https://orcid.org/0000-0001-6812-1659
Figures
Abstract
Background
The World Health Organization recommended a minimum of 33 months between consecutive live births to reduce the incidence of adverse pregnancy outcomes. Poorly spaced pregnancies are associated with poor maternal and child health outcomes such as low birth weight, stillbirth, uterine rupture, neonatal mortality, maternal mortality, child malnutrition, and maternal hemorrhage. However, there was limited evidence on the duration of birth interval and its predictors among reproductive-age women in Ethiopia. Therefore, this study aimed to investigate the duration of birth interval and its predictors among reproductive-age women in Ethiopia.
Methods
A secondary data analysis was conducted based on the 2016 Ethiopian Demographic and Health Survey data. A total weighted sample of 11022 reproductive-age women who gave birth within five years preceding the survey was included for analysis. To identify the predictors, the Gompertz gamma shared frailty model was fitted. The theta value, Akakie Information Criteria (AIC), Bayesian Information Criteria (BIC), and deviance was used for model selection. Variables with a p-value of less than 0.2 in the bi-variable analysis were considered for the multivariable analysis. In the multivariable Gompertz gamma shared frailty analysis, the Adjusted Hazard Ratio (AHR) with a 95% Confidence Interval (CI) was reported to show the strength and statistical significance of the association.
Results
The median inter-birth interval in Ethiopia was 38 months (95% CI: 37.58, 38.42). Being living in Addis Ababa (AHR = 0.15, 95% CI: 0.03, 0.70), being rural resident (AHR = 1.13, 95% CI: 1.01, 1.23), being Muslim religious follower (AHR = 6.53, 95% CI: 2.35, 18.18), having three birth (AHR = 0.51, 95% CI: 0.10, 0.83), having four birth (AHR = 0.30, 95% CI: 0.09, 0.74), five and above births (AHR = 0.10, 95% CI: 0.02, 0.41), and using contraceptive (AHR = 2.35, 95% CI: 1.16, 4.77) were found significant predictors of duration of birth interval.
Conclusion
The length of the inter-birth interval was consistent with the World Health Organization recommendation. Therefore, health care interventions that enhance modern contraceptive utilization among women in rural areas and Muslim religious followers would be helpful to optimize birth interval.
Citation: Tesema GA, Worku MG, Teshale AB (2021) Duration of birth interval and its predictors among reproductive-age women in Ethiopia: Gompertz gamma shared frailty modeling. PLoS ONE 16(2): e0247091. https://doi.org/10.1371/journal.pone.0247091
Editor: Frank T. Spradley, University of Mississippi Medical Center, UNITED STATES
Received: October 11, 2020; Accepted: January 2, 2021; Published: February 19, 2021
Copyright: © 2021 Tesema et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data used in this study are from the Measure DHS program (www.dhsprogram.com) and can be accessed following the protocol outlined in the Methods section.
Funding: The author(s) received no specific funding for this work
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: AHR, Adjusted Hazard Ratio; AIC, Akaike Information Criteria; BIC, Bayesian Information Criteria; CI, Confidence Interval; CHR, Crude Hazard Ratio; EAs, Enumeration Areas; EDHS, Ethiopian Demographic and Health Survey; IUGR, Intrauterine Growth Restriction; SSA, Sub-Saharan Africa; WHO, World Health Organization
Background
The World Health Organization (WHO) defines the inter-birth interval as the time elapsed between two consecutive live births [1]. The WHO recommends a minimum of 33 months between two successive live births to optimize maternal and newborn health [2, 3]. The short birth interval is defined as the period between birth to successive pregnancy less than 24 months or an inter-birth interval of fewer than 33 months [4]. Like many sub-Saharan African countries, Ethiopia is one of the countries with a high fertility rate (4.3). Which is the second-most populous country in Africa with a population of 114,963,588 [5]. Inter-birth interval has a significant impact on the country’s population size and maternal and child health [6, 7].
