What Type of Country Experiences the Highest Rate of Low-birth-weight Babies
J Prev Med Public Health. 2017 Jan; fifty(1): 18–28.
Distribution and Determinants of Depression Nascency Weight in Developing Countries
Rashidul Alam Mahumud
1Health Economics and Financing Research, Health Systems and Population Studies Segmentation, International Centre for Diarrhoeal Disease Research, People's republic of bangladesh (icddr,b), Dhaka, Bangladesh
Marufa Sultana
oneHealth Economics and Financing Research, Health Systems and Population Studies Partitioning, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
Abdur Razzaque Sarker
oneHealth Economics and Financing Research, Health Systems and Population Studies Partition, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, People's republic of bangladesh
2Section of Management Science, University of Strathclyde, Glasgow, United Kingdom
Received 2016 Sep 19; Accepted 2016 December xix.
Abstract
Objectives
Depression nascency weight (LBW) is a major public health business concern, especially in developing countries, and is frequently related to child morbidity and mortality. This written report aimed to place cardinal determinants that influence the prevalence of LBW in selected developing countries.
Methods
Secondary data assay was conducted using 10 recent Demography and Health Surveys from developing countries based on the availability of the required information for the years 2010 to 2013. Associations of demographic, socioeconomic, customs-based, and individual factors of the mother with LBW in infants were evaluated using multivariate logistic regression assay.
Results
The overall prevalence of LBW in the study countries was 15.nine% (range, 9.0 to 35.1%). The following factors were shown to take a meaning clan with the risk of having an LBW babe in developing countries: maternal historic period of 35 to 49 years (adjusted odds ratio [aOR], 1.7; 95% confidence interval [CI], 1.ii to 3.1; p<0.01), inadequate antenatal care (ANC) (aOR, 1.vii; 95% CI, 1.1 to 2.viii; p<0.01), illiteracy (aOR, ane.5; 95% CI, 1.1 to 2.7; p<0.001), delayed conception (aOR, 1.8; 95% CI, 1.four to two.5; p<0.001), low torso mass index (aOR, 1.6; 95% CI, one.2 to 2.1; p<0.001) and existence in the poorest socioeconomic stratum (aOR, 1.4; 95% CI, 1.1 to 1.8; p<0.001).
Conclusions
This study demonstrated that delayed conception, avant-garde maternal historic period, and inadequate ANC visits had independent effects on the prevalence of LBW. Strategies should be implemented based on these findings with the goal of developing policy options for improving the overall maternal health condition in developing countries.
Keywords: Developing countries, Global health, Low birth weight, Odds ratio
INTRODUCTION
Infant birth weight is a significant predictor of the immediate and future health status of a newborn. Low nativity weight (LBW) is a major public health concern and ane of the strongest single take chances factors for early neonatal mortality and morbidity [one,2]. According to the World Health Organization, the prevalence of LBW is 15.5% globally, and 96.v% of LBW infants are built-in in developing countries [3,4]. LBW has been defined as a nascency weight of less than 2500 g regardless of gestational age. Consequently, LBW is considered to be associated with a greater risk of early childhood death than is associated with normal birth weight [5]. Furthermore, information technology is a significant factor associated with higher probabilities of infection, greater susceptibility to childhood disease, lower chances of child survival, long-term physical and mental deficiencies, and problems related to beliefs, learning, and psychosocial improvements during childhood [two,half dozen]. In the perinatal menses, LBW infants are in a critical state with regard to survival, and approximately half of all neonatal deaths are directly or indirectly linked to LBW [7]. This adverse pregnancy outcome may be influenced by several weather, such every bit heart disease, diabetes, hypertension, behavioral disorders, dumb cognitive role, psychological disorders, and a substantial risk of complications related to the stoma includes the esophagus, breadbasket, duodenum, ileum, colon, pleural cavity, ureters, urinary bladder, and kidney pelvis etc. [8], and ordinarily incurs long-term fiscal burdens for households [nine,10]. Furthermore, with the demographic change of increased life expectancy at birth in developing countries, children born with LBW can cause an increased economic burden and an increased affliction burden [10,11]. Consequently, LBW is considered as a universal threat for developing countries that creates a barrier for child evolution [12,thirteen]. Previous studies have shown several factors to be determinants of LBW and have demonstrated that preventing those factors tin can help reduce early childhood morbidity and bloodshed [14]. The determinants of LBW can be broadly classified equally genetic, constitutional, obstetric, nutritional, related to maternal morbidities in the antenatal period, toxic exposure-related, and linked to antenatal care (ANC). Other factors including smoking, maternal historic period, nativity spacing, ANC, anemia, genital infections, maternal ill health, and stress have too been reported [15]. Inquiry on the prevalence and determinants of LBW has been conducted using nationwide population-based survey data, with some studies focusing on developing countries. All the same, almost of the multi-country studies were conducted using recalled birth weight data, with mothers reporting information about the size of their newborn infant (due east.g., very modest, small, normal, large, and very large) from memory, which may have affected the accuracy of the results regarding LBW [16]. This report used a continuous type of nascence weight data derived from Census and Health Surveys (DHSs) among x selected developing countries. However, global development has entered a new era, as world leaders have evaluated the achievements of the Millennium Development Goals and adopted the 2030 Agenda for Sustainable Development in the proper noun of Sustainable Evolution Goals (SDGs). The specific SDGs known equally the wellness goal (goal No. 3) aims to "ensure healthy lives and promote well-being for all at all ages," with one of the important targets being to ensure universal access to reproductive health intendance services, including family planning, data and instruction, and the integration of reproductive health into national strategies and programs. The aim of this written report was to investigate the distribution and determinants of LBW in selected developing countries so that policy makers in all countries can design effective plans for building stronger communities, emphasizing a comprehensive approach to reach their objectives, particularly SDG-3.
METHODS
Study Design
Secondary data assay was carried out using DHS data for the period of 2010 to 2013 from the following least-developed countries equally defined past the World Bank: US (2010), Kingdom of cambodia (2010), Colombia (2010), Indonesia (2012), Jordan (2012), Nepal (2011), Pakistan (2012-2013), Tanzania (2010), Uganda (2011), and Zimbabwe (2010-2011). Moreover, those surveys used continuous of nascence weight data, which was some other criterion for choosing those countries.
Data Drove and Sampling Technique
The DHS collected national-level household-based survey data on birth weight retrospectively from mothers whose youngest child was under five years of age. The DHS used a stratified, two-stage cluster sampling design. The first stage involved selecting samples from a master sampling frame constructed from enumeration, and the second stage involved systematic sampling of the households listed from each cluster, to ensure that adequate numbers of completed individual interviews were obtained. The survey collected data through questionnaire-based face-to-face interviews, for which women of reproductive age (15 to 49 years) were interviewed based on the Mensurate DHS programme model. Each respondent (mother) was asked to provide a detailed nativity history for births in the preceding survey. Nascence weight was recorded using the metric scale (in grams) in all selected report countries. Details regarding the sample pattern, specific consent, and information collection procedures have been reported elsewhere, in the DHS reports from the individual countries [17].
