Ceren V. Akpinar1, Asli A. Teneler2
1Department of Public Health, Giresun University Faculty of Medicine, Giresun, Turkey. 2Giresun Central Community Health Centre, Giresun, Turkey (Correspondence: A.A. Teneler:
Abstract
Background: Adolescent motherhood can cause lifelong health inequalities for mothers and children.
Am: To compare the frequency of negative birth outcomes and stunting in children aged 5 years of adolescent and nonadolescent mothers, and to determine the relationship with sociodemographic factors based on the Turkey Demographic and Health Survey.
Methods: This was a secondary analysis of the Turkey Demographic and Health Survey 2018. Logistic regression analysis was conducted on a sample of 2755 women aged 15–49 years who gave a live birth in the past 5 years.
Results: Term low birthweight and stunting were significantly higher in children of adolescent mothers. Multivariable analysis revealed that lack of education, poverty, and living in eastern Turkey increased the risk of delivering a term low birthweight infant. The risk of being stunted was 2.22 times higher in women with low socioeconomic status, and 2.86 times higher in low birthweight infants.
Conclusion: A large sample from the Turkey Demographic and Health Survey emphasized the necessity of planning of maternal and child health services by considering maternal education level, income inequality, and even regional inequality. These results support the notion that macroenvironmental factors have a marked impact on maternal and child health.
Keywords: adolescent pregnancy, low birthweight, stunting, social inequalities, Turkey
Citation: Akpinar CV, Teneler AA. Secondary analysis of Turkish national data investigating negative birth outcomes and stunting related to social factors and adolescent motherhood. East Mediterr Health J. https://doi.org/10.26719/emhj.23.074 Received: 16/8/2022; Accepted: 22/12/2022
Copyright: © Authors; licensee World Health Organization. EMHJ is an open access journal. All papers published in EMHJ are available under the Creative Commons Attribution Non-Commercial ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo).
Introduction
Adolescent pregnancy can result in lifetime health disparities for mothers and their children. Compared with nonadolescent mothers, adolescent mothers are more likely to have lower educational level, less financial independence, worse mental health, and less social support (1–4). All these factors may contribute to the high prevalence of malnutrition in adolescent mothers (5). Globally, 13% of all births are given by women aged 15–19 years in emerging countries (6). In Turkey, the adolescent pregnancy rate was 10.2% in 1993 but it decreased to 4% by 2018 (7). Although the rate of adolescent pregnancy has decreased over the years, it is still important when the resultant health and social problems are considered.
The most important indicator of chronic malnutrition in children is stunting (8). In the last 20 years, although there has been a decrease globally in stunting in children aged < 5 years, differences between regions and within countries remain (9,10). In Turkey, the rate of stunting in children aged 20 million births per year (12). In Turkey, 12% of live births are low birthweight (7). Socioeconomic factors, maternal age, maternal education, maternal body mass index, and antenatal care and nutrition are risk factors for low birthweight (3, 4, 13, 14). As expected, adolescent mothers are at higher risk of adverse birth outcomes, such as premature birth and low birthweight, because they usually have worse antenatal care and conditions (4, 15, 16).
Although there are data on the socioeconomic vulnerabilities and health risks of adolescent mothers in Turkey, it is unclear what effect adolescent motherhood has on negative birth outcomes and stunting. We used the national data from the 2018 Turkey Demographic and Health Survey to: (1) compare the frequency of negative birth outcomes (low birthweight, preterm birth, and term low birthweight) and stunting in children aged < 5 years of adolescent and nonadolescent mothers; and (2) investigate the sociodemographic factors affecting negative birth outcomes and stunting in children of adolescent and nonadolescent mothers.
Methods
Study design, participants and measurements
This study used secondary data analysis of the 2018 Turkey Demographic and Health Survey that focused on adolescent and nonadolescent mothers aged 15–49 years and their children aged 0–5 years. The survey was a nationally representative cross-section that was conducted by Hacettepe University Institute of Population Studies every 5 years since 1993 to monitor population health and maternal and child health indicators. The purpose of the survey was to gather data at the household level to formulate national indicators related to demographics, fertility, child mortality, maternal health, and nutritional status of women and children. The survey data are used by public institutions, especially the Ministry of Health, for the planning of health services (17).
