Low birth weight (LBW) defined by WHO as weight at birth of less than 2.5 kg. LBW accounts for nearly half of all perinatal and one-third of all infant deaths. Around 20 million LBW babies are born each year, with 95.6% of them in developing countries. Antenatal care can significantly mitigate the incidence of low birth weight (LBW) in low and middle income countries, according to studies. The purpose of this paper is to assess the effect of antenatal care on LBW using the most recent DHS data since 2012 for each country.
This study was based on the most recent Demographic and Health Survey (DHS) data of 52 low and middle income countries. A total of 228,907 women aged 13-49 years were included in the study. Logistic regression model was applied. P < 0.05 was considered statistically significant for all tests performed in the study. In the multivariable, the Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) was reported for potential determinant factors of LBW.
The overall prevalence of low birth weight in low and middle income countries is 11.3% [95% CI: 11.2%, 11.4%]. Most of the women (47.8%) who had given birth five years preceding the survey were young, aged 25-34 years. Sex of child, maternal education, birth order, preceding birth interval, residence, type of birth, wealth status, four and above ANC were found to be significant determinant of low birth weight.
low birth weight is still a major public health problem in low and middle income countries. Enhancing maternal education and quality ANC service is recommended to reduce LBW. In addition it is better to strength economy of family with special attention multiple birth.
Antenatal care, Low birth weight, Low and middle income countries
ANC: Antenatal Care; AOR: Adjusted Odd Ratio; CI: Confidence Interval; LBW: Low Birth Weight; WHO: World Health Organization
World health organization defines low birth weight (LBW) as birth weight of less than 2.5 kg [1]. A birth weight of less than 2500 grams has been agreed upon as the international standard for low birth weight (LBW). Preferably, the measurement is made within the first hour of life, before significant postnatal weight loss has taken place [2]. Infants born at LBW have serious health and developmental problems, which can have a significant financial impact on society [3]. Low birth weight is linked to an increased risk of disease and death, compromised immune system, and delayed cognitive development [4].
One-third of infant mortality and nearly half of all perinatal deaths are caused by LBW [5]. Low birth weight babies have a 40 times higher mortality rate within the first four weeks of life than babies with normal birth weights. Babies with LBW account for 1/3 of all infant fatalities and half of all perinatal deaths [2]. According to WHO estimates, each year, more than 20 million LBW babies are born throughout the world, accounting for 15.5% of all live births and roughly 95.6% of them in developing nations [6].
According to regional statistics, low- and middle-income countries (LMICs), which account for almost all occurrences of LBW, bear a disproportionately heavy burden of newborn death globally [5]. Burkina Faso, Ghana, Malawi, Senegal, and Uganda each have a prevalence of LBW of 13.4%, 10.2%, 12.1%, 15.7%, and 10%, respectively [7].
Numerous studies conducted in developing countries have shown that raising the standard of prenatal care (ANC) can dramatically lower the incidence of LBW. Accessibility to ANC, the number of ANC visits, and the content of ANC are all indicators of quality ANC [8-10].
The purpose of this paper is to assess the effect of antenatal care on low birth weight in low and middle income countries using the most recent DHS data since 2012 for each country.
Our study analyzed DHS data from 52 low- and middle-income nations. The DHS was created in the 1980s as a nationally representative household survey by the United States Agency for International Development (USAID) [11]. We analyzed all nations with surveys conducted since 2012. When more than one survey has been conducted since 2012, we choose the most recent one for each country.
Dependent variable: This study analyzed only the numerical birth weight data contained in the DHS survey for only the most recent children. Finally, birth weight data were classified into two groups: Normal birth weight (birth weight ≥ 2500 g-4000 g) or LBW (birth weight < 2500 g). Data from children with a missing birth weight and overweight children were excluded from the analysis.
Independent variables: Child birth weight is influenced by a number of circumstances, including the ANC. ANC is linked to socioeconomic factors as wealth index, employment status, and educational attainment. Birth weight is affected by ANC as well as other health factors including the location of the delivery. These characteristics are linked to the outcome of interest in a similar way to maternal factors as the age of mothers, maternal educational status and others. In addition to maternal factors connected to ANC and birth weight, socioeconomic factors are also linked to child parameters such as birth order and prior birth interval.