Result Variable
The DHS recorded birth weight data from mothers whose youngest child was less than five years onetime in the five years preceding the survey using wellness bill of fare records. Entries on health cards were mostly completed by a physician or a health worker and given to mothers upon discharge from the health facility (east.g., hospital, clinic or any other healthcare institution). Reporting birth weight information on wellness cards has been establish to be more than reliable than obtaining birth weight data through maternal recollect [18]. The birth weight information derived from the DHS may include possible misclassifications, every bit the DHS used the proxy variable of the reported size of the infant at nativity, which may pb to potential heaping [xviii-21]. This study analyzed merely the numerical birth weight data contained in the DHS survey for but the nearly recent children. Finally, birth weight data were classified into two groups: non-LBW (birth weight ≥2500 k) or LBW (nascence weight <2500 1000). Data from children with a missing birth weight, mothers with twin or multiple pregnancies, and stillbirths were excluded from the assay.
Contained Variables
The study variables were selected based on epidemiological data, prior studies, a review of the relevant published demographic studies, and the available information in the DHS datasets, with a consideration of potential confounders [22-24]. Individual-level factors such every bit maternal age, the tiptop of the mother, sex of the child, educational status, occupational status, parity, ANC visits, intake of atomic number 26 during pregnancy, maternal hemoglobin (Hb) levels, and nutritional condition, equally well equally community-level factors, such as wealth condition and place of residence, were considered in the study. Maternal age was divided into the categories of ≤19 years, 20-34 years, and 35-49 years, and maternal tiptop was defined as short (≤145 cm), average (146-155 cm), or tall (>155 cm). The sex of the child was recorded every bit male or female person. Education level was divers every bit no education, primary instruction, or secondary or higher education, and current occupational status was classified as not working or working. Frequency of ANC visits was defined as inadequate (0 or 1), intermediate (2 or 3), or adequate (4 or more), and parity was classified equally first birth, 2-3 births, four or more than births. Age at first cohabitation was divers every bit ≤12 years, 13-17 years, or ≥18 years. Whether the mother had taken iron pills during pregnancy was recorded every bit yes or no. Maternal Hb levels were measured using the HemoCue (HemoCue, Angelholm, Sweden) rapid testing method, and participants were divided based on whether their Hb level was <12.0 g/dL or ≥12.0 g/dL. Height and body weight were obtained from the dataset, and body mass index (BMI) was calculated every bit the ratio of weight in kilograms to pinnacle in meters squared (kg/thouii). BMI was further categorized into three groups: low (≤18.5 kg/one thousand2), normal or salubrious weight (18.5-24.9 kg/m2) or overweight (BMI >24.9 kg/thousand2). The DHS applied an nugget-based approach to estimate household wealth status, which was measured based on the buying of durable assets. Each variable (nugget) was dichotomized as 1 if present and 0 if non, and the wealth index was constructed using principal component assay (PCA). Weights were adamant past gene scores derived from the first principal component in the PCA. The constructed wealth index values were and then assigned to each private based on mutual variables. We established cutoff values for percentiles of the population, and we classified participants into three groups: poor (bottom forty%), centre (middle 40%), or rich (top twenty%), following the cutoffs used in an before study. Place of residence was classified as rural or urban.
Statistical Analysis
In the descriptive analyses, the characteristics of the study population for selected countries were expressed as percentages (%) with 95% confidence interval (CIs). For independent variables, the category found to be at the to the lowest degree take a chance for having an LBW baby in the analysis was considered as the reference for constructing odds ratios (ORs). A multivariate logistic regression model was applied to estimate ORs as a measure of the associations between LBW and related risk factors afterwards because potential confounders. The diagnostic tests were employed in the analyses. Normality examination for the nativity weight data was accomplished through graphically. Goodness of fit was assessed using the Hosmer and Lemeshow statistic [25]. The variance inflation gene (VIF) test was performed to determine whether multicollinearity was present. For all the tests conducted in the report, p<0.05 were considered to indicate statistical significance. In the analyses, the sampling weight was adapted based on the DHS data [26], and all statistical analyses were carried out using Stata/SE 13.0 (StataCorp, College Station, TX, U.s.a.).
Ethical Approving
Ethical clearance to conduct the DHS was obtained from the Measure DHS and the Ethics Committee of ICF Macro (Calverton, MD, U.s.a.). The DHS data are publicly accessible and were made available to united states upon request by Measure out DHS.
RESULTS
Population Characteristics
A total of 59 932 live births were recorded in the study countries (Table 1); Republic of indonesia had the highest number (fifteen 135 live births), followed by Republic of colombia (12 029 live births). Birth weight data were demonstrated to be usually distributed (Effigy 1). The overall prevalence of LBW was fifteen.nine% (95% CI, 15.6 to sixteen.2%), and the average birth weight of LBW babies was 2179 k (Effigy 2). Pakistan had the highest prevalence of LBW (35.one%; 95% CI, 32.9 to 37.iii%), followed by Nepal (29.7%; 95% CI, 27.7 to 31.vii%), with boilerplate birth weights of 1988 g and 2255 thou, respectively (Table 1).
Distribution of nascence weight (BW) for selected 10 developing countries (A) Armenia, (B) Cambodia, (C) Colombia, (D) Republic of indonesia, (E) Hashemite kingdom of jordan, (F) Nepal, (Thou) Pakistan, (H) Tanzania, (I) Uganda, and (J) Republic of zimbabwe.
Prevalence of low birth weight (LBW) in developing countries.
Table 1.
Distribution of birth weight for respondents' most recent pregnancy in x selected developing countries, with the years surveyed
| Countries | Survey years 1 | No. of live births 2 | LBW 3 | Extreme LBW 4 | Overall prevalence of LBW 5 | ||
|---|---|---|---|---|---|---|---|
| Average weight (k) | Prevalence | Boilerplate weight (g) | Prevalence | ||||
| Armenia | 2010 | 1426 | 2214.8 | 8.4 | 1178.six | 0.five | 9.0 |
| Cambodia | 2010 | 5929 | 2292.4 | fourteen.5 | 1085.0 | 0.four | 14.2 |
| Republic of colombia | 2010 | 12 029 | 2267.viii | 12.2 | 1114.six | ane.0 | 11.8 |
| Indonesia | 2012 | 15 135 | 2288.7 | 12.ii | 1098.5 | 0.7 | 12.9 |
| Jordan | 2012 | 9734 | 2202.2 | 19.6 | 1036.four | 1.three | 22.0 |
| Nepal | 2011 | 1955 | 2294.four | 27.ane | 1171.ane | i.0 | 29.7 |
| Pakistan | 2012-2013 | 1458 | 2147.nine | 31.4 | 1079.9 | 5.8 | 35.i |
| Tanzania | 2010 | 4325 | 2285.8 | xiii.0 | 1072.7 | 0.four | 13.9 |
| Uganda | 2011 | 4078 | 2231.2 | fifteen.8 | 1012.3 | 0.8 | 16.9 |
| Zimbabwe | 2010-2011 | 3862 | 2270.six | 14.ii | 1039.3 | 0.8 | 14.5 |
| Total | 59 932 | 2251.7 | 14.9 | 1076.nine | 1.0 | 15.9 | |
The bulk of the mothers (73.5%) were between twenty and 34 years of age, and more than than half of the mothers did not have any formal didactics, with the highest proportion institute in Pakistan (57.2%), followed by Nepal (46.5%) (Table 2). Overall, 52% of mothers were non-working, with the highest corporeality observed in Jordan (85.7%), followed by Pakistan (74.two%). Approximately 93.eight% of mothers had taken iron pills, and more than than 63% of mothers had not an adequate level of Hb (<12.0 g/dL). Overall, approximately 69.eight% of mothers received adequate ANC (4 or more visits) during their last pregnancy. However, the highest percentages of acceptable ANC were observed among the mothers in Armenia (94.8%), Republic of colombia (89.8%), Indonesia (88.4%), and Jordan (94.5%). Nearly one-half of the mothers lived in households with a low socioeconomic condition (Tabular array 2).