For the main data of the 2018 Turkey Demographic and Health Survey, a weighted, multistage, stratified cluster sampling approach was used. Two questionnaires for households and individuals were used to collect data by face-to-face interview. Out of 9056 women aged 15–49 years in these households, 7346 (81.1%) were interviewed. The sampling design details and the results of the main data of the study were reported in the 2018 Turkey Demographic and Health Survey Analysis and Report (7).
We used the individual questionnaire dataset to analyse 2755 women aged 15–49 years who had a live birth up to 5 years before the questionnaire was administered. There were no available data for the birthweight and date of birth of 117 children, or for the height of 653 children. Identification of the secondary dataset and the inclusion and exclusion criteria for the study are shown in Figure 1.
The dependent variables were having a child in the past 5 years with negative birth outcomes (low birthweight, preterm birth, and term low birthweight) and stunting. Stunting was defined using the 2006 WHO growth standard reference point based on z score ≤ 2 standard deviations (18). Negative birth outcomes were: (1) low birthweight, < 2500 g at birth; (2) preterm, born before 37 weeks’ gestation; and (3) term low birthweight, born at ≥ 37 weeks’ gestation and < 2500 g at birth.
Maternal age was the main independent variable and was categorized as adolescent (15–19 years) and nonadolescent (20–29, 30–39, and 40–49 years). Maternal educational level was defined as no education, primary, secondary, and high school, and while evaluating the variable, the secondary and high school categories were combined. Welfare status was categorized as richest, richer, middle, poorer, and poorest according to wealth index, and evaluated by combining them into 3 groups as rich (richest and richer), middle, and poor (poorer and poorest). The country data were divided into 5 regions of west, south, central, north, and east. The residential area was considered as urban or rural. The gender of the child was categorized as male or female. For the stunting dependent variable, children’s age was evaluated monthly and categorized into 3 groups (0–11, 12–23, and 24–59 months). Antenatal visits were categorized as yes (mother attended ≥ 4 visits) or no (mother did not attend ≥ 4 visits or did not know the answer). The variables used in this study were categorized according to the Demographic and Health Surveys guidelines (19).
Ethical considerations
The 2018 Turkey Demographic and Health Survey was evaluated and approved by Hacettepe University Ethics Commission. The researchers obtained permission on 2 December 2021 from Hacettepe University Institute of Population Studies to use the data.
Data analysis
Results
In the study group of 2755 mothers, 189 (6.8%) were adolescent. Table 1 shows the sociodemographic characteristics of adolescent and nonadolescent mothers. Eighty-two (43.4%) adolescent mothers had secondary or higher education compared with 1309 (51.0%) nonadolescent mothers. One hundred and twenty-five (66.1%) adolescent mothers and 1233 (48.1%) nonadolescent mothers were poorer or poorest. Sixty-six (34.9%) adolescent and 768 (29.9%) nonadolescent mothers lived in rural areas. One hundred and six (56.0%) adolescent and 218 (28.1%) nonadolescent mothers had not received adequate antenatal care. There were significant differences between adolescent and nonadolescent mothers in terms of educational level, welfare status, and antenatal care during pregnancy (P < 0.05).
Table 2 compares the rates of negative birth outcomes and the indicators of chronic malnutrition according to maternal age (adolescent/nonadolescent category). There were 2638 negative birth outcomes: 338 (12.8%) low birthweight, 405 (15.4%) preterm birth, and 205 (7.8%) term low birthweight. In addition, 116 (5.5%) children were stunted. The rate of low birthweight was 14.8% in adolescent mothers and 12.7% in nonadolescent mothers. Preterm birth rate was similar for the 2 groups. The rate of delivering a term low birthweight infant was 11.8% in adolescent mothers and 7.5% in nonadolescent mothers, and this difference was significant (P < 0.05). Stunting, which is an indicator of chronic malnutrition in children aged < 5 years, was seen in 8.7% of children of adolescent mothers and 5.2% of children of nonadolescent mothers, and this difference was significant (P < 0.05).