A short birth interval is responsible for the huge number of maternal and perinatal mortality in low-and middle-income countries [8]. Globally, an estimated 2.6 million stillbirths occur annually [9]. Of which, 67% of the global stillbirth occurred in Sub-Saharan Africa including Ethiopia [10], and most of the stillbirths occur during the intrapartum period that can be preventable by optimizing birth interval [11, 12]. Very short (less than 18–27 months) and very long (typically over 54–59 months) birth intervals are associated with poor health outcomes for both mothers and babies [2]. Previous literature evidenced that both shorter and longer birth intervals have been associated with poor pregnancy outcomes such as low birth weight, Intra-Uterine Growth Restriction (IUGR), prenatal death, Antepartum Hemorrhage (APH), neonatal and maternal mortality [13, 14]. Besides, it imposes a huge financial burden, mental, and psychological consequences to the mothers and the family [4].
Studies on birth interval showed that household wealth status [15], residence [15], husband education [16], maternal education [17, 18], contraceptive use [19, 20], media exposure [21], women health care decision making autonomy [22], religion [23, 24], maternal occupation [15], breastfeeding duration [23], parity [24], and maternal age [25] were significant predictors of birth interval.
Though optimal birth spacing is strongly linked to better health outcomes for both mothers and babies [26], more than half of women in Ethiopia have shorter birth intervals [15]. However, there is limited evidence on the duration of birth interval and its predictors among reproductive-age women in Ethiopia. Therefore, this study aimed to investigate the duration of birth intervals and its predictors among reproductive-age women in Ethiopia. Thus, this study findings would help to work on factors to optimize birth spacing.
Methods
Data source and sampling procedure
This research was performed based on data from the 2016 Ethiopian Demographic and Health Survey (EDHS). The 2016 EDHS was the fourth survey conducted every five years in Ethiopia. It is mainly aimed at producing updated indicators related to health and health. Situated in the Horn of Africa, Ethiopia is the second-most populous country in Africa, next to Nigeria, with a fertility rate of 4.3, it has a total population of 114,963, 588. Nine regional states (Afar, Amhara, Benishangul-Gumuz, Gambella, Harari, Oromia, Somali, Southern Nations, Nationalities and People’s Region (SNNPR) and Tigray) and two administrative cities (Addis Ababa and Dire-Dawa) constitute the country. A two-stage cluster sampling technique was employed to select the study participants for EDHS 2016. In the first stage, 645 enumeration areas (EAs) (202 in urban areas) were selected with a probability proportional to the size of the EA, while in the second stage, an average of 28 households was systematically selected for each EA. All reproductive-age women who gave birth within five years preceding the survey in the selected enumeration areas were the study population. A total weighted sample of 11022 women who gave birth within five years preceding the survey was included for this study. The detailed methodological procedure was presented in the full EDHS 2016 report [27].
Measurement of variables
The birth interval was defined as the duration of months between the birth of the index child and the subsequent live birth. The event was defined as the occurrence of live birth after the index child, while women who did not give birth until the end of the follow-up period were considered as censored. The event was recorded as success "if a woman gave live birth after the index child” or failure “if a woman did not give birth until the end of the follow-up period). The independent variables considered for this study were categorized as socio-demographic and economic variables such as residence, region, religion, maternal education, maternal age, husband education, maternal occupation, sex of household head, media exposure, and wealth status, and maternal obstetric and health services related factors such as parity, women health care decision making autonomy, distance to the health facility, and contraceptive use (Table 1).
Data management and analysis
The weighted data were used for the overall analysis to take into account the sampling design to get reliable statistical estimates. Descriptive and summary statistics were conducted using STATA version 14 software. The EDHS data violates the independence of observations and equal variance assumptions since women within the same cluster might share similar characteristics than women in another cluster.
As this study considered time to event data, survival analysis was considered. The Kaplan-Meier (K-M) and the log-rank test were done to compare the survival curves across categories of different explanatory variables.
Cox proportional hazard model was fitted to identify the predictors of birth interval. The Proportional Hazard (PH) assumption was assessed using the global Schoenfeld residual test., and the PH assumption was violated (Table 2). Therefore, parametric survival models should be fitted to get a reliable estimate. Because the EDHS data structure was hierarchical, we have checked whether there is clustering or not by running the frailty model (random effect survival model) and the theta was significant at the null model (θ = 0.24, 95% CI: 0.19, 0.30) (LR test of theta = 0: X2 = 226.36, p < 0.001) it indicates that there was unobserved heterogeneity or shared frailty, that means women in one cluster were more likely to be correlated within the same cluster.