Table two.
Distribution of groundwork characteristics in the written report population from 10 selected developing countries 1
| Background characteristics | Countries | |||||
|---|---|---|---|---|---|---|
| Armenia | Kingdom of cambodia | Colombia | Republic of indonesia | Jordan | Nepal | |
| Maternal historic period (y) | ||||||
| ≤ xix | 2.2 (i.5, iii.3) | 2.6 (2.three, iii.1) | 10.v (ix.ix, 11.ane) | iii.0 (2.six, 3.three) | 1.eight (ane.4, 2.3) | 7.ane (6.2, eight.0) |
| 20-34 | 89.0 (86.8, 91.0) | 76.5 (75.3, 77.6) | 72.4 (71.5, 73.2) | 71.iv (70.v, 72.4) | 69.five (68.0, 71.0) | 81.iii (eighty.0, 82.5) |
| 35-49 | 8.8 (7.0, 10.9) | 20.9 (19.7, 22.1) | 17.2 (xvi.5, 18.0) | 25.6 (24.7, 26.6) | 28.7 (27.2, 30.2) | 11.7 (ten.vii, 12.7) |
| Maternal height (cm) | ||||||
| Short (≤ 145) | 5.iii (4.5, half dozen.1) | ii.8 (2.5, 3.1) | 0.7 (0.5, 0.9) | eleven.1 (9.3, xiii.iii) | ||
| Average (146-155) | NA | 59.3 (57.half dozen, 61.1) | 37.viii (36.9, 38.6) | NA | 25.iv (24.4, 26.5) | 61.1 (57.9, 64.ii) |
| Tall (>155) | 35.4 (33.7, 37.1) | 59.iv (58.5, 60.3) | 73.nine (72.viii, 75) | 27.eight (25.0, 30.vii) | ||
| Sex of kid | ||||||
| Male | 51.eight (49.2, 54.four) | 51.5 (50.two, 52.viii) | 51.7 (50.8, 52.six) | 50.nine (50.1, 51.7) | 52.1 (51.1, 53.one) | 51.6 (49.4, 53.eight) |
| Female | 48.2 (45.6, l.8) | 48.5 (47.2, 49.8) | 48.three (47.4, 49.two) | 49.1 (48.three, 49.9) | 47.nine (46.9, 48.ix) | 48.4 (46.2, fifty.half-dozen) |
| Maternal educational activity | ||||||
| No educational activity | 16.half-dozen (16.two, sixteen.9) | 17.0 (16.7, 17.2) | iii.0 (2.vii, iii.two) | three.ii (3.0, 3.5) | 3.0 (2.7, 3.iii) | 46.v (45.1, 47.8) |
| Primary | 32.2 (32.8, 33.6) | 32.1 (31.viii, 32.four) | thirty.4 (29.seven, 31.ane) | 30.seven (30.1, 31.iv) | 7.0 (vi.5, seven.v) | 20.0 (18.9, 21.1) |
| Secondary or college | fifty.2 (49.8, fifty.vii) | l.9 (50.6, 51.2) | 66.7 (66.0, 67.4) | 66.0 (65.4, 66.seven) | ninety.0 (89.4, 90.5) | 33.5 (32.three, 34.8) |
| Maternal occupation | ||||||
| Not working | 84.nine (82.6, 87.0) | 33.5 (32.2, 34.8) | 54.iv (53.five, 55.4) | 52.3 (51.ii, 53.3) | 85.seven (84.half dozen, 86.viii) | 45.i (43.4, 46.7) |
| Working | 15.1 (13.0, 17.4) | 66.v (65.2, 67.8) | 45.6 (44.half dozen, 46.5) | 47.8 (46.7, 48.eight) | 14.three (13.2, 15.4) | 54.9 (53.three, 56.6) |
| Marriage to first birth interval (mo) | ||||||
| First nativity | 54.half-dozen (51.3, 57.8) | 35.6 (34.3, 36.ix) | 44.six (43.5, 45.eight) | 46.9 (45.eight, 47.9) | 49.5 (47.viii, 51.1) | 24.4 (23.0, 25.ix) |
| <24 | 32.0 (29.ii, 35.0) | 35.vii (34.three, 37.0) | 24.9 (24.0, 25.nine) | 31.4 (thirty.4, 32.four) | 31.7 (xxx.ii, 33.iii) | 32.3 (30.8, 33.9) |
| 24-47 | eleven.2 (ix.2, thirteen.5) | 22.2 (21.1, 23.four) | twenty.six (19.7, 21.6) | 15.ix (15.one, 16.75) | 14.2 (13.1, fifteen.4) | 28.9 (27.5, thirty.5) |
| ≥48 | two.3 (1.5, three.3) | 6.5 (five.nine, 7.2) | 9.8 (9.1, 10.v) | 5.8 (5.3, half dozen.four) | 4.6 (iv.0, v.iv) | fourteen.iii (xiii.2, xv.5) |
| Parity | ||||||
| Starting time child | 47.ii (44.6, 49.8) | 38.4 (37.ii, 39.6) | 44.0 (43.one, 44.9) | 40.0 (39.2, twoscore.8) | 23.4 (22.6, 24.3) | 50.6 (48.4, 52.viii) |
| 2-3 | 49.6 (47.0, 52.two) | 43.two (41.9, 44.four) | 44.8 (43.9, 45.6) | 47.2 (46.4, 48.0) | 39.0 (38.1, 40.0) | 40.iv (38.2, 42.6) |
| ≥iv | three.two (2.four, 4.three) | 18.four (17.5, xix.four) | eleven.3 (10.7, eleven.viii) | 12.eight (12.ii, thirteen.three) | 37.five (36.6, 38.5) | 9.1 (7.9, x.4) |
| Took iron pills | ||||||
| Yes | 93.8 (91.6, 95.5) | 98.four (98.0, 98.seven) | NA | 86.8 (86.0, 87.6) | 96.one (95.3, 96.7) | 97.7 (97.2, 98.ane) |
| No | 6.2 (iv.6, viii.4) | 1.six (1.32, 2.02) | 13.two (12.4, 13.9) | 3.nine (3.3, 4.7) | 2.iii (ane.9, 2.8) | |
| Maternal anemia (Hb, g/dL) | ||||||
| Bloodless (<12.0) | NA | 55.1 (53.2, 57.0) | NA | NA | 61.three (59.3, 63.three) | 62.1 (59.7, 64.4) |
| Non-anemic (≥12.0) | 44.nine (43.0, 46.8) | 38.vii (36.7, 40.seven) | 37.nine (35.6, 40.3) | |||
| No. of ANC visits | ||||||
| Inadequate (0 or i) | 1.2 (0.vi, 2.9) | 15.two (13.7, 16.8) | three.9 (2.8, 4.5) | iv.7 (three.six, 6.8) | one.5 (1.0, ii.4) | 21.2 (eighteen.6, 25.three) |
| Intermediate (2 or iii) | 4.0 (2.6, 6.5) | 25.2 (23.three, 27.2) | 6.iii (4.half dozen, 7.0) | 6.9 (5.6, eight.5) | four.0 (iii.0, 5.3) | 28.vii (26.0, 31.4) |
| Adequate (4 or more than) | 94.8 (93.0, 96.1) | 59.half dozen (58.2, 61.1) | 89.8 (89.1, 90.4) | 88.four (87.8, 89.1) | 94.5 (93.five, 95.4) | 50.1 (48.two, 52.0) |
