Low birth weight is associated with non-negligible perinatal morbidity risks and long-term high cardiovascular morbidity risk [1-3]. Thus, in recent years, some studies have shown that low birth weight is a predictive factor of delayed cognitive development, chronic disease development in adulthood [3]. There is a higher risk of cesarean delivery for low and high weight newborns compared to gestational age [1]. The Institute of Medicine revised its guidelines for gestational weight gain standards in 2009 [4]. Women with gestational weight gain (GWG) below the norm are at greater risk of giving birth to low weight newborns. In contrast, women with high GWG are at greater risk of giving birth to macrosomic or high weight newborn relative to gestational age [5]. Few studies in the literature are interested in neonatal health in relation to the nutritional status of the pregnant in Africa South of the Sahara. The objectives of this work were to evaluate the nutritional status of pregnant women and their newborns, and to determine the factors associated with the weight of newborns in the maternity wards of the city of Parakou in 2017.

We carried out a descriptive and analytical prospective study in the 7 public maternity hospitals and in the maternity ward of the departmental teaching hospital (CHUD) of the city of Parakou in northern Benin from 1^st July to 30^th September, 2016.

The study population consisted of pregnant women living in the city of Parakou, followed up during antenatal consultations (ANC) in the public maternity wards of this city and their newborns.

We included in this work pregnant women in the second or the third trimester of pregnancy who had come to ANC during the study period, who resided in Parakou during the survey period, who had a health card including their height and at least their weight in the first trimester of pregnancy and who had given birth in public maternity hospitals in this city during the study period.

We excluded the pregnant women who had refused to participate in the survey or whose weight in the first trimester of pregnancy had not been marked in their health card or who had been lost to follow-up during the survey.

We conducted a random convenience sampling of pregnant women who come to ANC in one of the public maternity wards in the city of Parakou.

The dependent variables were:

• The GWG determined by the difference between the weight of the pregnant woman at delivery and that recorded in the first trimester or before pregnancy. Recommended GWG intervals (kg) for the entire pregnancy based on Body Mass Index (BMI) were: 12.5-18 if BMI5].

• In newborns, birth weights were classified using the intrauterine growth curves of Alihonou [6] which is a Beninese local reference curve for classifying newborns as hypotrophic (GA weight curve below the 10^th percentile), normotrophic (GA weight curve between the 10^th and the 90^th percentile), and hypertrophic (GA weight curve above the 90^th percentile) as defined by Clausson et al. [4].

The independent variables were: gestational age (GA), maternal Body Mass Index (BMI), physical activity level (PAL), social and economic well-being level (SEWL), obstetric characteristics (parity).

The GA was determined on the basis of the date of the last menstrual period when it was known or on the basis of the first trimester ultrasound. But when the GA was obtained by both methods, we used the age of the ultrasound for analysis. The mother's nutritional status was assessed in the first trimester of pregnancy by her Body Mass Index (BMI=Weight/height in square metres in kg/m²). A BMI 7].

Physical activity levels were classified into six categories according to Ambroise M. classification: Table 1 [8].

Table 1: Classification of physical activity level.

Data were collected through individual interviews and health cards exploitation, using a survey sheet.

Treatment and analysis of the data

Double data entry was done using Epi Data 3.1 software. Univariate and multivariate analytical descriptive statistics were generated by the SPSS 21 software. The quantitative variables were expressed on average with standard deviation and the qualitative variables in percentage. In the univariate analysis, the Chi-square test the exact one of Fischer was used for the comparison of percentages. The strength and intensity of the association were estimated by the odd-ratio with a 95% confidence interval.

Ethical considerations

The consent of Borgou/Alibori Health Departmental Direction and the management team of the various maternity hospitals were obtained. All participants received detailed information about the study and gave their consent.

Characteristics of pregnant women

A total of 205 pregnant women were included in the study. The pregnant women were aged 16 to 43 years with a mean age of 26.6 ± 5.4 years. Those aged 25-29 accounted for 30.7% of the sample. Over two thirds of the study populations were married women (88%). Half of the pregnant women (50.7%) had no education and 6.3% had a university degree. Seventy-five pregnant women (36.6%) had a high socio-economic well-being level.

The prevalence of obese, overweight, or lean pregnant women were respectively 9.8% (20/205), 21.5% (45/205), and 9.3% (19/205) (Table 2).