Shared frailty model with baseline distributions (Weibull, Gompertz, Exponential, log-logistic, and lognormal) and frailty distributions (gamma and inverse Gaussian) were modeled by taking EAs/clusters as a random effect. Gompertz gamma shared frailty model was the best-fitted model since it had the highest values of log-likelihood and AIC. Variable with a p-value less than 0.20 in the bivariable Gompertz gamma shared frailty analysis was included in the multivariable analysis. In the multivariable Gompertz gamma shared frailty analysis, the Adjusted Hazard Ratio (AHR) with 95% Confidence Interval (CI) were reported to declare the strength and significance of the association between birth interval and independent variables.
Result
Socio-demographic and economic characteristics of the respondent
A total of 11022 reproductive-age women were included in the study. Of these, 4851 (44.0%) were from the Oromia region and 9807 (89.0%) were rural residents. Nearly one-third (30.4%) of women were aged 25–29 years. The majority (66.1%) of the mothers did not have formal education whereas 37.3% of their husbands attained a primary level of education (Table 3).
Maternal obstetric and maternal health services related characteristics
Of the total, 4752 (43.1%) of the mothers had five and above births. About 6676 (60.6%) were perceived distance to a health facility as a big problem. More than half (62.3%) of the mothers made health care decisions jointly with her husband and 31.3% of the women using one of the modern contraceptives (Table 4).
Predictors of birth interval
The median duration of birth interval in Ethiopia was 38 months (95% CI: 37.58, 38.42). The log-rank test found that residence, maternal education, husband education, maternal occupation, husband occupation, religion, parity, contraceptive use, health care access problem, health care decision making autonomy, wealth status, and sex of household head showed a statistically significant difference in probability of giving birth after the index child (log-rank, p<005) (Table 5). Based on deviance, AIC, BIC, and theta value, the shared frailty with Gompertz distribution and gamma frailty was the best-fitted model for the data (Table 6).
In the Gompertz gamma shared frailty model; religion, residence, contraceptive use, region, and parity preceding birth interval and birth size were significant predictors of birth interval. Women in Addis Ababa were 85% less likely (AHR = 0.15, 95% CI: 0.03, 0.70) to have subsequent birth compared to women in the Oromia region. Rural resident women were 1.13 times (AHR = 1.13, 95% CI: 1.01, 1,23) more likely to give subsequent birth than urban residents. Muslim and other (protestant and catholic) religious follower women were 6.53 times (AHR = 6.53, 95% CI: 2.35, 18.18) and 4.03 times (AHR = 4.03, 95% CI: 1.40, 11.60) more likely to have subsequent birth compared to orthodox Christian followers, respectively. Women who had three births, fourth births, and five and above births were 49% (AHR = 0.51, 95% CI: 0.10, 0.83), 70% (AHR = 0.30, 95% CI: 0.09, 0.74), and 90% (AHR = 0.10, 95% CI: 0.02, 0.41) less likely to have subsequent birth than women who had two and fewer than two births, respectively. Besides, women who did not use any kind of contraceptive were 2.35 times (AHR = 2.35, 95% CI: 1.16, 4.77) more likely to have subsequent birth compared to contraceptive users (Table 6).
Discussion
In this study, the median birth interval among reproductive age women in Ethiopia was 38 months (95% CI: 37.58, 38.42). This finding was higher than the study findings [28, 29] and WHO recommendations [30]. This could be due to the establishment of health extension workers and the expansion of primary health care units that could increase access to family planning services in Ethiopia [31]. Family planning service utilization such as modern contraceptive use is identified as the key intervention strategy to optimize birth spacing, contraceptive users have long birth interval than non-users. Besides, currently in Ethiopia, several public health programs are working on enhancing women empowerment and maternal education, this could contribute to this difference.
In the Gompertz gamma shared frailty model; residence, region, religion, parity, and contraceptive use were the significant predictors of birth interval. Women living in Addis Ababa were less likely to have subsequent birth as compared to women living in the Oromia region. This could be due to the difference in availability and accessibility of maternal health services such as family planning services and access to health information [32]. In Addis Ababa, women may have a better socioeconomic status and education resulting in better health care knowledge towards reproductive health care services such as family planning use [33]. Besides, women in Addis Ababa are more educated and therefore they understand the health implications of closely spaced birth intervals, this could enhance women to have optimal birth intervals [34].