| Place of delivery | ||||||
| Facility | 99.ix (99.5, 100) | 72.7 (71.2, 74.one) | 98.6 (98.3, 98.viii) | 70.2 (69.2, 71.2) | 99 (98.6, 99.3) | 35.3 (29.v, 45.6) |
| Domicile | 0.i (0.0, 0.5) | 27.3 (25.nine, 28.8) | 1.4 (1.2, 1.seven) | 29.8 (28.8, thirty.viii) | i (0.7, 1.6) | 64.7 (51.9, 71.nine) |
| Nutritional status | ||||||
| Low BMI | fifteen.6 (14.3, 17.0) | 3.8 (3.5, 4.2) | two.1 (i.v, 2.8) | 19.5 (17.6, 21.5) | ||
| Normal BMI | NA | 72.7 (71.1, 74.3) | 49.seven (48.8, 50.6) | NA | 32.eight (30.8, 34.7) | 71.0 (68.7, 73.i) |
| Overweight | 11.7 (10.6, 12.ix) | 46.5 (45.6, 47.four) | 65.ii (63.2, 67.1) | ix.5 (8.2, 11.0) | ||
| Wealth status | ||||||
| Poor (lower 40%) | 40.viii (37.7, 43.9) | 48.ane (46.8, 49.5) | 48.2 (47.iii, 49.2) | 41.two (40.2, 42.2) | 45.5 (43.ix, 47.1) | 47.seven (46.1, 49.3) |
| Center (middle 40%) | 40.5 (37.three, 43.7) | 35.5 (34.two, 36.8) | 39.8 (38.eight, 40.eight) | 39.8 (38.viii, 40.9) | xl.8 (39.ii, 42.four) | 38.4 (36.eight, 40.i) |
| Rich (upper 20%) | 18.7 (16.0, 21.eight) | 16.4 (15.5, 17.4) | 12.0 (11.iii, 12.vii) | 19.0 (18.ane, nineteen.9) | 13.8 (12.4, xv.3) | thirteen.9 (12.8, 15.0) |
| Place of residence | ||||||
| Urban | 58.4 (55.23, 61.5) | 15.half-dozen (14.8, 16.five) | 72.0 (71.1, 72.8) | 49.6 (48.5, 50.seven) | 81.46 (eighty.v, 82.4) | 9.3 (8.vii, ten.0) |
| Rural | 41.6 (38.5, 44.viii) | 84.4 (83.five, 85.2) | 28.0 (27.2, 28.9) | 50.4 (49.three, 51.5) | eighteen.5 (17.7, 19.v) | 90.seven (90.0, 91.3) |
| Full (north) | 1426 | 5929 | 12 029 | xv 135 | 9734 | 1955 |
| | ||||||
| Background characteristics | Countries | |||||
| Pakistan | Tanzania | Republic of uganda | Zimbabwe | All countries | ||
| | ||||||
| Maternal age (y) | ||||||
| ≤ 19 | two.2 (i.9, 2.6) | v.3 (4.7, 5.nine) | 5.8 (v.ii, 6.4) | 7.2 (6.4, 8.0) | 5.1 (5.0, 5.2) | |
| 20-34 | 78.0 (77.0, 79.0) | 70.2 (69.0, 71.four) | 72.four (71.2, 73.5) | 76.9 (75.6, 78.i) | 73.five (73.2, 73.7) | |
| 35-49 | 19.8 (xviii.eight, 20.7) | 24.vi (23.5, 25.vii) | 21.8 (20.8, 22.9) | xvi.0 (fourteen.9, 17.1) | 21.4 (21.2, 21.7) | |
| Maternal elevation (cm) | ||||||
| Short (≤ 145) | ii.0 (1.1, three.6) | 2.9 (2.five, 3.5) | 1.1 (0.vii, 1.9) | 0.half-dozen (0.4, 0.9) | 0.six (0.4, 0.ix) | |
| Average (146-155) | forty.vii (36.7, 44.eight) | 40.one (38.seven, 41.vi) | 23.six (21.4, 26) | 19.3 (eighteen.0, twenty.five) | 19.iii (18.0, 20.v) | |
| Alpine (>155) | 57.3 (53.2, 61.3) | 57.0 (55.5, 58.4) | 75.three (72.8, 77.5) | 80.i (78.9, 81.iv) | 80.1 (78.ix, 81.4) | |
| Sexual practice of kid | ||||||
| Male person | 52.5 (49.nine, 55.1) | l.vii (49.2, 52.2) | 49.8 (48.3, 51.four) | 49.eight (48.3, 51.iv) | l.eight (49.two, 52.four) | |
| Female | 47.5 (44.nine, 50.1) | 49.3 (47.8, 50.8) | 50.2 (48.6, 51.seven) | 50.2 (48.6, 51.7) | 49.2 (47.6, 50.viii) | |
| Maternal education | ||||||
| No education | 57.2 (56.iii, 58.1) | 25.4 (24.4, 26.3) | eighteen.1 (17.iii, 19.00 | ane.eight (1.4, 2.1) | l.9 (fifty.6, 51.two) | |
| Primary | 14.iv (13.seven, 15.0) | 63.1 (62.1, 64.2) | 59.4 (58.three, lx.five) | 32.eight (31.half-dozen, 37.1) | 17.0 (16.7, 17.2) | |
| Secondary or higher | 28.five (27.seven, 29.3) | 11.5 (10.eight, 12.2) | 22.four (21.v, 23.4) | 65.4 (64.1, 66.7) | 32.1 (31.8, 32.iv) | |
| Maternal occupation | ||||||
| Not working | 74.2 (73.1, 75.four) | xiii.ii (12.3, 14.one) | 25.0 (23.9, 26.one) | 65.ii (63.8, 66.half-dozen) | 52.9 (52.6, 53.2) | |
| Working | 25.viii (24.6, vii.0) | 86.viii (85.nine, 87.7) | 75.0 (73.nine, 76.1) | 34.8 (33.5, 36.2) | 47.1 (46.viii, 47.4) | |
| Marriage to first birth interval (mo) | ||||||
| First birth | 32.half-dozen (31.4, 33.eight) | 43.five (42.1, 45.0) | 48.vi (47.one, 50.0) | 58.iii (56.7, 59.9) | 43.2 (42.9, 43.five) | |
| <24 | 28.seven (27.6, ix.nine) | 36.ii (34.eight, 37.7) | 29.6 (28.three, 30.9) | 26.7 (25.iii, 28.one) | 31.0 (30.7, 31.3) | |
| 24-47 | 25.3 (24.two, 6.iv) | 16.2 (15.1, 17.iii) | 16.2 (15.1, 17.3) | eleven.0 (10.0, 12.0) | 18.four (xviii.1, 18.6) | |
| ≥48 | 13.four (12.6, 14.iii) | 4.0 (3.v, four.6) | 5.7 (5.1, half dozen.4) | iv.1 (3.5, 4.7) | seven.iv (7.ii, seven.six) | |
| Parity | ||||||
| First child | 33.9 (31.5, 36.4) | 26.0 (24.7, 27.3) | 26.0 (24.7, 27.three) | 22.v (21.2, 23.viii) | 35.5 (34.1, 37.1) | |
| 2-3 | 42.vii (40.2, 45.three) | 37.1 (35.7, 38.vi) | 37.1 (35.vii, 38.6) | 34.2 (32.8, 35.7) | 45.7 (44.ane, 47.2) | |