The study population characteristics for the chosen countries were expressed as percentages (%) with a 95% confidence interval (CIs) in the descriptive analysis. After taking into account potential confounders, a multivariate logistic regression model was used to estimate ORs as a measure of the relationships between LBW and related risk factors. The analysis made use of the diagnostic tests. The Hosmer and Lemeshow statistic was used to assess goodness of fit [12]. To find out if multi-collinearity existed, the variance inflation factor (VIF) test was used. Stata version 14 was used for all statistical analyses and p < 0.05 was considered statistically significant for all tests performed in the study.
A total of 228,907 women aged 13-49 years formed a sample in this study. Most of the women who had given birth five years preceding the survey were young, aged 25-34 years with 109,330 (47.8%), had secondary level of education 87,540 (38.2%), were working currently 118,510 (52.1%) and 154,122 (67.3%) were currently married. Of these women, almost 133738 (61.9%) perceived the distance to the health center as not a big problem and 128,078 (56.0%) women were from rural areas. The overall prevalence of low birth weight in low and middle income countries is 11.3% [95% CI: 11.2%, 11.4%] (Table 1 and Table 2).
Table 1: Descriptive characteristics of child birth weight among reproductive health women in low and middle income countries. View Table 1
Table 2: Factors associated with low birth weight in low and middle income countries. View Table 2
The odds of having low birth weight among poorer, middle, richer and richest household wealth were decreased by 11% [AOR = 0.89, 95% CI: 0.84, 0.94], 20% times [AOR 0.80, 95% CI: 0.75, 0.84), 15% [AOR 0.75, 95% CI: 0.71, 0.80], and 33% [AOR 0.67, 95% CI: 0.67, 0.071] compared to poorest household wealth, respectively. Second of multiple and third of multiple births had 8.25 times [AOR 8.25, 95% CI: 7.63, 8.92] and 33.81 times [AOR 33.81, 95% CI: 16.49, 69, 40] higher odds of having low birth weight compared to single births, respectively. Children who were 2nd, 3rd, 4th, 5th, and 6th and above birth order had 12% [AOR 0.88, 95% CI: 0.81, 0.96], 13% [AOR 0.87, 95% CI: 0.80, 0.95], 9%[AOR 0.91, 95% CI 0.84, 0.99], 12% [AOR 0.88, 95% CI: 0.80, 0.95], and 7% [AOR 0.93, 95% CI: 0.87, 0.99] lower odds of having low birth weight compared to first birth respectively.
Female children, later wanted and no more wanted pregnancy had 1.28 times [AOR 1.28; 95% CI: 1.24, 1.33], 1.08 times [AOR 1.08, 95%CI: 1.03, 1.14] and 1.21 times [AOR 1.21, 95% CI: 1.14, 1.29] higher odds of being low birth weight compared to male children and wanted pregnancy. The odds of low birth weight among autonomous women, optimal and long preceding birth interval decreased by 2% [AOR 0.98, 95% CI 0.93, 1.03], 17% [AOR 0.83, 95% CI: 0.79, 0.87] and 12% [AOR 0.88, 95% CI: 0.83, 0.94] compared to those women who don't have an autonomy and low preceding birth interval.
The odds of a higher level of low birth weight among children from the rural and family size of 6-10 and > 10 decreased by 16% [AOR 0.84, 95% CI 0.81, 0.88], 7% [AOR 0.93, 95% CI: 0.89, 0.96] and [AOR 0.84, 95% CI 0.84, 0.96] compared to children from urban and family size less than 6, respectively. Women who had primary, secondary and higher education had lower odds of having low birth weight than women who hadn't formal education, and those whose partners had primary, secondary and higher education.
We looked into the effect of ANC visits and other variables on infant birth weight using information from extensive, nationally representative demographic and health surveys from low- and middle-income countries.
Low birth weight is still a significant public health issue in low and middle income nations, as evidenced by our investigation the prevalence is 11.3% [95% CI: 11.2%, 11.4%]. Our finding was higher than systematic and meta-analysis results in Iran 8.5% [13], Nepal 9.4% [14], Nigeria 6.3% [15], China 5.1% [16]. Our finding was lower than a study done in Kenya 12.3% [17], Jordan 13.8 [18], a systemic and meta-analysis result done in Ethiopia 14.1% [19]. Additionally, the national, regional, and global systematic analysis found that the result of this study was lower than estimates for the world and sub-Saharan countries of 14.6% and 16.4% [20]. This may be related to measures taken to reduce maternal and newborn deaths in low-income countries [21].