Women who were Muslim and other (catholic and protestant) religious followers were more likely to have subsequent birth than Orthodox Christian religious followers. It is consistent with studies reported in Netherland [35], Saudi Arabia [36], and Manipur [37], it is mainly related to the difference in community practices across regions [38, 39]. In the Ethiopian context, family planning methods utilization such as modern contraceptive use is poor in Muslims and Protestants religious followers this might be the possible reason for the short interbirth intervals [40]. Besides, evidence suggested that Muslims’ attitude towards family planning use is unfavorable and have a lower approval rate towards contraceptive use [41].
Parity was a significant predictor of birth interval. Women who had three births and above were less likely to have subsequent birth than women who had two birth and less. This is consistent with study findings in Tanzania [6], Bangladesh [4], and Iran [17]. The possible justification may be because mothers who have more than two births may not desire extra children since they face an economic burden to raise their children [42]. Besides, multiparous women are at increased risk of pregnancy-related complications they need to have adequate birth spacing to restore from the previous pregnancy and lactation to get a good pregnancy outcome [43].
Women who were not using contraceptives had a higher hazard of giving subsequent birth compared to women who used contraceptives. It is in line with study findings [15, 19, 44], this could be since contraceptive use is one of the most important factors affecting birth interval, and it’s identified as the key strategy to optimize birth interval [19, 45]. Women who use modern contraceptive space births longer than non-users [20]. The hazard of having subsequent birth among rural residents was higher than women living in urban areas. It is consistent with previous studies [46, 47], the possible explanation might be due to the residential variation in reproductive health care services. Urban women have good access to family planning services than rural residents as many of the health facilities are highly concentrated in urban areas. Besides, urban women are more educated and know the maternal and child health implication of short birth intervals [48].
The result of this study should be interpreted in light of the following limitations. First, the EDHS survey did not incorporate clinically confirmed data rather it relied on mothers’ or caregivers’ reports and might have the possibility of social desirability and recall bias. These might underestimate, overestimate, or reverse the strength of association. Besides, the cross-sectional nature of the study does not allow to infer the temporal relationship between birth interval and the factors. Despite the abovementioned limitations, this study has numerous strengths. First, the study is based on weighted EDHS data that can be generalizable to reproductive-age women in Ethiopia. Moreover, the use of advanced statistical modeling that took into account the nested nature of the DHS data to get reliable standard error and estimate.
Conclusion
Though reproductive health services such as family planning services have expanded, inadequate birth interval remains a major public health care concern in Ethiopia. Place of residence, religion, parity, contraceptive use, and the region were found significant predictors of birth interval. These findings highlight that health programs working on improving maternal health care access such as family planning services should be scaled up to optimize birth interval in rural residents. Besides, health care programs should work in collaboration with religious leaders about modern contraceptive utilization to have adequate birth interval to improve maternal and child health outcomes.
References
- 1. Conde-Agudelo A, Rosas-Bermúdez A, Kafury-Goeta AC: Effects of birth spacing on maternal health: a systematic review. American journal of obstetrics and gynecology 2007, 196(4):297–308. pmid:17403398
- 2. Rutstein SO: Effects of preceding birth intervals on neonatal, infant and under‐five years mortality and nutritional status in developing countries: evidence from the demographic and health surveys. International Journal of Gynecology & Obstetrics 2005, 89:S7–S24. pmid:15820369
- 3. Fotso JC, Cleland J, Mberu B, Mutua M, Elungata P: Birth spacing and child mortality: an analysis of prospective data from the Nairobi urban health and demographic surveillance system. Journal of biosocial science 2013, 45(6):779–798. pmid:22958417
- 4. De Jonge HC, Azad K, Seward N, Kuddus A, Shaha S, Beard J, et al. Determinants and consequences of short birth interval in rural Bangladesh: a cross-sectional study. BMC pregnancy and childbirth 2014, 14(1):427. pmid:25539669
- 5.
Worldometer (www.Worldometers.info) In.; 2020.
- 6. Exavery A, Mrema S, Shamte A, Bietsch K, Mosha D, Mbaruku G, et al. Levels and correlates of non-adherence to WHO recommended inter-birth intervals in Rufiji, Tanzania. BMC pregnancy and childbirth 2012, 12(1):152. pmid:23237623
- 7. Casterline JB, Odden C: Trends in inter-birth intervals in developing countries 1965–2014. Population and Development Review 2016:173–194.