Table 3 shows the factors associated with term low birthweight in a sample of 2638 women who gave birth in the past 5 years. Adolescent motherhood was evaluated as the main independent variable. Term low birthweight, which was significantly different in the children of adolescent and nonadolescent mothers, lost significance in the adjusted analysis (AOR 1.50, 95% CI: 0.90–2.49). Multivariate analysis showed that lack of maternal education (AOR 1.75, 95% CI: 1.22–2.50), poverty (AOR 2.09, 95% CI: 1.44–3.02), and living in eastern Turkey (AOR 1.39, 95% CI: 1.01–1.92) increased the risk of term low birthweight.
Multivariate analysis of the factors associated with stunting in 2102 women who gave birth in the last 5 years is shown in Table 4. Adolescent motherhood was evaluated as the main independent variable. There was a significant difference in child stunting between adolescent and nonadolescent mothers but after adjustment, there was no significance (AOR 0.77, 95% CI: 0.36–1.64). The risk of being stunted was 2.22 times higher (95% CI: 1.47–3.50) in the poorest/poorer group compared with other socioeconomic status. Children born with low birthweight were 2.86 times more likely to be stunted than children born with normal birthweight (95% CI: 1.90–4.30). The risk of stunting was increased 1.69 times (95% CI: 1.12–2.53) in children aged 12–23 months compared with 0–11 months, and 1.65 times (95% CI: 1.20–2.65) in children aged 24–59 months.
Discussion
We evaluated the sociodemographic characteristics of adolescent and nonadolescent mothers, negative birth outcomes, and frequency of stunting of their children in Turkey using data from the 2018 Turkey Demographic and Health Survey. We also investigated the risk factors associated with term low birthweight and stunting. We found that adolescent mothers had lower educational level, were poorer, and did not receive adequate antenatal care compared with nonadolescent mothers. Although term low birthweight and stunting were risk factors in children of adolescent compared with nonadolescent mothers, they were no longer significant when adjusted for socioeconomic variables. This indicates that if socioeconomic status of adolescent mothers is improved, their risk of negative birth outcomes and stunting will be reduced. Our results could be explained by women with good socioeconomic status not becoming pregnant during adolescence. However, some studies have reported that young maternal age is not the sole reason for negative birth outcomes, and other factors such as emotional response, coping skills, and social resources may be involved (20, 21). If adolescent pregnancies are well planned and there is adequate prenatal care, they will cease to be high risk (22).
Low maternal educational level was a risk factor for term low birthweight in multivariate analysis, which is consistent with previous studies (23, 24). Term low birthweight was higher in the poorest households and in eastern Turkey, which is less well developed than western Turkey. The significant association between low socioeconomic status and low birthweight that was shown in this study was also found in other studies (25, 26). Low socioeconomic and educational statuses lead to low health consciousness and low nutritional status, which can increase the risk of low birthweight. There is considerable variation in the prevalence of low birthweight across regions and within countries; however, most occurs in low- and middle-income countries and especially in the most vulnerable populations in these countries.
Multivariate analysis showed that being poorer was a risk factor for stunting. Similarly, in the National Family Health Survey of India, stunting was more common in those living in poorer rural areas (27). These findings were similar to a study conducted in the United Republic of Tanzania and indicated that children in lower socioeconomic groups had a greater risk of stunting compared with those in higher socioeconomic groups (28). Several other studies have found that household socioeconomic status is a prominent predictor of child stunting (29, 30). The availability of high-quality foods and affordability of nutrient-rich foods affect a family’s ability to provide a healthy diet and prevent child stunting. Higher household income enables more to be spent on food and child care (12). This is in line with the suggestion that households with larger income, as a proxy for household wealth, have more money to spend on child nutrition, which lowers the prevalence of stunting (31).
