Socioeconomic risk factors for low birth weight newborns: A population-based study

Abstract

Low birth weight (LBW) is an important indicator of maternal health and poverty. This study explored the socioeconomic factors associated with LBW.

METHODS:

Data was collected from a 4-year maternal-newborn registry.

RESULTS:

There were 5,316 LBW and 54,029 normal birth weight (NBW). The prevalence of LBW was 9%. The Native women in the LBW group compared to non-native women were 10.4% (1784/5316) vs. 8.4% (3532/5316) with a P-value of 0.001. There were more illiterate mothers in the LBW compared to the NBW, respectively: 8.1% (1597/19497) vs. 7.5% (1763/23230) with a P-value of 0.001. Working mothers tend to have more LBW infants compared to mothers with NBW, 8.4% (1588/17217) vs. 7.9% (2532/31891) and P-value 0.001. Young mothers (<20 years old) with early childbearing had more LBW compared to older mothers, respectively 12.7% (180/1414) vs. 8.9% (5149/52919) P-value <0.001. Women with no antenatal care reported a high rate of LBW compared to women with regular antenatal care: 14.2% (516/3696) vs. 8.6% (4741/55691) P-value <0.001. LBW babies were born more from assisted conception pregnancies (38% compared to 8.4% of normal pregnancies) P-value <0.001. Smoking mothers scored higher with LBW at 13.6% vs. 8.3% and a P-value of 0.001. There were no differences between the two groups regarding religion, consanguinity, marital status, or family income.

CONCLUSION:

Risk factors for low birth weight can be improved by providing antenatal care, smoking cessation, optimizing high-risk pregnancy care, and governing assisted reproduction regulations.

Keywords

Low birth weight maternal newborn outcome socioeconomic

1 Introduction

Low birth weight has a substantial impact on both the success of prenatal care and the prevalence of childhood illness and death. There is a significant correlation between low birth weight and household economic position. Babies born to low-income, uneducated moms have low birth weights [1, 2]. Low birth weights were linked to parents with lower levels of education. Local environmental influences and the father’s degree of education, on the other hand, appear to have a stronger impact on the development of the child while still in the womb. Low birth weight has been associated to socioeconomic status, but the data is still conflicting [3]. Births to moms who smoke, eat poorly, drink excessively, or are underweight have been consistently linked to low birth weight infants [4]. Although preterm delivery is frequently related with LBW, it remains a serious public health concern in developed nations [4–7]. It has recently been discovered that genetic effects may not play a significant role [8–11]. In comparison to individual socioeconomic indicators, it has been revealed that health outcome measurements in England and Wales greatly understate the strength of the correlations between socioeconomic position and health outcomes [12]. Socioeconomic status variables such as maternal and paternal education, maternal and paternal work, and family income may have an impact on reproductive outcomes (low birth weight, small for gestational age, preterm delivery). Birth weight is also linked to mortality, mental retardation, and motor disability later in life. Low birth weight (LBW) refers to babies whose birth weight is less than 2500 grams [14, 15]. Many risk factors for LBW have been identified, including parental ethnicity, genetic and chromosomal disorders, and preterm birth. The most prevalent causes of LBW are preterm birth (before 37 weeks) and intrauterine growth limitations (birth weight less than the 10th centile) [9, 16]. The state of Qatar has lower rates of maternal, perinatal, and neonatal death and morbidity when compared to other developed countries [17, 18]. The bulk of non-Qataris residing in Qatar are from the Middle East, South Asia, and Southeast Asia; native-born Qataris account for only 35% of the population [19]. The variety of nations represented here substantially enhances the opportunity to investigate racial and ethnic influences on any disease. The goal of this study is to examine the economic and social conditions of a newly formed, highly industrialized, rich and cosmopolitan country.

