Seasonal Changes in Birth Weight in a Semi Urban Community in the Gambia: A 4 Year Retrospective Study and Lessons for the Future

Research Article

Austin J Public Health Epidemiol. 2015;2(1): 1016.

Seasonal Changes in Birth Weight in a Semi Urban Community in the Gambia: A 4 Year Retrospective Study and Lessons for the Future

Owolabi OA¹*, Marong L², Muhammad AK¹, Townend J¹, Idoko OT¹ and Ota MOC1,3

1Vaccinology Theme, Medical Research Council Unit, Gambia

2Fajikunda Health centre, Gambia

3WHO Regional Office for Africa, Brazzaville, Congo

*Corresponding author: Owolabi OA, Vaccinology Theme, Medical Research Council Unit, PO Box 273,Banjul, Gambia

Received: January 14, 2015; Accepted: April 10, 2015; Published: April 13, 2015


Objective: Birth weights are determined by several factors, including seasonal changes in host behavior, environmental and maternal factors. Human birth seasonality can impact on the pattern of diseases and demand on the health system. The objective of this retrospective study was to review the pattern of birth weight of babies born in a community health centre over a period of four years.

Materials and Methods: A four year retrospective study of live singleton births at Fajikunda Health centre from 2007 to 2010. Data that included birth weight, gender, age and parity of mother were obtained from the records of the health centre. Statistical analyses were done using random effects model.

Results: There were 8521 live singletons births over the four years, 4402 (51.7%) males and 4119 (48.3%) females. The proportion of low birth weight (<2500 g) in the population was less than 5% of the total singleton births per year. Strong evidence of monthly variation in birth weight was found after adjusting for year, parity, gender, mother`s age and date of birth (month/ year) specific error terms (p<0.0001). Birth weight was higher from May to September and reached peak in May to July. The average birth weight declined progressively over the four years (p<0.001): from 2007 to 2008 (p=0.99), 2008 to 2009 (p=0.03) and from 2009 to 2010 (p=0.06). Birth weight increased by 127.3 (95% CI: 107.2; 147.6) g per unit increase in parity up to the 5th and the decreased (p<0.0001). Average birth weight of female babies was 114.1 (93.3; 135.0) g lower than the males (p<0.0001). Mother’s age was not associated with birth weight.

Conclusion: We have observed a progressive decline of birth weight with a striking seasonal variation in The Gambia. Further understanding of the reasons behind these changes is required to guide programmes and interventions.

Keywords: Mean birth weight; Maternal age; Parity; Macrosomia; Fajikunda


Human populations in different settings show patterns of seasonal variation in reproduction that is reflected typically in the variation of birth rates [1]. The key features of birth seasonality are in the rate of birth, the phase or season of birth, and the birth weight. The season of birth can impact on the subsequent pattern of diseases during the life time [2,3]. The influence of season on pregnancy outcome is likely through a number of factors including human activities/behavior, nutritional pattern, and disease prevalence. The dry season, a period of decreased maternal labor and abundant food stored from previous harvest season, is characterized by favorable pregnancy outcomes as evidenced by birth weights well above 3000 g and maternal weight gains (>0.5 kg/week) comparable to industrialized countries [4-8].

The weight of a baby at birth is an important outcome of pregnancy and a very important factor that subsequently determines infant and childhood morbidity and mortality [9-11]. Increased episodes of diarrhea, pneumonia within the first five years of life and early onset stunting have been associated with birth weight less than 2500g [12-14]. Babies born with weight =4000g are associated with birth injuries, hypoglycemia resulting in neurological insults [15-17] .

In high income countries, the mean birth weight and proportion of macrosomia (= 4000g) have been on the increase. These constituted about 6- 10% of all deliveries, with a yearly increase in birth weight ranging from 1- 5g as reported in National data from Norway, Sweden, Denmark, USA and Canada [18-30]. The observed increase in birth weight and macrosomia have been associated with high Body Mass Index (BMI), pregnancy weight gain, inter- pregnancy weight changes, increasing maternal age and parity, and reduced maternal smoking [18,19,26,31-34].