Our large sample data from the 2018 Turkey Demographic and Health Survey indicated that economic status was the main risk factor for negative birth outcomes and stunting. Special attention must be paid to individuals who have low educational levels, low income, and live in eastern Turkey. To improve child health, we suggest that it is more important to improve education and reduce inter-regional poverty rather than trying to reduce adolescent pregnancies. These results support the idea that macroenvironmental factors have a marked impact on maternal and child health.
In our multivariate analysis, being older than 2 years was a risk factor for stunting. Children’s age in months had a nonlinear, upward-sloping effect on the probability of stunting. Therefore, children tend to be more stunted as they age, although this effect diminishes over time (31). Stunting was more common in children older than 18 months in the National Family Health Survey of India, and children aged < 24 years had a higher risk of stunting in Rwanda (27, 32). The results are consistent with the theory that worsening intrauterine conditions, as measured by birth size and other factors, increase the likelihood of stunting (31). The fact that the risk of stunting increases with age indicates that chronic malnutrition is becoming severe.
Our study had some limitations. Firstly, there were some missing data, such as age at which the children ceased breastfeeding, accompanied by many confounding factors, maternal body mass index, and maternal birth weight. Secondly, the main data in the 2108 Turkey Demographic and Health Survey were collected 4 years ago. Finally, the lack of anthropological data for all children led to a reduction in the sample size. Regardless of the limitations, it was possible to identify the risk factors for stunting and term low birthweight in the eastern and western provinces of Turkey, after multivariate linear regression analysis or adjustment for all missing confounders.
Conclusion
This study adds to the limited research examining the association between adolescent pregnancy and adverse birth outcomes and stunting in Turkey. Our results suggest that it would be more beneficial to make changes at the macroenvironmental level to reduce low birthweight and stunting. The social role of women living in eastern Turkey is perhaps the root cause of these health inequalities. Strengthening the position of women in society will prevent adolescent pregnancies and contribute to the prevention of other health inequalities. Our results emphasize the necessity of planning maternal and child health services by considering the educational level of women, income inequalities, and even regional inequalities, while defining the risk factors related to adolescent pregnancy.
References
1. Boden JM, Fergusson DM, John Horwood L. Early motherhood and subsequent life outcomes. J Child Psychol Psychiatry. 2008 Feb;49(2):151–60. https://doi.org/10.1111/j.1469-7610.2007.01830.x PMID:18093114
2. Norris S, Norris ML, Sibbald E, Aubry T, Harrison ME, Lafontaine G et al. Demographic characteristics associated with pregnant and postpartum youth referred for mental health services in a community outreach center. J Can Acad Child Adolesc Psychiatry. 2016 Fall;25(3):152–8. PMID:27924145
3. Le Roux K, Christodoulou J, Stansert-Katzen L, Dippenaar E, Laurenzi C, M. le Roux I et al. A longitudinal cohort study of rural adolescent vs adult South African mothers and their children from birth to 24 months. BMC Pregnancy Childbirth. 2019; 19(24):1–8. https://doi.org/10.1186/s12884-018-2164-8
4. Banke-Thomas OE, Banke-Thomas AO, Ameh CA. Factors influencing utilisation of maternal health services by adolescent mothers in low-and middle-income countries: a systematic review. BMC Pregnancy Childbirth. 2017;17(65):1–14. https://doi.org/10.1186/s12884-017-1246-3
5. Olodu MD, Adeyemi AG, Olowookere SA, Esimai OA. Nutritional status of under-five children born to teenage mothers in an urban setting, south-western Nigeria. BMC Res Notes. 2019 Mar 4;12(1):116. https://doi.org/10.1186/s13104-019-4147-x PMID:30832719
6. Darroch JE, Woog V, Bankole A. Adding it up: costs and benefits of meeting the contraceptive needs of adolescents. New York: Guttmacher Institute, 2016 (https://www.guttmacher.org/report/adding-it-meeting-contraceptive-needs-of-adolescents, accessed 15 April 2023).