2 Methods

A retrospective data analysis of 59,308 births is presented. The data was compiled by the PEARL-Peristat newborn and mother registry in 2011, 2012, 2017, and 2018. Peristat registry was funded by the Qatar National Research Fund (QNRF). This study compares LBW (less than 2500 grams at birth) and NBW (more than 2500 grams at birth) neonates against several socioeconomic characteristics. Each variable was divided into the best socioeconomic environment (the control group) and the less optimum socioeconomic environment. (the risk group). Maternal nationality (national vs. resident), religion (Muslim vs. non-Muslim), level of education (high vs. non-existent or limited), the mother’s occupation (housewife vs. working), family income (high vs. low), housing (separate vs. shared), consanguinity (no vs. yes), early childbearing (older than 20 years old vs. younger than 20 years old (yes vs no). Follow up and delivery in Level 3 referral facilities vs. Level 1 and 2 hospitals

Table 1
Socio-economic factors

Socio-economic factors Low Birth weight
(5316) Normal weight
(54029) OR CI 95%
P-value

Number % Number %

Nationality 1.3

Qatari 1784 10.4 15335 91.6 1.21–1.35

Non-Qatari^* 3532 8.4 38694 89.6 p < 0.001

Marital status 1.06

Married 4229 8.8 43758 91.2 0.9–1.33

Single^* 182 9.2 1796 90.8 0.8

Divorced/separated/other^* 12 10.9 98 89.1

Father’s education 1.09

Illiterate^* 53 8.0 607 92.0 1.018–1.17

Elementary^* 184 7.8 2173 92.2 p < 0.001^*

Secondary/high school^* 1272 8.5 13642 91.5

University or above 1772 7.2 22713 92.8

Mother’s education 1.09

Illiterate^* 109 5.8 1763 94.2 1.02–1.17

Elementary^* 202 8.6 2153 91.4 p < 0.014^*

Secondary/high school^* 1286 8.4 13984 91.6

University or above 1754 7.6 21476 92.4

Father’s occupation 0.93

Full-time worker 3178 7.7 37859 92.3 0.69–1.17

Part-time worker 13 6.0 205 94.0 0.53

Unemployed^* 80 8.3 887 91.7

Mother’s occupation 1.16

Full-time worker^* 1572 9.1 15645 90.9 1.087–1.2

Part-time worker^* 16 7.7 191 92.3 p < 0.001^*

Housewife 2532 7.9 29359 92.1 df = 2

Father’s income 1.01

Less than 3 thousand^USD 1274 7.6 15405 92.4 0.93–1.089

3–6 thousand USD 975 7.4 12154 92.6 p = 0.772

>6 thousand USD 559 7.6 6779 92.4 df = 2

Mother’s income 1.14

Less than 3 thousand^USD 597 8.3 6602 91.7 0.92–1.17

3–6 thousand USD 350 7.8 4135 92.2 p = 0.526

>6 thousand USD 162 8.5 1736 91.5 df = 2

Housing 1.14

Owned 1205 8.4 13109 91.6 1.06–1.23

Rented house^* 2048 7.4 25466 92.6 p < 0.004

Type of house 1.9

Common accommodation^* 757 8.6 8078 91.4 1.73–2.073

Separate accommodation 2520 7.4 31000 92.5 p < 0.0001

Cultural norms / fertility behaviors

Consanguinity 1.02

None 2234 7.7 26709 92.3 0.95–1.10

Yes^* 1046 7.9 12234 92.1 p = 0.574

Early childbearing 1.5

Mother <20 yrs.^* 180 12.7 1234 87.3 1.3–1.8

Mother 20+ yrs. 5149 8.9 52919 91.1 p < 0.0001

High risk pregnancy^* 1.9

Yes^* 1130 10.2 9998 89.8 1.11–1.27

No 4199 8.7 44155 91.3 p < 0.0001^*

Gravidity 0.8

0–3 3730 9.6 35217 90.4 0.75–0.85

High gravidity [>3]^* 1595 7.8 18913 92.2 p < 0.0001^*

Socio-economic factors	Low Birth weight (5316)	Normal weight (54029)	OR CI 95% P-value
Nationality					1.3
Qatari	1784	10.4	15335	91.6	1.21–1.35
Non-Qatari^*	3532	8.4	38694	89.6	p < 0.001
Marital status					1.06
Married	4229	8.8	43758	91.2	0.9–1.33
Single^*	182	9.2	1796	90.8	0.8
Divorced/separated/other^*	12	10.9	98	89.1
Father’s education					1.09
Illiterate^*	53	8.0	607	92.0	1.018–1.17
