mortality are indicators used globally as measures of a country’s health status. Among the 8 millennium development goals (MDGs), this study aimed to address goal four (MDG 4) on the reduction of child mortality and six (MDG 6) on combating HIV and other diseases. We assessed different health conditions caused by bacterial vaginosis (BV) that could have life-long effects among infants. We aimed to address the time effects of BV on the long-term cause of infants' morbidities when asymmetry is assumed. We analyzed infant data from HIV-positive mothers with known BV status from a randomized controlled trial study conducted in Nairobi, Kenya. We aimed to investigate the effect of BV on infant morbidity with time from birth up to the age of 6 months. We derived a score for morbidity incidences depending on illnesses reported in the register during scheduled visits only. By adjusting for the mother’s BV status, child’s HIV status, sex, feeding status, and weight for age, we used two approaches for analysis. We considered and fitted the traditional generalized estimating (GEE) equations and our proposed skewed generalized estimating equations (SGEE). Overall, we included information on 327 infants. One thousand nine hundred sixty-two repeated measurements were available for analysis. Among the 327 mothers, 148 (45%) tested positive for BV, while 179 (55%) tested negative. We found that BV, gender, and time were associated with multiple health conditions in infants. Infants of women who tested positive for BV, at month 1, had 4.46 higher odds of various health conditions compared to infants of mothers who tested negative. The effects of BV tended to decrease with time, and at 5 months of age, children in the BV group had 1.10 times the odds of experiencing morbidity incidence. In the SGEE model, BV was statistically significant at the 0.05 level with a positive coefficient, indicating that children in the BV group had a higher probability of experiencing multiple morbidities. BV is a significant predictor of infant morbidity because its effects on exposed infants could persist over time. In contrast, the traditional GEE results showed an insignificant positive coefficient. The results indicate the need to factor in the skewness during analysis in case of data transformation, especially when converting from continuous to binary data for parsimony and straightforward interpretation of the effects of covariates. Maternal BV status was positively associated with morbidity incidences, which highlights the need for early intervention for infected women. Accelerated programs promoting access to BV treatment with proper infant handling practices that better deal with emerging multiple health conditions in infants may prove useful in reducing the incidence of infant morbidity in Kenya. Emphasis on care to promote better health for infants during growth is necessary to achieve the MDGs.
Joint generalized estimating equations for longitudinal binary data