Table 2: Distribution of pregnant women according to their age, socio-economic level, Gestational Weight Gain based on their nutritional status (N=205).

The proportions of pregnant women with normal or high GWG were respectively 48.8% (100/205) and 41.9% (86/205). GWG was significantly related to the nutritional status of pregnant women before pregnancy (p=0.000). Indeed a proportional increase of the GWG with the BMI of the pregnant women had been noted (Table 2).

Nutritional status of pregnant women

BMI was significantly associated with the pregnant women age (p=0.000), Socio-Economic Well-being Level (p=0.000), parity (p=0.009), GPG (p=0.000) (Table 2).

There were more cesarean in obese or overweight pregnant women than in normal weight pregnant women: 25%; 24.4% versus 7.4% (p=0.003) (Table 3).

Table 3: Distribution of pregnant women according to mode of delivery and nutritional characteristics.

State of newborns

The proportions of hypotrophic, normotrophic and hypertrophic newborns were respectively 7.8% (16/205), 27.8% (57/205) and 64.4% (132/205).

Newborn hypotrophy was associated with low levels of socioeconomic well-being (p=0.000), low BMI of pregnant women (p=0.000), GWG (p=0.000), Physical Activity Level (p=0.000) and GA (p=0.000) (Table 4).

Table 4: Distribution of hypotrophic or normotrophic newborns according to the main sociodemographic characteristics of mothers.

Newborn hypertrophy was proportionally associated with obesity (p=0.003), high GWG (p=0.000), and low physical activity of pregnant women (p=0.000) (Table 5).

Table 5: Distribution of hypertrophic and normotrophic newborns based on socio-demographic, nutritional and anthropometric characteristics of mothers.

Perinatal mortality was significantly associated with low BMI (15.8%, p=0.038), and low GPG (26.3%, p=0.000) (Table 6).

Table 6: Distribution of Perinatal mortality based on nutritional characteristics of mothers.

The prevalence of overweight, obesity and thinness in pregnant women was respectively 21.5%, 9.8% and 9.3%. A previous study reported higher prevalence of overweight and obesity in the capital city of our country respectively 30.6%, 18% [9]. The prevalence of obesity in pregnant women is higher in developed countries where obesity is a public health problem: in France 9.9% [10], Canada 16% [11], United Kingdom [12]. The very different eating habits and lifestyles in these countries may explain this difference.

The proportions of pregnant women who had high or low GWG were respectively 41.9% and 9.3%. These proportions of high and low GWG were lower than those observed by Crane and al [13] in Canada, respectively 52.3% and 17.1%. A study in Taiwan found lower proportions of high GWG and higher proportions of low GWG respectively 27.3% and 27.7% [14]. In our series, insufficient GPG was associated with perinatal mortality. Like Goldstein [15] we found that when GWG is not within recommended limits, it is associated with others perinatals complications (neonatal hypotrophy, neonatal hypertrophy).

In our series, obese or overweight pregnant women were at greater risk of delivering by cesarean section. Several studies had shown that obese and overweight pregnant women were more at risk of delivering by cesarean section [9,16]. Dempsey [16] in the United States had shown that a BMI greater than 30 multiplied by three to six the risk of cesarean section. They explained this by a higher risk of preeclampsia, fetal macrosomia and dynamic dystocia leading to cesarean section.

Our results showed that birth weight increased significantly with BMI (p=0.003): Obese or overweight pregnant women had a higher risk of giving birth to hypertrophic newborns. Several studies had also shown that overweight women were more likely to deliver newborns whose weight is over their gestational age weight [7,17,18]. We found in our series that lean pregnant women were more likely to give birth to hypotrophic newborns. Several studies have reported that the frequency of hypotrophic newborns was very low in obese women compared to normal weight women [7,19].

In our series, birth weight was significantly related to GWG (p=0.000). It increased when the GWG became important. Thus, pregnant women with high GWG were more likely to give birth to newborns of high weight. In contrast, pregnant w

omen who had not reached the recommended GWG were more likely to give birth to hypotrophic newborns. Several authors had agreed with the results reported in our work [13,17]. Viswanathan et al. [17] also found that women who do not achieve the recommended GWG during pregnancy are at risk of giving birth to a premature, gestational-age or low weight newborn.