Elementary^*	184	7.8	2173	92.2	p < 0.001^*
Secondary/high school^*	1272	8.5	13642	91.5
University or above	1772	7.2	22713	92.8
Mother’s education					1.09
Illiterate^*	109	5.8	1763	94.2	1.02–1.17
Elementary^*	202	8.6	2153	91.4	p < 0.014^*
Secondary/high school^*	1286	8.4	13984	91.6
University or above	1754	7.6	21476	92.4
Father’s occupation					0.93
Full-time worker	3178	7.7	37859	92.3	0.69–1.17
Part-time worker	13	6.0	205	94.0	0.53
Unemployed^*	80	8.3	887	91.7
Mother’s occupation					1.16
Full-time worker^*	1572	9.1	15645	90.9	1.087–1.2
Part-time worker^*	16	7.7	191	92.3	p < 0.001^*
Housewife	2532	7.9	29359	92.1	df = 2
Father’s income					1.01
Less than 3 thousand^*USD	1274	7.6	15405	92.4	0.93–1.089
3–6 thousand USD	975	7.4	12154	92.6	p = 0.772
>6 thousand USD	559	7.6	6779	92.4	df = 2
Mother’s income					1.14
Less than 3 thousand^*USD	597	8.3	6602	91.7	0.92–1.17
3–6 thousand USD	350	7.8	4135	92.2	p = 0.526
>6 thousand USD	162	8.5	1736	91.5	df = 2
Housing					1.14
Owned	1205	8.4	13109	91.6	1.06–1.23
Rented house^*	2048	7.4	25466	92.6	p < 0.004
Type of house					1.9
Common accommodation^*	757	8.6	8078	91.4	1.73–2.073
Separate accommodation	2520	7.4	31000	92.5	p < 0.0001
Cultural norms / fertility behaviors
Consanguinity					1.02
None	2234	7.7	26709	92.3	0.95–1.10
Yes^*	1046	7.9	12234	92.1	p = 0.574
Early childbearing					1.5
Mother <20 yrs.^*	180	12.7	1234	87.3	1.3–1.8
Mother 20+ yrs.	5149	8.9	52919	91.1	p < 0.0001
High risk pregnancy^*					1.9
Yes^*	1130	10.2	9998	89.8	1.11–1.27
No	4199	8.7	44155	91.3	p < 0.0001^*
Gravidity					0.8
0–3	3730	9.6	35217	90.4	0.75–0.85
High gravidity [>3]^*	1595	7.8	18913	92.2	p < 0.0001^*

^*High risk subject group OR: Odds ratio CI: Confidence interval.

Table 2

Low Birth weight: Quantitative determinants: Independent t-test to compare means among maternal/neonatal outcome categories. Independent t-test to compare means among birth weight categories

Birth weight	N	Mean	Std. Deviation	P-value
male-female education	Normal weight	38504	.1346	1.15920	0.042^*
[educational difference]	LBW [<2500]	3240	.0914	1.18743
male-female income	Normal weight	12966	.2905	1.11646	0.028^*
[income difference]	LBW [<2500]	1156	.3694	1.17303
Crowding index	Normal weight	37830	1.8432	1.10866	p < 0.001^*
	LBW [<2500]	3160	1.7610	1.07054
Number of rooms	Normal weight	37947	3.57	2.173	p = 0.020^*
	LBW [<2500]	3172	3.67	2.055
Number of family members	Normal weight	39242	6.20	5.135	p = 0.513
	LBW [<2500]	3287	6.14	5.223
Number of children at home	Normal weight	37925	2.61	2.708	p < 0.001^*
	LBW [<2500]	3097	2.37	2.676
Parity	Normal weight	54119	1.77	1.746	p < 0.001^*
	LBW [<2500]	5324	1.40	1.696
Duration of stay days [mother]	Normal weight	54091	2.22	6.753	p < 0.001^*
	LBW [<2500]	5324	3.03	5.403
Duration of stay days [child]	Normal weight	49279	2.14	8.423	p < 0.001^*
	LBW [<2500]	4670	12.06	22.740

LBW: low birth weight.

2.1 Statistics

According to Altman (1991), the odds ratio (OR), its standard error, and 95% confidence interval are calculated, with the standard error of the log odds ratio constituting the 95% confidence interval.

2.2 Significance test

The P-value is computed based on Sheskin, 2004 (p. 542). The standard normal deviation (z-value) is determined as ln (), and the P-value is the area of the normal distribution outside of z (n (OR)). The P-value is the proportion of the normal distribution that falls outside of z [20]. The ratio of LBW to LBW plus NBW stated as 100%, was used to determine the rate percentile.