Studies conducted in the developing countries showed lower pregnancy weight gains and lower birth weights in babies born to mothers whose third trimester occurred in hungry (nutritionally adverse) season [13,35] .

The birth weight in the rural areas of The Gambia has previously been determined [7], but an equivalent in the urban area has not until now. The birth weight of an individual is one of the known risk factors predicting the occurrence of communicable and non-communicable diseases in childhood and beyond [36-41]. A study of the birth weight of newborn in our environment is critical to our health care planning in preparedness for the evolution of diseases thought to be alien in our context in adulthood and beyond. This will equally afford the opportunity to determine the mean birth weight in the urban area as a comparator to what is already known in the rural setting in The Gambia. The knowledge from this study will contribute to determining the mean birth weight from different parts of the world, particularly the developing world, prompting investigations into potential causes for changes and seasonal variability in The Gambia. Therefore, a more detailed understanding of the pattern of birth rate and birth weight is needed to guide maternal and child health programmes and practices, as well as predict the associated consequences in the future.

Materials and Methods

This was a retrospective study at the Fajikunda Health Center (Western Region, The Gambia) for the years 2007 to 2010. This health centre is one of the six major health centers in the country, and provides primary health care for a catchment area that comprises of 10 settlements located around the health centre with a population of about 200,000 (2003 national census). The health center runs regular under-5 welfare clinics, antenatal clinics with Voluntary Counseling and Testing (VCT) for HIV and treats acute illnesses for both adults and children. It has 16 beds for admission of acute pediatric and adult cases, a delivery ward of 5 beds and a standby 24- hour ambulance services for transportation of severe or complicated cases to the only tertiary health facility that is about 20 km south of the health center. During the period of the study the health center was being run by an average of 19 registered nurses/ midwives and 12 nurse attendants. The most experienced nurse was in charge as no doctor was assigned.

Participants` data were obtained from the birth registers and independently entered into an open access spreadsheet by two trained nurse/ field workers and verified. Data on singleton live births were used for the purpose of analysis in this study. Twins and infants (singleton) with missing data on birth weight, gender, maternal age and parity were excluded. All weights were measured using TANITA BD-585 digital baby scale with maximum capacity of 20kg and readability of 10g, manufactured by TANITA Corporation Tokyo, Japan. The scale was regularly calibrated by the nurse/ midwives twice daily for the purpose of consistency of measurements, using a standard weight. The birth weight was reported in kilograms but for the purpose of analysis this was reverted to grams. Information on gestational age in completed weeks as determined by the first day of the last menstrual period or ultrasound in early pregnancy was generally unavailable because of the high illiteracy rate of the mothers and lack of required equipment at the facility. Maturity scoring of the newborns was also not routinely done at the facility. Maternal age was documented in years and the birth order (parity) was calculated from the number of previous live births of the mothers.

Statistical Methods

Statistical analyses were carried out using STATA 12.1. A descriptive analysis was performed with the use of chi-square test or Kruskal- Wallis test where applicable. We fitted a random effects model with date of birth (month/ year) as cluster to assess the seasonal variations in birth weight. Babies born in the same month of the same year belonged to the same cluster. Each month/ year of birth had its own error component, which remained constant across births within that date. Month and year were categorical, parity was continuous, quadratic term of parity, gender and age as continuous were used as explanatory variables. Mothers with parity higher or equal to 6 were pooled together because very few mothers (less than 1%) had parity higher than 6. Parity in the following: 0, 1, 2, 3, 4, 5, and 6 or above was used as continuous variable in the model but the ungrouped parity (0 to 12) was used for descriptive purpose. Restricted Maximum Likelihood (REML) estimation method was used to fit the random effects model. We used contrast with Bonferroni`s correction to assess the yearly variation in birth weight.


Birth counts and maternal characteristics

A total of 8995 births were observed during the study period, with the following data missing; parity 19 (0.2%), maternal age 53 (0.6%), newborn gender 63 (0.7%), birth weight 39 (0.4%). The number of still births and multiple births over the four year of study were 151 (1.7%) and 146 (1.6%) respectively. As shown in Table 1, the total singleton live births over the 4 year period studied was 8521 (94.8%), and the yearly proportion of singleton live births ranged from 93.7% to 96.0%.