- 8. Kozuki N, Lee AC, Silveira MF, Victora CG, Adair L, Humphrey J, et al. The associations of birth intervals with small-for-gestational-age, preterm, and neonatal and infant mortality: a meta-analysis. BMC public health 2013, 13(S3):S3.
- 9. Lawn JE, Blencowe H, Waiswa P, Amouzou A, Mathers C, Hogan D, et al. Stillbirths: rates, risk factors, and acceleration towards 2030. The Lancet 2016, 387(10018):587–603. pmid:26794078
- 10. Lawn JE, Gravett MG, Nunes TM, Rubens CE, Stanton C: Global report on preterm birth and stillbirth (1 of 7): definitions, description of the burden and opportunities to improve data. BMC pregnancy and childbirth 2010, 10(1):S1. pmid:20233382
- 11. Lawn JE, Blencowe H, Pattinson R, Cousens S, Kumar R, Ibiebele I, et al., Committee LsSSS: Stillbirths: Where? When? Why? How to make the data count? The Lancet 2011, 377(9775):1448–1463. pmid:21496911
- 12. Alkema L, Chou D, Hogan D, Zhang S, Moller A-B, Gemmill A, et al. Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Maternal Mortality Estimation Inter-Agency Group. The Lancet 2016, 387(10017):462–474.
- 13. Conde‐Agudelo A, Rosas‐Bermudez A, Castaño F, Norton MH: Effects of birth spacing on maternal, perinatal, infant, and child health: a systematic review of causal mechanisms. Studies in family planning 2012, 43(2):93–114. pmid:23175949
- 14. Barros FC, Bhutta ZA, Batra M, Hansen TN, Victora CG, Rubens CE, Group GR: Global report on preterm birth and stillbirth (3 of 7): evidence for effectiveness of interventions. BMC pregnancy and childbirth 2010, 10(S1):S3. pmid:20233384
- 15. Yohannes S, Wondafrash M, Abera M, Girma E: Duration and determinants of birth interval among women of child bearing age in Southern Ethiopia. BMC pregnancy and childbirth 2011, 11(1):38. pmid:21599927
- 16. Fallahzadeh H, Farajpour Z, Emam Z: Duration and determinants of birth interval in Yazd, Iran: a population study. Iranian journal of reproductive medicine 2013, 11(5):379. pmid:24639769
- 17. Hajian-Tilaki K, Asnafi N, Aliakbarnia-Omrani F: The patterns and determinants of birth interval in multiparous women in Babol, northern Iran. Southeast Asian journal of tropical medicine and public health 2009, 40(4):852. pmid:19842424
- 18. Whitworth A, Stephenson R: Birth spacing, sibling rivalry and child mortality in India. Social science & medicine 2002, 55(12):2107–2119. pmid:12409124
- 19. Yeakey MP, Muntifering CJ, Ramachandran DV, Myint Y, Creanga AA, Tsui AO: How contraceptive use affects birth intervals: results of a literature review. Studies in family planning 2009, 40(3):205–214. pmid:19852410
- 20. Begna Z, Assegid S, Kassahun W, Gerbaba M: Determinants of inter birth interval among married women living in rural pastoral communities of southern Ethiopia: a case control study. BMC pregnancy and childbirth 2013, 13(1):116. pmid:23688144
- 21. Aychiluhm SB, Tadesse AW, Mare KU, Abdu M, Ketema A: A multilevel analysis of short birth interval and its determinants among reproductive age women in developing regions of Ethiopia. Plos one 2020, 15(8):e0237602. pmid:32845940
- 22. Upadhyay UD, Hindin MJ: Do higher status and more autonomous women have longer birth intervals?: Results from Cebu, Philippines. Social science & medicine 2005, 60(11):2641–2655. pmid:15814188
- 23. Pimentel J, Ansari U, Omer K, Gidado Y, Baba MC, Andersson N, et al. Factors associated with short birth interval in low-and middle-income countries: a systematic review. BMC Pregnancy and Childbirth 2020, 20(1):1–17. pmid:32164598
- 24. De Jonge HC, Azad K, Seward N, Kuddus A, Shaha S, Beard J, et al. Determinants and consequences of short birth interval in rural Bangladesh: a cross-sectional study. BMC pregnancy and childbirth 2014, 14(1):1–7. pmid:25539669
- 25.