7. Turkey Demographic and Health Survey 2018. Ankara: Hacettepe University Institute of Population Studies, T.R. Presidency of Turkey Directorate of Strategy and Budget, and TÜBITAK; 2019 ( https://fs.hacettepe.edu.tr/hips/dosyalar/Ara%C5%9Ft%C4%B1rmalar%20-%20raporlar/2018%20TNSA/TDHS2018_mainReport_compressed.pdf, accessed 15 April 2023).
8. Stunting in a nutshell [website]. Geneva: World Health Organization; 2015 (https://www.who.int/news/item/19-11-2015-stunting-in-a-nutshell, accessed 15 April 2023).
9. Joint child malnutrition estimates [website]. Geneva: World Health Organization (https://www.who.int/data/gho/data/themes/topics/joint-child-malnutrition-estimates-unicef-who-wb, accessed 15 April 2023).
10. Malnutrition in children [website]. UNICEF (https://data.unicef.org/topic/nutrition/malnutrition/, accessed 15 April 2023).
11. Ndemwa M, Wanyua S, Kaneko S, Karama M, Anselimo M. Nutritional status and association of demographic characteristics with malnutrition among children less than 24 months in Kwale County, Kenya. Pan Afr Med J. 2017 Nov;28:265. https://doi.org/10.11604/pamj.2017.28.265.12703 PMID:29881508
12. Global nutrition targets 2025: low birth weight policy brief. Geneva: World Health Organization; 2014 (https://apps.who.int/iris/handle/10665/149020, accessed 15 April 2023).
13. Mumbare SS, Maindarkar G, Darade R. Maternal risk factors associated with term low birth weight neonates: a matched-pair case control study. Indian Pediatr. 2012 Jan;49(1):25-28. https://doi.org/10.1007/s13312-012-0010-z PMID:21719926
14. Nabugoomu J, Seruwagi GK, Corbett K, Kanyesigye E, Horton S, Hanning R. Needs and barriers of teen mothers in rural Eastern Uganda: stakeholders’ perceptions regarding maternal/child nutrition and health. Int J Environ Res Public Health. 2018 Dec 7;15(12):2776. https://doi.org/10.3390/ijerph15122776 PMID:30544550
15. Amjad S, MacDonald I, Chambers T, Osornio‐Vargas A, Chandra S, Voaklander D et al. Social determinants of health and adverse maternal and birth outcomes in adolescent pregnancies: a systematic review and meta-analysis. Paediatr Perinat Epidemiol. 2019 Jan;33(1):88-99. https://doi.org/10.1111/ppe.12529 PMID:30516287
16. Chen XK, Wen SW, Fleming N, Demissie K, Rhoads GG, Walker M. Teenage pregnancy and adverse birth outcomes: a large population based retrospective cohort study. Int J Epidemiol. 2007 Apr;36(2):368–73. https://doi.org/10.1093/ije/dyl284 PMID:17213208
17. Turkey Demographic and Health Survey 2018 – final report. Ankara: Hacettepe University Institute of Population Studies, T.R. Presidency of Turkey Directorate of Strategy and Budget, and TÜBITAK; 2019 (https://dhsprogram.com/publications/publication-FR372-DHS-Final-Reports.cfm, accessed 15 April 2023).
18. WHO child growth standards : training course on child growth assessment. Geneva: World Health Organization; 2008 (https://apps.who.int/iris/handle/10665/43601, accessed 15 April 2023).
19. The DHS Program Demographic and Health Surveys. Available datasets [website]. Rockville, MD, USAID (https://dhsprogram.com/data/available-datasets.cfm, accessed 15 April 2023).
