A cross-sectional study of determinants of birth weight of neonates in the Greater Accra region of Ghana

Socio-demographic characteristics of respondents

Almost all of the respondents were on health insurance (99.1 %). Over half of the
respondents (56.3 %) earned less than GH¢100.00 per month while only 2.5 % earned
GH¢1000.00 or more, Table 1. Their occupations were grouped into ‘Professional’, referring to Teachers, Engineers,
Medical Doctors, etc., followed by ‘Middle Level Officers’, referring to respondents
engaged in white-collar jobs (whether private or public) such as secretaries, managers,
etc. The rest were ‘Trades’, referring to artisans such as hair-dressers, seamstresses,
caterers, etc., and finally traders, also referring to traders in the local markets
or business women operating mini-markets or super markets, etc. It turned out that
less than half of the respondents (34.5 %) were traders, 5.5 % were professionals,
while 4.6 % were middle level officers. Almost 40 % of them were unemployed. The modal
parity was 1 and the median was 2. Parity was however re-grouped into 0–1, 2–3 and??4.
About 44 % were expecting up to their second child while a little over 11 % were expecting
at least their fourth child. A great majority of them were married (85.4 %) while
a little over half of them had completed either Junior Secondary or Senior Secondary
school. About 9.6 % had either never been to school or had completed primary school,
and 35.9 % had completed tertiary education. The ages of the respondents were pre-grouped
from ‘Under 20 years’,’20–29 years’ all the way to’40 years and above’. The modal
age group was 20–29 year (48.8 %) closely followed by 30–39 years (43.1 %) whereas
the least was 40 years and above (3.2 %), Table 1.

Table 1. Socio-demographic characteristics of respondents

Anthropometric measurements, gestation and hemoglobin levels of women at birth

Table 2 contains the frequencies of gestation at birth, systolic and diastolic blood pressure,
hemoglobin at birth, and BMI at birth. There is a significant positive correlation
between systolic blood pressure and baby’s weight at birth (r?=?0.216, p?=?0.001), diastolic blood pressure and baby’s weight at birth (r?=?0.214, p?=?0.001), and parity and baby’s weight at birth (r?=?0.140, p?=?0.021) and between mother’s age and baby’s weight at birth (0.108, p?=?0.05). The mean gestation at birth was almost 39 weeks, the mean BMI of mother
at birth was 28.8 kg/m
²
, and the mean systolic blood pressure at birth was 114.5 mmHg while that of the diastolic
blood pressure at birth was 70.3 mmHg. The hemoglobin at birth was 11.3. The anthropometric
measurements were re-grouped in Table 2. Majority (over 60 %) of the mothers were in the 35–39.9 gestation at birth group
while a similar proportion (over 60 %) of the mothers were in the 90–119.9 mmHg group.
Majority of the mothers (over 80 %) had their diastolic blood pressure in the 60–89.9 mmHg
group. The most represented hemoglobin at birth (25.6 %) fell in the 11–11.9 group.
The most common BMI at birth (58.0 %) fell in the 20–29.9 kg/m
²
group.

Table 2. Anthropometric measurements, gestation and hemoglobin levels of women at birth

Whereas majority of the low birth weights were recorded among the female neonates,
(60.3 %), the opposite was the case for the recorded normal birth weights (55.2 %
of male neonates), Table 3. On birth weight and hemoglobin levels of mothers, whereas majority of both low birth
weights and normal birth weights were non-anemic, the proportion of the anemic among
the low birth weights (33.8 %) was almost twice that recorded among the normal birth
weights (19.6 %). It is also interesting to quickly point out that whereas majority
(64.5 %) of the low birth weights were premature births, the opposite was the case
among the normal birth weights (71.8 %).

Table 3. Prevalence of low birth weight and normal birth weight

In Table 4, there is confirmation to the finding in Table 3 that the low birth weights recorded a significantly (p??0.001) lower gestation (34.8?±?3.8 weeks) than the normal birth weights (37.3?±?3.3).
It is also the case, per the underlying data, that mothers of normal weight neonates
(29.0?±?6.3) have a significantly (p?=?0.034) higher BMI than their low birth weight counterparts (27.3?±?5.4). However,
the systolic blood pressure of mothers of normal birth weight neonates (113.3?±?17.0)
are significantly lower (p??0.001) than that of the mothers of low birth weight neonates (122.2?±?30.0). A
similar picture can be seen with the case of diastolic blood pressure (69.8?±?13.2
for normal birth weight and 75.6?±?20.7 for low birth weight with a significance of
p?=?0.001). However, mothers’ hemoglobin levels had no significant association with
birth weights of neonates, Table 4.

Table 4. Association between birth weight of neonates and anthropometric characteristics of
mothers

One of the areas of interest in this study was how the mean birth weights of the neonates
were affected by the various levels of the socio-demographic and anthropometric parameters
of mothers, Table 5. As the BMI of the mother generally rises, the birth weight of her neonate also rises,
however this association is not statistically significant at 95 % confidence level,
Table 5. This same trend show in the remaining parameters investigated such as Age of mother,
Educational level of mother, Mother’s occupation, Mother’s monthly income, Gestation
at birth, Systolic and Diastolic blood pressures and Mother’s haemoglobin level at
birth were seen to have no significant association with the birth weight of the neonates.