| ≥4 | 23.4 (21.iii, 25.6) | 36.ix (35.five, 38.three) | 36.9 (35.5, 38.iii) | 43.3 (41.8, 44.8) | eighteen.8 (17.6, 20.0) | |
| Took iron pills | ||||||
| Yes | 92.9 (92.ii, 93.v) | 98.seven (98.iii, 99.0) | 93.2 (92.v, 93.8) | NA | 93.viii (93.6, 94.viii) | |
| No | 7.2 (6.5, 7.8) | i.3 (ane.0, 1.seven) | 6.eight (half-dozen.2, vii.5) | 6.ii (6.0, 6.iv) | ||
| Maternal anemia (Hb, m/dL) | ||||||
| Bloodless (<12.0) | NA | 59.4 (58.1, 60.7) | 74.9 (72.8, 76.eight) | 72.3 (lxx.nine, 73.six) | 63.ane (62.three, 63.viii) | |
| Not-anemic (≥12.0) | 40.6 (39.3, 42.0) | 25.i (23.ii, 27.2) | 27.vii (26.4, 29.ane) | 36.9 (36.two, 37.7) | ||
| Number of ANC visits | ||||||
| Inadequate (0 or 1) | 37.8 (33.2, 40.8) | 5.5 (3.7, half-dozen.8) | viii.3 (6.8, 9.5) | 12.7 (10.ii, 15.8) | 11.iv (9.8, 14.three) | |
| Intermediate (2 or 3) | 25.6 (23.half-dozen, 27.8) | 51.5 (48.ix, 54.3) | 43.ii (twoscore.six, 45.ix) | 21.half-dozen (19.7, 23.6) | eighteen.8 (sixteen.2, twenty.7) | |
| Adequate (4 or more) | 36.6 (35.1, 38.1) | 43.0 (41.four, 44.7) | 48.5 (46.eight, 50.1) | 65.seven (64.i, 67.3) | 69.viii (69.5, 70.1) | |
| Place of delivery | ||||||
| Facility | 48.2 (47.6, 52.9) | 52.8 (45.vi, 56.9) | 57.6 (45.9, 61.2) | 65.3 (59.two, 68.9) | 86.8 (86.4, 87.1) | |
| Domicile | 51.eight (48.2, 53.9) | 47.2 (42.vi, 55.ii) | 42.four (39.5, 49.ane) | 34.7 (29.8, 38.9) | xiii.2 (12.9, 13.6) | |
| Nutritional status | ||||||
| Depression BMI | xiv.half-dozen (thirteen.1, xvi.three) | 9.0 (viii.iii, ix.8) | nine.vii (viii.5, 11.0) | 4.9 (5.three, 6.6) | 7.6 (vii.4, seven.8) | |
| Normal BMI | 54.2 (52.one, 56.3) | 73.2 (72.0, 74.iv) | 73.9 (71.9, 75.8) | 64.vii (63.3, 66.1) | 57.ii (56.8, 57.6) | |
| Overweight | 31.2 (29.iii, 33.one) | 17.8 (16.eight, 18.ix) | 16.5 (xiv.9, 18.ii) | 29.iv (28.1, 30.8) | 35.2 (34.8, 35.6) | |
| Wealth condition | ||||||
| Poor (lower xl%) | 45.1 (43.eight, 46.iii) | 44.vii (43.4, 46.ane) | 43.viii (42.5, 45.1) | 43.9 (42.5, 45.3) | l.5 (50.ane, 50.8) | |
| Heart (middle xl%) | 39.2 (38.0, 40.four) | 41.i (39.8, 42.4) | 37.vii (36.four, 38.ix) | 40.4 (39.0, 1.ix) | 35.5 (35.2, 35.8) | |
| Rich (upper 20%) | 15.7 (fourteen.9, 16.6) | fourteen.2 (13.2, fifteen.1) | eighteen.5 (17.5, xix.6) | 15.vii (xiv.7, 16.8) | 14.1 (13.nine, 14.3) | |
| Place of residence | ||||||
| Urban | 29.1 (28.1, xxx.2) | 20.3 (xix.2, 21.5) | 14.2 (13.4, 15.one) | 29.8 (28.4, 31.2) | 42.0 (41.half dozen, 42.four) | |
| Rural | 70.9 (69.viii, 72.0) | 79.vii (78.6, fourscore.viii) | 85.8 (84.9, 86.6) | lxx.2 (68.viii, 71.6) | 58.0 (57.6, 58.5) | |
| Total (n) | 1458 | 4325 | 4078 | 3862 | 59 932 | |
Factors Influencing the Determinants of Depression Birth Weight
In this report, step-up methods were used to enter all factors into a single regression model for adapted assay (Table three). This model showed that a number of factors significantly influenced LBW. The regression model explained 22% of total variation (Cox-Snell R2 =22%). The VIF examination, which had a mean (maximum) value of 2.22 (four.12), indicated that no evidence of multicollinearity was present in the regression model. The Hosmer and Lemeshow statistic showed no meaning difference between the model and observed data, confirming a good fit of the model to the data. Mothers with advanced age (35 to 49 years) had a significantly greater risk of delivering LBW babies than younger mothers (p<0.01) (Table iii). Illiterate mothers (no formal education) had a higher risk of delivering LBW babies than more than highly educated mothers in Armenia (OR, one.4; 95% CI, one.ane to two.2; p<0.01), Indonesia (OR, 2.5; 95% CI, 1.5 to 4.iv; p<0.001), Jordan (OR, 1.vi; 95% CI, ane.1 to 2.7; p<0.01), Nepal (OR, 1.three; 95% CI, one.1 to i.v; p<0.001), Pakistan (OR, 2.six; 95% CI, 1.three to six.6; p<0.001), and Uganda (OR, 2.1; 95% CI, i.6 to vii.6; p<0.01). Female babies were more prone to have a LBW than male person babies in Armenia (OR, i.4; 95% CI, ane.1 to 1.8; p<0.01), Kingdom of cambodia (OR, ane.4; 95% CI, 1.1 to 1.6; p<0.01), Republic of colombia (OR, 1.3; 95% CI, i.1 to ane.5; p<0.001), Republic of indonesia (OR, one.2; 95% CI, one.1 to 1.three; p<0.001), Hashemite kingdom of jordan (OR, ane.six; 95% CI, 1.3 to 1.eight; p<0.001), and Tanzania (OR, 1.4; 95% CI, one.one to i.9; p<0.001), as well every bit in all countries overall (OR, 1.4; 95% CI, i.3 to 1.6; p<0.001).