20. Klein JD. American Academy of Pediatrics Committee on Adolescence. Adolescent pregnancy: current trends and issues. Pediatrics. 2005 Jul;116(1):281–6. https://doi.org/ 10.1542/peds.2005-0999 PMID:15995071
21. Aruda MM, Waddicor K, Frese L, Cole JCM, Burke P. Early pregnancy in adolescents: diagnosis, assessment, options counseling, and referral. J Pediatr Health Care. 2010 Jan–Feb;24(1):4–13. https://doi.org/10.1016/j.pedhc.2008.11.003 PMID:20122473
22. Geist RR, Beyth Y, Shashar D, Beller U, Samueloff A. Perinatal outcome of teenage pregnancies in a selected group of patients. J Adolesc Gynecol. 2006 Jun;19(3):189–93. https://doi.org/10.1016/j.jpag.2006.02.005 PMID:16731412
23. Jafari F, Eftekhar H, Pourreza A, Mousavi J. Socio-economic and medical determinants of low birth weight in Iran: 20 years after establishment of a primary healthcare network. Public Health. 2010 Mar;124(3):153–8. https://doi.org/10.1016/j.puhe.2010.02.003 PMID:20226486
24. Chen Y, Li G, Ruan Y, Zou L, Wang X, Zhang W. An epidemiological survey on low birth weight infants in China and analysis of outcomes of full-term low birth weight infants. BMC Pregnancy Childbirth. 2013 Dec 26;13:242–50. PMID:24370213
25. Viengsakhone L, Yoshida Y, Harun-Or-Rashid M, Sakamoto J. Factors affecting low birth weight at four central hospitals in vientiane, Lao PDR. Nagoya J Med Sci. 2010 Feb;72(1-2):51-58. https://doi.org/10.1186/1471-2393-13-242 PMID:20229703
26. Sharma M, Kumar D, Huria A, Gupta P. Maternal risk factors of low birth weight in Chandigarh India. Internet J Health. 2008;9(1):1–4. https://doi.org/10.5580/10f1
27. National Family Health Survey (NFHS-3) 2005–06 India. Volume 1. Mumbai: International Institute of Population Sciences; 2007 (https://dhsprogram.com/pubs/pdf/frind3/frind3-vol1andvol2.pdf, accessed 15 April 2023).
28. Mtongwa RH, Festo C, Elisaria E. A comparative analysis of determinants of low birth weight and stunting among under five children of adolescent and non-adolescent mothers using 2015/16 Tanzania Demographic and Health Survey (TDHS). BMC Nutr. 2021 Nov 4;7(1):1–10. https://doi.org/10.1186/s40795-021-00468-6 PMID:34732260
29. Bukusuba J, Kaaya AN, Atukwase A. Predictors of stunting in Children Aged 6 to 59 months: a case-control study in Southwest Uganda. Food Nutr Bull. 2017 Dec;38(4):542–53. https://doi.org/10.1177/0379572117731666 PMID:28978233
30. Wamani H, Astrøm AN, Peterson S, Tumwine JK, Tylleskär T. Boys are more stunted than girls in sub-Saharan Africa: a meta-analysis of 16 demographic and health surveys. BMC Pediatr. 2007 Apr 10;7:17). https://doi.org/10.1186/1471-2431-7-17 PMID:17425787
31. Van Der Knaap I, The determinants of sex differences in child stunting in Sub Saharan Africa: a multilevel logistic regression analysis [thesis]. Nijmegen: Radboud University; 2018.