Table 5. Association between socio-demographic and anthropometric characteristics of mothers
and birth weights of neonates

For the binary logistic regression, the Nagelkerke R Square (=0.236) shows that about
23.6 % of the variation in the outcome variable (Birth Weight) is explained by this
logistic model. In the Wald statistics (this determines the relative importance of
the predictor variables in predicting the response, thus the higher the more important
and vice versa) column of Table 6, Gestation-at-birth (Wald?=?9.4) happens to be the most important predictor of a
mother’s likelihood of having normal birth weight. This is followed by Diastolic-blood-pressure-at-birth
(Wald?=?7.08), and mother’s-weight-at-birth (Wald?=?7.07). However the remaining variables
were not significant in predicting a mother’s likelihood of having normal birth weight
baby.

Table 6. Results of binary logit – determinants of birth weight

Diastolic-blood-pressure-at-birth (0.008) was the only significant factor that predicted
baby’s weight at birth. The Exp (B) and 95 % C.I. columns of Table 6 give us the odds ratios and their corresponding 95 % confidence interval estimates
respectively. An increase in a mother’s diastolic blood pressure at birth has a 4.7 %
(95 % CI 2.2 to 7.9 %) decrease in the odds of having a normal birth weight baby.

The overall accuracy of this model to predict subjects having normal birth weight
(with a predicted probability of 0.5 or greater) is 93.7 % (Table 6). The sensitivity is given as 497/498?=?99.8 % and the specificity is 6/39?=?15.4 %.
The model has a positive predictive value (PPV)?=?497/530?=?93.8 % and negative predictive
value (NPV)?=?6/7?=?85.7 %.

Discussion

The bulk of incidents of low birth weight are found in developing countries, the major
cause of which is preterm birth (37 weeks) 15]. One key finding in this study is the fact that the mothers of neonates with low
birth weight had significantly lower BMI and gestation at birth than their normal
birth weight counterparts. This is seen in the association between birth weight and
anthropometric characteristics of mothers in this article. We could not however demonstrate,
with the study data, that maternal characteristics such as age, education, occupation,
monthly income and haemoglobin at birth are significant determinants of birth weight
of neonates. This is unlike studies that have demonstrated that poor families are
more likely to have LBW neonates than well to do ones 19]. In their study titled “Maternal anthropometric measurements and other factors: relation
with birth weight of neonates”, Tabrizi and Saraswathi 20] considered family income, among others, as a predictive factor of birth weight of
neonates 21].

Meanwhile, several studies across the world have shown that, education affects neonatal
birth weight 6], 19], 21], though it has been established in literature that the causes of LBW in neonates
differ between developing and developed societies 15], 22]–25]. It is also reported in de AlencarBritto et al. that age, BMI and family income were
significantly associated with LBW in neonates 26]. However in this study, they were not.

There was no significant association between gestation at birth and birth weight of
neonates, mother’s BMI and birth weight of neonates, systolic blood pressure and birth
weight of neonates, as well as diastolic blood pressure and birth weight of neonates.
Though the gestation at birth, mothers’ height and weight at birth were lower for
LBW neonates than their NBW counterparts, that difference was not statistically significant.
Whereas the systolic and diastolic blood pressures and were higher for mothers of
LBW neonates than their NBW counterparts, only the diastolic blood pressure showed
a statistically significant difference. These findings in the current study run through
several studies over the world 20], 27], 28]. However, in developing countries, gestation at birth is a determinant of birth weight
29].

There was a significant positive association between the BMI of mothers, on one side,
and the weights of their neonates. Thus mothers of normal birth weight neonates were
also significantly taller and heavier than their low birth weight counterparts 29]. This is similar to the findings of Momen et al. 17] in their study titled Anthropometric assessment of nutritional status of Bangladeshi pregnant women and
weight of their newborns, conducted in Bangladesh. In their study they found a positive association between
the weight of mothers and that of their neonates. Similarly, these findings in the
current study also run through the studies of Hassan et al., titled relationship between maternal characteristics and neonatal birth size in Egypt, in which correlation tests between maternal and neonatal anthropometric measurements
revealed that for both sexes combined maternal weight had a significant positive correlation
with neonatal weight 27]. The relationship between the BMIs of mothers and the birth weights of their neonates
was not statistically significant in this study as a Bangladeshi study revealed that
a combination of the initial weight and height of the mother was not a good determinant
of neonatal birth weight 27]. The same study showed that maternal weight was the best determinant of neonatal
birth weight whereas in this current study, gestation at birth proved to be the best
determinant of neonatal birth weight. However, other studies have also shown that
not only are BMI, weight and height predictors of birth weight of neonates but that
the most important predictor of birth weight is weight at first visit, followed by
BMI and then Height, in descending order 29]. On the other hand, this study found that Gestation-at-birth was the most important
determinant of birth weight of neonates, followed by Diastolic Blood Pressure and
mother’s weight-at-birth for the study area.

Mothers’ hemoglobin levels had no association with birth weights of their neonates
in this current study. Other studies have however shown the contrary 30]–32].