Table iii.
Factors influencing determinants of depression birth weight for selected 10 developing countries
| Factors | Countries | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Armenia | Kingdom of cambodia | Colombia | Indonesia | Jordan | Nepal | Islamic republic of pakistan | Tanzania | Uganda | Zimbabwe | All countries | |
| Abiding | 0.4 (0.i, 0.8) ** | 0.1 (0.0, 0.2) *** | 0.i (0.ane, 0.4) *** | 0.1 (0.0, 0.two) *** | 0.2 (0.1, 0.4) *** | 0.4 (0.01, 4.7) | 0.02 (0.0, 1.9) * | 0.02 (0.0, 2.ii) * | 0.0 (0.0, 0.3) * | 0.i (0.0, 0.4) *** | 0.6 (0.1, 1.nine) *** |
| Maternal age (y) | |||||||||||
| ≤19 | 1.0 | i.0 | ane.0 | 1.0 | one.0 | 1.0 | i.0 | 1.0 | 1.0 | one.0 | i.0 |
| twenty-34 | 0.3 (0.i, ane.i) | 2.0 (0.5, eight.0) | 0.viii (0.half dozen, 1.1) | 0.8 (0.5, one.2) | 0.v (0.2, 0.9) | 0.5 (0.2, i.03) | 9.7 (0.2, 483.4) | 0.6 (0.3, 1.iv) | 2.2 (0.ii, 19.5) | 0.5 (0.3, 0.8) | 0.vii (0.5, one.0) |
| 35-49 | 1.6 (1.1, 2.8) * | 3.7 (1.9, 5.iii) ** | 1.ix (1.half-dozen, iii.2) *** | 0.9 (0.6, 1.3) | 1.4 (1.i, 2.8) *** | 1.six (1.i, 2.5) ** | 7.7 (1.2, 14.1) ** | 1.4 (1.one, three.0) ** | one.four (1.one, 3.ix) ** | 1.6 (i.1, two.2) ** | ane.7 (1.2, 3.1) ** |
| Maternal height (cm) | |||||||||||
| Short (≤ 145) | ane.0 | ane.0 | 1.0 | ane.0 | one.0 | one.0 | 1.0 | 1.0 | ane.0 | 1.0 | ane.0 |
| Average (146-155) | NA | i.v (0.9, 2.3) ** | two.iii (1.half dozen, 3.1) *** | NA | ane.3 (0.eight, 2.2) | 1.1 (0.vii, 1.8) | 1.1 (0.3, 3.1) | 1.one (0.5, i.ix) | one.2 (0.nine, 2.1) | 2.9 (1 , 8.2) * | i.2 (1.0, 1.six) |
| Tall (>155) | NA | 0.eight (0.6, 0.9) *** | 0.seven (0.half-dozen, 0.8) *** | NA | 0.6(0.six, 0.seven) *** | 0.viii (0.6, i.2) | 0.seven (0.v, 0.9) ** | 0.7 (0.v, 0.viii) *** | 0.5 (0.iii, 0.seven) *** | 0.viii (0.6 , 0.ix) * | 0.7 (0.6, 0.viii) *** |
| Sexual activity of child | |||||||||||
| Male | one.0 | i.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Female | 1.iv (1.1, 1.8) ** | ane.4 (1.1, one.half-dozen) ** | i.3 (1.i, ane.5) *** | one.ii (i.i, 1.3) *** | 1.6 (1.3, 1.8) *** | 1.ane (0.vii, i.half-dozen) | 1.2 (0.7, 1.7) | 1.4 (1.1, one.9) *** | 1.2 (0.seven, 2.i) | 1.ii (0.7, 2.0) | 1.4 (1.3, ane.half-dozen) *** |
| Maternal education | |||||||||||
| No education | 1.4 (1.1, ii.2) ** | 0.nine (0.v, 1.viii) | 1.iii (0.6, 2.9) | 2.v (ane.five, iv.4) *** | 1.6 (1.1, 2.seven) ** | 1.3 (i.1, 1.5) *** | ii.vi (i.1, half-dozen.6) *** | 0.6 (0.three, one.5) | ii.one (one.ane, 7.6) ** | 0.8 (0.1, 5.5) | ane.5 (1.1, 2.7) *** |
| Principal | one.6 (0.6, four.6) | 1.1 (0.7, 1.eight) | 0.9 (0.7, 1.ii) | 1.4 (1.2, one.7) ** | ane.4 (1.1, 2.i) * | 1.4 (0.six, 2.2) | 2.8 (i.three, 6.1) *** | 0.half-dozen (0.3, 0.8) * | 0.6 (0.2, ane.5) | 1.1 (0.7, 1.half-dozen) | 1.6 (1.two, 1.8) * |
| Secondary or higher | 1.0 | 1.0 | 1.0 | ane.0 | i.0 | one.0 | 1.0 | ane.0 | 1.0 | 1.0 | 1.0 |
| Maternal occupation | |||||||||||
| Not working | 1.0 | one.0 | 1.0 | 1.0 | one.0 | ane.0 | ane.0 | 1.0 | one.0 | one.0 | 1.0 |
| Working | i.one (0.five, 2.2) | ane.2 (0.8, one.7) | 1.0 (0.9, 1.2) | 1.0 (0.9, i.2) | 0.ix (0.7, one.3) | one.5 (ane.1, 2.8) ** | 1.4 (ane.1, 2.7) *** | 0.7 (0.5, 1.2) | 0.9 (0.5, 2.1) | 1.2 (0.eight , ane.6) | 0.8 (0.six, one.9) |
| Marriage to first birth interval (mo) | |||||||||||
| Start nascency | ane.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | one.0 | 1.0 | 1.0 | 1.0 |
| <24 | 0.5 (0.3, 0.ix) | 1.3 (0.ix, ii.1) | ane.i (0.nine, 1.iv) | 0.8 (0.7, 0.ix) * | one.2 (0.9, 1.five) | 0.9 (0.five, 1.vii) | 0.9 (0.4, one.seven) | 0.9 (0.6, 1.half dozen) | 1.8 (0.viii, 4.1) | 1.3 (0.8, i.eight) | 1.2 (0.ix, one.4) |
| 24-47 | 1.iv (0.half dozen, 2.9) | one.2 (0.7, 2.0) | 1.3 (0.9, 1.4) | 0.nine (0.8, 1.ii) | 1.ane (0.8, one.five) | ane.1 (0.five, 2.1) | one.5 (0.7, 3.i) | i.3 (0.viii, 2.iii) | 2.9 (1.2, 7.1) | one.4 (0.8, ii.four) | 1.2 (0.8, one.5) |
| ≥ 48 | 2.eight (1.half dozen, 4.1) *** | i.9 (i.i, 3.7) ** | 1.4 (i.1, 1.9) ** | 0.9 (0.7, i.4) | 2.2 (1.4, 3.3) *** | 0.8 (0.iii, two.3) | 0.eight (0.3, 2.3) | 2.4 (ane.1, 5.four) ** | 2.2 (one.2, 3.5) ** | 1.5 (0.half dozen, iii.3) | ane.eight (i.4, 2.5) *** |
| Parity | |||||||||||
| First child | 1.5 (1.i, 2.7) ** | one.3 (0.9, i.9) ** | 1.iii (ane.1, 3.two) *** | one.7 (one.1, ii.9) *** | 1.0 (0.viii, 1.3) | 1.4 (one.1, 2.ane) ** | ane.four (1.1, 3.1) *** | i.4 (one.1, 2.8) *** | 1.4 (1.one, 2.ix) ** | i.iii (ane.0, 1.eight) * | 1.5 (ane.1, 2.9) *** |
| ii-3 | 1.0 (0.6, ane.v) | 0.8 (0.five, 1.ii) | 0.eight (0.7, 0.9) | 0.half dozen (0.half dozen, 0.7) * | ane.1 (0.9, 1.iv) | 0.7 (0.4, 1.2) | 0.7 (0.four, 1.2) | 0.six (0.4, 0.9) | 0.6 (0.3, i.iii) | 0.vii (0.v, 0.9) | 1.6 (0.3, 2.9) |
| ≥4 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | i.0 | 1.0 | i.0 | 1.0 |
| Took fe pills | |||||||||||
| No | i.7 (0.8, 4.3) | 2.5 (1.1, seven.v) * | NA | 1.three (one.1, one.5) ** | 4.iv (3.two, vi.i) *** | 0.2 (0.1, 13.5) | 4.2 (1.8, 9.5) *** | 0.v (0.ane, 3.ix) | 0.9 (0.3, 3.2) | NA | iii.0 (two.iv, 4.1) *** |
| Yes | 1.0 | 1.0 | 1.0 | i.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Maternal anemia (Hb, g/dL) | |||||||||||
| Anemic (<12.0) | 1.0 | i.0 | 1.0 | 1.0 | 1.0 | ane.0 | 1.0 | 1.0 | one.0 | 1.0 | ane.0 |