3 Results

There were 5,316 LBW and 54,029 NBW. The prevalence of LBW was 9%. The Native women in the LBW group compared to non-native women were 10.4% (1784/5316) vs. 8.4% (3532/5316) with a P-value of 0.001. There were more illiterate mothers in the LBW compared to the NBW, respectively: 8.1% (1597/19497) vs. 7.5% (1763/23230) with a P-value of 0.001. Working mothers tend to have more LBW infants compared to mothers with NBW: 8.4% (1588/17217) vs. 7.9% (2532/31891) and P-value <0.001. Young mothers (<20 years old) with early childbearing had more LBW compared to older mothers, respectively 12.7% (180/1414) vs. 8.9% (5149/52919) P-value <0.001. Women with no antenatal care reported a high rate of LBW compared to women with regular antenatal care: 14.2% (516/3696) vs. 8.6% (4741/55691) P-value <0.001. LBW babies were born more often from assisted conception pregnancies (38% compared to normal pregnancies, 8.4%) P-value 0.001. There were more high-risk pregnancies in the LBW (21% vs. 18%) P-value <0.001. Smoking mothers scored higher with LBW at 13.6% vs. 8.3% and a P-value of 0.001. More women with LBW are delivered in our tertiary women’s hospital compared to secondary hospitals, respectively: 9.4% (4721/5420) vs. 6.7% (45699/8389) P-value <0.001. There were no differences between the two groups regarding religion (P-value 0.45 and one Odds ratio), consanguinity, marital status, or family income.

4 Discussion

Low birth weight has a substantial impact on both the efficacy of prenatal care and the incidence of childhood illness and death. There is substantial evidence associating low birth weight with the economic position of the parents. Babies born to low-income and low-education moms have low birth weights [1, 2]. Low levels of parental education related to the lowest birth weights. On the other hand, it seems that the local environment and the father’s level of education have a bigger effect on how the fetus grows and develops. Low birth weight has been associated with socioeconomic status, but the evidence is still inconclusive [3]. The association between low birth weight and births to moms who smoke, have poor diets, drink excessively, or are underweight has been established [4]. Even though LBW is often linked to preterm birth, it is still a major public health issue in developed countries [4–7]. Recent research indicates that genetic effects may not play a significant role [8–11]. When compared to individual socioeconomic measures, the correlations between socioeconomic position and health outcomes in England and Wales are much weaker when measured by health outcomes [12]. Variables related to a family’s socioeconomic status, such as the mother’s and father’s education, the mother’s and father’s jobs, and the family’s income, can influence the child’s development (low birth weight, small for gestational age, preterm delivery). Additionally, birth weight is correlated with mortality, mental retardation, and motor disability in adulthood. Babies weighing less than 2500 grams at birth are considered to have low birth weight or LBW [14, 15]. Risk factors for LBW include the ethnicity of the parents, genetic and chromosomal abnormalities, and being born early. The most prevalent causes of LBW are preterm birth [before 37 weeks) and intrauterine growth limitations (birth weight less than the 10th centile) [9, 16]. Qatar has lower rates of maternal, perinatal, and neonatal death and morbidity compared to other wealthy nations [17, 18]. The majority of Qatar’s non-Qatari population is comprised of people from the Middle East, South Asia, and Southeast Asia; Qataris are just 35 percent of the population [19]. The fact that people from many different cultures are here makes it much easier to study how race and culture affect any disease. The goal of this study is to figure out how the economy and society of a brand-new, highly industrialized, and cosmopolitan country are doing.

Footnotes

Acknowledgments

The Authors would like to thank Qatar national research fund for funding the PEARL-Peristat maternal and newborn registry and Medical research center of Hamad Medical Corporation.

Disclosure statements

There are no conflicts of interest among the authors. There are no financial or commercial rewards associated with the submitted scientific manuscript.

The Pearl-Peristat Maternal and Newborn Registry 2016–2019 was funded by the Qatar National Research Fund (QNRF) in order to support the study of the authors (2, 4, and 5). Medical research center study number 13064/13, QNRF number: NPRP 6-238-3-059.The date of the most recent IRB approval was October 7, 2018. In compliance with its research regulations, the Medical research center of Hamad Medical Corporation has evaluated and accepted the terms of this agreement.

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