Several factors contributed for the occurrence of low birth weight. Poorer, middle, richer and richest wealth status associated with a reduced probability of LBW compared to the poorest. This finding is supported by other studies [18,22]. This demonstrates that, as shown in other settings, poverty plays a significant role in determining birth weight [23,24]. Additionally, low-income households might not be able to afford proper prenatal care [25], compared to more affluent mothers, low-income mothers consume less food overall [26].
Numerous studies have found a U-shaped relationship between maternal age and LBW, with teenagers and older mothers having the highest risk [12,27]; however, this particular trend was not revealed by our data neither was associated with LBW.
Female sex of child was statistically significant factor for higher odds of LBW, this finding supported by other studies in Jordan and Ethiopia [18,28]. The relationship may result from male fetuses being expelled later than female fetuses, so that males are more likely to be macerated [29].
Furthermore, we found that multiple births, later wanted and no more wanted pregnancies had higher odds of LBW compared to single birth, male children and wanted pregnancy. Agreeing with previous studies, the odds of LBW decreased as the level maternal education increased [14,18]. Women with little to no education and/or understanding are more likely to engage in unhealthy behaviors (e.g., smoking, drug or substance uses, etc.). Furthermore, they might not have access to adequate healthcare resources (such as prenatal care or iron supplements), which could have an impact on fetal growth [30].
Poor maternal education, rural residence and large family size were significantly associated with increased odds of LBW. This is in line with previous studies [18,19]. This may be because the woman lives in an urban area rather than a rural one, where access to medical services, health knowledge, and dietary awareness are more prevalent [31].
The present study showed that the odds of LBW decreased among the mothers who had optimal and long preceding birth interval. It is consistent with studies done in India [32], Jordan [18]. The maternal nutritional depletion hypothesis, which claims that a close succession of pregnancies and the lactation period worsen the mother's nutritional status and that there is insufficient time for the mother to recover from the physiological stress and strain of the prior pregnancy before she is subjected to the stresses of the next, is one explanation for the connection between short birth interval and LBW [33].
Autonomous women and higher birth order associated with lower odd of LBW. This is supported by other studies [34,35]. This could be as a result of low levels of autonomy in health care decision-making, which can result in low consumption of prenatal food and micronutrient supplementation, which could lead to subpar prenatal care, subpar maternal health and nutritional status, and subpar fetal growth resulting to LBW [36].
This study found a strong association between having greater than or equal to four ANC visit and reduced the odds of LBW and the result is in agreement with previous studies [15] this is as a result of antenatal care providing routine height and weight monitoring, detection of medical issues with the mother or the fetus, advise against cigarette or drug use, psychosocial support, nutritional guidance, and early intervention that may reduce adverse pregnancy outcomes, such as LBW [37].
The limitation of this study is that not include some important predictors like maternal weight and anemia.
A major public health issue in low- and middle-income nations continues to be low birth weight. Low birth weight was found to be significantly affected by the child's sex, the mother's education, the child's birth order, the time between births, the residence, the type of birth, the wealth status, and ANC visits of four and above. This conclusion shows that strengthening women's autonomy and women's with multiple births should receive more attention. In order to reduce LBW, it is also crucial to improve family economic condition, access to education, and quality ANC service.
This study was conducted under the Declaration of Helsinki and since we were using publicly accessible data, ethical approval was not needed. However, by registering or online requesting, we accessed the data set from the DHS website (https:/dhsprogram.com) and no personal identifiers were found in the data set.
Not applicable.
Data is available online and you can access it from https://dhsprogram.com/data/dataset_admin/index.cfm
The authors declare that they have no competing interests.
No funding was available for this study.
We would like to acknowledge the measure DHS program which granted as permission to use DHS data.
RET developed the research protocol and tool, trained the data collector, supervise the data collection, managed and analyzed the data, interpreted the findings, and wrote the manuscript. FMA and AZA have been involved in research protocol and tool development, trained the data collector, supervises the data collection, managed and analyzed the data, interpreted the findings, and wrote the manuscript. TA and BAT have been involved in research protocol and tool development managed and analyzed the data, interpreted the findings, and wrote the manuscript. RET, FMA, AZA, TA and BAT have been involved in research protocol and tool development, supervise the data collection, and wrote the manuscript. Finally, all authors read and approved the revised manuscript.