| Non-anemic (≥12.0) | NA | one.3 (0.9, one.9) | NA | NA | 0.ix (0.7, i.one) | ii.0 (1.2, three.3) *** | NA | 1.2 (0.8, 1.eight) | i.3 (0.5, 2.9) | 0.8 (0.5, 1.1) | 1.0 (0.nine , 1.2) |
| No. of ANC visits | |||||||||||
| Inadequate (0 or 1) | 0.viii (0.2, 5.4) | ane.3 (0.6, 2.vii) | 3.four (two.2, 5.4) ** | 2.iv (1.3, 3.4) *** | 3.half dozen (1.6, 8.1) *** | one.5 (1.1, 5.9) ** | 1.3 (i.1, i.eight) ** | 3.6 (ane.v, 8.9) *** | 3.ii (1.8, 7.1) *** | 4.9 (2.9, 8.2) *** | 1.seven (1.1, 2.8) ** |
| Intermediate (ii or iii) | 3.vi (0.7, xviii.4) | 1.ane (0.four, 2.7) | 2.7 (i.vii, 4.6) *** | two.0 (one.2, 3.3) *** | 1.7 (1.1, 4.3) ** | one.7 (0.6, four.8) | 2.3 (0.6, 9.8) | two.1 (one.2, 3.1) | ii.3 (0.3, xix.ane) | 3.2 (ane.4, 7.2) *** | 1.5 (ane.ane, 2.eight) ** |
| Adequate (four or more) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | i.0 | 1.0 | ane.0 | 1.0 | ane.0 | ane.0 |
| Identify of commitment | |||||||||||
| Facility | 1.0 | ane.0 | 1.0 | i.0 | 1.0 | 1.0 | 1.0 | 1.0 | ane.0 | i.0 | 1.0 |
| Home | NA | ane.two (0.6, two.4) | NA | 1.4 (1.1, 2.1) ** | NA | 1.iv (1.2, 2.ix) ** | 1.ii (0.nine, 2.ix) | ane.5 (1.2, three.two) * | 1.3 (1.0, ii.9) ** | 2.five (2.ane, three.v) * | 1.6 (1.3, 2.1) ** |
| Nutritional status | |||||||||||
| Depression BMI | NA | 2.9 (i.4, vi.three) *** | 1.v (1.1, 2.0) ** | NA | 2.2 (one.3, three.ix) *** | i.9 (1.1, four.9) ** | i.5 (1.1, 3.1) ** | one.ii (0.9, ii.half dozen) ** | i.9 (1.2, four.8) ** | ane.2 (0.9, ane.9) ** | 1.6 (ane.ii, 2.1) *** |
| Normal BMI | NA | one.six (0.viii, 3.1) | 0.7 (0.six, 0.eight) | NA | 1.three (1.1, 1.half dozen) ** | 1.4 (0.6, 2.ix) | 0.7 (0.4, 1.2) | 1.0 (0.six, 1.seven) | 2.4 (0.8, 5.5) | 0.9 (0.6, 1.4) | 1.1 (0.ix, ane.iii) |
| Overweight | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | one.0 | 1.0 | ane.0 |
| Wealth status | |||||||||||
| Poor (lower 40%) | two.0 (1.one, five.0) * | i.6 (one.two, 3.two) ** | 1.3 (1.one, 1.viii) *** | ane.3 (1.1, 1.7) ** | 1.7 (1.2, 2.nine) ** | 1.5 (1.1, ii.3) ** | iii.4 (one.9, seven.five) ** | 1.4 (1.1, 2.8) * | 0.vii (0.2, 2.6) | 1.3 (1.1, 2.2) ** | i.4 (ane.1, 1.8) ** |
| Middle (middle forty%) | 1.1 (0.5, two.3) | 1.2 (0.6, ii.iv) | i.0 (0.8, 1.iii) | 1.two (0.9, i.5) | 0.ix (0.6, 1.one) | 0.8 (0.4, 1.5) | 0.9 (0.iv, 1.7) | 0.eight (0.5, one.5) | one.1 (0.3, iii.half dozen) | 1.2 (0.viii, 1.viii) | 1.0 (0.8, 1.3) |
| Rich (upper 20)% | 1.0 | 1.0 | one.0 | i.0 | 1.0 | i.0 | ane.0 | one.0 | ane.0 | 1.0 | 1.0 |
| Identify of residence | |||||||||||
| Urban | one.0 | 1.0 | 1.0 | 1.0 | i.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | i.0 |
| Rural | 1.4 (1.1, 1.half-dozen) ** | 1.v (ane.i, 2.8) ** | 1.0 (0.viii, 1.8) | 1.three (one.1, 1.5) ** | i.v (i.i, 1.ix) ** | one.3 (1.1, 2.ii) ** | 0.9 (0.v, one.9) | 0.v (0.3, 0.9) ** | 1.one (0.9, 1.nine) ** | 0.eight (0.6, 1.3) | ane.5 (1.1, 1.9) ** |
| Total (n) | 1426 | 5929 | 12 029 | fifteen 135 | 9734 | 1955 | 1458 | 4325 | 4078 | 3862 | 59 932 |
| Likelihood ratio chi-square | 31.seven ** | 82.5 *** | 82.eight *** | 22.5 *** | 149.5 *** | 38.3 *** | 78.0 *** | 29.2 *** | 40.eight *** | 89.iii *** | 212.8 *** |
| Cox-Snell R2 (%) | 12.9 | 19.7 | eleven.8 | 18.vii | 22.1 | 23.0 | 15.8 | xiv.3 | 22.1 | 29.3 | 22.0 |
| Hosmer-Lemeshow statistic | 335.vi *** | 293.3 ** | 792.3 *** | 385.7 *** | 286.7 *** | 163.9 *** | 744.3 *** | 280.iii *** | 254.eight *** | 836.4 *** | 427.3 *** |
| Mean VIF (Max) | 3.2 (4.6) | 2.9 (3.vii) | ii.half-dozen (four.6) | three.2 (three.9) | 3.six (4.ane) | 3.4 (4.3) | 3.i (four.v) | 3.9 (4.3) | 3.9 (4.6) | 3.9 (4.9) | two.two (4.i) |
Moreover, delayed formulation (over 48 months) had significant relationship with LBW in Armenia (OR, 2.8; 95% CI, 1.half dozen to iv.1; p<0.01), Cambodia (OR, 1.ix; 95% CI, 1.1 to 3.7; p<0.01), Colombia (OR, 1.four; 95% CI, 1.one to 1.9; p<0.01), Jordan (OR, 2.2; 95% CI, one.4 to 3.3; p<0.001), Tanzania (OR, ii.4; 95% CI, 1.1 to five.4; p<0.01), and Uganda (OR, 2.two; 95% CI, 1.2 to 3.5; p<0.001). In all countries, ANC visits were associated with significant reductions in LBW, while receiving inadequate ANC was associated with an elevated take a chance of LBW (OR, 1.7; 95% CI, i.1 to ii.viii; p<0.01). In improver, in most of the countries, we observed a significantly increased risk of LBW in newborns born to mothers with sure specific characteristics, such every bit depression BMI (OR, i.six; 95% CI, 1.two to 2.ane; p<0.001) (with normal weight as the reference), primiparity (OR, 1.5; 95% CI, i.ane to 2.nine; p<0.001) (with parity of 4 or above every bit the reference), residing in rural communities (OR, 1.5; 95% CI, 1.i to i.nine; p<0.001), besides every bit lower wealth status of households (OR, 1.4; 95% CI, one.two to i.8; p<0.001) in comparison with the rich group.
DISCUSSION