32. Habimana S, Biracyaza E. Risk factors of stunting among children under 5 years of age in the eastern and western provinces of Rwanda: analysis of Rwanda Demographic and Health Survey 2014/2015. Pediatric Health Med Ther. 2019 Oct 25;10:115–30. https://doi.org/10.2147/PHMT.S222198 PMID:31695558
Table 1. Sociodemographic characteristics of adolescent and nonadolescent mothers (N= 2755)
|
Sociodemographic characteristics |
Adolescent mother, n (%) |
Nonadolescent mother, n (%) |
Total n (%) |
P |
|
Educational level None Primary Secondary or higher |
27 (14.3) 80 (42.3) 82 (43.4) |
437 (17.0) 820 (32.0) 1309 (51.0) |
464 (16.8) 900 (32.7) 1391 (50.5) |
0.01 |
|
Welfare status Poorest/poorer Middle Richer/richest |
125 (66.1) 34 (18.0) 30 (15.9) |
1233 (48.1) 507 (19.8) 826 (32.1) |
1358 (49.3) 541 (19.6) 856 (31.1) |
<0.01 |
|
Region West South Central North East |
45 (23.8) 32 (16.9) 34 (18.0) 12 (6.3) 66 (34.9) |
646 (25.2) 348 (13.6) 437 (17.0) 233 (9.1) 902 (35.2) |
691 (25.1) 380 (13.8) 471 (17.1) 245 (8.9) 968 (35.1 ) |
0.53 |
|
Residential area Urban Rural |
123 (65.1) 66 (34.9) |
1798 (70.1) 768 (29.9) |
1921 (69.7) 834 (30.3) |
0.08 |
|
Antenatal visit (≥ 4 visits)a Yes No |
83 (43.9) 106 (56.1) |
1844 (71.9) 218 (28.1) |
1927 (85.6) 324 (14.4) |
<0.01 |
|
aSome missing data. |
||||
Table 2. Number and percentage distribution of negative birth outcomes and stunting of children by maternal age
|
|
Adolescent mother, n (%) |
Non |
Total n (%) |
P |
|
Negative birth outcomes (N = 2638: 169 adolescent and 2469 nonadolescent mothers) |
||||
|
Low birthweight |
25 (14.8) |
313 (12.7) |
338 (12.8) |
0.24 |
|
Preterm birth |
28 (1 |
377 (15.3 |
405 (1 |
0.51 |
|
Term low birthweight |
20 (11.8) |
185 (7.5) |
205 (7.8) |
0.04 |
|
Chronic malnutrition (N = 2102: 138 adolescent and 1964 nonadolescent mothers) |
||||
|
Stunting |
12 (8.7) |
104 (5.3 |
116 (5.5) |
0.03 |
Table 3. Logistic regression results for the factors associated with term low birthweight
|
|
|
N |
n (%) |
Crude OR |
95% CI |
P |
AOR |
95% CI |
P |
||
|
Maternal age, yr |
15–19 |
169 |
20 (11.8) |
1.65 |
1.01 |
2.70 |
0.04 |
1.50 |
0.90 |
2.49 |
0.11 |
|
20–49 (ref) |
2469 |
185 (7.5) |
|
|
|
|
|
|
|
|
|
|
Educational level |
None |
407 |
64 (15.7) |
2.76 |
2.01 |
3.79 |
<0.01 |
1.75 |
1.22 |
2.50 |
0.02 |
|
Primary |
856 |
70 (8.2) |
1.08 |
0.80 |
1.46 |
0.5 |
|
|
|
|
|
|
Secondary and higher (ref) |
1375 |
71 (5.2) |
|
|
|
|
|
|
|
|
|
|
Welfare status
|
Poorest/poorer |
1262 |
145 (11.5) |
2.84 |
2.08 |
3.88 |
<0.01 |
2.09 |
1.44 |
3.02 |
<0.01 |
|
Middle |
531 |
34 (6.4) |
0.77 |
0.52 |
1.13 |
0.18 |
|
|
|
|
|
|
Rich/richest (ref) |
845 |
26 (3.1) |
|
|
|
|
|
|
|
|
|
|
Region |
West (ref) |
673 |
10 (4.5) |
|
|
|
|
|
|
|
|
|
South |
368 |
31 (8.4) |
1.10 |
0.74 |
1.65 |
0.61 |
|
|
|
|
|
|
Central |
464 |
22 (4.7) |
0.54 |
0.34 |
1.15 |
0.08 |
|
|
|
|
|
|
North |
241 |
11 (4.6) |
0.54 |
0.29 |
1.01 |
0.05 |
|
|
|
|
|
|
East |
892 |
104 (11.7) |
2.15 |
1.61 |
2.86 |
<0.01 |
1.39 |
1.01 |
1.92 |
0.04 |
|
|
Residential area |
Urban (ref) |
1856 |
126 (6.8) |
|
|
|
|
|
|
|
|
|
Rural |
782 |
79 (10.1) |
1.54 |
1.14 |
2.07 |
0.004 |
0.96 |
0.69 |
1.33 |
0.83 |
|
|
Antenatal visit |
Yes (ref) |
1886 |
125 (6.6) |
|
|
|
|
|
|
|
|
|
No |
752 |
80 (10.6) |
2.04 |
1.30 |
3.20 |
0.001 |
1.21 |
0.89 |
1.65 |
0.21 |
|
|
Child sex |
Male (ref) |
1335 |
92 (6.9) |
|
|
|
|
|
|
|
|
|
Female |
1303 |
113 (8.7) |
1.28 |
0.96 |
1.70 |
0.08 |
|
|
|
|
|
AOR = adjusted odds ratio; CI = confidence interval.