Brown W, Ahmed S, Roche N, Sonneveldt E, Darmstadt GL: Impact of family planning programs in reducing high-risk births due to younger and older maternal age, short birth intervals, and high parity. In: Seminars in perinatology: 2015: Elsevier; 2015: 338–344. https://doi.org/10.1053/j.semperi.2015.06.006 pmid:26169538
- 26.
Singh S, Darroch JE: Adding it up: Costs and benefits of contraceptive services. Guttmacher Institute and UNFPA 2012.
- 27.
ICF CSACEa: Ethiopia Demographic and Health Survey 2016 Addis Ababa, Ethiopia, and Rockville, maryland, USA: CSA and ICF 2016.
- 28. Tessema GA, Zeleke BM, Ayele TA: Birth interval and its predictors among married women in Dabat District, Northwest Ethiopia: A retrospective follow up study. African journal of reproductive health 2013, 17(2):39–45. pmid:24069750
- 29.
Yadeta D, Seifadin A: Duration of Birth Interval and Associated Factors among Married Women in Dodota Woreda, Arsi Zone, Ethiopia. Harmaya University; 2016.
- 30.
Marston C: Report of a technical consultation on birth spacing, Geneva, 13–15 June 2005. 2006.
- 31. Olson DJ, Piller A: Ethiopia: an emerging family planning success story. Studies in family planning 2013, 44(4):445–459. pmid:24323662
- 32.
Ababa A: Ethiopia. Abstract available from: https://wfphaconfexcom/wfpha/2012/webprogram/Paper10587html 2013.
- 33. Gordon C, Sabates R, Bond R, Wubshet T: Women’s education and modern contraceptive use in Ethiopia. International Journal of Education 2011, 3(1):1.
- 34. Thapa DK, Niehof A: Women’s autonomy and husbands’ involvement in maternal health care in Nepal. Social Science & Medicine 2013, 93:1–10. pmid:23906115
- 35. Van Bavel J, Kok J: Birth spacing in the Netherlands. The effects of family composition, occupation and religion on birth intervals, 1820–1885. European Journal of Population/Revue européenne de démographie 2004, 20(2):119–140.
- 36. Rasheed P, Al Dabal B: Birth interval: perceptions and practices among urban-based Saudi Arabian women. EMHJ-Eastern Mediterranean Health Journal, 13 (4), 881–892, 2007 2007. pmid:17955772
- 37. Hemochandra L, Singh NS, Singh AA: Factors determining the closed birth interval in Rural Manipur. Journal of Human Ecology 2010, 29(3):209–213.
- 38. Chatters LM: Religion and health: Public health research and practice. Annual review of public health 2000, 21(1):335–367. pmid:10884957
- 39. McQuillan K: When does religion influence fertility? Population and development review 2004, 30(1):25–56.
- 40.
Roudi-Fahimi F: Islam and family planning: Population Reference Bureau Washington, DC; 2004.
- 41. Duze MC, Mohammed IZ: Male knowledge, attitude, and family planning practices in Northern Nigeria. African Journal of Reproductive Health 2006, 10(3):53–65. pmid:17518131
- 42.
Hoffman LW, Hoffman ML: The value of children to parents: Department of Population Planning School of Public Health, University of …; 1973.
- 43.
Notestein FW: Economic problems of population change: Oxford University Press London; 1953.
- 44. Merali S: The relationship between contraceptive use and maternal and infant health outcomes in Tajikistan. Contraception 2016, 93(3):216–221. pmid:26621105
- 45. Timæus IM, Moultrie TA: On postponement and birth intervals. Population and Development Review 2008, 34(3):483–510.
- 46. Trussell J, Martin LG, Feldman R, Palmore JA, Concepcion M, Dato’Abu DNLB: Determinants of birth-interval length in the Philippines, Malaysia, and Indonesia: A hazard-model analysis. Demography 1985:145–168.
- 47. Rahman MS, Howlader T, Masud MS, Rahman ML: Association of low-birth weight with malnutrition in children under five years in Bangladesh: Do mother’s education, socio-economic status, and birth interval matter? PloS one 2016, 11(6).
- 48. Chacko E: Women’s use of contraception in rural India:: a village-level study. Health & place 2001, 7(3):197–208. pmid:11439255