In this study, we identified potential determinants of the prevalence of LBW in developing countries. Our findings demonstrated that advanced maternal historic period (35 to 49 years), lack of ANC, primiparity, illiteracy, afterwards conception, and being in the poorest socioeconomic stratum were significantly associated with LBW. Previous studies have too establish that women with advanced maternal age are more likely to give birth to LBW babies [i,2,27-29]. Pregnant women anile ≥35 years are more likely to increase the probability of hazard having pregnancy complications compared with younger women, like as, gestational diabetes, placenta praevia, breech presentation, that might be cause of delivering babies with LBW. Women with poor educational status were generally at a college take a chance of having an LBW baby than mothers with secondary or college education. These findings are consistent with those of some previous studies conducted in developing countries [1,thirty-32]. We found that later on conception was associated with a significantly greater risk of LBW. This may exist related to age, because increased age is related to common chronic diseases such every bit arthritis, hypertension, and diabetes prior to pregnancy [27]. However, these findings are in contrast with those of another report conducted in a developing country [31]. The present report likewise observed an increased run a risk of LBW among newborns born to mothers with a depression BMI in comparison to normal-weight mothers. This finding parallels those of earlier studies conducted in depression-middle income countries showing that infants of low-BMI mothers had a significantly higher likelihood of LBW [31,33-36]. Additionally, low socioeconomic status was a gamble factor of LBW, confirming the findings of previous studies that the poorest women in developing countries are at a significantly higher risk of delivering LBW infants [32,37].
The nowadays study found that receiving insufficient ANC was a pregnant correspondent to LBW. Specifically, in women who failed to receive whatever ANC or had inadequate ANC than recommended, the adventure of LBW was higher than in women attention the standard number of ANC visits [38]. Like results have too been reported in previous studies conducted in developing countries, although the magnitude of gamble appears to vary substantially in different settings depending on the ANC organisation and the degree of attendance [28,31,35,39]. Comparison our findings to those of prior studies, the prove suggests that the degree of risk may exist diluted in settings with a standard frequency of ANC. Women living in rural communities had a greater risk of LBW than urban mothers. Similar results have been found in other studies [ane,2,6,35]. Although this written report has some force, such equally the large sample size and quality of data, it also has important limitations. The selected countries were establish to take a large amount of missing birth weight information. They were likewise selected to ensure geographical coverage of less developed regions as well as based on the presence of available data related to the study variables. The reported number of home deliveries may accept been influenced by social, cultural, and economic factors, and is likely to be state-specific and region-specific, as well equally to modify over time, and these possibilities were not captured in this assay. Moreover, the selected DHSs were conducted in different years, which may accept resulted in inconsistencies. A loftier per centum of babies delivered at dwelling house had inadequate nascence weight measurements, with a large proportion of missing data. Consequently, many samples were excluded from the study. The aggregation of country data into regional summaries past wealth quintile may have caused errors through the combination of wealth quintiles from countries at differing wealth levels. Additional multilevel analysis of existing datasets could provide more detailed data for individual countries on adverse pregnancy outcomes also every bit on health-seeking behavior related to maternal and child health.
In summary, this study identified some significant risk factors with independent effects on the prevalence of LBW in selected developing countries. Among these factors, inadequate ANC, delayed formulation, and maternal historic period had a greater potential effect on birth weight. Improvements in these specific risk factors might have the positive outcome in reducing the incidence of LBW. However, interventions to meliorate the educational levels of women and female children are as well important for reducing the prevalence of LBW. Different strategies should be implemented because the settings of private countries, with appropriate community-based interventions focusing on these factors so that policy-makers can pattern effective plans for improving overall maternal and kid health in selected developing countries.
Acknowledgments
The International Centre for Diarrhoeal Affliction Research, Bangladesh (icddr,b) gratefully acknowledges the donors who provide unrestricted support: the Government of the People's Commonwealth of Bangladesh; Global Affairs Canada (GAC); Swedish International Development Cooperation Agency (Sida) and the Department for International Evolution (UK Assistance). We gratefully acknowledge these donors for their support and commitment to icddr,b'south research efforts. The authors would likewise like to thank the Mensurate DHS programme for providing access to the information used in the study.
Footnotes
CONFLICT OF Involvement
The authors have no conflicts of interest associated with the material presented in this newspaper.
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