Table 4. Logistic regression results for the factors associated with stunting
|
|
|
N |
n (%) |
Crude OR |
95% CI |
P |
AOR |
95% CI |
P |
||
|
Maternal age, yr |
15–19 |
138 |
12 (8.7) |
1.23 |
1.02 |
2.60 |
0.03 |
0.77 |
0.36 |
1.64 |
0.50 |
|
20–49 (ref) |
1964 |
104 (5.2) |
|
|
|
|
|
|
|
|
|
|
Educational level |
None |
350 |
42 (12.0) |
1.94 |
1.33 |
2.82 |
<0.01 |
1.01 |
0.63 |
1.61 |
0.96 |
|
Primary |
706 |
52 (7.4) |
0.97 |
0.69 |
1.38 |
0.08 |
|
|
|
|
|
|
Secondary and higher (ref) |
1046 |
63 (6.0) |
|
|
|
|
|
|
|
|
|
|
Welfare status |
Poorest/poorer |
1070 |
114 (10.7) |
2.74 |
1.91 |
3.93 |
<0.01 |
2.22 |
1.47 |
3.50 |
<0.01 |
|
Middle |
405 |
21 (5.2) |
0.62 |
0.39 |
1.07 |
0.06 |
|
|
|
|
|
|
Rich/richest (ref) |
627 |
22 (3.5) |
|
|
|
|
|
|
|
|
|
|
Region |
West (ref) |
528 |
26 (4.9) |
|
|
|
|
|
|
|
|
|
South |
308 |
24 (7.8) |
1.05 |
0.67 |
1.65 |
0.81 |
|
|
|
|
|
|
Central |
343 |
20 (5.8) |
0.73 |
0.45 |
1.19 |
0.20 |
|
|
|
|
|
|
North |
208 |
16 (7.7) |
1.03 |
0.60 |
1.77 |
0.89 |
|
|
|
|
|
|
East |
715 |
71 (9.9) |
1.66 |
1.20 |
2.31 |
0.02 |
1.08 |
0.73 |
1.60 |
0.68 |
|
|
Residential area |
Urban (ref) |
1461 |
95 (6.5) |
|
|
|
|
|
|
|
|
|
Rural |
641 |
62 (9.7) |
1.54 |
1.10 |
2.15 |
0.01 |
0.99 |
0.67 |
1.48 |
0.99 |
|
|
Birthweight |
<2500 |
248 |
38 (15.3) |
3.01 |
2.01 |
4.48 |
<0.01 |
2.86 |
1.90 |
4.30 |
<0.01 |
|
≥2500 (ref) |
1781 |
101 (5.7) |
|
|
|
|
|
|
|
|
|
|
Child sex |
Male |
1072 |
82 (7.6) |
|
|
|
|
|
|
|
|
|
Female (ref) |
1030 |
75 (7.3) |
0.94 |
0.68 |
1.31 |
0.74 |
|
|
|
|
|
|
Child age, mo |
0–11 (ref) |
401 |
14 (3.5) |
|
|
|
|
|
|
|
|
|
12–23 |
380 |
39 (10.3) |
1.55 |
1.06 |
2.27 |
0.02 |
1.69 |
1.12 |
2.53 |
0.01 |
|
|
24–59 |
1321 |
104 (7.9) |
1.17 |
1.11 |
1.65 |
0.03 |
1.65 |
1.20 |
2.65 |
0.02 |
|
AOR = adjusted odds ratio; CI = confidence interval.
Figure 1. Identification of secondary dataset.
